Compare commits
57 Commits
no-model
...
scenario-s
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2c4ba6eb9b |
@@ -17,6 +17,9 @@ DATABASE_URL="postgresql://postgres:postgres@localhost:5432/openpipe?schema=publ
|
||||
# https://help.openai.com/en/articles/4936850-where-do-i-find-my-secret-api-key
|
||||
OPENAI_API_KEY=""
|
||||
|
||||
# Replicate API token. Create a token here: https://replicate.com/account/api-tokens
|
||||
REPLICATE_API_TOKEN=""
|
||||
|
||||
NEXT_PUBLIC_SOCKET_URL="http://localhost:3318"
|
||||
|
||||
# Next Auth
|
||||
|
||||
5
.vscode/settings.json
vendored
5
.vscode/settings.json
vendored
@@ -1,6 +1,3 @@
|
||||
{
|
||||
"eslint.format.enable": true,
|
||||
"editor.codeActionsOnSave": {
|
||||
"source.fixAll.eslint": true
|
||||
}
|
||||
"eslint.format.enable": true
|
||||
}
|
||||
|
||||
@@ -19,7 +19,6 @@ FROM base as builder
|
||||
|
||||
# Include all NEXT_PUBLIC_* env vars here
|
||||
ARG NEXT_PUBLIC_POSTHOG_KEY
|
||||
ARG NEXT_PUBLIC_IS_PUBLIC_PLAYGROUND
|
||||
ARG NEXT_PUBLIC_SOCKET_URL
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
11
README.md
11
README.md
@@ -8,10 +8,10 @@ OpenPipe is a flexible playground for comparing and optimizing LLM prompts. It l
|
||||
|
||||
These are simple experiments users have created that show how OpenPipe works.
|
||||
|
||||
- [Country Capitals](https://openpipe.ai/experiments/11111111-1111-1111-1111-111111111111)
|
||||
- [Reddit User Needs](https://openpipe.ai/experiments/22222222-2222-2222-2222-222222222222)
|
||||
- [OpenAI Function Calls](https://openpipe.ai/experiments/2ebbdcb3-ed51-456e-87dc-91f72eaf3e2b)
|
||||
- [Activity Classification](https://openpipe.ai/experiments/3950940f-ab6b-4b74-841d-7e9dbc4e4ff8)
|
||||
- [Country Capitals](https://app.openpipe.ai/experiments/11111111-1111-1111-1111-111111111111)
|
||||
- [Reddit User Needs](https://app.openpipe.ai/experiments/22222222-2222-2222-2222-222222222222)
|
||||
- [OpenAI Function Calls](https://app.openpipe.ai/experiments/2ebbdcb3-ed51-456e-87dc-91f72eaf3e2b)
|
||||
- [Activity Classification](https://app.openpipe.ai/experiments/3950940f-ab6b-4b74-841d-7e9dbc4e4ff8)
|
||||
|
||||
<img src="https://github.com/openpipe/openpipe/assets/176426/fc7624c6-5b65-4d4d-82b7-4a816f3e5678" alt="demo" height="400px">
|
||||
|
||||
@@ -43,7 +43,8 @@ Natively supports [OpenAI function calls](https://openai.com/blog/function-calli
|
||||
|
||||
## Supported Models
|
||||
|
||||
OpenPipe currently supports GPT-3.5 and GPT-4. Wider model support is planned.
|
||||
- All models available through the OpenAI [chat completion API](https://platform.openai.com/docs/guides/gpt/chat-completions-api)
|
||||
- Llama2 [7b chat](https://replicate.com/a16z-infra/llama7b-v2-chat), [13b chat](https://replicate.com/a16z-infra/llama13b-v2-chat), [70b chat](https://replicate.com/replicate/llama70b-v2-chat).
|
||||
|
||||
## Running Locally
|
||||
|
||||
|
||||
15
package.json
15
package.json
@@ -12,7 +12,7 @@
|
||||
"dev:next": "next dev",
|
||||
"dev:wss": "pnpm tsx --watch src/wss-server.ts",
|
||||
"dev:worker": "NODE_ENV='development' pnpm tsx --watch src/server/tasks/worker.ts",
|
||||
"dev": "concurrently --kill-others 'pnpm dev:next' 'pnpm dev:wss'",
|
||||
"dev": "concurrently --kill-others 'pnpm dev:next' 'pnpm dev:wss' 'pnpm dev:worker'",
|
||||
"postinstall": "prisma generate",
|
||||
"lint": "next lint",
|
||||
"start": "next start",
|
||||
@@ -21,6 +21,7 @@
|
||||
"check": "concurrently 'pnpm lint' 'pnpm tsc' 'pnpm prettier . --check'"
|
||||
},
|
||||
"dependencies": {
|
||||
"@apidevtools/json-schema-ref-parser": "^10.1.0",
|
||||
"@babel/preset-typescript": "^7.22.5",
|
||||
"@babel/standalone": "^7.22.9",
|
||||
"@chakra-ui/next-js": "^2.1.4",
|
||||
@@ -39,6 +40,7 @@
|
||||
"@trpc/next": "^10.26.0",
|
||||
"@trpc/react-query": "^10.26.0",
|
||||
"@trpc/server": "^10.26.0",
|
||||
"ast-types": "^0.14.2",
|
||||
"chroma-js": "^2.4.2",
|
||||
"concurrently": "^8.2.0",
|
||||
"cors": "^2.8.5",
|
||||
@@ -51,10 +53,13 @@
|
||||
"graphile-worker": "^0.13.0",
|
||||
"immer": "^10.0.2",
|
||||
"isolated-vm": "^4.5.0",
|
||||
"json-schema-to-typescript": "^13.0.2",
|
||||
"json-stringify-pretty-compact": "^4.0.0",
|
||||
"jsonschema": "^1.4.1",
|
||||
"lodash-es": "^4.17.21",
|
||||
"next": "^13.4.2",
|
||||
"next-auth": "^4.22.1",
|
||||
"next-query-params": "^4.2.3",
|
||||
"nextjs-routes": "^2.0.1",
|
||||
"openai": "4.0.0-beta.2",
|
||||
"pluralize": "^8.0.0",
|
||||
@@ -68,10 +73,16 @@
|
||||
"react-select": "^5.7.4",
|
||||
"react-syntax-highlighter": "^15.5.0",
|
||||
"react-textarea-autosize": "^8.5.0",
|
||||
"recast": "^0.23.3",
|
||||
"replicate": "^0.12.3",
|
||||
"socket.io": "^4.7.1",
|
||||
"socket.io-client": "^4.7.1",
|
||||
"superjson": "1.12.2",
|
||||
"tsx": "^3.12.7",
|
||||
"type-fest": "^4.0.0",
|
||||
"use-query-params": "^2.2.1",
|
||||
"uuid": "^9.0.0",
|
||||
"vite-tsconfig-paths": "^4.2.0",
|
||||
"zod": "^3.21.4",
|
||||
"zustand": "^4.3.9"
|
||||
},
|
||||
@@ -83,6 +94,7 @@
|
||||
"@types/cors": "^2.8.13",
|
||||
"@types/eslint": "^8.37.0",
|
||||
"@types/express": "^4.17.17",
|
||||
"@types/json-schema": "^7.0.12",
|
||||
"@types/lodash-es": "^4.17.8",
|
||||
"@types/node": "^18.16.0",
|
||||
"@types/pluralize": "^0.0.30",
|
||||
@@ -90,6 +102,7 @@
|
||||
"@types/react": "^18.2.6",
|
||||
"@types/react-dom": "^18.2.4",
|
||||
"@types/react-syntax-highlighter": "^15.5.7",
|
||||
"@types/uuid": "^9.0.2",
|
||||
"@typescript-eslint/eslint-plugin": "^5.59.6",
|
||||
"@typescript-eslint/parser": "^5.59.6",
|
||||
"eslint": "^8.40.0",
|
||||
|
||||
466
pnpm-lock.yaml
generated
466
pnpm-lock.yaml
generated
@@ -1,10 +1,13 @@
|
||||
lockfileVersion: '6.1'
|
||||
lockfileVersion: '6.0'
|
||||
|
||||
settings:
|
||||
autoInstallPeers: true
|
||||
excludeLinksFromLockfile: false
|
||||
|
||||
dependencies:
|
||||
'@apidevtools/json-schema-ref-parser':
|
||||
specifier: ^10.1.0
|
||||
version: 10.1.0
|
||||
'@babel/preset-typescript':
|
||||
specifier: ^7.22.5
|
||||
version: 7.22.5(@babel/core@7.22.9)
|
||||
@@ -59,6 +62,9 @@ dependencies:
|
||||
'@trpc/server':
|
||||
specifier: ^10.26.0
|
||||
version: 10.26.0
|
||||
ast-types:
|
||||
specifier: ^0.14.2
|
||||
version: 0.14.2
|
||||
chroma-js:
|
||||
specifier: ^2.4.2
|
||||
version: 2.4.2
|
||||
@@ -95,9 +101,15 @@ dependencies:
|
||||
isolated-vm:
|
||||
specifier: ^4.5.0
|
||||
version: 4.5.0
|
||||
json-schema-to-typescript:
|
||||
specifier: ^13.0.2
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||||
version: 13.0.2
|
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json-stringify-pretty-compact:
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||||
specifier: ^4.0.0
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||||
version: 4.0.0
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||||
jsonschema:
|
||||
specifier: ^1.4.1
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||||
version: 1.4.1
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||||
lodash-es:
|
||||
specifier: ^4.17.21
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||||
version: 4.17.21
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||||
@@ -107,6 +119,9 @@ dependencies:
|
||||
next-auth:
|
||||
specifier: ^4.22.1
|
||||
version: 4.22.1(next@13.4.2)(react-dom@18.2.0)(react@18.2.0)
|
||||
next-query-params:
|
||||
specifier: ^4.2.3
|
||||
version: 4.2.3(next@13.4.2)(react@18.2.0)(use-query-params@2.2.1)
|
||||
nextjs-routes:
|
||||
specifier: ^2.0.1
|
||||
version: 2.0.1(next@13.4.2)
|
||||
@@ -146,6 +161,12 @@ dependencies:
|
||||
react-textarea-autosize:
|
||||
specifier: ^8.5.0
|
||||
version: 8.5.0(@types/react@18.2.6)(react@18.2.0)
|
||||
recast:
|
||||
specifier: ^0.23.3
|
||||
version: 0.23.3
|
||||
replicate:
|
||||
specifier: ^0.12.3
|
||||
version: 0.12.3
|
||||
socket.io:
|
||||
specifier: ^4.7.1
|
||||
version: 4.7.1
|
||||
@@ -158,6 +179,18 @@ dependencies:
|
||||
tsx:
|
||||
specifier: ^3.12.7
|
||||
version: 3.12.7
|
||||
type-fest:
|
||||
specifier: ^4.0.0
|
||||
version: 4.0.0
|
||||
use-query-params:
|
||||
specifier: ^2.2.1
|
||||
version: 2.2.1(react-dom@18.2.0)(react@18.2.0)
|
||||
uuid:
|
||||
specifier: ^9.0.0
|
||||
version: 9.0.0
|
||||
vite-tsconfig-paths:
|
||||
specifier: ^4.2.0
|
||||
version: 4.2.0(typescript@5.0.4)
|
||||
zod:
|
||||
specifier: ^3.21.4
|
||||
version: 3.21.4
|
||||
@@ -187,6 +220,9 @@ devDependencies:
|
||||
'@types/express':
|
||||
specifier: ^4.17.17
|
||||
version: 4.17.17
|
||||
'@types/json-schema':
|
||||
specifier: ^7.0.12
|
||||
version: 7.0.12
|
||||
'@types/lodash-es':
|
||||
specifier: ^4.17.8
|
||||
version: 4.17.8
|
||||
@@ -208,6 +244,9 @@ devDependencies:
|
||||
'@types/react-syntax-highlighter':
|
||||
specifier: ^15.5.7
|
||||
version: 15.5.7
|
||||
'@types/uuid':
|
||||
specifier: ^9.0.2
|
||||
version: 9.0.2
|
||||
'@typescript-eslint/eslint-plugin':
|
||||
specifier: ^5.59.6
|
||||
version: 5.59.6(@typescript-eslint/parser@5.59.6)(eslint@8.40.0)(typescript@5.0.4)
|
||||
@@ -259,6 +298,17 @@ packages:
|
||||
'@jridgewell/gen-mapping': 0.3.3
|
||||
'@jridgewell/trace-mapping': 0.3.18
|
||||
|
||||
/@apidevtools/json-schema-ref-parser@10.1.0:
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resolution: {integrity: sha512-3e+viyMuXdrcK8v5pvP+SDoAQ77FH6OyRmuK48SZKmdHJRFm87RsSs8qm6kP39a/pOPURByJw+OXzQIqcfmKtA==}
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engines: {node: '>= 16'}
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dependencies:
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'@jsdevtools/ono': 7.1.3
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'@types/json-schema': 7.0.12
|
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'@types/lodash.clonedeep': 4.5.7
|
||||
js-yaml: 4.1.0
|
||||
lodash.clonedeep: 4.5.0
|
||||
dev: false
|
||||
|
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||||
engines: {node: '>=6.9.0'}
|
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@@ -564,6 +614,16 @@ packages:
|
||||
'@babel/helper-validator-identifier': 7.22.5
|
||||
to-fast-properties: 2.0.0
|
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|
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/@bcherny/json-schema-ref-parser@10.0.5-fork:
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engines: {node: '>= 16'}
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dependencies:
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'@jsdevtools/ono': 7.1.3
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'@types/json-schema': 7.0.12
|
||||
call-me-maybe: 1.0.2
|
||||
js-yaml: 4.1.0
|
||||
dev: false
|
||||
|
||||
/@chakra-ui/accordion@2.2.0(@chakra-ui/system@2.5.8)(framer-motion@10.12.17)(react@18.2.0):
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peerDependencies:
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@@ -2385,6 +2445,10 @@ packages:
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'@jridgewell/resolve-uri': 3.1.0
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'@jridgewell/sourcemap-codec': 1.4.14
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peerDependencies:
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@@ -2806,6 +2870,13 @@ packages:
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dependencies:
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'@types/minimatch': 5.1.2
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dependencies:
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dependencies:
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@@ -2847,6 +2923,10 @@ packages:
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-- Add new columns allowing NULL values
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-- Update existing records to have the default values
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/*
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Warnings:
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- You are about to drop the column `streamingChannel` on the `ScenarioVariantCell` table. All the data in the column will be lost.
|
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*/
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-- AlterTable
|
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ALTER TABLE "ScenarioVariantCell" DROP COLUMN "streamingChannel";
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@@ -22,18 +22,20 @@ model Experiment {
|
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createdAt DateTime @default(now())
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updatedAt DateTime @updatedAt
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TemplateVariable TemplateVariable[]
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PromptVariant PromptVariant[]
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TestScenario TestScenario[]
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Evaluation Evaluation[]
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templateVariables TemplateVariable[]
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promptVariants PromptVariant[]
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testScenarios TestScenario[]
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evaluations Evaluation[]
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}
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model PromptVariant {
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id String @id @default(uuid()) @db.Uuid
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label String
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constructFn String
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model String
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||||
label String
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constructFn String
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constructFnVersion Int
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model String
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modelProvider String
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uiId String @default(uuid()) @db.Uuid
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visible Boolean @default(true)
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model ScenarioVariantCell {
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id String @id @default(uuid()) @db.Uuid
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statusCode Int?
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errorMessage String?
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retryTime DateTime?
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streamingChannel String?
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retrievalStatus CellRetrievalStatus @default(COMPLETE)
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statusCode Int?
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errorMessage String?
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retryTime DateTime?
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retrievalStatus CellRetrievalStatus @default(COMPLETE)
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modelOutput ModelOutput?
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promptVariantId String @db.Uuid
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promptVariant PromptVariant @relation(fields: [promptVariantId], references: [id], onDelete: Cascade)
|
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prompt Json?
|
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testScenarioId String @db.Uuid
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testScenario TestScenario @relation(fields: [testScenarioId], references: [id], onDelete: Cascade)
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scenarioVariantCellId String @db.Uuid
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scenarioVariantCell ScenarioVariantCell @relation(fields: [scenarioVariantCellId], references: [id], onDelete: Cascade)
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outputEvaluation OutputEvaluation[]
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outputEvaluations OutputEvaluation[]
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@@unique([scenarioVariantCellId])
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@@index([inputHash])
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createdAt DateTime @default(now())
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updatedAt DateTime @updatedAt
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OutputEvaluation OutputEvaluation[]
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outputEvaluations OutputEvaluation[]
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}
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model OutputEvaluation {
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@@ -176,8 +178,8 @@ model Organization {
|
||||
|
||||
createdAt DateTime @default(now())
|
||||
updatedAt DateTime @updatedAt
|
||||
OrganizationUser OrganizationUser[]
|
||||
Experiment Experiment[]
|
||||
organizationUsers OrganizationUser[]
|
||||
experiments Experiment[]
|
||||
}
|
||||
|
||||
enum OrganizationUserRole {
|
||||
@@ -231,15 +233,15 @@ model Session {
|
||||
}
|
||||
|
||||
model User {
|
||||
id String @id @default(uuid()) @db.Uuid
|
||||
name String?
|
||||
email String? @unique
|
||||
emailVerified DateTime?
|
||||
image String?
|
||||
accounts Account[]
|
||||
sessions Session[]
|
||||
OrganizationUser OrganizationUser[]
|
||||
Organization Organization[]
|
||||
id String @id @default(uuid()) @db.Uuid
|
||||
name String?
|
||||
email String? @unique
|
||||
emailVerified DateTime?
|
||||
image String?
|
||||
accounts Account[]
|
||||
sessions Session[]
|
||||
organizationUsers OrganizationUser[]
|
||||
organizations Organization[]
|
||||
}
|
||||
|
||||
model VerificationToken {
|
||||
|
||||
@@ -7,9 +7,13 @@ const defaultId = "11111111-1111-1111-1111-111111111111";
|
||||
await prisma.organization.deleteMany({
|
||||
where: { id: defaultId },
|
||||
});
|
||||
await prisma.organization.create({
|
||||
data: { id: defaultId },
|
||||
});
|
||||
|
||||
// If there's an existing org, just seed into it
|
||||
const org =
|
||||
(await prisma.organization.findFirst({})) ??
|
||||
(await prisma.organization.create({
|
||||
data: { id: defaultId },
|
||||
}));
|
||||
|
||||
await prisma.experiment.deleteMany({
|
||||
where: {
|
||||
@@ -21,7 +25,7 @@ await prisma.experiment.create({
|
||||
data: {
|
||||
id: defaultId,
|
||||
label: "Country Capitals Example",
|
||||
organizationId: defaultId,
|
||||
organizationId: org.id,
|
||||
},
|
||||
});
|
||||
|
||||
@@ -46,8 +50,10 @@ await prisma.promptVariant.createMany({
|
||||
label: "Prompt Variant 1",
|
||||
sortIndex: 0,
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
modelProvider: "openai/ChatCompletion",
|
||||
constructFnVersion: 1,
|
||||
constructFn: dedent`
|
||||
prompt = {
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
messages: [
|
||||
{
|
||||
@@ -56,15 +62,17 @@ await prisma.promptVariant.createMany({
|
||||
}
|
||||
],
|
||||
temperature: 0,
|
||||
}`,
|
||||
})`,
|
||||
},
|
||||
{
|
||||
experimentId: defaultId,
|
||||
label: "Prompt Variant 2",
|
||||
sortIndex: 1,
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
modelProvider: "openai/ChatCompletion",
|
||||
constructFnVersion: 1,
|
||||
constructFn: dedent`
|
||||
prompt = {
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
messages: [
|
||||
{
|
||||
@@ -73,7 +81,7 @@ await prisma.promptVariant.createMany({
|
||||
}
|
||||
],
|
||||
temperature: 0,
|
||||
}`,
|
||||
})`,
|
||||
},
|
||||
],
|
||||
});
|
||||
@@ -99,30 +107,41 @@ await prisma.testScenario.deleteMany({
|
||||
},
|
||||
});
|
||||
|
||||
const countries = [
|
||||
"Afghanistan",
|
||||
"Albania",
|
||||
"Algeria",
|
||||
"Andorra",
|
||||
"Angola",
|
||||
"Antigua and Barbuda",
|
||||
"Argentina",
|
||||
"Armenia",
|
||||
"Australia",
|
||||
"Austria",
|
||||
"Austrian Empire",
|
||||
"Azerbaijan",
|
||||
"Baden",
|
||||
"Bahamas, The",
|
||||
"Bahrain",
|
||||
"Bangladesh",
|
||||
"Barbados",
|
||||
"Bavaria",
|
||||
"Belarus",
|
||||
"Belgium",
|
||||
"Belize",
|
||||
"Benin (Dahomey)",
|
||||
"Bolivia",
|
||||
"Bosnia and Herzegovina",
|
||||
"Botswana",
|
||||
];
|
||||
await prisma.testScenario.createMany({
|
||||
data: [
|
||||
{
|
||||
experimentId: defaultId,
|
||||
sortIndex: 0,
|
||||
variableValues: {
|
||||
country: "Spain",
|
||||
},
|
||||
data: countries.map((country, i) => ({
|
||||
experimentId: defaultId,
|
||||
sortIndex: i,
|
||||
variableValues: {
|
||||
country: country,
|
||||
},
|
||||
{
|
||||
experimentId: defaultId,
|
||||
sortIndex: 1,
|
||||
variableValues: {
|
||||
country: "USA",
|
||||
},
|
||||
},
|
||||
{
|
||||
experimentId: defaultId,
|
||||
sortIndex: 2,
|
||||
variableValues: {
|
||||
country: "Chile",
|
||||
},
|
||||
},
|
||||
],
|
||||
})),
|
||||
});
|
||||
|
||||
const variants = await prisma.promptVariant.findMany({
|
||||
@@ -145,5 +164,5 @@ await Promise.all(
|
||||
testScenarioId: scenario.id,
|
||||
})),
|
||||
)
|
||||
.map((cell) => generateNewCell(cell.promptVariantId, cell.testScenarioId)),
|
||||
.map((cell) => generateNewCell(cell.promptVariantId, cell.testScenarioId, { stream: false })),
|
||||
);
|
||||
|
||||
@@ -6,4 +6,7 @@ echo "Migrating the database"
|
||||
pnpm prisma migrate deploy
|
||||
|
||||
echo "Starting the server"
|
||||
pnpm start
|
||||
|
||||
pnpm concurrently --kill-others \
|
||||
"pnpm start" \
|
||||
"pnpm tsx src/server/tasks/worker.ts"
|
||||
@@ -1,48 +0,0 @@
|
||||
/* eslint-disable @typescript-eslint/no-var-requires */
|
||||
|
||||
import YAML from "yaml";
|
||||
import fs from "fs";
|
||||
import path from "path";
|
||||
import { openapiSchemaToJsonSchema } from "@openapi-contrib/openapi-schema-to-json-schema";
|
||||
import assert from "assert";
|
||||
import { type AcceptibleInputSchema } from "@openapi-contrib/openapi-schema-to-json-schema/dist/mjs/openapi-schema-types";
|
||||
|
||||
const OPENAPI_URL =
|
||||
"https://raw.githubusercontent.com/openai/openai-openapi/0c432eb66fd0c758fd8b9bd69db41c1096e5f4db/openapi.yaml";
|
||||
|
||||
const convertOpenApiToJsonSchema = async (url: string) => {
|
||||
// Fetch the openapi document
|
||||
const response = await fetch(url);
|
||||
const openApiYaml = await response.text();
|
||||
|
||||
// Parse the yaml document
|
||||
const openApiDocument = YAML.parse(openApiYaml) as AcceptibleInputSchema;
|
||||
|
||||
// Convert the openapi schema to json schema
|
||||
const jsonSchema = openapiSchemaToJsonSchema(openApiDocument);
|
||||
|
||||
const modelProperty = jsonSchema.components.schemas.CreateChatCompletionRequest.properties.model;
|
||||
|
||||
assert(modelProperty.oneOf.length === 2, "Expected model to have oneOf length of 2");
|
||||
|
||||
// We need to do a bit of surgery here since the Monaco editor doesn't like
|
||||
// the fact that the schema says `model` can be either a string or an enum,
|
||||
// and displays a warning in the editor. Let's stick with just an enum for
|
||||
// now and drop the string option.
|
||||
modelProperty.type = "string";
|
||||
modelProperty.enum = modelProperty.oneOf[1].enum;
|
||||
modelProperty.oneOf = undefined;
|
||||
|
||||
// Get the directory of the current script
|
||||
const currentDirectory = path.dirname(import.meta.url).replace("file://", "");
|
||||
|
||||
// Write the JSON schema to a file in the current directory
|
||||
fs.writeFileSync(
|
||||
path.join(currentDirectory, "openai.schema.json"),
|
||||
JSON.stringify(jsonSchema, null, 2),
|
||||
);
|
||||
};
|
||||
|
||||
convertOpenApiToJsonSchema(OPENAPI_URL)
|
||||
.then(() => console.log("JSON schema has been written successfully."))
|
||||
.catch((err) => console.error(err));
|
||||
@@ -1,52 +0,0 @@
|
||||
import fs from "fs";
|
||||
import path from "path";
|
||||
import openapiTS, { type OpenAPI3 } from "openapi-typescript";
|
||||
import YAML from "yaml";
|
||||
import { pick } from "lodash-es";
|
||||
import assert from "assert";
|
||||
|
||||
const OPENAPI_URL =
|
||||
"https://raw.githubusercontent.com/openai/openai-openapi/0c432eb66fd0c758fd8b9bd69db41c1096e5f4db/openapi.yaml";
|
||||
|
||||
// Generate TypeScript types from OpenAPI
|
||||
|
||||
const schema = await fetch(OPENAPI_URL)
|
||||
.then((res) => res.text())
|
||||
.then((txt) => YAML.parse(txt) as OpenAPI3);
|
||||
|
||||
console.log(schema.components?.schemas?.CreateChatCompletionRequest);
|
||||
|
||||
// @ts-expect-error just assume this works, the assert will catch it if it doesn't
|
||||
const modelProperty = schema.components?.schemas?.CreateChatCompletionRequest?.properties?.model;
|
||||
|
||||
assert(modelProperty.oneOf.length === 2, "Expected model to have oneOf length of 2");
|
||||
|
||||
// We need to do a bit of surgery here since the Monaco editor doesn't like
|
||||
// the fact that the schema says `model` can be either a string or an enum,
|
||||
// and displays a warning in the editor. Let's stick with just an enum for
|
||||
// now and drop the string option.
|
||||
modelProperty.type = "string";
|
||||
modelProperty.enum = modelProperty.oneOf[1].enum;
|
||||
modelProperty.oneOf = undefined;
|
||||
|
||||
delete schema["paths"];
|
||||
assert(schema.components?.schemas);
|
||||
schema.components.schemas = pick(schema.components?.schemas, [
|
||||
"CreateChatCompletionRequest",
|
||||
"ChatCompletionRequestMessage",
|
||||
"ChatCompletionFunctions",
|
||||
"ChatCompletionFunctionParameters",
|
||||
]);
|
||||
console.log(schema);
|
||||
|
||||
let openApiTypes = await openapiTS(schema);
|
||||
|
||||
// Remove the `export` from any line that starts with `export`
|
||||
openApiTypes = openApiTypes.replaceAll("\nexport ", "\n");
|
||||
|
||||
// Get the directory of the current script
|
||||
const currentDirectory = path.dirname(import.meta.url).replace("file://", "");
|
||||
|
||||
// Write the TypeScript types. We only want to use this in our in-app editor, so
|
||||
// save as a .txt so VS Code doesn't try to auto-import definitions from it.
|
||||
fs.writeFileSync(path.join(currentDirectory, "openai.types.ts.txt"), openApiTypes);
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,148 +0,0 @@
|
||||
/**
|
||||
* This file was auto-generated by openapi-typescript.
|
||||
* Do not make direct changes to the file.
|
||||
*/
|
||||
|
||||
|
||||
/** OneOf type helpers */
|
||||
type Without<T, U> = { [P in Exclude<keyof T, keyof U>]?: never };
|
||||
type XOR<T, U> = (T | U) extends object ? (Without<T, U> & U) | (Without<U, T> & T) : T | U;
|
||||
type OneOf<T extends any[]> = T extends [infer Only] ? Only : T extends [infer A, infer B, ...infer Rest] ? OneOf<[XOR<A, B>, ...Rest]> : never;
|
||||
|
||||
type paths = Record<string, never>;
|
||||
|
||||
type webhooks = Record<string, never>;
|
||||
|
||||
interface components {
|
||||
schemas: {
|
||||
CreateChatCompletionRequest: {
|
||||
/**
|
||||
* @description ID of the model to use. See the [model endpoint compatibility](/docs/models/model-endpoint-compatibility) table for details on which models work with the Chat API.
|
||||
* @example gpt-3.5-turbo
|
||||
* @enum {string}
|
||||
*/
|
||||
model: "gpt-4" | "gpt-4-0613" | "gpt-4-32k" | "gpt-4-32k-0613" | "gpt-3.5-turbo" | "gpt-3.5-turbo-16k" | "gpt-3.5-turbo-0613" | "gpt-3.5-turbo-16k-0613";
|
||||
/** @description A list of messages comprising the conversation so far. [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb). */
|
||||
messages: (components["schemas"]["ChatCompletionRequestMessage"])[];
|
||||
/** @description A list of functions the model may generate JSON inputs for. */
|
||||
functions?: (components["schemas"]["ChatCompletionFunctions"])[];
|
||||
/** @description Controls how the model responds to function calls. "none" means the model does not call a function, and responds to the end-user. "auto" means the model can pick between an end-user or calling a function. Specifying a particular function via `{"name":\ "my_function"}` forces the model to call that function. "none" is the default when no functions are present. "auto" is the default if functions are present. */
|
||||
function_call?: OneOf<["none" | "auto", {
|
||||
/** @description The name of the function to call. */
|
||||
name: string;
|
||||
}]>;
|
||||
/**
|
||||
* @description What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
|
||||
*
|
||||
* We generally recommend altering this or `top_p` but not both.
|
||||
*
|
||||
* @default 1
|
||||
* @example 1
|
||||
*/
|
||||
temperature?: number | null;
|
||||
/**
|
||||
* @description An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.
|
||||
*
|
||||
* We generally recommend altering this or `temperature` but not both.
|
||||
*
|
||||
* @default 1
|
||||
* @example 1
|
||||
*/
|
||||
top_p?: number | null;
|
||||
/**
|
||||
* @description How many chat completion choices to generate for each input message.
|
||||
* @default 1
|
||||
* @example 1
|
||||
*/
|
||||
n?: number | null;
|
||||
/**
|
||||
* @description If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb).
|
||||
*
|
||||
* @default false
|
||||
*/
|
||||
stream?: boolean | null;
|
||||
/**
|
||||
* @description Up to 4 sequences where the API will stop generating further tokens.
|
||||
*
|
||||
* @default null
|
||||
*/
|
||||
stop?: (string | null) | (string)[];
|
||||
/**
|
||||
* @description The maximum number of [tokens](/tokenizer) to generate in the chat completion.
|
||||
*
|
||||
* The total length of input tokens and generated tokens is limited by the model's context length. [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) for counting tokens.
|
||||
*
|
||||
* @default inf
|
||||
*/
|
||||
max_tokens?: number;
|
||||
/**
|
||||
* @description Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
|
||||
*
|
||||
* [See more information about frequency and presence penalties.](/docs/api-reference/parameter-details)
|
||||
*
|
||||
* @default 0
|
||||
*/
|
||||
presence_penalty?: number | null;
|
||||
/**
|
||||
* @description Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
|
||||
*
|
||||
* [See more information about frequency and presence penalties.](/docs/api-reference/parameter-details)
|
||||
*
|
||||
* @default 0
|
||||
*/
|
||||
frequency_penalty?: number | null;
|
||||
/**
|
||||
* @description Modify the likelihood of specified tokens appearing in the completion.
|
||||
*
|
||||
* Accepts a json object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.
|
||||
*
|
||||
* @default null
|
||||
*/
|
||||
logit_bias?: Record<string, unknown> | null;
|
||||
/**
|
||||
* @description A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).
|
||||
*
|
||||
* @example user-1234
|
||||
*/
|
||||
user?: string;
|
||||
};
|
||||
ChatCompletionRequestMessage: {
|
||||
/**
|
||||
* @description The role of the messages author. One of `system`, `user`, `assistant`, or `function`.
|
||||
* @enum {string}
|
||||
*/
|
||||
role: "system" | "user" | "assistant" | "function";
|
||||
/** @description The contents of the message. `content` is required for all messages except assistant messages with function calls. */
|
||||
content?: string;
|
||||
/** @description The name of the author of this message. `name` is required if role is `function`, and it should be the name of the function whose response is in the `content`. May contain a-z, A-Z, 0-9, and underscores, with a maximum length of 64 characters. */
|
||||
name?: string;
|
||||
/** @description The name and arguments of a function that should be called, as generated by the model. */
|
||||
function_call?: {
|
||||
/** @description The name of the function to call. */
|
||||
name?: string;
|
||||
/** @description The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function. */
|
||||
arguments?: string;
|
||||
};
|
||||
};
|
||||
ChatCompletionFunctions: {
|
||||
/** @description The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64. */
|
||||
name: string;
|
||||
/** @description The description of what the function does. */
|
||||
description?: string;
|
||||
parameters?: components["schemas"]["ChatCompletionFunctionParameters"];
|
||||
};
|
||||
/** @description The parameters the functions accepts, described as a JSON Schema object. See the [guide](/docs/guides/gpt/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format. */
|
||||
ChatCompletionFunctionParameters: {
|
||||
[key: string]: unknown;
|
||||
};
|
||||
};
|
||||
responses: never;
|
||||
parameters: never;
|
||||
requestBodies: never;
|
||||
headers: never;
|
||||
pathItems: never;
|
||||
}
|
||||
|
||||
type external = Record<string, never>;
|
||||
|
||||
type operations = Record<string, never>;
|
||||
@@ -1,6 +0,0 @@
|
||||
{
|
||||
"compilerOptions": {
|
||||
"target": "esnext",
|
||||
"moduleResolution": "nodenext"
|
||||
}
|
||||
}
|
||||
@@ -1,19 +1,22 @@
|
||||
import { Textarea, type TextareaProps } from "@chakra-ui/react";
|
||||
import ResizeTextarea from "react-textarea-autosize";
|
||||
import React from "react";
|
||||
import React, { useLayoutEffect, useState } from "react";
|
||||
|
||||
export const AutoResizeTextarea: React.ForwardRefRenderFunction<
|
||||
HTMLTextAreaElement,
|
||||
TextareaProps & { minRows?: number }
|
||||
> = (props, ref) => {
|
||||
> = ({ minRows = 1, overflowY = "hidden", ...props }, ref) => {
|
||||
const [isRerendered, setIsRerendered] = useState(false);
|
||||
useLayoutEffect(() => setIsRerendered(true), []);
|
||||
|
||||
return (
|
||||
<Textarea
|
||||
minH="unset"
|
||||
overflow="hidden"
|
||||
minRows={minRows}
|
||||
overflowY={isRerendered ? overflowY : "hidden"}
|
||||
w="100%"
|
||||
resize="none"
|
||||
ref={ref}
|
||||
minRows={1}
|
||||
transition="height none"
|
||||
as={ResizeTextarea}
|
||||
{...props}
|
||||
|
||||
142
src/components/ChangeModelModal/ChangeModelModal.tsx
Normal file
142
src/components/ChangeModelModal/ChangeModelModal.tsx
Normal file
@@ -0,0 +1,142 @@
|
||||
import {
|
||||
Button,
|
||||
HStack,
|
||||
Icon,
|
||||
Modal,
|
||||
ModalBody,
|
||||
ModalCloseButton,
|
||||
ModalContent,
|
||||
ModalFooter,
|
||||
ModalHeader,
|
||||
ModalOverlay,
|
||||
Spinner,
|
||||
Text,
|
||||
VStack,
|
||||
} from "@chakra-ui/react";
|
||||
import { type PromptVariant } from "@prisma/client";
|
||||
import { isObject, isString } from "lodash-es";
|
||||
import { useState } from "react";
|
||||
import { RiExchangeFundsFill } from "react-icons/ri";
|
||||
import { type ProviderModel } from "~/modelProviders/types";
|
||||
import { api } from "~/utils/api";
|
||||
import { useExperiment, useHandledAsyncCallback, useVisibleScenarioIds } from "~/utils/hooks";
|
||||
import { lookupModel, modelLabel } from "~/utils/utils";
|
||||
import CompareFunctions from "../RefinePromptModal/CompareFunctions";
|
||||
import { ModelSearch } from "./ModelSearch";
|
||||
import { ModelStatsCard } from "./ModelStatsCard";
|
||||
|
||||
export const ChangeModelModal = ({
|
||||
variant,
|
||||
onClose,
|
||||
}: {
|
||||
variant: PromptVariant;
|
||||
onClose: () => void;
|
||||
}) => {
|
||||
const originalModel = lookupModel(variant.modelProvider, variant.model);
|
||||
const [selectedModel, setSelectedModel] = useState({
|
||||
provider: variant.modelProvider,
|
||||
model: variant.model,
|
||||
} as ProviderModel);
|
||||
const [convertedModel, setConvertedModel] = useState<ProviderModel | undefined>();
|
||||
const visibleScenarios = useVisibleScenarioIds();
|
||||
|
||||
const utils = api.useContext();
|
||||
|
||||
const experiment = useExperiment();
|
||||
|
||||
const { mutateAsync: getModifiedPromptMutateAsync, data: modifiedPromptFn } =
|
||||
api.promptVariants.getModifiedPromptFn.useMutation();
|
||||
|
||||
const [getModifiedPromptFn, modificationInProgress] = useHandledAsyncCallback(async () => {
|
||||
if (!experiment) return;
|
||||
|
||||
await getModifiedPromptMutateAsync({
|
||||
id: variant.id,
|
||||
newModel: selectedModel,
|
||||
});
|
||||
setConvertedModel(selectedModel);
|
||||
}, [getModifiedPromptMutateAsync, onClose, experiment, variant, selectedModel]);
|
||||
|
||||
const replaceVariantMutation = api.promptVariants.replaceVariant.useMutation();
|
||||
|
||||
const [replaceVariant, replacementInProgress] = useHandledAsyncCallback(async () => {
|
||||
if (
|
||||
!variant.experimentId ||
|
||||
!modifiedPromptFn ||
|
||||
(isObject(modifiedPromptFn) && "status" in modifiedPromptFn)
|
||||
)
|
||||
return;
|
||||
await replaceVariantMutation.mutateAsync({
|
||||
id: variant.id,
|
||||
constructFn: modifiedPromptFn,
|
||||
streamScenarios: visibleScenarios,
|
||||
});
|
||||
await utils.promptVariants.list.invalidate();
|
||||
onClose();
|
||||
}, [replaceVariantMutation, variant, onClose, modifiedPromptFn]);
|
||||
|
||||
const originalLabel = modelLabel(variant.modelProvider, variant.model);
|
||||
const selectedLabel = modelLabel(selectedModel.provider, selectedModel.model);
|
||||
const convertedLabel =
|
||||
convertedModel && modelLabel(convertedModel.provider, convertedModel.model);
|
||||
|
||||
return (
|
||||
<Modal
|
||||
isOpen
|
||||
onClose={onClose}
|
||||
size={{ base: "xl", sm: "2xl", md: "3xl", lg: "5xl", xl: "7xl" }}
|
||||
>
|
||||
<ModalOverlay />
|
||||
<ModalContent w={1200}>
|
||||
<ModalHeader>
|
||||
<HStack>
|
||||
<Icon as={RiExchangeFundsFill} />
|
||||
<Text>Change Model</Text>
|
||||
</HStack>
|
||||
</ModalHeader>
|
||||
<ModalCloseButton />
|
||||
<ModalBody maxW="unset">
|
||||
<VStack spacing={8}>
|
||||
<ModelStatsCard label="Original Model" model={originalModel} />
|
||||
{originalLabel !== selectedLabel && (
|
||||
<ModelStatsCard
|
||||
label="New Model"
|
||||
model={lookupModel(selectedModel.provider, selectedModel.model)}
|
||||
/>
|
||||
)}
|
||||
<ModelSearch selectedModel={selectedModel} setSelectedModel={setSelectedModel} />
|
||||
{isString(modifiedPromptFn) && (
|
||||
<CompareFunctions
|
||||
originalFunction={variant.constructFn}
|
||||
newFunction={modifiedPromptFn}
|
||||
leftTitle={originalLabel}
|
||||
rightTitle={convertedLabel}
|
||||
/>
|
||||
)}
|
||||
</VStack>
|
||||
</ModalBody>
|
||||
|
||||
<ModalFooter>
|
||||
<HStack>
|
||||
<Button
|
||||
colorScheme="gray"
|
||||
onClick={getModifiedPromptFn}
|
||||
minW={24}
|
||||
isDisabled={originalLabel === selectedLabel || modificationInProgress}
|
||||
>
|
||||
{modificationInProgress ? <Spinner boxSize={4} /> : <Text>Convert</Text>}
|
||||
</Button>
|
||||
<Button
|
||||
colorScheme="blue"
|
||||
onClick={replaceVariant}
|
||||
minW={24}
|
||||
isDisabled={!convertedModel || modificationInProgress || replacementInProgress}
|
||||
>
|
||||
{replacementInProgress ? <Spinner boxSize={4} /> : <Text>Accept</Text>}
|
||||
</Button>
|
||||
</HStack>
|
||||
</ModalFooter>
|
||||
</ModalContent>
|
||||
</Modal>
|
||||
);
|
||||
};
|
||||
36
src/components/ChangeModelModal/ModelSearch.tsx
Normal file
36
src/components/ChangeModelModal/ModelSearch.tsx
Normal file
@@ -0,0 +1,36 @@
|
||||
import { Text, VStack } from "@chakra-ui/react";
|
||||
import { type LegacyRef } from "react";
|
||||
import Select from "react-select";
|
||||
import { useElementDimensions } from "~/utils/hooks";
|
||||
|
||||
import { flatMap } from "lodash-es";
|
||||
import frontendModelProviders from "~/modelProviders/frontendModelProviders";
|
||||
import { type ProviderModel } from "~/modelProviders/types";
|
||||
import { modelLabel } from "~/utils/utils";
|
||||
|
||||
const modelOptions = flatMap(Object.entries(frontendModelProviders), ([providerId, provider]) =>
|
||||
Object.entries(provider.models).map(([modelId]) => ({
|
||||
provider: providerId,
|
||||
model: modelId,
|
||||
})),
|
||||
) as ProviderModel[];
|
||||
|
||||
export const ModelSearch = (props: {
|
||||
selectedModel: ProviderModel;
|
||||
setSelectedModel: (model: ProviderModel) => void;
|
||||
}) => {
|
||||
const [containerRef, containerDimensions] = useElementDimensions();
|
||||
|
||||
return (
|
||||
<VStack ref={containerRef as LegacyRef<HTMLDivElement>} w="full">
|
||||
<Text>Browse Models</Text>
|
||||
<Select<ProviderModel>
|
||||
styles={{ control: (provided) => ({ ...provided, width: containerDimensions?.width }) }}
|
||||
getOptionLabel={(data) => modelLabel(data.provider, data.model)}
|
||||
getOptionValue={(data) => modelLabel(data.provider, data.model)}
|
||||
options={modelOptions}
|
||||
onChange={(option) => option && props.setSelectedModel(option)}
|
||||
/>
|
||||
</VStack>
|
||||
);
|
||||
};
|
||||
109
src/components/ChangeModelModal/ModelStatsCard.tsx
Normal file
109
src/components/ChangeModelModal/ModelStatsCard.tsx
Normal file
@@ -0,0 +1,109 @@
|
||||
import {
|
||||
GridItem,
|
||||
HStack,
|
||||
Link,
|
||||
SimpleGrid,
|
||||
Text,
|
||||
VStack,
|
||||
type StackProps,
|
||||
} from "@chakra-ui/react";
|
||||
import { type lookupModel } from "~/utils/utils";
|
||||
|
||||
export const ModelStatsCard = ({
|
||||
label,
|
||||
model,
|
||||
}: {
|
||||
label: string;
|
||||
model: ReturnType<typeof lookupModel>;
|
||||
}) => {
|
||||
if (!model) return null;
|
||||
return (
|
||||
<VStack w="full" align="start">
|
||||
<Text fontWeight="bold" fontSize="sm" textTransform="uppercase">
|
||||
{label}
|
||||
</Text>
|
||||
|
||||
<VStack w="full" spacing={6} bgColor="gray.100" p={4} borderRadius={4}>
|
||||
<HStack w="full" align="flex-start">
|
||||
<Text flex={1} fontSize="lg">
|
||||
<Text as="span" color="gray.600">
|
||||
{model.provider} /{" "}
|
||||
</Text>
|
||||
<Text as="span" fontWeight="bold" color="gray.900">
|
||||
{model.name}
|
||||
</Text>
|
||||
</Text>
|
||||
<Link
|
||||
href={model.learnMoreUrl}
|
||||
isExternal
|
||||
color="blue.500"
|
||||
fontWeight="bold"
|
||||
fontSize="sm"
|
||||
ml={2}
|
||||
>
|
||||
Learn More
|
||||
</Link>
|
||||
</HStack>
|
||||
<SimpleGrid
|
||||
w="full"
|
||||
justifyContent="space-between"
|
||||
alignItems="flex-start"
|
||||
fontSize="sm"
|
||||
columns={{ base: 2, md: 4 }}
|
||||
>
|
||||
<SelectedModelLabeledInfo label="Context Window" info={model.contextWindow} />
|
||||
{model.promptTokenPrice && (
|
||||
<SelectedModelLabeledInfo
|
||||
label="Input"
|
||||
info={
|
||||
<Text>
|
||||
${(model.promptTokenPrice * 1000).toFixed(3)}
|
||||
<Text color="gray.500"> / 1K tokens</Text>
|
||||
</Text>
|
||||
}
|
||||
/>
|
||||
)}
|
||||
{model.completionTokenPrice && (
|
||||
<SelectedModelLabeledInfo
|
||||
label="Output"
|
||||
info={
|
||||
<Text>
|
||||
${(model.completionTokenPrice * 1000).toFixed(3)}
|
||||
<Text color="gray.500"> / 1K tokens</Text>
|
||||
</Text>
|
||||
}
|
||||
/>
|
||||
)}
|
||||
{model.pricePerSecond && (
|
||||
<SelectedModelLabeledInfo
|
||||
label="Price"
|
||||
info={
|
||||
<Text>
|
||||
${model.pricePerSecond.toFixed(3)}
|
||||
<Text color="gray.500"> / second</Text>
|
||||
</Text>
|
||||
}
|
||||
/>
|
||||
)}
|
||||
<SelectedModelLabeledInfo label="Speed" info={<Text>{model.speed}</Text>} />
|
||||
</SimpleGrid>
|
||||
</VStack>
|
||||
</VStack>
|
||||
);
|
||||
};
|
||||
|
||||
const SelectedModelLabeledInfo = ({
|
||||
label,
|
||||
info,
|
||||
...props
|
||||
}: {
|
||||
label: string;
|
||||
info: string | number | React.ReactElement;
|
||||
} & StackProps) => (
|
||||
<GridItem>
|
||||
<VStack alignItems="flex-start" {...props}>
|
||||
<Text fontWeight="bold">{label}</Text>
|
||||
<Text>{info}</Text>
|
||||
</VStack>
|
||||
</GridItem>
|
||||
);
|
||||
77
src/components/ExperimentSettingsDrawer/DeleteButton.tsx
Normal file
77
src/components/ExperimentSettingsDrawer/DeleteButton.tsx
Normal file
@@ -0,0 +1,77 @@
|
||||
import {
|
||||
Button,
|
||||
Icon,
|
||||
AlertDialog,
|
||||
AlertDialogBody,
|
||||
AlertDialogFooter,
|
||||
AlertDialogHeader,
|
||||
AlertDialogContent,
|
||||
AlertDialogOverlay,
|
||||
useDisclosure,
|
||||
Text,
|
||||
} from "@chakra-ui/react";
|
||||
|
||||
import { useRouter } from "next/router";
|
||||
import { useRef } from "react";
|
||||
import { BsTrash } from "react-icons/bs";
|
||||
import { api } from "~/utils/api";
|
||||
import { useExperiment, useHandledAsyncCallback } from "~/utils/hooks";
|
||||
|
||||
export const DeleteButton = () => {
|
||||
const experiment = useExperiment();
|
||||
const mutation = api.experiments.delete.useMutation();
|
||||
const utils = api.useContext();
|
||||
const router = useRouter();
|
||||
|
||||
const { isOpen, onOpen, onClose } = useDisclosure();
|
||||
const cancelRef = useRef<HTMLButtonElement>(null);
|
||||
|
||||
const [onDeleteConfirm] = useHandledAsyncCallback(async () => {
|
||||
if (!experiment.data?.id) return;
|
||||
await mutation.mutateAsync({ id: experiment.data.id });
|
||||
await utils.experiments.list.invalidate();
|
||||
await router.push({ pathname: "/experiments" });
|
||||
onClose();
|
||||
}, [mutation, experiment.data?.id, router]);
|
||||
|
||||
return (
|
||||
<>
|
||||
<Button
|
||||
size="sm"
|
||||
variant={{ base: "outline", lg: "ghost" }}
|
||||
colorScheme="red"
|
||||
fontWeight="normal"
|
||||
onClick={onOpen}
|
||||
>
|
||||
<Icon as={BsTrash} boxSize={4} />
|
||||
<Text display={{ base: "none", lg: "block" }} ml={2}>
|
||||
Delete Experiment
|
||||
</Text>
|
||||
</Button>
|
||||
|
||||
<AlertDialog isOpen={isOpen} leastDestructiveRef={cancelRef} onClose={onClose}>
|
||||
<AlertDialogOverlay>
|
||||
<AlertDialogContent>
|
||||
<AlertDialogHeader fontSize="lg" fontWeight="bold">
|
||||
Delete Experiment
|
||||
</AlertDialogHeader>
|
||||
|
||||
<AlertDialogBody>
|
||||
If you delete this experiment all the associated prompts and scenarios will be deleted
|
||||
as well. Are you sure?
|
||||
</AlertDialogBody>
|
||||
|
||||
<AlertDialogFooter>
|
||||
<Button ref={cancelRef} onClick={onClose}>
|
||||
Cancel
|
||||
</Button>
|
||||
<Button colorScheme="red" onClick={onDeleteConfirm} ml={3}>
|
||||
Delete
|
||||
</Button>
|
||||
</AlertDialogFooter>
|
||||
</AlertDialogContent>
|
||||
</AlertDialogOverlay>
|
||||
</AlertDialog>
|
||||
</>
|
||||
);
|
||||
};
|
||||
@@ -6,13 +6,14 @@ import {
|
||||
DrawerHeader,
|
||||
DrawerOverlay,
|
||||
Heading,
|
||||
Stack,
|
||||
VStack,
|
||||
} from "@chakra-ui/react";
|
||||
import EditScenarioVars from "./EditScenarioVars";
|
||||
import EditEvaluations from "./EditEvaluations";
|
||||
import EditScenarioVars from "../OutputsTable/EditScenarioVars";
|
||||
import EditEvaluations from "../OutputsTable/EditEvaluations";
|
||||
import { useAppStore } from "~/state/store";
|
||||
import { DeleteButton } from "./DeleteButton";
|
||||
|
||||
export default function SettingsDrawer() {
|
||||
export default function ExperimentSettingsDrawer() {
|
||||
const isOpen = useAppStore((state) => state.drawerOpen);
|
||||
const closeDrawer = useAppStore((state) => state.closeDrawer);
|
||||
|
||||
@@ -22,13 +23,16 @@ export default function SettingsDrawer() {
|
||||
<DrawerContent>
|
||||
<DrawerCloseButton />
|
||||
<DrawerHeader>
|
||||
<Heading size="md">Settings</Heading>
|
||||
<Heading size="md">Experiment Settings</Heading>
|
||||
</DrawerHeader>
|
||||
<DrawerBody>
|
||||
<Stack spacing={6}>
|
||||
<EditScenarioVars />
|
||||
<EditEvaluations />
|
||||
</Stack>
|
||||
<DrawerBody h="full" pb={4}>
|
||||
<VStack h="full" justifyContent="space-between">
|
||||
<VStack spacing={6}>
|
||||
<EditScenarioVars />
|
||||
<EditEvaluations />
|
||||
</VStack>
|
||||
<DeleteButton />
|
||||
</VStack>
|
||||
</DrawerBody>
|
||||
</DrawerContent>
|
||||
</Drawer>
|
||||
57
src/components/OutputsTable/AddVariantButton.tsx
Normal file
57
src/components/OutputsTable/AddVariantButton.tsx
Normal file
@@ -0,0 +1,57 @@
|
||||
import { Box, Flex, Icon, Spinner } from "@chakra-ui/react";
|
||||
import { BsPlus } from "react-icons/bs";
|
||||
import { Text } from "@chakra-ui/react";
|
||||
import { api } from "~/utils/api";
|
||||
import {
|
||||
useExperiment,
|
||||
useExperimentAccess,
|
||||
useHandledAsyncCallback,
|
||||
useVisibleScenarioIds,
|
||||
} from "~/utils/hooks";
|
||||
import { cellPadding } from "../constants";
|
||||
import { ActionButton } from "./ScenariosHeader";
|
||||
|
||||
export default function AddVariantButton() {
|
||||
const experiment = useExperiment();
|
||||
const mutation = api.promptVariants.create.useMutation();
|
||||
const utils = api.useContext();
|
||||
const visibleScenarios = useVisibleScenarioIds();
|
||||
|
||||
const [onClick, loading] = useHandledAsyncCallback(async () => {
|
||||
if (!experiment.data) return;
|
||||
await mutation.mutateAsync({
|
||||
experimentId: experiment.data.id,
|
||||
streamScenarios: visibleScenarios,
|
||||
});
|
||||
await utils.promptVariants.list.invalidate();
|
||||
}, [mutation]);
|
||||
|
||||
const { canModify } = useExperimentAccess();
|
||||
if (!canModify) return <Box w={cellPadding.x} />;
|
||||
|
||||
return (
|
||||
<Flex w="100%" justifyContent="flex-end">
|
||||
<ActionButton
|
||||
onClick={onClick}
|
||||
py={5}
|
||||
leftIcon={<Icon as={loading ? Spinner : BsPlus} boxSize={6} mr={loading ? 1 : 0} />}
|
||||
>
|
||||
<Text display={{ base: "none", md: "flex" }}>Add Variant</Text>
|
||||
</ActionButton>
|
||||
{/* <Button
|
||||
alignItems="center"
|
||||
justifyContent="center"
|
||||
fontWeight="normal"
|
||||
bgColor="transparent"
|
||||
_hover={{ bgColor: "gray.100" }}
|
||||
px={cellPadding.x}
|
||||
onClick={onClick}
|
||||
height="unset"
|
||||
minH={headerMinHeight}
|
||||
>
|
||||
<Icon as={loading ? Spinner : BsPlus} boxSize={6} mr={loading ? 1 : 0} />
|
||||
<Text display={{ base: "none", md: "flex" }}>Add Variant</Text>
|
||||
</Button> */}
|
||||
</Flex>
|
||||
);
|
||||
}
|
||||
47
src/components/OutputsTable/FloatingLabelInput.tsx
Normal file
47
src/components/OutputsTable/FloatingLabelInput.tsx
Normal file
@@ -0,0 +1,47 @@
|
||||
import { FormLabel, FormControl, type TextareaProps } from "@chakra-ui/react";
|
||||
import { useState } from "react";
|
||||
import AutoResizeTextArea from "../AutoResizeTextArea";
|
||||
|
||||
export const FloatingLabelInput = ({
|
||||
label,
|
||||
value,
|
||||
...props
|
||||
}: { label: string; value: string } & TextareaProps) => {
|
||||
const [isFocused, setIsFocused] = useState(false);
|
||||
|
||||
return (
|
||||
<FormControl position="relative">
|
||||
<FormLabel
|
||||
position="absolute"
|
||||
left="10px"
|
||||
top={isFocused || !!value ? 0 : 3}
|
||||
transform={isFocused || !!value ? "translateY(-50%)" : "translateY(0)"}
|
||||
fontSize={isFocused || !!value ? "12px" : "16px"}
|
||||
transition="all 0.15s"
|
||||
zIndex="5"
|
||||
bg="white"
|
||||
px={1}
|
||||
lineHeight="1"
|
||||
pointerEvents="none"
|
||||
color={isFocused ? "blue.500" : "gray.500"}
|
||||
>
|
||||
{label}
|
||||
</FormLabel>
|
||||
<AutoResizeTextArea
|
||||
px={3}
|
||||
pt={3}
|
||||
pb={2}
|
||||
onFocus={() => setIsFocused(true)}
|
||||
onBlur={() => setIsFocused(false)}
|
||||
borderRadius="md"
|
||||
borderColor={isFocused ? "blue.500" : "gray.400"}
|
||||
autoComplete="off"
|
||||
value={value}
|
||||
maxHeight={32}
|
||||
overflowY="auto"
|
||||
overflowX="hidden"
|
||||
{...props}
|
||||
/>
|
||||
</FormControl>
|
||||
);
|
||||
};
|
||||
@@ -1,57 +0,0 @@
|
||||
import { Button, type ButtonProps, HStack, Spinner, Icon } from "@chakra-ui/react";
|
||||
import { BsPlus } from "react-icons/bs";
|
||||
import { api } from "~/utils/api";
|
||||
import { useExperiment, useExperimentAccess, useHandledAsyncCallback } from "~/utils/hooks";
|
||||
|
||||
// Extracted Button styling into reusable component
|
||||
const StyledButton = ({ children, onClick }: ButtonProps) => (
|
||||
<Button
|
||||
fontWeight="normal"
|
||||
bgColor="transparent"
|
||||
_hover={{ bgColor: "gray.100" }}
|
||||
px={2}
|
||||
onClick={onClick}
|
||||
>
|
||||
{children}
|
||||
</Button>
|
||||
);
|
||||
|
||||
export default function NewScenarioButton() {
|
||||
const { canModify } = useExperimentAccess();
|
||||
|
||||
const experiment = useExperiment();
|
||||
const mutation = api.scenarios.create.useMutation();
|
||||
const utils = api.useContext();
|
||||
|
||||
const [onClick] = useHandledAsyncCallback(async () => {
|
||||
if (!experiment.data) return;
|
||||
await mutation.mutateAsync({
|
||||
experimentId: experiment.data.id,
|
||||
});
|
||||
await utils.scenarios.list.invalidate();
|
||||
}, [mutation]);
|
||||
|
||||
const [onAutogenerate, autogenerating] = useHandledAsyncCallback(async () => {
|
||||
if (!experiment.data) return;
|
||||
await mutation.mutateAsync({
|
||||
experimentId: experiment.data.id,
|
||||
autogenerate: true,
|
||||
});
|
||||
await utils.scenarios.list.invalidate();
|
||||
}, [mutation]);
|
||||
|
||||
if (!canModify) return null;
|
||||
|
||||
return (
|
||||
<HStack spacing={2}>
|
||||
<StyledButton onClick={onClick}>
|
||||
<Icon as={BsPlus} boxSize={6} />
|
||||
Add Scenario
|
||||
</StyledButton>
|
||||
<StyledButton onClick={onAutogenerate}>
|
||||
<Icon as={autogenerating ? Spinner : BsPlus} boxSize={6} mr={autogenerating ? 1 : 0} />
|
||||
Autogenerate Scenario
|
||||
</StyledButton>
|
||||
</HStack>
|
||||
);
|
||||
}
|
||||
@@ -1,40 +0,0 @@
|
||||
import { Box, Button, Icon, Spinner, Text } from "@chakra-ui/react";
|
||||
import { BsPlus } from "react-icons/bs";
|
||||
import { api } from "~/utils/api";
|
||||
import { useExperiment, useExperimentAccess, useHandledAsyncCallback } from "~/utils/hooks";
|
||||
import { cellPadding, headerMinHeight } from "../constants";
|
||||
|
||||
export default function NewVariantButton() {
|
||||
const experiment = useExperiment();
|
||||
const mutation = api.promptVariants.create.useMutation();
|
||||
const utils = api.useContext();
|
||||
|
||||
const [onClick, loading] = useHandledAsyncCallback(async () => {
|
||||
if (!experiment.data) return;
|
||||
await mutation.mutateAsync({
|
||||
experimentId: experiment.data.id,
|
||||
});
|
||||
await utils.promptVariants.list.invalidate();
|
||||
}, [mutation]);
|
||||
|
||||
const { canModify } = useExperimentAccess();
|
||||
if (!canModify) return <Box w={cellPadding.x} />;
|
||||
|
||||
return (
|
||||
<Button
|
||||
w="100%"
|
||||
alignItems="center"
|
||||
justifyContent="center"
|
||||
fontWeight="normal"
|
||||
bgColor="transparent"
|
||||
_hover={{ bgColor: "gray.100" }}
|
||||
px={cellPadding.x}
|
||||
onClick={onClick}
|
||||
height="unset"
|
||||
minH={headerMinHeight}
|
||||
>
|
||||
<Icon as={loading ? Spinner : BsPlus} boxSize={6} mr={loading ? 1 : 0} />
|
||||
<Text display={{ base: "none", md: "flex" }}>Add Variant</Text>
|
||||
</Button>
|
||||
);
|
||||
}
|
||||
@@ -6,11 +6,11 @@ import SyntaxHighlighter from "react-syntax-highlighter";
|
||||
import { docco } from "react-syntax-highlighter/dist/cjs/styles/hljs";
|
||||
import stringify from "json-stringify-pretty-compact";
|
||||
import { type ReactElement, useState, useEffect } from "react";
|
||||
import { type ChatCompletion } from "openai/resources/chat";
|
||||
import useSocket from "~/utils/useSocket";
|
||||
import { OutputStats } from "./OutputStats";
|
||||
import { ErrorHandler } from "./ErrorHandler";
|
||||
import { CellOptions } from "./CellOptions";
|
||||
import frontendModelProviders from "~/modelProviders/frontendModelProviders";
|
||||
|
||||
export default function OutputCell({
|
||||
scenario,
|
||||
@@ -33,18 +33,19 @@ export default function OutputCell({
|
||||
|
||||
if (!templateHasVariables) disabledReason = "Add a value to the scenario variables to see output";
|
||||
|
||||
// if (variant.config === null || Object.keys(variant.config).length === 0)
|
||||
// disabledReason = "Save your prompt variant to see output";
|
||||
|
||||
const [refetchInterval, setRefetchInterval] = useState(0);
|
||||
const { data: cell, isLoading: queryLoading } = api.scenarioVariantCells.get.useQuery(
|
||||
{ scenarioId: scenario.id, variantId: variant.id },
|
||||
{ refetchInterval },
|
||||
);
|
||||
|
||||
const { mutateAsync: hardRefetchMutate, isLoading: refetchingOutput } =
|
||||
api.scenarioVariantCells.forceRefetch.useMutation();
|
||||
const [hardRefetch] = useHandledAsyncCallback(async () => {
|
||||
const provider =
|
||||
frontendModelProviders[variant.modelProvider as keyof typeof frontendModelProviders];
|
||||
|
||||
type OutputSchema = Parameters<typeof provider.normalizeOutput>[0];
|
||||
|
||||
const { mutateAsync: hardRefetchMutate } = api.scenarioVariantCells.forceRefetch.useMutation();
|
||||
const [hardRefetch, hardRefetching] = useHandledAsyncCallback(async () => {
|
||||
await hardRefetchMutate({ scenarioId: scenario.id, variantId: variant.id });
|
||||
await utils.scenarioVariantCells.get.invalidate({
|
||||
scenarioId: scenario.id,
|
||||
@@ -55,20 +56,19 @@ export default function OutputCell({
|
||||
});
|
||||
}, [hardRefetchMutate, scenario.id, variant.id]);
|
||||
|
||||
const fetchingOutput = queryLoading || refetchingOutput;
|
||||
const fetchingOutput = queryLoading || hardRefetching;
|
||||
|
||||
const awaitingOutput =
|
||||
!cell ||
|
||||
cell.retrievalStatus === "PENDING" ||
|
||||
cell.retrievalStatus === "IN_PROGRESS" ||
|
||||
refetchingOutput;
|
||||
hardRefetching;
|
||||
useEffect(() => setRefetchInterval(awaitingOutput ? 1000 : 0), [awaitingOutput]);
|
||||
|
||||
const modelOutput = cell?.modelOutput;
|
||||
|
||||
// Disconnect from socket if we're not streaming anymore
|
||||
const streamedMessage = useSocket(cell?.streamingChannel);
|
||||
const streamedContent = streamedMessage?.choices?.[0]?.message?.content;
|
||||
// TODO: disconnect from socket if we're not streaming anymore
|
||||
const streamedMessage = useSocket<OutputSchema>(cell?.id);
|
||||
|
||||
if (!vars) return null;
|
||||
|
||||
@@ -81,25 +81,30 @@ export default function OutputCell({
|
||||
</Center>
|
||||
);
|
||||
|
||||
if (!cell && !fetchingOutput) return <Text color="gray.500">Error retrieving output</Text>;
|
||||
if (!cell && !fetchingOutput)
|
||||
return (
|
||||
<VStack>
|
||||
<CellOptions refetchingOutput={hardRefetching} refetchOutput={hardRefetch} />
|
||||
<Text color="gray.500">Error retrieving output</Text>
|
||||
</VStack>
|
||||
);
|
||||
|
||||
if (cell && cell.errorMessage) {
|
||||
return <ErrorHandler cell={cell} refetchOutput={hardRefetch} />;
|
||||
return (
|
||||
<VStack>
|
||||
<CellOptions refetchingOutput={hardRefetching} refetchOutput={hardRefetch} />
|
||||
<ErrorHandler cell={cell} refetchOutput={hardRefetch} />
|
||||
</VStack>
|
||||
);
|
||||
}
|
||||
|
||||
const response = modelOutput?.output as unknown as ChatCompletion;
|
||||
const message = response?.choices?.[0]?.message;
|
||||
|
||||
if (modelOutput && message?.function_call) {
|
||||
const rawArgs = message.function_call.arguments ?? "null";
|
||||
let parsedArgs: string;
|
||||
try {
|
||||
parsedArgs = JSON.parse(rawArgs);
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
} catch (e: any) {
|
||||
parsedArgs = `Failed to parse arguments as JSON: '${rawArgs}' ERROR: ${e.message as string}`;
|
||||
}
|
||||
const normalizedOutput = modelOutput
|
||||
? provider.normalizeOutput(modelOutput.output)
|
||||
: streamedMessage
|
||||
? provider.normalizeOutput(streamedMessage)
|
||||
: null;
|
||||
|
||||
if (modelOutput && normalizedOutput?.type === "json") {
|
||||
return (
|
||||
<VStack
|
||||
w="100%"
|
||||
@@ -110,7 +115,7 @@ export default function OutputCell({
|
||||
justifyContent="space-between"
|
||||
>
|
||||
<VStack w="full" flex={1} spacing={0}>
|
||||
<CellOptions refetchingOutput={refetchingOutput} refetchOutput={hardRefetch} />
|
||||
<CellOptions refetchingOutput={hardRefetching} refetchOutput={hardRefetch} />
|
||||
<SyntaxHighlighter
|
||||
customStyle={{ overflowX: "unset", width: "100%", flex: 1 }}
|
||||
language="json"
|
||||
@@ -120,13 +125,7 @@ export default function OutputCell({
|
||||
}}
|
||||
wrapLines
|
||||
>
|
||||
{stringify(
|
||||
{
|
||||
function: message.function_call.name,
|
||||
args: parsedArgs,
|
||||
},
|
||||
{ maxLength: 40 },
|
||||
)}
|
||||
{stringify(normalizedOutput.value, { maxLength: 40 })}
|
||||
</SyntaxHighlighter>
|
||||
</VStack>
|
||||
<OutputStats modelOutput={modelOutput} scenario={scenario} />
|
||||
@@ -134,13 +133,12 @@ export default function OutputCell({
|
||||
);
|
||||
}
|
||||
|
||||
const contentToDisplay =
|
||||
message?.content ?? streamedContent ?? JSON.stringify(modelOutput?.output);
|
||||
const contentToDisplay = (normalizedOutput?.type === "text" && normalizedOutput.value) || "";
|
||||
|
||||
return (
|
||||
<VStack w="100%" h="100%" justifyContent="space-between" whiteSpace="pre-wrap">
|
||||
<VStack w="full" alignItems="flex-start" spacing={0}>
|
||||
<CellOptions refetchingOutput={refetchingOutput} refetchOutput={hardRefetch} />
|
||||
<CellOptions refetchingOutput={hardRefetching} refetchOutput={hardRefetch} />
|
||||
<Text>{contentToDisplay}</Text>
|
||||
</VStack>
|
||||
{modelOutput && <OutputStats modelOutput={modelOutput} scenario={scenario} />}
|
||||
|
||||
@@ -22,7 +22,7 @@ export const OutputStats = ({
|
||||
return (
|
||||
<HStack w="full" align="center" color="gray.500" fontSize="2xs" mt={{ base: 0, md: 1 }}>
|
||||
<HStack flex={1}>
|
||||
{modelOutput.outputEvaluation.map((evaluation) => {
|
||||
{modelOutput.outputEvaluations.map((evaluation) => {
|
||||
const passed = evaluation.result > 0.5;
|
||||
return (
|
||||
<Tooltip
|
||||
|
||||
@@ -9,7 +9,7 @@ import { Box, Button, Flex, HStack, Icon, Spinner, Stack, Tooltip, VStack } from
|
||||
import { cellPadding } from "../constants";
|
||||
import { BsX } from "react-icons/bs";
|
||||
import { RiDraggable } from "react-icons/ri";
|
||||
import AutoResizeTextArea from "../AutoResizeTextArea";
|
||||
import { FloatingLabelInput } from "./FloatingLabelInput";
|
||||
|
||||
export default function ScenarioEditor({
|
||||
scenario,
|
||||
@@ -74,9 +74,9 @@ export default function ScenarioEditor({
|
||||
return (
|
||||
<HStack
|
||||
alignItems="flex-start"
|
||||
pr={cellPadding.x}
|
||||
px={cellPadding.x}
|
||||
py={cellPadding.y}
|
||||
pl={canModify ? 0 : cellPadding.x}
|
||||
spacing={0}
|
||||
height="100%"
|
||||
draggable={!variableInputHovered}
|
||||
onDragStart={(e) => {
|
||||
@@ -96,42 +96,43 @@ export default function ScenarioEditor({
|
||||
onDrop={onReorder}
|
||||
backgroundColor={isDragTarget ? "gray.100" : "transparent"}
|
||||
>
|
||||
{canModify && (
|
||||
<Stack alignSelf="flex-start" opacity={props.hovered ? 1 : 0} spacing={0}>
|
||||
{props.canHide && (
|
||||
<>
|
||||
<Tooltip label="Hide scenario" hasArrow>
|
||||
{/* for some reason the tooltip can't position itself properly relative to the icon without the wrapping box */}
|
||||
<Button
|
||||
variant="unstyled"
|
||||
color="gray.400"
|
||||
height="unset"
|
||||
width="unset"
|
||||
minW="unset"
|
||||
onClick={onHide}
|
||||
_hover={{
|
||||
color: "gray.800",
|
||||
cursor: "pointer",
|
||||
}}
|
||||
>
|
||||
<Icon as={hidingInProgress ? Spinner : BsX} boxSize={6} />
|
||||
</Button>
|
||||
</Tooltip>
|
||||
<Icon
|
||||
as={RiDraggable}
|
||||
boxSize={6}
|
||||
color="gray.400"
|
||||
_hover={{ color: "gray.800", cursor: "pointer" }}
|
||||
/>
|
||||
</>
|
||||
)}
|
||||
{canModify && props.canHide && (
|
||||
<Stack
|
||||
alignSelf="flex-start"
|
||||
opacity={props.hovered ? 1 : 0}
|
||||
spacing={0}
|
||||
ml={-cellPadding.x}
|
||||
>
|
||||
<Tooltip label="Hide scenario" hasArrow>
|
||||
{/* for some reason the tooltip can't position itself properly relative to the icon without the wrapping box */}
|
||||
<Button
|
||||
variant="unstyled"
|
||||
color="gray.400"
|
||||
height="unset"
|
||||
width="unset"
|
||||
minW="unset"
|
||||
onClick={onHide}
|
||||
_hover={{
|
||||
color: "gray.800",
|
||||
cursor: "pointer",
|
||||
}}
|
||||
>
|
||||
<Icon as={hidingInProgress ? Spinner : BsX} boxSize={hidingInProgress ? 4 : 6} />
|
||||
</Button>
|
||||
</Tooltip>
|
||||
<Icon
|
||||
as={RiDraggable}
|
||||
boxSize={6}
|
||||
color="gray.400"
|
||||
_hover={{ color: "gray.800", cursor: "pointer" }}
|
||||
/>
|
||||
</Stack>
|
||||
)}
|
||||
|
||||
{variableLabels.length === 0 ? (
|
||||
<Box color="gray.500">{vars.data ? "No scenario variables configured" : "Loading..."}</Box>
|
||||
) : (
|
||||
<VStack spacing={1}>
|
||||
<VStack spacing={4} flex={1} py={2}>
|
||||
{variableLabels.map((key) => {
|
||||
const value = values[key] ?? "";
|
||||
const layoutDirection = value.length > 20 ? "column" : "row";
|
||||
@@ -143,31 +144,14 @@ export default function ScenarioEditor({
|
||||
flexWrap="wrap"
|
||||
width="full"
|
||||
>
|
||||
<Box
|
||||
bgColor="blue.100"
|
||||
color="blue.600"
|
||||
px={1}
|
||||
my="3px"
|
||||
fontSize="xs"
|
||||
fontWeight="bold"
|
||||
>
|
||||
{key}
|
||||
</Box>
|
||||
<AutoResizeTextArea
|
||||
px={2}
|
||||
py={1}
|
||||
placeholder="empty"
|
||||
borderRadius="sm"
|
||||
fontSize="sm"
|
||||
lineHeight={1.2}
|
||||
value={value}
|
||||
<FloatingLabelInput
|
||||
label={key}
|
||||
isDisabled={!canModify}
|
||||
_disabled={{ opacity: 1, cursor: "default" }}
|
||||
style={{ width: "100%" }}
|
||||
value={value}
|
||||
onChange={(e) => {
|
||||
setValues((prev) => ({ ...prev, [key]: e.target.value }));
|
||||
}}
|
||||
maxH="32"
|
||||
overflowY="auto"
|
||||
onKeyDown={(e) => {
|
||||
if (e.key === "Enter" && (e.metaKey || e.ctrlKey)) {
|
||||
e.preventDefault();
|
||||
@@ -175,12 +159,6 @@ export default function ScenarioEditor({
|
||||
onSave();
|
||||
}
|
||||
}}
|
||||
resize="none"
|
||||
overflow="hidden"
|
||||
flex={layoutDirection === "row" ? 1 : undefined}
|
||||
borderColor={hasChanged ? "blue.300" : "transparent"}
|
||||
_hover={{ borderColor: "gray.300" }}
|
||||
_focus={{ borderColor: "blue.500", outline: "none", bg: "white" }}
|
||||
onMouseEnter={() => setVariableInputHovered(true)}
|
||||
onMouseLeave={() => setVariableInputHovered(false)}
|
||||
/>
|
||||
|
||||
74
src/components/OutputsTable/ScenarioPaginator.tsx
Normal file
74
src/components/OutputsTable/ScenarioPaginator.tsx
Normal file
@@ -0,0 +1,74 @@
|
||||
import { Box, HStack, IconButton } from "@chakra-ui/react";
|
||||
import {
|
||||
BsChevronDoubleLeft,
|
||||
BsChevronDoubleRight,
|
||||
BsChevronLeft,
|
||||
BsChevronRight,
|
||||
} from "react-icons/bs";
|
||||
import { usePage, useScenarios } from "~/utils/hooks";
|
||||
|
||||
const ScenarioPaginator = () => {
|
||||
const [page, setPage] = usePage();
|
||||
const { data } = useScenarios();
|
||||
|
||||
if (!data) return null;
|
||||
|
||||
const { scenarios, startIndex, lastPage, count } = data;
|
||||
|
||||
const nextPage = () => {
|
||||
if (page < lastPage) {
|
||||
setPage(page + 1, "replace");
|
||||
}
|
||||
};
|
||||
|
||||
const prevPage = () => {
|
||||
if (page > 1) {
|
||||
setPage(page - 1, "replace");
|
||||
}
|
||||
};
|
||||
|
||||
const goToLastPage = () => setPage(lastPage, "replace");
|
||||
const goToFirstPage = () => setPage(1, "replace");
|
||||
|
||||
return (
|
||||
<HStack pt={4}>
|
||||
<IconButton
|
||||
variant="ghost"
|
||||
size="sm"
|
||||
onClick={goToFirstPage}
|
||||
isDisabled={page === 1}
|
||||
aria-label="Go to first page"
|
||||
icon={<BsChevronDoubleLeft />}
|
||||
/>
|
||||
<IconButton
|
||||
variant="ghost"
|
||||
size="sm"
|
||||
onClick={prevPage}
|
||||
isDisabled={page === 1}
|
||||
aria-label="Previous page"
|
||||
icon={<BsChevronLeft />}
|
||||
/>
|
||||
<Box>
|
||||
{startIndex}-{startIndex + scenarios.length - 1} / {count}
|
||||
</Box>
|
||||
<IconButton
|
||||
variant="ghost"
|
||||
size="sm"
|
||||
onClick={nextPage}
|
||||
isDisabled={page === lastPage}
|
||||
aria-label="Next page"
|
||||
icon={<BsChevronRight />}
|
||||
/>
|
||||
<IconButton
|
||||
variant="ghost"
|
||||
size="sm"
|
||||
onClick={goToLastPage}
|
||||
isDisabled={page === lastPage}
|
||||
aria-label="Go to last page"
|
||||
icon={<BsChevronDoubleRight />}
|
||||
/>
|
||||
</HStack>
|
||||
);
|
||||
};
|
||||
|
||||
export default ScenarioPaginator;
|
||||
@@ -4,11 +4,13 @@ import { cellPadding } from "../constants";
|
||||
import OutputCell from "./OutputCell/OutputCell";
|
||||
import ScenarioEditor from "./ScenarioEditor";
|
||||
import type { PromptVariant, Scenario } from "./types";
|
||||
import { borders } from "./styles";
|
||||
|
||||
const ScenarioRow = (props: {
|
||||
scenario: Scenario;
|
||||
variants: PromptVariant[];
|
||||
canHide: boolean;
|
||||
rowStart: number;
|
||||
}) => {
|
||||
const [isHovered, setIsHovered] = useState(false);
|
||||
|
||||
@@ -21,15 +23,21 @@ const ScenarioRow = (props: {
|
||||
onMouseLeave={() => setIsHovered(false)}
|
||||
sx={isHovered ? highlightStyle : undefined}
|
||||
borderLeftWidth={1}
|
||||
{...borders}
|
||||
rowStart={props.rowStart}
|
||||
colStart={1}
|
||||
>
|
||||
<ScenarioEditor scenario={props.scenario} hovered={isHovered} canHide={props.canHide} />
|
||||
</GridItem>
|
||||
{props.variants.map((variant) => (
|
||||
{props.variants.map((variant, i) => (
|
||||
<GridItem
|
||||
key={variant.id}
|
||||
onMouseEnter={() => setIsHovered(true)}
|
||||
onMouseLeave={() => setIsHovered(false)}
|
||||
sx={isHovered ? highlightStyle : undefined}
|
||||
rowStart={props.rowStart}
|
||||
colStart={i + 2}
|
||||
{...borders}
|
||||
>
|
||||
<Box h="100%" w="100%" px={cellPadding.x} py={cellPadding.y}>
|
||||
<OutputCell key={variant.id} scenario={props.scenario} variant={variant} />
|
||||
|
||||
@@ -1,52 +1,82 @@
|
||||
import { Button, GridItem, HStack, Heading } from "@chakra-ui/react";
|
||||
import {
|
||||
Button,
|
||||
type ButtonProps,
|
||||
HStack,
|
||||
Text,
|
||||
Icon,
|
||||
Menu,
|
||||
MenuButton,
|
||||
MenuList,
|
||||
MenuItem,
|
||||
IconButton,
|
||||
Spinner,
|
||||
} from "@chakra-ui/react";
|
||||
import { cellPadding } from "../constants";
|
||||
import { useElementDimensions, useExperimentAccess } from "~/utils/hooks";
|
||||
import { stickyHeaderStyle } from "./styles";
|
||||
import { BsPencil } from "react-icons/bs";
|
||||
import {
|
||||
useExperiment,
|
||||
useExperimentAccess,
|
||||
useHandledAsyncCallback,
|
||||
useScenarios,
|
||||
} from "~/utils/hooks";
|
||||
import { BsGear, BsPencil, BsPlus, BsStars } from "react-icons/bs";
|
||||
import { useAppStore } from "~/state/store";
|
||||
import { api } from "~/utils/api";
|
||||
|
||||
export const ScenariosHeader = ({
|
||||
headerRows,
|
||||
numScenarios,
|
||||
}: {
|
||||
headerRows: number;
|
||||
numScenarios: number;
|
||||
}) => {
|
||||
export const ActionButton = (props: ButtonProps) => (
|
||||
<Button size="sm" variant="ghost" color="gray.600" {...props} />
|
||||
);
|
||||
|
||||
export const ScenariosHeader = () => {
|
||||
const openDrawer = useAppStore((s) => s.openDrawer);
|
||||
const { canModify } = useExperimentAccess();
|
||||
const scenarios = useScenarios();
|
||||
|
||||
const [ref, dimensions] = useElementDimensions();
|
||||
const topValue = dimensions ? `-${dimensions.height - 24}px` : "-455px";
|
||||
const experiment = useExperiment();
|
||||
const createScenarioMutation = api.scenarios.create.useMutation();
|
||||
const utils = api.useContext();
|
||||
|
||||
const [onAddScenario, loading] = useHandledAsyncCallback(
|
||||
async (autogenerate: boolean) => {
|
||||
if (!experiment.data) return;
|
||||
await createScenarioMutation.mutateAsync({
|
||||
experimentId: experiment.data.id,
|
||||
autogenerate,
|
||||
});
|
||||
await utils.scenarios.list.invalidate();
|
||||
},
|
||||
[createScenarioMutation],
|
||||
);
|
||||
|
||||
return (
|
||||
<GridItem
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
ref={ref as any}
|
||||
display="flex"
|
||||
alignItems="flex-end"
|
||||
rowSpan={headerRows}
|
||||
px={cellPadding.x}
|
||||
py={cellPadding.y}
|
||||
// Only display the part of the grid item that has content
|
||||
sx={{ ...stickyHeaderStyle, top: topValue }}
|
||||
>
|
||||
<HStack w="100%">
|
||||
<Heading size="xs" fontWeight="bold" flex={1}>
|
||||
Scenarios ({numScenarios})
|
||||
</Heading>
|
||||
{canModify && (
|
||||
<Button
|
||||
size="xs"
|
||||
<HStack w="100%" pb={cellPadding.y} pt={0} align="center" spacing={0}>
|
||||
<Text fontSize={16} fontWeight="bold">
|
||||
Scenarios ({scenarios.data?.count})
|
||||
</Text>
|
||||
{canModify && (
|
||||
<Menu>
|
||||
<MenuButton
|
||||
as={IconButton}
|
||||
mt={1}
|
||||
variant="ghost"
|
||||
color="gray.500"
|
||||
aria-label="Edit"
|
||||
leftIcon={<BsPencil />}
|
||||
onClick={openDrawer}
|
||||
>
|
||||
Edit Vars
|
||||
</Button>
|
||||
)}
|
||||
</HStack>
|
||||
</GridItem>
|
||||
aria-label="Edit Scenarios"
|
||||
icon={<Icon as={loading ? Spinner : BsGear} />}
|
||||
/>
|
||||
<MenuList fontSize="md" zIndex="dropdown" mt={-3}>
|
||||
<MenuItem
|
||||
icon={<Icon as={BsPlus} boxSize={6} mx="-5px" />}
|
||||
onClick={() => onAddScenario(false)}
|
||||
>
|
||||
Add Scenario
|
||||
</MenuItem>
|
||||
<MenuItem icon={<BsStars />} onClick={() => onAddScenario(true)}>
|
||||
Autogenerate Scenario
|
||||
</MenuItem>
|
||||
<MenuItem icon={<BsPencil />} onClick={openDrawer}>
|
||||
Edit Vars
|
||||
</MenuItem>
|
||||
</MenuList>
|
||||
</Menu>
|
||||
)}
|
||||
</HStack>
|
||||
);
|
||||
};
|
||||
|
||||
@@ -1,17 +1,52 @@
|
||||
import { Box, Button, HStack, Spinner, Tooltip, useToast, Text } from "@chakra-ui/react";
|
||||
import { useRef, useEffect, useState, useCallback } from "react";
|
||||
import { useExperimentAccess, useHandledAsyncCallback, useModifierKeyLabel } from "~/utils/hooks";
|
||||
import { type PromptVariant } from "./types";
|
||||
import { api } from "~/utils/api";
|
||||
import {
|
||||
Box,
|
||||
Button,
|
||||
HStack,
|
||||
IconButton,
|
||||
Spinner,
|
||||
Text,
|
||||
Tooltip,
|
||||
useToast,
|
||||
} from "@chakra-ui/react";
|
||||
import { useCallback, useEffect, useRef, useState } from "react";
|
||||
import { FiMaximize, FiMinimize } from "react-icons/fi";
|
||||
import { editorBackground } from "~/state/sharedVariantEditor.slice";
|
||||
import { useAppStore } from "~/state/store";
|
||||
import { api } from "~/utils/api";
|
||||
import {
|
||||
useExperimentAccess,
|
||||
useHandledAsyncCallback,
|
||||
useModifierKeyLabel,
|
||||
useVisibleScenarioIds,
|
||||
} from "~/utils/hooks";
|
||||
import { type PromptVariant } from "./types";
|
||||
|
||||
export default function VariantEditor(props: { variant: PromptVariant }) {
|
||||
const { canModify } = useExperimentAccess();
|
||||
const monaco = useAppStore.use.sharedVariantEditor.monaco();
|
||||
const editorRef = useRef<ReturnType<NonNullable<typeof monaco>["editor"]["create"]> | null>(null);
|
||||
const containerRef = useRef<HTMLDivElement | null>(null);
|
||||
const [editorId] = useState(() => `editor_${Math.random().toString(36).substring(7)}`);
|
||||
const [isChanged, setIsChanged] = useState(false);
|
||||
|
||||
const [isFullscreen, setIsFullscreen] = useState(false);
|
||||
|
||||
const toggleFullscreen = useCallback(() => {
|
||||
setIsFullscreen((prev) => !prev);
|
||||
editorRef.current?.focus();
|
||||
}, [setIsFullscreen]);
|
||||
|
||||
useEffect(() => {
|
||||
const handleEsc = (event: KeyboardEvent) => {
|
||||
if (event.key === "Escape" && isFullscreen) {
|
||||
toggleFullscreen();
|
||||
}
|
||||
};
|
||||
|
||||
window.addEventListener("keydown", handleEsc);
|
||||
return () => window.removeEventListener("keydown", handleEsc);
|
||||
}, [isFullscreen, toggleFullscreen]);
|
||||
|
||||
const lastSavedFn = props.variant.constructFn;
|
||||
|
||||
const modifierKey = useModifierKeyLabel();
|
||||
@@ -33,6 +68,7 @@ export default function VariantEditor(props: { variant: PromptVariant }) {
|
||||
const replaceVariant = api.promptVariants.replaceVariant.useMutation();
|
||||
const utils = api.useContext();
|
||||
const toast = useToast();
|
||||
const visibleScenarios = useVisibleScenarioIds();
|
||||
|
||||
const [onSave, saveInProgress] = useHandledAsyncCallback(async () => {
|
||||
if (!editorRef.current) return;
|
||||
@@ -48,13 +84,11 @@ export default function VariantEditor(props: { variant: PromptVariant }) {
|
||||
if (!model) return;
|
||||
|
||||
// Make sure the user defined the prompt with the string "prompt\w*=" somewhere
|
||||
const promptRegex = /prompt\s*=/;
|
||||
const promptRegex = /definePrompt\(/;
|
||||
if (!promptRegex.test(currentFn)) {
|
||||
console.log("no prompt");
|
||||
console.log(currentFn);
|
||||
toast({
|
||||
title: "Missing prompt",
|
||||
description: "Please define the prompt (eg. `prompt = { ...`).",
|
||||
description: "Please define the prompt (eg. `definePrompt(...`",
|
||||
status: "error",
|
||||
});
|
||||
return;
|
||||
@@ -63,6 +97,7 @@ export default function VariantEditor(props: { variant: PromptVariant }) {
|
||||
const resp = await replaceVariant.mutateAsync({
|
||||
id: props.variant.id,
|
||||
constructFn: currentFn,
|
||||
streamScenarios: visibleScenarios,
|
||||
});
|
||||
if (resp.status === "error") {
|
||||
return toast({
|
||||
@@ -101,11 +136,23 @@ export default function VariantEditor(props: { variant: PromptVariant }) {
|
||||
readOnly: !canModify,
|
||||
});
|
||||
|
||||
// Workaround because otherwise the commands only work on whatever
|
||||
// editor was loaded on the page last.
|
||||
// https://github.com/microsoft/monaco-editor/issues/2947#issuecomment-1422265201
|
||||
editorRef.current.onDidFocusEditorText(() => {
|
||||
// Workaround because otherwise the command only works on whatever
|
||||
// editor was loaded on the page last.
|
||||
// https://github.com/microsoft/monaco-editor/issues/2947#issuecomment-1422265201
|
||||
editorRef.current?.addCommand(monaco.KeyMod.CtrlCmd | monaco.KeyCode.Enter, onSave);
|
||||
editorRef.current?.addCommand(monaco.KeyMod.CtrlCmd | monaco.KeyCode.KeyS, onSave);
|
||||
|
||||
editorRef.current?.addCommand(
|
||||
monaco.KeyMod.CtrlCmd | monaco.KeyMod.Shift | monaco.KeyCode.KeyF,
|
||||
toggleFullscreen,
|
||||
);
|
||||
|
||||
// Exit fullscreen with escape
|
||||
editorRef.current?.addCommand(monaco.KeyCode.Escape, () => {
|
||||
if (isFullscreen) {
|
||||
toggleFullscreen();
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
editorRef.current.onDidChangeModelContent(checkForChanges);
|
||||
@@ -134,8 +181,40 @@ export default function VariantEditor(props: { variant: PromptVariant }) {
|
||||
}, [canModify]);
|
||||
|
||||
return (
|
||||
<Box w="100%" pos="relative">
|
||||
<div id={editorId} style={{ height: "400px", width: "100%" }}></div>
|
||||
<Box
|
||||
w="100%"
|
||||
ref={containerRef}
|
||||
sx={
|
||||
isFullscreen
|
||||
? {
|
||||
position: "fixed",
|
||||
top: 0,
|
||||
left: 0,
|
||||
right: 0,
|
||||
bottom: 0,
|
||||
}
|
||||
: { h: "400px", w: "100%" }
|
||||
}
|
||||
bgColor={editorBackground}
|
||||
zIndex={isFullscreen ? 1000 : "unset"}
|
||||
pos="relative"
|
||||
_hover={{ ".fullscreen-toggle": { opacity: 1 } }}
|
||||
>
|
||||
<Box id={editorId} w="100%" h="100%" />
|
||||
<Tooltip label={`${modifierKey} + ⇧ + F`}>
|
||||
<IconButton
|
||||
className="fullscreen-toggle"
|
||||
aria-label="Minimize"
|
||||
icon={isFullscreen ? <FiMinimize /> : <FiMaximize />}
|
||||
position="absolute"
|
||||
top={2}
|
||||
right={2}
|
||||
onClick={toggleFullscreen}
|
||||
opacity={0}
|
||||
transition="opacity 0.2s"
|
||||
/>
|
||||
</Tooltip>
|
||||
|
||||
{isChanged && (
|
||||
<HStack pos="absolute" bottom={2} right={2}>
|
||||
<Button
|
||||
@@ -148,7 +227,7 @@ export default function VariantEditor(props: { variant: PromptVariant }) {
|
||||
>
|
||||
Reset
|
||||
</Button>
|
||||
<Tooltip label={`${modifierKey} + Enter`}>
|
||||
<Tooltip label={`${modifierKey} + S`}>
|
||||
<Button size="sm" onClick={onSave} colorScheme="blue" w={16} disabled={saveInProgress}>
|
||||
{saveInProgress ? <Spinner boxSize={4} /> : <Text>Save</Text>}
|
||||
</Button>
|
||||
|
||||
@@ -1,13 +1,15 @@
|
||||
import { Grid, GridItem } from "@chakra-ui/react";
|
||||
import { Grid, GridItem, type GridItemProps } from "@chakra-ui/react";
|
||||
import { api } from "~/utils/api";
|
||||
import NewScenarioButton from "./NewScenarioButton";
|
||||
import NewVariantButton from "./NewVariantButton";
|
||||
import AddVariantButton from "./AddVariantButton";
|
||||
import ScenarioRow from "./ScenarioRow";
|
||||
import VariantEditor from "./VariantEditor";
|
||||
import VariantHeader from "../VariantHeader/VariantHeader";
|
||||
import VariantStats from "./VariantStats";
|
||||
import { ScenariosHeader } from "./ScenariosHeader";
|
||||
import { stickyHeaderStyle } from "./styles";
|
||||
import { borders } from "./styles";
|
||||
import { useScenarios } from "~/utils/hooks";
|
||||
import ScenarioPaginator from "./ScenarioPaginator";
|
||||
import { Fragment } from "react";
|
||||
|
||||
export default function OutputsTable({ experimentId }: { experimentId: string | undefined }) {
|
||||
const variants = api.promptVariants.list.useQuery(
|
||||
@@ -15,68 +17,90 @@ export default function OutputsTable({ experimentId }: { experimentId: string |
|
||||
{ enabled: !!experimentId },
|
||||
);
|
||||
|
||||
const scenarios = api.scenarios.list.useQuery(
|
||||
{ experimentId: experimentId as string },
|
||||
{ enabled: !!experimentId },
|
||||
);
|
||||
const scenarios = useScenarios();
|
||||
|
||||
if (!variants.data || !scenarios.data) return null;
|
||||
|
||||
const allCols = variants.data.length + 1;
|
||||
const headerRows = 3;
|
||||
const allCols = variants.data.length + 2;
|
||||
const variantHeaderRows = 3;
|
||||
const scenarioHeaderRows = 1;
|
||||
const scenarioFooterRows = 1;
|
||||
const visibleScenariosCount = scenarios.data.scenarios.length;
|
||||
const allRows =
|
||||
variantHeaderRows + scenarioHeaderRows + visibleScenariosCount + scenarioFooterRows;
|
||||
|
||||
return (
|
||||
<Grid
|
||||
p={4}
|
||||
pt={4}
|
||||
pb={24}
|
||||
pl={4}
|
||||
display="grid"
|
||||
gridTemplateColumns={`250px repeat(${variants.data.length}, minmax(300px, 1fr)) auto`}
|
||||
sx={{
|
||||
"> *": {
|
||||
borderColor: "gray.300",
|
||||
borderBottomWidth: 1,
|
||||
borderRightWidth: 1,
|
||||
},
|
||||
}}
|
||||
fontSize="sm"
|
||||
>
|
||||
<ScenariosHeader headerRows={headerRows} numScenarios={scenarios.data.length} />
|
||||
|
||||
{variants.data.map((variant) => (
|
||||
<VariantHeader key={variant.uiId} variant={variant} canHide={variants.data.length > 1} />
|
||||
))}
|
||||
<GridItem
|
||||
rowSpan={scenarios.data.length + headerRows}
|
||||
padding={0}
|
||||
// Have to use `style` instead of emotion style props to work around css specificity issues conflicting with the "> *" selector on Grid
|
||||
style={{ borderRightWidth: 0, borderBottomWidth: 0 }}
|
||||
h={8}
|
||||
sx={stickyHeaderStyle}
|
||||
>
|
||||
<NewVariantButton />
|
||||
<GridItem rowSpan={variantHeaderRows}>
|
||||
<AddVariantButton />
|
||||
</GridItem>
|
||||
|
||||
{variants.data.map((variant) => (
|
||||
<GridItem key={variant.uiId}>
|
||||
<VariantEditor variant={variant} />
|
||||
</GridItem>
|
||||
))}
|
||||
{variants.data.map((variant) => (
|
||||
<GridItem key={variant.uiId}>
|
||||
<VariantStats variant={variant} />
|
||||
</GridItem>
|
||||
))}
|
||||
{scenarios.data.map((scenario) => (
|
||||
{variants.data.map((variant, i) => {
|
||||
const sharedProps: GridItemProps = {
|
||||
...borders,
|
||||
colStart: i + 2,
|
||||
borderLeftWidth: i === 0 ? 1 : 0,
|
||||
marginLeft: i === 0 ? "-1px" : 0,
|
||||
};
|
||||
return (
|
||||
<Fragment key={variant.uiId}>
|
||||
<VariantHeader
|
||||
variant={variant}
|
||||
canHide={variants.data.length > 1}
|
||||
rowStart={1}
|
||||
{...sharedProps}
|
||||
/>
|
||||
<GridItem rowStart={2} {...sharedProps}>
|
||||
<VariantEditor variant={variant} />
|
||||
</GridItem>
|
||||
<GridItem rowStart={3} {...sharedProps}>
|
||||
<VariantStats variant={variant} />
|
||||
</GridItem>
|
||||
</Fragment>
|
||||
);
|
||||
})}
|
||||
|
||||
<GridItem
|
||||
colSpan={allCols - 1}
|
||||
rowStart={variantHeaderRows + 1}
|
||||
colStart={1}
|
||||
{...borders}
|
||||
borderRightWidth={0}
|
||||
>
|
||||
<ScenariosHeader />
|
||||
</GridItem>
|
||||
|
||||
{scenarios.data.scenarios.map((scenario, i) => (
|
||||
<ScenarioRow
|
||||
rowStart={i + variantHeaderRows + scenarioHeaderRows + 2}
|
||||
key={scenario.uiId}
|
||||
scenario={scenario}
|
||||
variants={variants.data}
|
||||
canHide={scenarios.data.length > 1}
|
||||
canHide={visibleScenariosCount > 1}
|
||||
/>
|
||||
))}
|
||||
<GridItem borderBottomWidth={0} borderRightWidth={0} w="100%" colSpan={allCols} padding={0}>
|
||||
<NewScenarioButton />
|
||||
<GridItem
|
||||
rowStart={variantHeaderRows + scenarioHeaderRows + visibleScenariosCount + 2}
|
||||
colStart={1}
|
||||
colSpan={allCols}
|
||||
>
|
||||
<ScenarioPaginator />
|
||||
</GridItem>
|
||||
|
||||
{/* Add some extra padding on the right, because when the table is too wide to fit in the viewport `pr` on the Grid isn't respected. */}
|
||||
<GridItem rowStart={1} colStart={allCols} rowSpan={allRows} w={4} borderBottomWidth={0} />
|
||||
</Grid>
|
||||
);
|
||||
}
|
||||
|
||||
@@ -1,8 +1,13 @@
|
||||
import { type SystemStyleObject } from "@chakra-ui/react";
|
||||
import { type GridItemProps, type SystemStyleObject } from "@chakra-ui/react";
|
||||
|
||||
export const stickyHeaderStyle: SystemStyleObject = {
|
||||
position: "sticky",
|
||||
top: "0",
|
||||
backgroundColor: "#fff",
|
||||
zIndex: 1,
|
||||
zIndex: 10,
|
||||
};
|
||||
|
||||
export const borders: GridItemProps = {
|
||||
borderRightWidth: 1,
|
||||
borderBottomWidth: 1,
|
||||
};
|
||||
|
||||
@@ -2,4 +2,4 @@ import { type RouterOutputs } from "~/utils/api";
|
||||
|
||||
export type PromptVariant = NonNullable<RouterOutputs["promptVariants"]["list"]>[0];
|
||||
|
||||
export type Scenario = NonNullable<RouterOutputs["scenarios"]["list"]>[0];
|
||||
export type Scenario = NonNullable<RouterOutputs["scenarios"]["list"]>["scenarios"][0];
|
||||
|
||||
@@ -1,44 +1,58 @@
|
||||
import { HStack, VStack } from "@chakra-ui/react";
|
||||
import { type StackProps, VStack, useBreakpointValue } from "@chakra-ui/react";
|
||||
import React from "react";
|
||||
import DiffViewer, { DiffMethod } from "react-diff-viewer";
|
||||
import Prism from "prismjs";
|
||||
import "prismjs/components/prism-javascript";
|
||||
import "prismjs/themes/prism.css"; // choose a theme you like
|
||||
|
||||
const highlightSyntax = (str: string) => {
|
||||
let highlighted;
|
||||
try {
|
||||
highlighted = Prism.highlight(str, Prism.languages.javascript as Prism.Grammar, "javascript");
|
||||
} catch (e) {
|
||||
console.error("Error highlighting:", e);
|
||||
highlighted = str;
|
||||
}
|
||||
return <pre style={{ display: "inline" }} dangerouslySetInnerHTML={{ __html: highlighted }} />;
|
||||
};
|
||||
|
||||
const CompareFunctions = ({
|
||||
originalFunction,
|
||||
newFunction = "",
|
||||
leftTitle = "Original",
|
||||
rightTitle = "Modified",
|
||||
...props
|
||||
}: {
|
||||
originalFunction: string;
|
||||
newFunction?: string;
|
||||
}) => {
|
||||
console.log("newFunction", newFunction);
|
||||
const highlightSyntax = (str: string) => {
|
||||
let highlighted;
|
||||
try {
|
||||
highlighted = Prism.highlight(str, Prism.languages.javascript as Prism.Grammar, "javascript");
|
||||
} catch (e) {
|
||||
console.error("Error highlighting:", e);
|
||||
highlighted = str;
|
||||
}
|
||||
return <pre style={{ display: "inline" }} dangerouslySetInnerHTML={{ __html: highlighted }} />;
|
||||
};
|
||||
leftTitle?: string;
|
||||
rightTitle?: string;
|
||||
} & StackProps) => {
|
||||
const showSplitView = useBreakpointValue(
|
||||
{
|
||||
base: false,
|
||||
md: true,
|
||||
},
|
||||
{
|
||||
fallback: "base",
|
||||
},
|
||||
);
|
||||
|
||||
return (
|
||||
<HStack w="full" spacing={5}>
|
||||
<VStack w="full" spacing={4} maxH="65vh" fontSize={12} lineHeight={1} overflowY="auto">
|
||||
<DiffViewer
|
||||
oldValue={originalFunction}
|
||||
newValue={newFunction || originalFunction}
|
||||
splitView={true}
|
||||
hideLineNumbers={true}
|
||||
leftTitle="Original"
|
||||
rightTitle={newFunction ? "Modified" : "Unmodified"}
|
||||
disableWordDiff={true}
|
||||
compareMethod={DiffMethod.CHARS}
|
||||
renderContent={highlightSyntax}
|
||||
/>
|
||||
</VStack>
|
||||
</HStack>
|
||||
<VStack w="full" spacing={4} fontSize={12} lineHeight={1} overflowY="auto" {...props}>
|
||||
<DiffViewer
|
||||
oldValue={originalFunction}
|
||||
newValue={newFunction || originalFunction}
|
||||
splitView={showSplitView}
|
||||
hideLineNumbers={!showSplitView}
|
||||
leftTitle={leftTitle}
|
||||
rightTitle={rightTitle}
|
||||
disableWordDiff={true}
|
||||
compareMethod={DiffMethod.CHARS}
|
||||
renderContent={highlightSyntax}
|
||||
showDiffOnly={false}
|
||||
/>
|
||||
</VStack>
|
||||
);
|
||||
};
|
||||
|
||||
|
||||
74
src/components/RefinePromptModal/CustomInstructionsInput.tsx
Normal file
74
src/components/RefinePromptModal/CustomInstructionsInput.tsx
Normal file
@@ -0,0 +1,74 @@
|
||||
import { Button, Spinner, InputGroup, InputRightElement, Icon, HStack } from "@chakra-ui/react";
|
||||
import { IoMdSend } from "react-icons/io";
|
||||
import AutoResizeTextArea from "../AutoResizeTextArea";
|
||||
|
||||
export const CustomInstructionsInput = ({
|
||||
instructions,
|
||||
setInstructions,
|
||||
loading,
|
||||
onSubmit,
|
||||
}: {
|
||||
instructions: string;
|
||||
setInstructions: (instructions: string) => void;
|
||||
loading: boolean;
|
||||
onSubmit: () => void;
|
||||
}) => {
|
||||
return (
|
||||
<InputGroup
|
||||
size="md"
|
||||
w="full"
|
||||
maxW="600"
|
||||
boxShadow="0 0 40px 4px rgba(0, 0, 0, 0.1);"
|
||||
borderRadius={8}
|
||||
alignItems="center"
|
||||
colorScheme="orange"
|
||||
>
|
||||
<AutoResizeTextArea
|
||||
value={instructions}
|
||||
onChange={(e) => setInstructions(e.target.value)}
|
||||
onKeyDown={(e) => {
|
||||
if (e.key === "Enter" && !e.metaKey && !e.ctrlKey && !e.shiftKey) {
|
||||
e.preventDefault();
|
||||
e.currentTarget.blur();
|
||||
onSubmit();
|
||||
}
|
||||
}}
|
||||
placeholder="Send custom instructions"
|
||||
py={4}
|
||||
pl={4}
|
||||
pr={12}
|
||||
colorScheme="orange"
|
||||
borderColor="gray.300"
|
||||
borderWidth={1}
|
||||
_hover={{
|
||||
borderColor: "gray.300",
|
||||
}}
|
||||
_focus={{
|
||||
borderColor: "gray.300",
|
||||
}}
|
||||
isDisabled={loading}
|
||||
/>
|
||||
<HStack></HStack>
|
||||
<InputRightElement width="8" height="full">
|
||||
<Button
|
||||
h="8"
|
||||
w="8"
|
||||
minW="unset"
|
||||
size="sm"
|
||||
onClick={() => onSubmit()}
|
||||
variant={instructions ? "solid" : "ghost"}
|
||||
mr={4}
|
||||
borderRadius="8"
|
||||
bgColor={instructions ? "orange.400" : "transparent"}
|
||||
colorScheme="orange"
|
||||
>
|
||||
{loading ? (
|
||||
<Spinner boxSize={4} />
|
||||
) : (
|
||||
<Icon as={IoMdSend} color={instructions ? "white" : "gray.500"} boxSize={5} />
|
||||
)}
|
||||
</Button>
|
||||
</InputRightElement>
|
||||
</InputGroup>
|
||||
);
|
||||
};
|
||||
65
src/components/RefinePromptModal/RefineAction.tsx
Normal file
65
src/components/RefinePromptModal/RefineAction.tsx
Normal file
@@ -0,0 +1,65 @@
|
||||
import { HStack, Icon, Heading, Text, VStack, GridItem } from "@chakra-ui/react";
|
||||
import { type IconType } from "react-icons";
|
||||
import { BsStars } from "react-icons/bs";
|
||||
|
||||
export const RefineAction = ({
|
||||
label,
|
||||
icon,
|
||||
desciption,
|
||||
activeLabel,
|
||||
onClick,
|
||||
loading,
|
||||
}: {
|
||||
label: string;
|
||||
icon?: IconType;
|
||||
desciption: string;
|
||||
activeLabel: string | undefined;
|
||||
onClick: (label: string) => void;
|
||||
loading: boolean;
|
||||
}) => {
|
||||
const isActive = activeLabel === label;
|
||||
|
||||
return (
|
||||
<GridItem w="80" h="44">
|
||||
<VStack
|
||||
w="full"
|
||||
h="full"
|
||||
onClick={() => {
|
||||
!loading && onClick(label);
|
||||
}}
|
||||
borderColor={isActive ? "blue.500" : "gray.200"}
|
||||
borderWidth={2}
|
||||
borderRadius={16}
|
||||
padding={6}
|
||||
backgroundColor="gray.50"
|
||||
_hover={
|
||||
loading
|
||||
? undefined
|
||||
: {
|
||||
backgroundColor: "gray.100",
|
||||
}
|
||||
}
|
||||
spacing={8}
|
||||
boxShadow="0 0 40px 4px rgba(0, 0, 0, 0.1);"
|
||||
cursor="pointer"
|
||||
opacity={loading ? 0.5 : 1}
|
||||
>
|
||||
<HStack cursor="pointer" spacing={6} fontSize="sm" fontWeight="medium" color="gray.500">
|
||||
<Icon as={icon || BsStars} boxSize={12} />
|
||||
<Heading size="md" fontFamily="inconsolata, monospace">
|
||||
{label}
|
||||
</Heading>
|
||||
</HStack>
|
||||
<Text
|
||||
fontSize="sm"
|
||||
color="gray.500"
|
||||
flexWrap="wrap"
|
||||
wordBreak="break-word"
|
||||
overflowWrap="break-word"
|
||||
>
|
||||
{desciption}
|
||||
</Text>
|
||||
</VStack>
|
||||
</GridItem>
|
||||
);
|
||||
};
|
||||
@@ -11,13 +11,20 @@ import {
|
||||
Text,
|
||||
Spinner,
|
||||
HStack,
|
||||
Icon,
|
||||
SimpleGrid,
|
||||
} from "@chakra-ui/react";
|
||||
import { BsStars } from "react-icons/bs";
|
||||
import { api } from "~/utils/api";
|
||||
import { useHandledAsyncCallback } from "~/utils/hooks";
|
||||
import { useHandledAsyncCallback, useVisibleScenarioIds } from "~/utils/hooks";
|
||||
import { type PromptVariant } from "@prisma/client";
|
||||
import { useState } from "react";
|
||||
import AutoResizeTextArea from "../AutoResizeTextArea";
|
||||
import CompareFunctions from "./CompareFunctions";
|
||||
import { CustomInstructionsInput } from "./CustomInstructionsInput";
|
||||
import { RefineAction } from "./RefineAction";
|
||||
import { isObject, isString } from "lodash-es";
|
||||
import { type RefinementAction, type SupportedProvider } from "~/modelProviders/types";
|
||||
import frontendModelProviders from "~/modelProviders/frontendModelProviders";
|
||||
|
||||
export const RefinePromptModal = ({
|
||||
variant,
|
||||
@@ -27,71 +34,112 @@ export const RefinePromptModal = ({
|
||||
onClose: () => void;
|
||||
}) => {
|
||||
const utils = api.useContext();
|
||||
const visibleScenarios = useVisibleScenarioIds();
|
||||
|
||||
const { mutateAsync: getRefinedPromptMutateAsync, data: refinedPromptFn } =
|
||||
api.promptVariants.getRefinedPromptFn.useMutation();
|
||||
const refinementActions =
|
||||
frontendModelProviders[variant.modelProvider as SupportedProvider].refinementActions || {};
|
||||
|
||||
const { mutateAsync: getModifiedPromptMutateAsync, data: refinedPromptFn } =
|
||||
api.promptVariants.getModifiedPromptFn.useMutation();
|
||||
const [instructions, setInstructions] = useState<string>("");
|
||||
|
||||
const [getRefinedPromptFn, refiningInProgress] = useHandledAsyncCallback(async () => {
|
||||
if (!variant.experimentId) return;
|
||||
await getRefinedPromptMutateAsync({
|
||||
id: variant.id,
|
||||
instructions,
|
||||
});
|
||||
}, [getRefinedPromptMutateAsync, onClose, variant, instructions]);
|
||||
const [activeRefineActionLabel, setActiveRefineActionLabel] = useState<string | undefined>(
|
||||
undefined,
|
||||
);
|
||||
|
||||
const [getModifiedPromptFn, modificationInProgress] = useHandledAsyncCallback(
|
||||
async (label?: string) => {
|
||||
if (!variant.experimentId) return;
|
||||
const updatedInstructions = label
|
||||
? (refinementActions[label] as RefinementAction).instructions
|
||||
: instructions;
|
||||
setActiveRefineActionLabel(label);
|
||||
await getModifiedPromptMutateAsync({
|
||||
id: variant.id,
|
||||
instructions: updatedInstructions,
|
||||
});
|
||||
},
|
||||
[getModifiedPromptMutateAsync, onClose, variant, instructions, setActiveRefineActionLabel],
|
||||
);
|
||||
|
||||
const replaceVariantMutation = api.promptVariants.replaceVariant.useMutation();
|
||||
|
||||
const [replaceVariant, replacementInProgress] = useHandledAsyncCallback(async () => {
|
||||
if (!variant.experimentId || !refinedPromptFn) return;
|
||||
if (
|
||||
!variant.experimentId ||
|
||||
!refinedPromptFn ||
|
||||
(isObject(refinedPromptFn) && "status" in refinedPromptFn)
|
||||
)
|
||||
return;
|
||||
await replaceVariantMutation.mutateAsync({
|
||||
id: variant.id,
|
||||
constructFn: refinedPromptFn,
|
||||
streamScenarios: visibleScenarios,
|
||||
});
|
||||
await utils.promptVariants.list.invalidate();
|
||||
onClose();
|
||||
}, [replaceVariantMutation, variant, onClose, refinedPromptFn]);
|
||||
|
||||
return (
|
||||
<Modal isOpen onClose={onClose} size={{ base: "xl", sm: "2xl", md: "7xl" }}>
|
||||
<Modal
|
||||
isOpen
|
||||
onClose={onClose}
|
||||
size={{ base: "xl", sm: "2xl", md: "3xl", lg: "5xl", xl: "7xl" }}
|
||||
>
|
||||
<ModalOverlay />
|
||||
<ModalContent w={1200}>
|
||||
<ModalHeader>Refine Your Prompt</ModalHeader>
|
||||
<ModalHeader>
|
||||
<HStack>
|
||||
<Icon as={BsStars} />
|
||||
<Text>Refine with GPT-4</Text>
|
||||
</HStack>
|
||||
</ModalHeader>
|
||||
<ModalCloseButton />
|
||||
<ModalBody maxW="unset">
|
||||
<VStack spacing={8}>
|
||||
<HStack w="full">
|
||||
<AutoResizeTextArea
|
||||
value={instructions}
|
||||
onChange={(e) => setInstructions(e.target.value)}
|
||||
onKeyDown={(e) => {
|
||||
if (e.key === "Enter" && !e.metaKey && !e.ctrlKey && !e.shiftKey) {
|
||||
e.preventDefault();
|
||||
e.currentTarget.blur();
|
||||
getRefinedPromptFn();
|
||||
}
|
||||
}}
|
||||
placeholder="Use chain of thought"
|
||||
<VStack spacing={4}>
|
||||
{Object.keys(refinementActions).length && (
|
||||
<>
|
||||
<SimpleGrid columns={{ base: 1, md: 2 }} spacing={8}>
|
||||
{Object.keys(refinementActions).map((label) => (
|
||||
<RefineAction
|
||||
key={label}
|
||||
label={label}
|
||||
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
|
||||
icon={refinementActions[label]!.icon}
|
||||
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
|
||||
desciption={refinementActions[label]!.description}
|
||||
activeLabel={activeRefineActionLabel}
|
||||
onClick={getModifiedPromptFn}
|
||||
loading={modificationInProgress}
|
||||
/>
|
||||
))}
|
||||
</SimpleGrid>
|
||||
<Text color="gray.500">or</Text>
|
||||
</>
|
||||
)}
|
||||
<CustomInstructionsInput
|
||||
instructions={instructions}
|
||||
setInstructions={setInstructions}
|
||||
loading={modificationInProgress}
|
||||
onSubmit={getModifiedPromptFn}
|
||||
/>
|
||||
<Button onClick={getRefinedPromptFn}>
|
||||
{refiningInProgress ? <Spinner boxSize={4} /> : <Text>Submit</Text>}
|
||||
</Button>
|
||||
</HStack>
|
||||
</VStack>
|
||||
<CompareFunctions
|
||||
originalFunction={variant.constructFn}
|
||||
newFunction={refinedPromptFn}
|
||||
newFunction={isString(refinedPromptFn) ? refinedPromptFn : undefined}
|
||||
maxH="40vh"
|
||||
/>
|
||||
</VStack>
|
||||
</ModalBody>
|
||||
|
||||
<ModalFooter>
|
||||
<HStack spacing={4}>
|
||||
<Button onClick={onClose}>Cancel</Button>
|
||||
<Button
|
||||
colorScheme="blue"
|
||||
onClick={replaceVariant}
|
||||
minW={24}
|
||||
disabled={!refinedPromptFn}
|
||||
isDisabled={replacementInProgress || !refinedPromptFn}
|
||||
>
|
||||
{replacementInProgress ? <Spinner boxSize={4} /> : <Text>Accept</Text>}
|
||||
</Button>
|
||||
|
||||
@@ -1,89 +0,0 @@
|
||||
import {
|
||||
VStack,
|
||||
Text,
|
||||
HStack,
|
||||
type StackProps,
|
||||
GridItem,
|
||||
SimpleGrid,
|
||||
Link,
|
||||
} from "@chakra-ui/react";
|
||||
import { modelStats } from "~/server/modelStats";
|
||||
import { type SupportedModel } from "~/server/types";
|
||||
|
||||
export const ModelStatsCard = ({ label, model }: { label: string; model: SupportedModel }) => {
|
||||
const stats = modelStats[model];
|
||||
return (
|
||||
<VStack w="full" align="start">
|
||||
<Text fontWeight="bold" fontSize="sm" textTransform="uppercase">
|
||||
{label}
|
||||
</Text>
|
||||
|
||||
<VStack w="full" spacing={6} bgColor="gray.100" p={4} borderRadius={4}>
|
||||
<HStack w="full" align="flex-start">
|
||||
<Text flex={1} fontSize="lg">
|
||||
<Text as="span" color="gray.600">
|
||||
{stats.provider} /{" "}
|
||||
</Text>
|
||||
<Text as="span" fontWeight="bold" color="gray.900">
|
||||
{model}
|
||||
</Text>
|
||||
</Text>
|
||||
<Link
|
||||
href={stats.learnMoreUrl}
|
||||
isExternal
|
||||
color="blue.500"
|
||||
fontWeight="bold"
|
||||
fontSize="sm"
|
||||
ml={2}
|
||||
>
|
||||
Learn More
|
||||
</Link>
|
||||
</HStack>
|
||||
<SimpleGrid
|
||||
w="full"
|
||||
justifyContent="space-between"
|
||||
alignItems="flex-start"
|
||||
fontSize="sm"
|
||||
columns={{ base: 2, md: 4 }}
|
||||
>
|
||||
<SelectedModelLabeledInfo label="Context" info={stats.contextLength} />
|
||||
<SelectedModelLabeledInfo
|
||||
label="Input"
|
||||
info={
|
||||
<Text>
|
||||
${(stats.promptTokenPrice * 1000).toFixed(3)}
|
||||
<Text color="gray.500"> / 1K tokens</Text>
|
||||
</Text>
|
||||
}
|
||||
/>
|
||||
<SelectedModelLabeledInfo
|
||||
label="Output"
|
||||
info={
|
||||
<Text>
|
||||
${(stats.promptTokenPrice * 1000).toFixed(3)}
|
||||
<Text color="gray.500"> / 1K tokens</Text>
|
||||
</Text>
|
||||
}
|
||||
/>
|
||||
<SelectedModelLabeledInfo label="Speed" info={<Text>{stats.speed}</Text>} />
|
||||
</SimpleGrid>
|
||||
</VStack>
|
||||
</VStack>
|
||||
);
|
||||
};
|
||||
|
||||
const SelectedModelLabeledInfo = ({
|
||||
label,
|
||||
info,
|
||||
...props
|
||||
}: {
|
||||
label: string;
|
||||
info: string | number | React.ReactElement;
|
||||
} & StackProps) => (
|
||||
<GridItem>
|
||||
<VStack alignItems="flex-start" {...props}>
|
||||
<Text fontWeight="bold">{label}</Text>
|
||||
<Text>{info}</Text>
|
||||
</VStack>
|
||||
</GridItem>
|
||||
);
|
||||
@@ -1,77 +0,0 @@
|
||||
import {
|
||||
Button,
|
||||
Modal,
|
||||
ModalBody,
|
||||
ModalCloseButton,
|
||||
ModalContent,
|
||||
ModalFooter,
|
||||
ModalHeader,
|
||||
ModalOverlay,
|
||||
VStack,
|
||||
Text,
|
||||
Spinner,
|
||||
} from "@chakra-ui/react";
|
||||
import { useState } from "react";
|
||||
import { type SupportedModel } from "~/server/types";
|
||||
import { ModelStatsCard } from "./ModelStatsCard";
|
||||
import { SelectModelSearch } from "./SelectModelSearch";
|
||||
import { api } from "~/utils/api";
|
||||
import { useExperiment, useHandledAsyncCallback } from "~/utils/hooks";
|
||||
|
||||
export const SelectModelModal = ({
|
||||
originalModel,
|
||||
variantId,
|
||||
onClose,
|
||||
}: {
|
||||
originalModel: SupportedModel;
|
||||
variantId: string;
|
||||
onClose: () => void;
|
||||
}) => {
|
||||
const [selectedModel, setSelectedModel] = useState<SupportedModel>(originalModel);
|
||||
const utils = api.useContext();
|
||||
|
||||
const experiment = useExperiment();
|
||||
|
||||
const createMutation = api.promptVariants.create.useMutation();
|
||||
|
||||
const [createNewVariant, creationInProgress] = useHandledAsyncCallback(async () => {
|
||||
if (!experiment?.data?.id) return;
|
||||
await createMutation.mutateAsync({
|
||||
experimentId: experiment?.data?.id,
|
||||
variantId,
|
||||
newModel: selectedModel,
|
||||
});
|
||||
await utils.promptVariants.list.invalidate();
|
||||
onClose();
|
||||
}, [createMutation, experiment?.data?.id, variantId, onClose]);
|
||||
|
||||
return (
|
||||
<Modal isOpen onClose={onClose} size={{ base: "xl", sm: "2xl", md: "3xl" }}>
|
||||
<ModalOverlay />
|
||||
<ModalContent w={1200}>
|
||||
<ModalHeader>Select a New Model</ModalHeader>
|
||||
<ModalCloseButton />
|
||||
<ModalBody maxW="unset">
|
||||
<VStack spacing={8}>
|
||||
<ModelStatsCard label="Original Model" model={originalModel} />
|
||||
{originalModel !== selectedModel && (
|
||||
<ModelStatsCard label="New Model" model={selectedModel} />
|
||||
)}
|
||||
<SelectModelSearch selectedModel={selectedModel} setSelectedModel={setSelectedModel} />
|
||||
</VStack>
|
||||
</ModalBody>
|
||||
|
||||
<ModalFooter>
|
||||
<Button
|
||||
colorScheme="blue"
|
||||
onClick={createNewVariant}
|
||||
minW={24}
|
||||
disabled={originalModel === selectedModel}
|
||||
>
|
||||
{creationInProgress ? <Spinner boxSize={4} /> : <Text>Continue</Text>}
|
||||
</Button>
|
||||
</ModalFooter>
|
||||
</ModalContent>
|
||||
</Modal>
|
||||
);
|
||||
};
|
||||
@@ -1,47 +0,0 @@
|
||||
import { VStack, Text } from "@chakra-ui/react";
|
||||
import { type LegacyRef, useCallback } from "react";
|
||||
import Select, { type SingleValue } from "react-select";
|
||||
import { type SupportedModel } from "~/server/types";
|
||||
import { useElementDimensions } from "~/utils/hooks";
|
||||
|
||||
const modelOptions: { value: SupportedModel; label: string }[] = [
|
||||
{ value: "gpt-3.5-turbo", label: "gpt-3.5-turbo" },
|
||||
{ value: "gpt-3.5-turbo-0613", label: "gpt-3.5-turbo-0613" },
|
||||
{ value: "gpt-3.5-turbo-16k", label: "gpt-3.5-turbo-16k" },
|
||||
{ value: "gpt-3.5-turbo-16k-0613", label: "gpt-3.5-turbo-16k-0613" },
|
||||
{ value: "gpt-4", label: "gpt-4" },
|
||||
{ value: "gpt-4-0613", label: "gpt-4-0613" },
|
||||
{ value: "gpt-4-32k", label: "gpt-4-32k" },
|
||||
{ value: "gpt-4-32k-0613", label: "gpt-4-32k-0613" },
|
||||
];
|
||||
|
||||
export const SelectModelSearch = ({
|
||||
selectedModel,
|
||||
setSelectedModel,
|
||||
}: {
|
||||
selectedModel: SupportedModel;
|
||||
setSelectedModel: (model: SupportedModel) => void;
|
||||
}) => {
|
||||
const handleSelection = useCallback(
|
||||
(option: SingleValue<{ value: SupportedModel; label: string }>) => {
|
||||
if (!option) return;
|
||||
setSelectedModel(option.value);
|
||||
},
|
||||
[setSelectedModel],
|
||||
);
|
||||
const selectedOption = modelOptions.find((option) => option.value === selectedModel);
|
||||
|
||||
const [containerRef, containerDimensions] = useElementDimensions();
|
||||
|
||||
return (
|
||||
<VStack ref={containerRef as LegacyRef<HTMLDivElement>} w="full">
|
||||
<Text>Browse Models</Text>
|
||||
<Select
|
||||
styles={{ control: (provided) => ({ ...provided, width: containerDimensions?.width }) }}
|
||||
value={selectedOption}
|
||||
options={modelOptions}
|
||||
onChange={handleSelection}
|
||||
/>
|
||||
</VStack>
|
||||
);
|
||||
};
|
||||
@@ -3,28 +3,34 @@ import { type PromptVariant } from "../OutputsTable/types";
|
||||
import { api } from "~/utils/api";
|
||||
import { RiDraggable } from "react-icons/ri";
|
||||
import { useExperimentAccess, useHandledAsyncCallback } from "~/utils/hooks";
|
||||
import { HStack, Icon, Text, GridItem } from "@chakra-ui/react"; // Changed here
|
||||
import { HStack, Icon, Text, GridItem, type GridItemProps } from "@chakra-ui/react"; // Changed here
|
||||
import { cellPadding, headerMinHeight } from "../constants";
|
||||
import AutoResizeTextArea from "../AutoResizeTextArea";
|
||||
import { stickyHeaderStyle } from "../OutputsTable/styles";
|
||||
import VariantHeaderMenuButton from "./VariantHeaderMenuButton";
|
||||
|
||||
export default function VariantHeader(props: { variant: PromptVariant; canHide: boolean }) {
|
||||
export default function VariantHeader(
|
||||
allProps: {
|
||||
variant: PromptVariant;
|
||||
canHide: boolean;
|
||||
} & GridItemProps,
|
||||
) {
|
||||
const { variant, canHide, ...gridItemProps } = allProps;
|
||||
const { canModify } = useExperimentAccess();
|
||||
const utils = api.useContext();
|
||||
const [isDragTarget, setIsDragTarget] = useState(false);
|
||||
const [isInputHovered, setIsInputHovered] = useState(false);
|
||||
const [label, setLabel] = useState(props.variant.label);
|
||||
const [label, setLabel] = useState(variant.label);
|
||||
|
||||
const updateMutation = api.promptVariants.update.useMutation();
|
||||
const [onSaveLabel] = useHandledAsyncCallback(async () => {
|
||||
if (label && label !== props.variant.label) {
|
||||
if (label && label !== variant.label) {
|
||||
await updateMutation.mutateAsync({
|
||||
id: props.variant.id,
|
||||
id: variant.id,
|
||||
updates: { label: label },
|
||||
});
|
||||
}
|
||||
}, [updateMutation, props.variant.id, props.variant.label, label]);
|
||||
}, [updateMutation, variant.id, variant.label, label]);
|
||||
|
||||
const reorderMutation = api.promptVariants.reorder.useMutation();
|
||||
const [onReorder] = useHandledAsyncCallback(
|
||||
@@ -32,7 +38,7 @@ export default function VariantHeader(props: { variant: PromptVariant; canHide:
|
||||
e.preventDefault();
|
||||
setIsDragTarget(false);
|
||||
const draggedId = e.dataTransfer.getData("text/plain");
|
||||
const droppedId = props.variant.id;
|
||||
const droppedId = variant.id;
|
||||
if (!draggedId || !droppedId || draggedId === droppedId) return;
|
||||
await reorderMutation.mutateAsync({
|
||||
draggedId,
|
||||
@@ -40,16 +46,16 @@ export default function VariantHeader(props: { variant: PromptVariant; canHide:
|
||||
});
|
||||
await utils.promptVariants.list.invalidate();
|
||||
},
|
||||
[reorderMutation, props.variant.id],
|
||||
[reorderMutation, variant.id],
|
||||
);
|
||||
|
||||
const [menuOpen, setMenuOpen] = useState(false);
|
||||
|
||||
if (!canModify) {
|
||||
return (
|
||||
<GridItem padding={0} sx={stickyHeaderStyle} borderTopWidth={1}>
|
||||
<GridItem padding={0} sx={stickyHeaderStyle} borderTopWidth={1} {...gridItemProps}>
|
||||
<Text fontSize={16} fontWeight="bold" px={cellPadding.x} py={cellPadding.y}>
|
||||
{props.variant.label}
|
||||
{variant.label}
|
||||
</Text>
|
||||
</GridItem>
|
||||
);
|
||||
@@ -64,6 +70,7 @@ export default function VariantHeader(props: { variant: PromptVariant; canHide:
|
||||
zIndex: menuOpen ? "dropdown" : stickyHeaderStyle.zIndex,
|
||||
}}
|
||||
borderTopWidth={1}
|
||||
{...gridItemProps}
|
||||
>
|
||||
<HStack
|
||||
spacing={4}
|
||||
@@ -71,7 +78,7 @@ export default function VariantHeader(props: { variant: PromptVariant; canHide:
|
||||
minH={headerMinHeight}
|
||||
draggable={!isInputHovered}
|
||||
onDragStart={(e) => {
|
||||
e.dataTransfer.setData("text/plain", props.variant.id);
|
||||
e.dataTransfer.setData("text/plain", variant.id);
|
||||
e.currentTarget.style.opacity = "0.4";
|
||||
}}
|
||||
onDragEnd={(e) => {
|
||||
@@ -112,8 +119,8 @@ export default function VariantHeader(props: { variant: PromptVariant; canHide:
|
||||
onMouseLeave={() => setIsInputHovered(false)}
|
||||
/>
|
||||
<VariantHeaderMenuButton
|
||||
variant={props.variant}
|
||||
canHide={props.canHide}
|
||||
variant={variant}
|
||||
canHide={canHide}
|
||||
menuOpen={menuOpen}
|
||||
setMenuOpen={setMenuOpen}
|
||||
/>
|
||||
|
||||
@@ -1,8 +1,7 @@
|
||||
import { type PromptVariant } from "../OutputsTable/types";
|
||||
import { api } from "~/utils/api";
|
||||
import { useHandledAsyncCallback } from "~/utils/hooks";
|
||||
import { useHandledAsyncCallback, useVisibleScenarioIds } from "~/utils/hooks";
|
||||
import {
|
||||
Button,
|
||||
Icon,
|
||||
Menu,
|
||||
MenuButton,
|
||||
@@ -11,15 +10,14 @@ import {
|
||||
MenuDivider,
|
||||
Text,
|
||||
Spinner,
|
||||
IconButton,
|
||||
} from "@chakra-ui/react";
|
||||
import { BsFillTrashFill, BsGear } from "react-icons/bs";
|
||||
import { BsFillTrashFill, BsGear, BsStars } from "react-icons/bs";
|
||||
import { FaRegClone } from "react-icons/fa";
|
||||
import { AiOutlineDiff } from "react-icons/ai";
|
||||
import { useState } from "react";
|
||||
import { RefinePromptModal } from "../RefinePromptModal/RefinePromptModal";
|
||||
import { RiExchangeFundsFill } from "react-icons/ri";
|
||||
import { SelectModelModal } from "../SelectModelModal/SelectModelModal";
|
||||
import { type SupportedModel } from "~/server/types";
|
||||
import { ChangeModelModal } from "../ChangeModelModal/ChangeModelModal";
|
||||
|
||||
export default function VariantHeaderMenuButton({
|
||||
variant,
|
||||
@@ -35,11 +33,13 @@ export default function VariantHeaderMenuButton({
|
||||
const utils = api.useContext();
|
||||
|
||||
const duplicateMutation = api.promptVariants.create.useMutation();
|
||||
const visibleScenarios = useVisibleScenarioIds();
|
||||
|
||||
const [duplicateVariant, duplicationInProgress] = useHandledAsyncCallback(async () => {
|
||||
await duplicateMutation.mutateAsync({
|
||||
experimentId: variant.experimentId,
|
||||
variantId: variant.id,
|
||||
streamScenarios: visibleScenarios,
|
||||
});
|
||||
await utils.promptVariants.list.invalidate();
|
||||
}, [duplicateMutation, variant.experimentId, variant.id]);
|
||||
@@ -52,21 +52,18 @@ export default function VariantHeaderMenuButton({
|
||||
await utils.promptVariants.list.invalidate();
|
||||
}, [hideMutation, variant.id]);
|
||||
|
||||
const [selectModelModalOpen, setSelectModelModalOpen] = useState(false);
|
||||
const [changeModelModalOpen, setChangeModelModalOpen] = useState(false);
|
||||
const [refinePromptModalOpen, setRefinePromptModalOpen] = useState(false);
|
||||
|
||||
return (
|
||||
<>
|
||||
<Menu isOpen={menuOpen} onOpen={() => setMenuOpen(true)} onClose={() => setMenuOpen(false)}>
|
||||
{duplicationInProgress ? (
|
||||
<Spinner boxSize={4} mx={3} my={3} />
|
||||
) : (
|
||||
<MenuButton>
|
||||
<Button variant="ghost">
|
||||
<Icon as={BsGear} />
|
||||
</Button>
|
||||
</MenuButton>
|
||||
)}
|
||||
<MenuButton
|
||||
as={IconButton}
|
||||
variant="ghost"
|
||||
aria-label="Edit Scenarios"
|
||||
icon={<Icon as={duplicationInProgress ? Spinner : BsGear} />}
|
||||
/>
|
||||
|
||||
<MenuList mt={-3} fontSize="md">
|
||||
<MenuItem icon={<Icon as={FaRegClone} boxSize={4} w={5} />} onClick={duplicateVariant}>
|
||||
@@ -74,12 +71,12 @@ export default function VariantHeaderMenuButton({
|
||||
</MenuItem>
|
||||
<MenuItem
|
||||
icon={<Icon as={RiExchangeFundsFill} boxSize={5} />}
|
||||
onClick={() => setSelectModelModalOpen(true)}
|
||||
onClick={() => setChangeModelModalOpen(true)}
|
||||
>
|
||||
Change Model
|
||||
</MenuItem>
|
||||
<MenuItem
|
||||
icon={<Icon as={AiOutlineDiff} boxSize={5} />}
|
||||
icon={<Icon as={BsStars} boxSize={5} />}
|
||||
onClick={() => setRefinePromptModalOpen(true)}
|
||||
>
|
||||
Refine
|
||||
@@ -99,12 +96,8 @@ export default function VariantHeaderMenuButton({
|
||||
)}
|
||||
</MenuList>
|
||||
</Menu>
|
||||
{selectModelModalOpen && (
|
||||
<SelectModelModal
|
||||
originalModel={variant.model as SupportedModel}
|
||||
variantId={variant.id}
|
||||
onClose={() => setSelectModelModalOpen(false)}
|
||||
/>
|
||||
{changeModelModalOpen && (
|
||||
<ChangeModelModal variant={variant} onClose={() => setChangeModelModalOpen(false)} />
|
||||
)}
|
||||
{refinePromptModalOpen && (
|
||||
<RefinePromptModal variant={variant} onClose={() => setRefinePromptModalOpen(false)} />
|
||||
|
||||
@@ -1,4 +1,13 @@
|
||||
import { HStack, Icon, VStack, Text, Divider, Spinner, AspectRatio } from "@chakra-ui/react";
|
||||
import {
|
||||
HStack,
|
||||
Icon,
|
||||
VStack,
|
||||
Text,
|
||||
Divider,
|
||||
Spinner,
|
||||
AspectRatio,
|
||||
SkeletonText,
|
||||
} from "@chakra-ui/react";
|
||||
import { RiFlaskLine } from "react-icons/ri";
|
||||
import { formatTimePast } from "~/utils/dayjs";
|
||||
import Link from "next/link";
|
||||
@@ -93,3 +102,13 @@ export const NewExperimentCard = () => {
|
||||
</AspectRatio>
|
||||
);
|
||||
};
|
||||
|
||||
export const ExperimentCardSkeleton = () => (
|
||||
<AspectRatio ratio={1.2} w="full">
|
||||
<VStack align="center" borderColor="gray.200" borderWidth={1} p={4} bg="gray.50">
|
||||
<SkeletonText noOfLines={1} w="80%" />
|
||||
<SkeletonText noOfLines={2} w="60%" />
|
||||
<SkeletonText noOfLines={1} w="80%" />
|
||||
</VStack>
|
||||
</AspectRatio>
|
||||
);
|
||||
|
||||
57
src/components/experiments/HeaderButtons/DeleteDialog.tsx
Normal file
57
src/components/experiments/HeaderButtons/DeleteDialog.tsx
Normal file
@@ -0,0 +1,57 @@
|
||||
import {
|
||||
Button,
|
||||
AlertDialog,
|
||||
AlertDialogBody,
|
||||
AlertDialogFooter,
|
||||
AlertDialogHeader,
|
||||
AlertDialogContent,
|
||||
AlertDialogOverlay,
|
||||
} from "@chakra-ui/react";
|
||||
|
||||
import { useRouter } from "next/router";
|
||||
import { useRef } from "react";
|
||||
import { api } from "~/utils/api";
|
||||
import { useExperiment, useHandledAsyncCallback } from "~/utils/hooks";
|
||||
|
||||
export const DeleteDialog = ({ onClose }: { onClose: () => void }) => {
|
||||
const experiment = useExperiment();
|
||||
const deleteMutation = api.experiments.delete.useMutation();
|
||||
const utils = api.useContext();
|
||||
const router = useRouter();
|
||||
|
||||
const cancelRef = useRef<HTMLButtonElement>(null);
|
||||
|
||||
const [onDeleteConfirm] = useHandledAsyncCallback(async () => {
|
||||
if (!experiment.data?.id) return;
|
||||
await deleteMutation.mutateAsync({ id: experiment.data.id });
|
||||
await utils.experiments.list.invalidate();
|
||||
await router.push({ pathname: "/experiments" });
|
||||
onClose();
|
||||
}, [deleteMutation, experiment.data?.id, router]);
|
||||
|
||||
return (
|
||||
<AlertDialog isOpen leastDestructiveRef={cancelRef} onClose={onClose}>
|
||||
<AlertDialogOverlay>
|
||||
<AlertDialogContent>
|
||||
<AlertDialogHeader fontSize="lg" fontWeight="bold">
|
||||
Delete Experiment
|
||||
</AlertDialogHeader>
|
||||
|
||||
<AlertDialogBody>
|
||||
If you delete this experiment all the associated prompts and scenarios will be deleted
|
||||
as well. Are you sure?
|
||||
</AlertDialogBody>
|
||||
|
||||
<AlertDialogFooter>
|
||||
<Button ref={cancelRef} onClick={onClose}>
|
||||
Cancel
|
||||
</Button>
|
||||
<Button colorScheme="red" onClick={onDeleteConfirm} ml={3}>
|
||||
Delete
|
||||
</Button>
|
||||
</AlertDialogFooter>
|
||||
</AlertDialogContent>
|
||||
</AlertDialogOverlay>
|
||||
</AlertDialog>
|
||||
);
|
||||
};
|
||||
42
src/components/experiments/HeaderButtons/HeaderButtons.tsx
Normal file
42
src/components/experiments/HeaderButtons/HeaderButtons.tsx
Normal file
@@ -0,0 +1,42 @@
|
||||
import { Button, HStack, Icon, Spinner, Text } from "@chakra-ui/react";
|
||||
import { useOnForkButtonPressed } from "./useOnForkButtonPressed";
|
||||
import { useExperiment } from "~/utils/hooks";
|
||||
import { BsGearFill } from "react-icons/bs";
|
||||
import { TbGitFork } from "react-icons/tb";
|
||||
import { useAppStore } from "~/state/store";
|
||||
|
||||
export const HeaderButtons = () => {
|
||||
const experiment = useExperiment();
|
||||
|
||||
const canModify = experiment.data?.access.canModify ?? false;
|
||||
|
||||
const { onForkButtonPressed, isForking } = useOnForkButtonPressed();
|
||||
|
||||
const openDrawer = useAppStore((s) => s.openDrawer);
|
||||
|
||||
if (experiment.isLoading) return null;
|
||||
|
||||
return (
|
||||
<HStack spacing={0} mt={{ base: 2, md: 0 }}>
|
||||
<Button
|
||||
onClick={onForkButtonPressed}
|
||||
mr={4}
|
||||
colorScheme={canModify ? undefined : "orange"}
|
||||
bgColor={canModify ? undefined : "orange.400"}
|
||||
minW={0}
|
||||
variant={canModify ? "ghost" : "solid"}
|
||||
>
|
||||
{isForking ? <Spinner boxSize={5} /> : <Icon as={TbGitFork} boxSize={5} />}
|
||||
<Text ml={2}>Fork</Text>
|
||||
</Button>
|
||||
{canModify && (
|
||||
<Button variant={{ base: "solid", md: "ghost" }} onClick={openDrawer}>
|
||||
<HStack>
|
||||
<Icon as={BsGearFill} />
|
||||
<Text>Settings</Text>
|
||||
</HStack>
|
||||
</Button>
|
||||
)}
|
||||
</HStack>
|
||||
);
|
||||
};
|
||||
@@ -0,0 +1,30 @@
|
||||
import { useCallback } from "react";
|
||||
import { api } from "~/utils/api";
|
||||
import { useExperiment, useHandledAsyncCallback } from "~/utils/hooks";
|
||||
import { signIn, useSession } from "next-auth/react";
|
||||
import { useRouter } from "next/router";
|
||||
|
||||
export const useOnForkButtonPressed = () => {
|
||||
const router = useRouter();
|
||||
|
||||
const user = useSession().data;
|
||||
const experiment = useExperiment();
|
||||
|
||||
const forkMutation = api.experiments.fork.useMutation();
|
||||
|
||||
const [onFork, isForking] = useHandledAsyncCallback(async () => {
|
||||
if (!experiment.data?.id) return;
|
||||
const forkedExperimentId = await forkMutation.mutateAsync({ id: experiment.data.id });
|
||||
await router.push({ pathname: "/experiments/[id]", query: { id: forkedExperimentId } });
|
||||
}, [forkMutation, experiment.data?.id, router]);
|
||||
|
||||
const onForkButtonPressed = useCallback(() => {
|
||||
if (user === null) {
|
||||
signIn("github").catch(console.error);
|
||||
} else {
|
||||
onFork();
|
||||
}
|
||||
}, [onFork, user]);
|
||||
|
||||
return { onForkButtonPressed, isForking };
|
||||
};
|
||||
@@ -9,7 +9,6 @@ export const env = createEnv({
|
||||
server: {
|
||||
DATABASE_URL: z.string().url(),
|
||||
NODE_ENV: z.enum(["development", "test", "production"]).default("development"),
|
||||
OPENAI_API_KEY: z.string().min(1),
|
||||
RESTRICT_PRISMA_LOGS: z
|
||||
.string()
|
||||
.optional()
|
||||
@@ -17,6 +16,8 @@ export const env = createEnv({
|
||||
.transform((val) => val.toLowerCase() === "true"),
|
||||
GITHUB_CLIENT_ID: z.string().min(1),
|
||||
GITHUB_CLIENT_SECRET: z.string().min(1),
|
||||
OPENAI_API_KEY: z.string().min(1),
|
||||
REPLICATE_API_TOKEN: z.string().default("placeholder"),
|
||||
},
|
||||
|
||||
/**
|
||||
@@ -42,6 +43,7 @@ export const env = createEnv({
|
||||
NEXT_PUBLIC_SOCKET_URL: process.env.NEXT_PUBLIC_SOCKET_URL,
|
||||
GITHUB_CLIENT_ID: process.env.GITHUB_CLIENT_ID,
|
||||
GITHUB_CLIENT_SECRET: process.env.GITHUB_CLIENT_SECRET,
|
||||
REPLICATE_API_TOKEN: process.env.REPLICATE_API_TOKEN,
|
||||
},
|
||||
/**
|
||||
* Run `build` or `dev` with `SKIP_ENV_VALIDATION` to skip env validation.
|
||||
|
||||
15
src/modelProviders/frontendModelProviders.ts
Normal file
15
src/modelProviders/frontendModelProviders.ts
Normal file
@@ -0,0 +1,15 @@
|
||||
import openaiChatCompletionFrontend from "./openai-ChatCompletion/frontend";
|
||||
import replicateLlama2Frontend from "./replicate-llama2/frontend";
|
||||
import { type SupportedProvider, type FrontendModelProvider } from "./types";
|
||||
|
||||
// TODO: make sure we get a typescript error if you forget to add a provider here
|
||||
|
||||
// Keep attributes here that need to be accessible from the frontend. We can't
|
||||
// just include them in the default `modelProviders` object because it has some
|
||||
// transient dependencies that can only be imported on the server.
|
||||
const frontendModelProviders: Record<SupportedProvider, FrontendModelProvider<any, any>> = {
|
||||
"openai/ChatCompletion": openaiChatCompletionFrontend,
|
||||
"replicate/llama2": replicateLlama2Frontend,
|
||||
};
|
||||
|
||||
export default frontendModelProviders;
|
||||
36
src/modelProviders/generateTypes.ts
Normal file
36
src/modelProviders/generateTypes.ts
Normal file
@@ -0,0 +1,36 @@
|
||||
import { type JSONSchema4Object } from "json-schema";
|
||||
import modelProviders from "./modelProviders";
|
||||
import { compile } from "json-schema-to-typescript";
|
||||
import dedent from "dedent";
|
||||
|
||||
export default async function generateTypes() {
|
||||
const combinedSchema = {
|
||||
type: "object",
|
||||
properties: {} as Record<string, JSONSchema4Object>,
|
||||
};
|
||||
|
||||
Object.entries(modelProviders).forEach(([id, provider]) => {
|
||||
combinedSchema.properties[id] = provider.inputSchema;
|
||||
});
|
||||
|
||||
Object.entries(modelProviders).forEach(([id, provider]) => {
|
||||
combinedSchema.properties[id] = provider.inputSchema;
|
||||
});
|
||||
|
||||
const promptTypes = (
|
||||
await compile(combinedSchema as JSONSchema4Object, "PromptTypes", {
|
||||
additionalProperties: false,
|
||||
bannerComment: dedent`
|
||||
/**
|
||||
* This type map defines the input types for each model provider.
|
||||
*/
|
||||
`,
|
||||
})
|
||||
).replace(/export interface PromptTypes/g, "interface PromptTypes");
|
||||
|
||||
return dedent`
|
||||
${promptTypes}
|
||||
|
||||
declare function definePrompt<T extends keyof PromptTypes>(modelProvider: T, input: PromptTypes[T])
|
||||
`;
|
||||
}
|
||||
10
src/modelProviders/modelProviders.ts
Normal file
10
src/modelProviders/modelProviders.ts
Normal file
@@ -0,0 +1,10 @@
|
||||
import openaiChatCompletion from "./openai-ChatCompletion";
|
||||
import replicateLlama2 from "./replicate-llama2";
|
||||
import { type SupportedProvider, type ModelProvider } from "./types";
|
||||
|
||||
const modelProviders: Record<SupportedProvider, ModelProvider<any, any, any>> = {
|
||||
"openai/ChatCompletion": openaiChatCompletion,
|
||||
"replicate/llama2": replicateLlama2,
|
||||
};
|
||||
|
||||
export default modelProviders;
|
||||
77
src/modelProviders/openai-ChatCompletion/codegen/codegen.ts
Normal file
77
src/modelProviders/openai-ChatCompletion/codegen/codegen.ts
Normal file
@@ -0,0 +1,77 @@
|
||||
/* eslint-disable @typescript-eslint/no-var-requires */
|
||||
|
||||
import YAML from "yaml";
|
||||
import fs from "fs";
|
||||
import path from "path";
|
||||
import { openapiSchemaToJsonSchema } from "@openapi-contrib/openapi-schema-to-json-schema";
|
||||
import $RefParser from "@apidevtools/json-schema-ref-parser";
|
||||
import { type JSONObject } from "superjson/dist/types";
|
||||
import assert from "assert";
|
||||
import { type JSONSchema4Object } from "json-schema";
|
||||
import { isObject } from "lodash-es";
|
||||
|
||||
// @ts-expect-error for some reason missing from types
|
||||
import parserEstree from "prettier/plugins/estree";
|
||||
import parserBabel from "prettier/plugins/babel";
|
||||
import prettier from "prettier/standalone";
|
||||
|
||||
const OPENAPI_URL =
|
||||
"https://raw.githubusercontent.com/openai/openai-openapi/0c432eb66fd0c758fd8b9bd69db41c1096e5f4db/openapi.yaml";
|
||||
|
||||
// Fetch the openapi document
|
||||
const response = await fetch(OPENAPI_URL);
|
||||
const openApiYaml = await response.text();
|
||||
|
||||
// Parse the yaml document
|
||||
let schema = YAML.parse(openApiYaml) as JSONObject;
|
||||
schema = openapiSchemaToJsonSchema(schema);
|
||||
|
||||
const jsonSchema = await $RefParser.dereference(schema);
|
||||
|
||||
assert("components" in jsonSchema);
|
||||
const completionRequestSchema = jsonSchema.components.schemas
|
||||
.CreateChatCompletionRequest as JSONSchema4Object;
|
||||
|
||||
// We need to do a bit of surgery here since the Monaco editor doesn't like
|
||||
// the fact that the schema says `model` can be either a string or an enum,
|
||||
// and displays a warning in the editor. Let's stick with just an enum for
|
||||
// now and drop the string option.
|
||||
assert(
|
||||
"properties" in completionRequestSchema &&
|
||||
isObject(completionRequestSchema.properties) &&
|
||||
"model" in completionRequestSchema.properties &&
|
||||
isObject(completionRequestSchema.properties.model),
|
||||
);
|
||||
|
||||
const modelProperty = completionRequestSchema.properties.model;
|
||||
assert(
|
||||
"oneOf" in modelProperty &&
|
||||
Array.isArray(modelProperty.oneOf) &&
|
||||
modelProperty.oneOf.length === 2 &&
|
||||
isObject(modelProperty.oneOf[1]) &&
|
||||
"enum" in modelProperty.oneOf[1],
|
||||
"Expected model to have oneOf length of 2",
|
||||
);
|
||||
modelProperty.type = "string";
|
||||
modelProperty.enum = modelProperty.oneOf[1].enum;
|
||||
delete modelProperty["oneOf"];
|
||||
|
||||
// The default of "inf" confuses the Typescript generator, so can just remove it
|
||||
assert(
|
||||
"max_tokens" in completionRequestSchema.properties &&
|
||||
isObject(completionRequestSchema.properties.max_tokens) &&
|
||||
"default" in completionRequestSchema.properties.max_tokens,
|
||||
);
|
||||
delete completionRequestSchema.properties.max_tokens["default"];
|
||||
|
||||
// Get the directory of the current script
|
||||
const currentDirectory = path.dirname(import.meta.url).replace("file://", "");
|
||||
|
||||
// Write the JSON schema to a file in the current directory
|
||||
fs.writeFileSync(
|
||||
path.join(currentDirectory, "input.schema.json"),
|
||||
await prettier.format(JSON.stringify(completionRequestSchema, null, 2), {
|
||||
parser: "json",
|
||||
plugins: [parserBabel, parserEstree],
|
||||
}),
|
||||
);
|
||||
@@ -0,0 +1,185 @@
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"model": {
|
||||
"description": "ID of the model to use. See the [model endpoint compatibility](/docs/models/model-endpoint-compatibility) table for details on which models work with the Chat API.",
|
||||
"example": "gpt-3.5-turbo",
|
||||
"type": "string",
|
||||
"enum": [
|
||||
"gpt-4",
|
||||
"gpt-4-0613",
|
||||
"gpt-4-32k",
|
||||
"gpt-4-32k-0613",
|
||||
"gpt-3.5-turbo",
|
||||
"gpt-3.5-turbo-16k",
|
||||
"gpt-3.5-turbo-0613",
|
||||
"gpt-3.5-turbo-16k-0613"
|
||||
]
|
||||
},
|
||||
"messages": {
|
||||
"description": "A list of messages comprising the conversation so far. [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb).",
|
||||
"type": "array",
|
||||
"minItems": 1,
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"role": {
|
||||
"type": "string",
|
||||
"enum": ["system", "user", "assistant", "function"],
|
||||
"description": "The role of the messages author. One of `system`, `user`, `assistant`, or `function`."
|
||||
},
|
||||
"content": {
|
||||
"type": "string",
|
||||
"description": "The contents of the message. `content` is required for all messages except assistant messages with function calls."
|
||||
},
|
||||
"name": {
|
||||
"type": "string",
|
||||
"description": "The name of the author of this message. `name` is required if role is `function`, and it should be the name of the function whose response is in the `content`. May contain a-z, A-Z, 0-9, and underscores, with a maximum length of 64 characters."
|
||||
},
|
||||
"function_call": {
|
||||
"type": "object",
|
||||
"description": "The name and arguments of a function that should be called, as generated by the model.",
|
||||
"properties": {
|
||||
"name": {
|
||||
"type": "string",
|
||||
"description": "The name of the function to call."
|
||||
},
|
||||
"arguments": {
|
||||
"type": "string",
|
||||
"description": "The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function."
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ["role"]
|
||||
}
|
||||
},
|
||||
"functions": {
|
||||
"description": "A list of functions the model may generate JSON inputs for.",
|
||||
"type": "array",
|
||||
"minItems": 1,
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"name": {
|
||||
"type": "string",
|
||||
"description": "The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64."
|
||||
},
|
||||
"description": {
|
||||
"type": "string",
|
||||
"description": "The description of what the function does."
|
||||
},
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"description": "The parameters the functions accepts, described as a JSON Schema object. See the [guide](/docs/guides/gpt/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format.",
|
||||
"additionalProperties": true
|
||||
}
|
||||
},
|
||||
"required": ["name"]
|
||||
}
|
||||
},
|
||||
"function_call": {
|
||||
"description": "Controls how the model responds to function calls. \"none\" means the model does not call a function, and responds to the end-user. \"auto\" means the model can pick between an end-user or calling a function. Specifying a particular function via `{\"name\":\\ \"my_function\"}` forces the model to call that function. \"none\" is the default when no functions are present. \"auto\" is the default if functions are present.",
|
||||
"oneOf": [
|
||||
{
|
||||
"type": "string",
|
||||
"enum": ["none", "auto"]
|
||||
},
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"name": {
|
||||
"type": "string",
|
||||
"description": "The name of the function to call."
|
||||
}
|
||||
},
|
||||
"required": ["name"]
|
||||
}
|
||||
]
|
||||
},
|
||||
"temperature": {
|
||||
"type": "number",
|
||||
"minimum": 0,
|
||||
"maximum": 2,
|
||||
"default": 1,
|
||||
"example": 1,
|
||||
"nullable": true,
|
||||
"description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n\nWe generally recommend altering this or `top_p` but not both.\n"
|
||||
},
|
||||
"top_p": {
|
||||
"type": "number",
|
||||
"minimum": 0,
|
||||
"maximum": 1,
|
||||
"default": 1,
|
||||
"example": 1,
|
||||
"nullable": true,
|
||||
"description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or `temperature` but not both.\n"
|
||||
},
|
||||
"n": {
|
||||
"type": "integer",
|
||||
"minimum": 1,
|
||||
"maximum": 128,
|
||||
"default": 1,
|
||||
"example": 1,
|
||||
"nullable": true,
|
||||
"description": "How many chat completion choices to generate for each input message."
|
||||
},
|
||||
"stream": {
|
||||
"description": "If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb).\n",
|
||||
"type": "boolean",
|
||||
"nullable": true,
|
||||
"default": false
|
||||
},
|
||||
"stop": {
|
||||
"description": "Up to 4 sequences where the API will stop generating further tokens.\n",
|
||||
"default": null,
|
||||
"oneOf": [
|
||||
{
|
||||
"type": "string",
|
||||
"nullable": true
|
||||
},
|
||||
{
|
||||
"type": "array",
|
||||
"minItems": 1,
|
||||
"maxItems": 4,
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
}
|
||||
]
|
||||
},
|
||||
"max_tokens": {
|
||||
"description": "The maximum number of [tokens](/tokenizer) to generate in the chat completion.\n\nThe total length of input tokens and generated tokens is limited by the model's context length. [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) for counting tokens.\n",
|
||||
"type": "integer"
|
||||
},
|
||||
"presence_penalty": {
|
||||
"type": "number",
|
||||
"default": 0,
|
||||
"minimum": -2,
|
||||
"maximum": 2,
|
||||
"nullable": true,
|
||||
"description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.\n\n[See more information about frequency and presence penalties.](/docs/api-reference/parameter-details)\n"
|
||||
},
|
||||
"frequency_penalty": {
|
||||
"type": "number",
|
||||
"default": 0,
|
||||
"minimum": -2,
|
||||
"maximum": 2,
|
||||
"nullable": true,
|
||||
"description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.\n\n[See more information about frequency and presence penalties.](/docs/api-reference/parameter-details)\n"
|
||||
},
|
||||
"logit_bias": {
|
||||
"type": "object",
|
||||
"x-oaiTypeLabel": "map",
|
||||
"default": null,
|
||||
"nullable": true,
|
||||
"description": "Modify the likelihood of specified tokens appearing in the completion.\n\nAccepts a json object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.\n"
|
||||
},
|
||||
"user": {
|
||||
"type": "string",
|
||||
"example": "user-1234",
|
||||
"description": "A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).\n"
|
||||
}
|
||||
},
|
||||
"required": ["model", "messages"]
|
||||
}
|
||||
87
src/modelProviders/openai-ChatCompletion/frontend.ts
Normal file
87
src/modelProviders/openai-ChatCompletion/frontend.ts
Normal file
@@ -0,0 +1,87 @@
|
||||
import { type JsonValue } from "type-fest";
|
||||
import { type SupportedModel } from ".";
|
||||
import { type FrontendModelProvider } from "../types";
|
||||
import { type ChatCompletion } from "openai/resources/chat";
|
||||
import { refinementActions } from "./refinementActions";
|
||||
|
||||
const frontendModelProvider: FrontendModelProvider<SupportedModel, ChatCompletion> = {
|
||||
name: "OpenAI ChatCompletion",
|
||||
|
||||
models: {
|
||||
"gpt-4-0613": {
|
||||
name: "GPT-4",
|
||||
contextWindow: 8192,
|
||||
promptTokenPrice: 0.00003,
|
||||
completionTokenPrice: 0.00006,
|
||||
speed: "medium",
|
||||
provider: "openai/ChatCompletion",
|
||||
learnMoreUrl: "https://openai.com/gpt-4",
|
||||
},
|
||||
"gpt-4-32k-0613": {
|
||||
name: "GPT-4 32k",
|
||||
contextWindow: 32768,
|
||||
promptTokenPrice: 0.00006,
|
||||
completionTokenPrice: 0.00012,
|
||||
speed: "medium",
|
||||
provider: "openai/ChatCompletion",
|
||||
learnMoreUrl: "https://openai.com/gpt-4",
|
||||
},
|
||||
"gpt-3.5-turbo-0613": {
|
||||
name: "GPT-3.5 Turbo",
|
||||
contextWindow: 4096,
|
||||
promptTokenPrice: 0.0000015,
|
||||
completionTokenPrice: 0.000002,
|
||||
speed: "fast",
|
||||
provider: "openai/ChatCompletion",
|
||||
learnMoreUrl: "https://platform.openai.com/docs/guides/gpt/chat-completions-api",
|
||||
},
|
||||
"gpt-3.5-turbo-16k-0613": {
|
||||
name: "GPT-3.5 Turbo 16k",
|
||||
contextWindow: 16384,
|
||||
promptTokenPrice: 0.000003,
|
||||
completionTokenPrice: 0.000004,
|
||||
speed: "fast",
|
||||
provider: "openai/ChatCompletion",
|
||||
learnMoreUrl: "https://platform.openai.com/docs/guides/gpt/chat-completions-api",
|
||||
},
|
||||
},
|
||||
|
||||
refinementActions,
|
||||
|
||||
normalizeOutput: (output) => {
|
||||
const message = output.choices[0]?.message;
|
||||
if (!message)
|
||||
return {
|
||||
type: "json",
|
||||
value: output as unknown as JsonValue,
|
||||
};
|
||||
|
||||
if (message.content) {
|
||||
return {
|
||||
type: "text",
|
||||
value: message.content,
|
||||
};
|
||||
} else if (message.function_call) {
|
||||
let args = message.function_call.arguments ?? "";
|
||||
try {
|
||||
args = JSON.parse(args);
|
||||
} catch (e) {
|
||||
// Ignore
|
||||
}
|
||||
return {
|
||||
type: "json",
|
||||
value: {
|
||||
...message.function_call,
|
||||
arguments: args,
|
||||
},
|
||||
};
|
||||
} else {
|
||||
return {
|
||||
type: "json",
|
||||
value: message as unknown as JsonValue,
|
||||
};
|
||||
}
|
||||
},
|
||||
};
|
||||
|
||||
export default frontendModelProvider;
|
||||
140
src/modelProviders/openai-ChatCompletion/getCompletion.ts
Normal file
140
src/modelProviders/openai-ChatCompletion/getCompletion.ts
Normal file
@@ -0,0 +1,140 @@
|
||||
/* eslint-disable @typescript-eslint/no-unsafe-call */
|
||||
import {
|
||||
type ChatCompletionChunk,
|
||||
type ChatCompletion,
|
||||
type CompletionCreateParams,
|
||||
} from "openai/resources/chat";
|
||||
import { countOpenAIChatTokens } from "~/utils/countTokens";
|
||||
import { type CompletionResponse } from "../types";
|
||||
import { omit } from "lodash-es";
|
||||
import { openai } from "~/server/utils/openai";
|
||||
import { truthyFilter } from "~/utils/utils";
|
||||
import { APIError } from "openai";
|
||||
import frontendModelProvider from "./frontend";
|
||||
import modelProvider, { type SupportedModel } from ".";
|
||||
|
||||
const mergeStreamedChunks = (
|
||||
base: ChatCompletion | null,
|
||||
chunk: ChatCompletionChunk,
|
||||
): ChatCompletion => {
|
||||
if (base === null) {
|
||||
return mergeStreamedChunks({ ...chunk, choices: [] }, chunk);
|
||||
}
|
||||
|
||||
const choices = [...base.choices];
|
||||
for (const choice of chunk.choices) {
|
||||
const baseChoice = choices.find((c) => c.index === choice.index);
|
||||
if (baseChoice) {
|
||||
baseChoice.finish_reason = choice.finish_reason ?? baseChoice.finish_reason;
|
||||
baseChoice.message = baseChoice.message ?? { role: "assistant" };
|
||||
|
||||
if (choice.delta?.content)
|
||||
baseChoice.message.content =
|
||||
((baseChoice.message.content as string) ?? "") + (choice.delta.content ?? "");
|
||||
if (choice.delta?.function_call) {
|
||||
const fnCall = baseChoice.message.function_call ?? {};
|
||||
fnCall.name =
|
||||
((fnCall.name as string) ?? "") + ((choice.delta.function_call.name as string) ?? "");
|
||||
fnCall.arguments =
|
||||
((fnCall.arguments as string) ?? "") +
|
||||
((choice.delta.function_call.arguments as string) ?? "");
|
||||
}
|
||||
} else {
|
||||
choices.push({ ...omit(choice, "delta"), message: { role: "assistant", ...choice.delta } });
|
||||
}
|
||||
}
|
||||
|
||||
const merged: ChatCompletion = {
|
||||
...base,
|
||||
choices,
|
||||
};
|
||||
|
||||
return merged;
|
||||
};
|
||||
|
||||
export async function getCompletion(
|
||||
input: CompletionCreateParams,
|
||||
onStream: ((partialOutput: ChatCompletion) => void) | null,
|
||||
): Promise<CompletionResponse<ChatCompletion>> {
|
||||
const start = Date.now();
|
||||
let finalCompletion: ChatCompletion | null = null;
|
||||
let promptTokens: number | undefined = undefined;
|
||||
let completionTokens: number | undefined = undefined;
|
||||
const modelName = modelProvider.getModel(input) as SupportedModel;
|
||||
|
||||
try {
|
||||
if (onStream) {
|
||||
const resp = await openai.chat.completions.create(
|
||||
{ ...input, stream: true },
|
||||
{
|
||||
maxRetries: 0,
|
||||
},
|
||||
);
|
||||
for await (const part of resp) {
|
||||
finalCompletion = mergeStreamedChunks(finalCompletion, part);
|
||||
onStream(finalCompletion);
|
||||
}
|
||||
if (!finalCompletion) {
|
||||
return {
|
||||
type: "error",
|
||||
message: "Streaming failed to return a completion",
|
||||
autoRetry: false,
|
||||
};
|
||||
}
|
||||
try {
|
||||
promptTokens = countOpenAIChatTokens(modelName, input.messages);
|
||||
completionTokens = countOpenAIChatTokens(
|
||||
modelName,
|
||||
finalCompletion.choices.map((c) => c.message).filter(truthyFilter),
|
||||
);
|
||||
} catch (err) {
|
||||
// TODO handle this, library seems like maybe it doesn't work with function calls?
|
||||
console.error(err);
|
||||
}
|
||||
} else {
|
||||
const resp = await openai.chat.completions.create(
|
||||
{ ...input, stream: false },
|
||||
{
|
||||
maxRetries: 0,
|
||||
},
|
||||
);
|
||||
finalCompletion = resp;
|
||||
promptTokens = resp.usage?.prompt_tokens ?? 0;
|
||||
completionTokens = resp.usage?.completion_tokens ?? 0;
|
||||
}
|
||||
const timeToComplete = Date.now() - start;
|
||||
|
||||
const { promptTokenPrice, completionTokenPrice } = frontendModelProvider.models[modelName];
|
||||
let cost = undefined;
|
||||
if (promptTokenPrice && completionTokenPrice && promptTokens && completionTokens) {
|
||||
cost = promptTokens * promptTokenPrice + completionTokens * completionTokenPrice;
|
||||
}
|
||||
|
||||
return {
|
||||
type: "success",
|
||||
statusCode: 200,
|
||||
value: finalCompletion,
|
||||
timeToComplete,
|
||||
promptTokens,
|
||||
completionTokens,
|
||||
cost,
|
||||
};
|
||||
} catch (error: unknown) {
|
||||
console.error("ERROR IS", error);
|
||||
if (error instanceof APIError) {
|
||||
return {
|
||||
type: "error",
|
||||
message: error.message,
|
||||
autoRetry: error.status === 429 || error.status === 503,
|
||||
statusCode: error.status,
|
||||
};
|
||||
} else {
|
||||
console.error(error);
|
||||
return {
|
||||
type: "error",
|
||||
message: (error as Error).message,
|
||||
autoRetry: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
||||
45
src/modelProviders/openai-ChatCompletion/index.ts
Normal file
45
src/modelProviders/openai-ChatCompletion/index.ts
Normal file
@@ -0,0 +1,45 @@
|
||||
import { type JSONSchema4 } from "json-schema";
|
||||
import { type ModelProvider } from "../types";
|
||||
import inputSchema from "./codegen/input.schema.json";
|
||||
import { type ChatCompletion, type CompletionCreateParams } from "openai/resources/chat";
|
||||
import { getCompletion } from "./getCompletion";
|
||||
import frontendModelProvider from "./frontend";
|
||||
|
||||
const supportedModels = [
|
||||
"gpt-4-0613",
|
||||
"gpt-4-32k-0613",
|
||||
"gpt-3.5-turbo-0613",
|
||||
"gpt-3.5-turbo-16k-0613",
|
||||
] as const;
|
||||
|
||||
export type SupportedModel = (typeof supportedModels)[number];
|
||||
|
||||
export type OpenaiChatModelProvider = ModelProvider<
|
||||
SupportedModel,
|
||||
CompletionCreateParams,
|
||||
ChatCompletion
|
||||
>;
|
||||
|
||||
const modelProvider: OpenaiChatModelProvider = {
|
||||
getModel: (input) => {
|
||||
if (supportedModels.includes(input.model as SupportedModel))
|
||||
return input.model as SupportedModel;
|
||||
|
||||
const modelMaps: Record<string, SupportedModel> = {
|
||||
"gpt-4": "gpt-4-0613",
|
||||
"gpt-4-32k": "gpt-4-32k-0613",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo-0613",
|
||||
"gpt-3.5-turbo-16k": "gpt-3.5-turbo-16k-0613",
|
||||
};
|
||||
|
||||
if (input.model in modelMaps) return modelMaps[input.model] as SupportedModel;
|
||||
|
||||
return null;
|
||||
},
|
||||
inputSchema: inputSchema as JSONSchema4,
|
||||
canStream: true,
|
||||
getCompletion,
|
||||
...frontendModelProvider,
|
||||
};
|
||||
|
||||
export default modelProvider;
|
||||
279
src/modelProviders/openai-ChatCompletion/refinementActions.ts
Normal file
279
src/modelProviders/openai-ChatCompletion/refinementActions.ts
Normal file
@@ -0,0 +1,279 @@
|
||||
import { TfiThought } from "react-icons/tfi";
|
||||
import { type RefinementAction } from "../types";
|
||||
import { VscJson } from "react-icons/vsc";
|
||||
|
||||
export const refinementActions: Record<string, RefinementAction> = {
|
||||
"Add chain of thought": {
|
||||
icon: VscJson,
|
||||
description: "Asking the model to plan its answer can increase accuracy.",
|
||||
instructions: `Adding chain of thought means asking the model to think about its answer before it gives it to you. This is useful for getting more accurate answers. Do not add an assistant message.
|
||||
|
||||
This is what a prompt looks like before adding chain of thought:
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-4",
|
||||
stream: true,
|
||||
messages: [
|
||||
{
|
||||
role: "system",
|
||||
content: \`Evaluate sentiment.\`,
|
||||
},
|
||||
{
|
||||
role: "user",
|
||||
content: \`This is the user's message: \${scenario.user_message}. Return "positive" or "negative" or "neutral"\`,
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
This is what one looks like after adding chain of thought:
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-4",
|
||||
stream: true,
|
||||
messages: [
|
||||
{
|
||||
role: "system",
|
||||
content: \`Evaluate sentiment.\`,
|
||||
},
|
||||
{
|
||||
role: "user",
|
||||
content: \`This is the user's message: \${scenario.user_message}. Return "positive" or "negative" or "neutral". Explain your answer before you give a score, then return the score on a new line.\`,
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
Here's another example:
|
||||
|
||||
Before:
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-3.5-turbo",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: \`Title: \${scenario.title}
|
||||
Body: \${scenario.body}
|
||||
|
||||
Need: \${scenario.need}
|
||||
|
||||
Rate likelihood on 1-3 scale.\`,
|
||||
},
|
||||
],
|
||||
temperature: 0,
|
||||
functions: [
|
||||
{
|
||||
name: "score_post",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
score: {
|
||||
type: "number",
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
function_call: {
|
||||
name: "score_post",
|
||||
},
|
||||
});
|
||||
|
||||
After:
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-3.5-turbo",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: \`Title: \${scenario.title}
|
||||
Body: \${scenario.body}
|
||||
|
||||
Need: \${scenario.need}
|
||||
|
||||
Rate likelihood on 1-3 scale. Provide an explanation, but always provide a score afterward.\`,
|
||||
},
|
||||
],
|
||||
temperature: 0,
|
||||
functions: [
|
||||
{
|
||||
name: "score_post",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
explanation: {
|
||||
type: "string",
|
||||
}
|
||||
score: {
|
||||
type: "number",
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
function_call: {
|
||||
name: "score_post",
|
||||
},
|
||||
});
|
||||
|
||||
Add chain of thought to the original prompt.`,
|
||||
},
|
||||
"Convert to function call": {
|
||||
icon: TfiThought,
|
||||
description: "Use function calls to get output from the model in a more structured way.",
|
||||
instructions: `OpenAI functions are a specialized way for an LLM to return output.
|
||||
|
||||
This is what a prompt looks like before adding a function:
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-4",
|
||||
stream: true,
|
||||
messages: [
|
||||
{
|
||||
role: "system",
|
||||
content: \`Evaluate sentiment.\`,
|
||||
},
|
||||
{
|
||||
role: "user",
|
||||
content: \`This is the user's message: \${scenario.user_message}. Return "positive" or "negative" or "neutral"\`,
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
This is what one looks like after adding a function:
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-4",
|
||||
stream: true,
|
||||
messages: [
|
||||
{
|
||||
role: "system",
|
||||
content: "Evaluate sentiment.",
|
||||
},
|
||||
{
|
||||
role: "user",
|
||||
content: scenario.user_message,
|
||||
},
|
||||
],
|
||||
functions: [
|
||||
{
|
||||
name: "extract_sentiment",
|
||||
parameters: {
|
||||
type: "object", // parameters must always be an object with a properties key
|
||||
properties: { // properties key is required
|
||||
sentiment: {
|
||||
type: "string",
|
||||
description: "one of positive/negative/neutral",
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
function_call: {
|
||||
name: "extract_sentiment",
|
||||
},
|
||||
});
|
||||
|
||||
Here's another example of adding a function:
|
||||
|
||||
Before:
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-3.5-turbo",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: \`Here is the title and body of a reddit post I am interested in:
|
||||
|
||||
title: \${scenario.title}
|
||||
body: \${scenario.body}
|
||||
|
||||
On a scale from 1 to 3, how likely is it that the person writing this post has the following need? If you are not sure, make your best guess, or answer 1.
|
||||
|
||||
Need: \${scenario.need}
|
||||
|
||||
Answer one integer between 1 and 3.\`,
|
||||
},
|
||||
],
|
||||
temperature: 0,
|
||||
});
|
||||
|
||||
After:
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-3.5-turbo",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: \`Title: \${scenario.title}
|
||||
Body: \${scenario.body}
|
||||
|
||||
Need: \${scenario.need}
|
||||
|
||||
Rate likelihood on 1-3 scale.\`,
|
||||
},
|
||||
],
|
||||
temperature: 0,
|
||||
functions: [
|
||||
{
|
||||
name: "score_post",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
score: {
|
||||
type: "number",
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
function_call: {
|
||||
name: "score_post",
|
||||
},
|
||||
});
|
||||
|
||||
Another example
|
||||
|
||||
Before:
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-3.5-turbo",
|
||||
stream: true,
|
||||
messages: [
|
||||
{
|
||||
role: "system",
|
||||
content: \`Write 'Start experimenting!' in \${scenario.language}\`,
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
After:
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-3.5-turbo",
|
||||
messages: [
|
||||
{
|
||||
role: "system",
|
||||
content: \`Write 'Start experimenting!' in \${scenario.language}\`,
|
||||
},
|
||||
],
|
||||
functions: [
|
||||
{
|
||||
name: "write_in_language",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
text: {
|
||||
type: "string",
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
function_call: {
|
||||
name: "write_in_language",
|
||||
},
|
||||
});
|
||||
|
||||
Add an OpenAI function that takes one or more nested parameters that match the expected output from this prompt.`,
|
||||
},
|
||||
};
|
||||
45
src/modelProviders/replicate-llama2/frontend.ts
Normal file
45
src/modelProviders/replicate-llama2/frontend.ts
Normal file
@@ -0,0 +1,45 @@
|
||||
import { type SupportedModel, type ReplicateLlama2Output } from ".";
|
||||
import { type FrontendModelProvider } from "../types";
|
||||
import { refinementActions } from "./refinementActions";
|
||||
|
||||
const frontendModelProvider: FrontendModelProvider<SupportedModel, ReplicateLlama2Output> = {
|
||||
name: "Replicate Llama2",
|
||||
|
||||
models: {
|
||||
"7b-chat": {
|
||||
name: "LLama 2 7B Chat",
|
||||
contextWindow: 4096,
|
||||
pricePerSecond: 0.0023,
|
||||
speed: "fast",
|
||||
provider: "replicate/llama2",
|
||||
learnMoreUrl: "https://replicate.com/a16z-infra/llama7b-v2-chat",
|
||||
},
|
||||
"13b-chat": {
|
||||
name: "LLama 2 13B Chat",
|
||||
contextWindow: 4096,
|
||||
pricePerSecond: 0.0023,
|
||||
speed: "medium",
|
||||
provider: "replicate/llama2",
|
||||
learnMoreUrl: "https://replicate.com/a16z-infra/llama13b-v2-chat",
|
||||
},
|
||||
"70b-chat": {
|
||||
name: "LLama 2 70B Chat",
|
||||
contextWindow: 4096,
|
||||
pricePerSecond: 0.0032,
|
||||
speed: "slow",
|
||||
provider: "replicate/llama2",
|
||||
learnMoreUrl: "https://replicate.com/replicate/llama70b-v2-chat",
|
||||
},
|
||||
},
|
||||
|
||||
refinementActions,
|
||||
|
||||
normalizeOutput: (output) => {
|
||||
return {
|
||||
type: "text",
|
||||
value: output.join(""),
|
||||
};
|
||||
},
|
||||
};
|
||||
|
||||
export default frontendModelProvider;
|
||||
60
src/modelProviders/replicate-llama2/getCompletion.ts
Normal file
60
src/modelProviders/replicate-llama2/getCompletion.ts
Normal file
@@ -0,0 +1,60 @@
|
||||
import { env } from "~/env.mjs";
|
||||
import { type ReplicateLlama2Input, type ReplicateLlama2Output } from ".";
|
||||
import { type CompletionResponse } from "../types";
|
||||
import Replicate from "replicate";
|
||||
|
||||
const replicate = new Replicate({
|
||||
auth: env.REPLICATE_API_TOKEN || "",
|
||||
});
|
||||
|
||||
const modelIds: Record<ReplicateLlama2Input["model"], string> = {
|
||||
"7b-chat": "5ec5fdadd80ace49f5a2b2178cceeb9f2f77c493b85b1131002c26e6b2b13184",
|
||||
"13b-chat": "6b4da803a2382c08868c5af10a523892f38e2de1aafb2ee55b020d9efef2fdb8",
|
||||
"70b-chat": "2d19859030ff705a87c746f7e96eea03aefb71f166725aee39692f1476566d48",
|
||||
};
|
||||
|
||||
export async function getCompletion(
|
||||
input: ReplicateLlama2Input,
|
||||
onStream: ((partialOutput: string[]) => void) | null,
|
||||
): Promise<CompletionResponse<ReplicateLlama2Output>> {
|
||||
const start = Date.now();
|
||||
|
||||
const { model, ...rest } = input;
|
||||
|
||||
try {
|
||||
const prediction = await replicate.predictions.create({
|
||||
version: modelIds[model],
|
||||
input: rest,
|
||||
});
|
||||
|
||||
const interval = onStream
|
||||
? // eslint-disable-next-line @typescript-eslint/no-misused-promises
|
||||
setInterval(async () => {
|
||||
const partialPrediction = await replicate.predictions.get(prediction.id);
|
||||
|
||||
if (partialPrediction.output) onStream(partialPrediction.output as ReplicateLlama2Output);
|
||||
}, 500)
|
||||
: null;
|
||||
|
||||
const resp = await replicate.wait(prediction, {});
|
||||
if (interval) clearInterval(interval);
|
||||
|
||||
const timeToComplete = Date.now() - start;
|
||||
|
||||
if (resp.error) throw new Error(resp.error as string);
|
||||
|
||||
return {
|
||||
type: "success",
|
||||
statusCode: 200,
|
||||
value: resp.output as ReplicateLlama2Output,
|
||||
timeToComplete,
|
||||
};
|
||||
} catch (error: unknown) {
|
||||
console.error("ERROR IS", error);
|
||||
return {
|
||||
type: "error",
|
||||
message: (error as Error).message,
|
||||
autoRetry: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
81
src/modelProviders/replicate-llama2/index.ts
Normal file
81
src/modelProviders/replicate-llama2/index.ts
Normal file
@@ -0,0 +1,81 @@
|
||||
import { type ModelProvider } from "../types";
|
||||
import frontendModelProvider from "./frontend";
|
||||
import { getCompletion } from "./getCompletion";
|
||||
|
||||
const supportedModels = ["7b-chat", "13b-chat", "70b-chat"] as const;
|
||||
|
||||
export type SupportedModel = (typeof supportedModels)[number];
|
||||
|
||||
export type ReplicateLlama2Input = {
|
||||
model: SupportedModel;
|
||||
prompt: string;
|
||||
max_length?: number;
|
||||
temperature?: number;
|
||||
top_p?: number;
|
||||
repetition_penalty?: number;
|
||||
debug?: boolean;
|
||||
};
|
||||
|
||||
export type ReplicateLlama2Output = string[];
|
||||
|
||||
export type ReplicateLlama2Provider = ModelProvider<
|
||||
SupportedModel,
|
||||
ReplicateLlama2Input,
|
||||
ReplicateLlama2Output
|
||||
>;
|
||||
|
||||
const modelProvider: ReplicateLlama2Provider = {
|
||||
getModel: (input) => {
|
||||
if (supportedModels.includes(input.model)) return input.model;
|
||||
|
||||
return null;
|
||||
},
|
||||
inputSchema: {
|
||||
type: "object",
|
||||
properties: {
|
||||
model: {
|
||||
type: "string",
|
||||
enum: supportedModels as unknown as string[],
|
||||
},
|
||||
system_prompt: {
|
||||
type: "string",
|
||||
description:
|
||||
"System prompt to send to Llama v2. This is prepended to the prompt and helps guide system behavior.",
|
||||
},
|
||||
prompt: {
|
||||
type: "string",
|
||||
description: "Prompt to send to Llama v2.",
|
||||
},
|
||||
max_new_tokens: {
|
||||
type: "number",
|
||||
description:
|
||||
"Maximum number of tokens to generate. A word is generally 2-3 tokens (minimum: 1)",
|
||||
},
|
||||
temperature: {
|
||||
type: "number",
|
||||
description:
|
||||
"Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value. (minimum: 0.01; maximum: 5)",
|
||||
},
|
||||
top_p: {
|
||||
type: "number",
|
||||
description:
|
||||
"When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens (minimum: 0.01; maximum: 1)",
|
||||
},
|
||||
repetition_penalty: {
|
||||
type: "number",
|
||||
description:
|
||||
"Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, less than 1 encourage it. (minimum: 0.01; maximum: 5)",
|
||||
},
|
||||
debug: {
|
||||
type: "boolean",
|
||||
description: "provide debugging output in logs",
|
||||
},
|
||||
},
|
||||
required: ["model", "prompt"],
|
||||
},
|
||||
canStream: true,
|
||||
getCompletion,
|
||||
...frontendModelProvider,
|
||||
};
|
||||
|
||||
export default modelProvider;
|
||||
3
src/modelProviders/replicate-llama2/refinementActions.ts
Normal file
3
src/modelProviders/replicate-llama2/refinementActions.ts
Normal file
@@ -0,0 +1,3 @@
|
||||
import { type RefinementAction } from "../types";
|
||||
|
||||
export const refinementActions: Record<string, RefinementAction> = {};
|
||||
70
src/modelProviders/types.ts
Normal file
70
src/modelProviders/types.ts
Normal file
@@ -0,0 +1,70 @@
|
||||
import { type JSONSchema4 } from "json-schema";
|
||||
import { type IconType } from "react-icons";
|
||||
import { type JsonValue } from "type-fest";
|
||||
import { z } from "zod";
|
||||
|
||||
export const ZodSupportedProvider = z.union([
|
||||
z.literal("openai/ChatCompletion"),
|
||||
z.literal("replicate/llama2"),
|
||||
]);
|
||||
|
||||
export type SupportedProvider = z.infer<typeof ZodSupportedProvider>;
|
||||
|
||||
export type Model = {
|
||||
name: string;
|
||||
contextWindow: number;
|
||||
promptTokenPrice?: number;
|
||||
completionTokenPrice?: number;
|
||||
pricePerSecond?: number;
|
||||
speed: "fast" | "medium" | "slow";
|
||||
provider: SupportedProvider;
|
||||
description?: string;
|
||||
learnMoreUrl?: string;
|
||||
};
|
||||
|
||||
export type ProviderModel = { provider: z.infer<typeof ZodSupportedProvider>; model: string };
|
||||
|
||||
export type RefinementAction = { icon?: IconType; description: string; instructions: string };
|
||||
|
||||
export type FrontendModelProvider<SupportedModels extends string, OutputSchema> = {
|
||||
name: string;
|
||||
models: Record<SupportedModels, Model>;
|
||||
refinementActions?: Record<string, RefinementAction>;
|
||||
|
||||
normalizeOutput: (output: OutputSchema) => NormalizedOutput;
|
||||
};
|
||||
|
||||
export type CompletionResponse<T> =
|
||||
| { type: "error"; message: string; autoRetry: boolean; statusCode?: number }
|
||||
| {
|
||||
type: "success";
|
||||
value: T;
|
||||
timeToComplete: number;
|
||||
statusCode: number;
|
||||
promptTokens?: number;
|
||||
completionTokens?: number;
|
||||
cost?: number;
|
||||
};
|
||||
|
||||
export type ModelProvider<SupportedModels extends string, InputSchema, OutputSchema> = {
|
||||
getModel: (input: InputSchema) => SupportedModels | null;
|
||||
canStream: boolean;
|
||||
inputSchema: JSONSchema4;
|
||||
getCompletion: (
|
||||
input: InputSchema,
|
||||
onStream: ((partialOutput: OutputSchema) => void) | null,
|
||||
) => Promise<CompletionResponse<OutputSchema>>;
|
||||
|
||||
// This is just a convenience for type inference, don't use it at runtime
|
||||
_outputSchema?: OutputSchema | null;
|
||||
} & FrontendModelProvider<SupportedModels, OutputSchema>;
|
||||
|
||||
export type NormalizedOutput =
|
||||
| {
|
||||
type: "text";
|
||||
value: string;
|
||||
}
|
||||
| {
|
||||
type: "json";
|
||||
value: JsonValue;
|
||||
};
|
||||
@@ -2,11 +2,13 @@ import { type Session } from "next-auth";
|
||||
import { SessionProvider } from "next-auth/react";
|
||||
import { type AppType } from "next/app";
|
||||
import { api } from "~/utils/api";
|
||||
import { ChakraProvider } from "@chakra-ui/react";
|
||||
import theme from "~/utils/theme";
|
||||
import Favicon from "~/components/Favicon";
|
||||
import "~/utils/analytics";
|
||||
import Head from "next/head";
|
||||
import { ChakraThemeProvider } from "~/theme/ChakraThemeProvider";
|
||||
import { SyncAppStore } from "~/state/sync";
|
||||
import NextAdapterApp from "next-query-params/app";
|
||||
import { QueryParamProvider } from "use-query-params";
|
||||
|
||||
const MyApp: AppType<{ session: Session | null }> = ({
|
||||
Component,
|
||||
@@ -21,10 +23,13 @@ const MyApp: AppType<{ session: Session | null }> = ({
|
||||
/>
|
||||
</Head>
|
||||
<SessionProvider session={session}>
|
||||
<SyncAppStore />
|
||||
<Favicon />
|
||||
<ChakraProvider theme={theme}>
|
||||
<Component {...pageProps} />
|
||||
</ChakraProvider>
|
||||
<ChakraThemeProvider>
|
||||
<QueryParamProvider adapter={NextAdapterApp}>
|
||||
<Component {...pageProps} />
|
||||
</QueryParamProvider>
|
||||
</ChakraThemeProvider>
|
||||
</SessionProvider>
|
||||
</>
|
||||
);
|
||||
|
||||
@@ -2,102 +2,37 @@ import {
|
||||
Box,
|
||||
Breadcrumb,
|
||||
BreadcrumbItem,
|
||||
Button,
|
||||
Center,
|
||||
Flex,
|
||||
Icon,
|
||||
Input,
|
||||
AlertDialog,
|
||||
AlertDialogBody,
|
||||
AlertDialogFooter,
|
||||
AlertDialogHeader,
|
||||
AlertDialogContent,
|
||||
AlertDialogOverlay,
|
||||
useDisclosure,
|
||||
Text,
|
||||
HStack,
|
||||
VStack,
|
||||
} from "@chakra-ui/react";
|
||||
import Link from "next/link";
|
||||
|
||||
import { useRouter } from "next/router";
|
||||
import { useState, useEffect, useRef } from "react";
|
||||
import { BsGearFill, BsTrash } from "react-icons/bs";
|
||||
import { useState, useEffect } from "react";
|
||||
import { RiFlaskLine } from "react-icons/ri";
|
||||
import OutputsTable from "~/components/OutputsTable";
|
||||
import SettingsDrawer from "~/components/OutputsTable/SettingsDrawer";
|
||||
import ExperimentSettingsDrawer from "~/components/ExperimentSettingsDrawer/ExperimentSettingsDrawer";
|
||||
import AppShell from "~/components/nav/AppShell";
|
||||
import { api } from "~/utils/api";
|
||||
import { useExperiment, useHandledAsyncCallback } from "~/utils/hooks";
|
||||
import { useAppStore } from "~/state/store";
|
||||
import { useSyncVariantEditor } from "~/state/sync";
|
||||
|
||||
const DeleteButton = () => {
|
||||
const experiment = useExperiment();
|
||||
const mutation = api.experiments.delete.useMutation();
|
||||
const utils = api.useContext();
|
||||
const router = useRouter();
|
||||
|
||||
const { isOpen, onOpen, onClose } = useDisclosure();
|
||||
const cancelRef = useRef<HTMLButtonElement>(null);
|
||||
|
||||
const [onDeleteConfirm] = useHandledAsyncCallback(async () => {
|
||||
if (!experiment.data?.id) return;
|
||||
await mutation.mutateAsync({ id: experiment.data.id });
|
||||
await utils.experiments.list.invalidate();
|
||||
await router.push({ pathname: "/experiments" });
|
||||
onClose();
|
||||
}, [mutation, experiment.data?.id, router]);
|
||||
|
||||
return (
|
||||
<>
|
||||
<Button
|
||||
size="sm"
|
||||
variant={{ base: "outline", lg: "ghost" }}
|
||||
colorScheme="gray"
|
||||
fontWeight="normal"
|
||||
onClick={onOpen}
|
||||
>
|
||||
<Icon as={BsTrash} boxSize={4} color="gray.600" />
|
||||
<Text display={{ base: "none", lg: "block" }} ml={2}>
|
||||
Delete Experiment
|
||||
</Text>
|
||||
</Button>
|
||||
|
||||
<AlertDialog isOpen={isOpen} leastDestructiveRef={cancelRef} onClose={onClose}>
|
||||
<AlertDialogOverlay>
|
||||
<AlertDialogContent>
|
||||
<AlertDialogHeader fontSize="lg" fontWeight="bold">
|
||||
Delete Experiment
|
||||
</AlertDialogHeader>
|
||||
|
||||
<AlertDialogBody>
|
||||
If you delete this experiment all the associated prompts and scenarios will be deleted
|
||||
as well. Are you sure?
|
||||
</AlertDialogBody>
|
||||
|
||||
<AlertDialogFooter>
|
||||
<Button ref={cancelRef} onClick={onClose}>
|
||||
Cancel
|
||||
</Button>
|
||||
<Button colorScheme="red" onClick={onDeleteConfirm} ml={3}>
|
||||
Delete
|
||||
</Button>
|
||||
</AlertDialogFooter>
|
||||
</AlertDialogContent>
|
||||
</AlertDialogOverlay>
|
||||
</AlertDialog>
|
||||
</>
|
||||
);
|
||||
};
|
||||
import { HeaderButtons } from "~/components/experiments/HeaderButtons/HeaderButtons";
|
||||
|
||||
export default function Experiment() {
|
||||
const router = useRouter();
|
||||
const experiment = useExperiment();
|
||||
const utils = api.useContext();
|
||||
const openDrawer = useAppStore((s) => s.openDrawer);
|
||||
useSyncVariantEditor();
|
||||
|
||||
useEffect(() => {
|
||||
useAppStore.getState().sharedVariantEditor.loadMonaco().catch(console.error);
|
||||
});
|
||||
|
||||
const [label, setLabel] = useState(experiment.data?.label || "");
|
||||
useEffect(() => {
|
||||
setLabel(experiment.data?.label || "");
|
||||
@@ -134,7 +69,7 @@ export default function Experiment() {
|
||||
py={2}
|
||||
w="full"
|
||||
direction={{ base: "column", sm: "row" }}
|
||||
alignItems="flex-start"
|
||||
alignItems={{ base: "flex-start", sm: "center" }}
|
||||
>
|
||||
<Breadcrumb flex={1}>
|
||||
<BreadcrumbItem>
|
||||
@@ -167,25 +102,9 @@ export default function Experiment() {
|
||||
)}
|
||||
</BreadcrumbItem>
|
||||
</Breadcrumb>
|
||||
{canModify && (
|
||||
<HStack>
|
||||
<Button
|
||||
size="sm"
|
||||
variant={{ base: "outline", lg: "ghost" }}
|
||||
colorScheme="gray"
|
||||
fontWeight="normal"
|
||||
onClick={openDrawer}
|
||||
>
|
||||
<Icon as={BsGearFill} boxSize={4} color="gray.600" />
|
||||
<Text display={{ base: "none", lg: "block" }} ml={2}>
|
||||
Edit Vars & Evals
|
||||
</Text>
|
||||
</Button>
|
||||
<DeleteButton />
|
||||
</HStack>
|
||||
)}
|
||||
<HeaderButtons />
|
||||
</Flex>
|
||||
<SettingsDrawer />
|
||||
<ExperimentSettingsDrawer />
|
||||
<Box w="100%" overflowX="auto" flex={1}>
|
||||
<OutputsTable experimentId={router.query.id as string | undefined} />
|
||||
</Box>
|
||||
|
||||
@@ -13,29 +13,36 @@ import {
|
||||
import { RiFlaskLine } from "react-icons/ri";
|
||||
import AppShell from "~/components/nav/AppShell";
|
||||
import { api } from "~/utils/api";
|
||||
import { ExperimentCard, NewExperimentCard } from "~/components/experiments/ExperimentCard";
|
||||
import {
|
||||
ExperimentCard,
|
||||
ExperimentCardSkeleton,
|
||||
NewExperimentCard,
|
||||
} from "~/components/experiments/ExperimentCard";
|
||||
import { signIn, useSession } from "next-auth/react";
|
||||
|
||||
export default function ExperimentsPage() {
|
||||
const experiments = api.experiments.list.useQuery();
|
||||
|
||||
const user = useSession().data;
|
||||
const authLoading = useSession().status === "loading";
|
||||
|
||||
if (user === null) {
|
||||
if (user === null || authLoading) {
|
||||
return (
|
||||
<AppShell title="Experiments">
|
||||
<Center h="100%">
|
||||
<Text>
|
||||
<Link
|
||||
onClick={() => {
|
||||
signIn("github").catch(console.error);
|
||||
}}
|
||||
textDecor="underline"
|
||||
>
|
||||
Sign in
|
||||
</Link>{" "}
|
||||
to view or create new experiments!
|
||||
</Text>
|
||||
{!authLoading && (
|
||||
<Text>
|
||||
<Link
|
||||
onClick={() => {
|
||||
signIn("github").catch(console.error);
|
||||
}}
|
||||
textDecor="underline"
|
||||
>
|
||||
Sign in
|
||||
</Link>{" "}
|
||||
to view or create new experiments!
|
||||
</Text>
|
||||
)}
|
||||
</Center>
|
||||
</AppShell>
|
||||
);
|
||||
@@ -44,7 +51,7 @@ export default function ExperimentsPage() {
|
||||
return (
|
||||
<AppShell title="Experiments">
|
||||
<VStack alignItems={"flex-start"} px={4} py={2}>
|
||||
<HStack minH={8} align="center">
|
||||
<HStack minH={8} align="center" pt={2}>
|
||||
<Breadcrumb flex={1}>
|
||||
<BreadcrumbItem>
|
||||
<Flex alignItems="center">
|
||||
@@ -55,7 +62,15 @@ export default function ExperimentsPage() {
|
||||
</HStack>
|
||||
<SimpleGrid w="full" columns={{ base: 1, md: 2, lg: 3, xl: 4 }} spacing={8} p="4">
|
||||
<NewExperimentCard />
|
||||
{experiments?.data?.map((exp) => <ExperimentCard key={exp.id} exp={exp} />)}
|
||||
{experiments.data && !experiments.isLoading ? (
|
||||
experiments?.data?.map((exp) => <ExperimentCard key={exp.id} exp={exp} />)
|
||||
) : (
|
||||
<>
|
||||
<ExperimentCardSkeleton />
|
||||
<ExperimentCardSkeleton />
|
||||
<ExperimentCardSkeleton />
|
||||
</>
|
||||
)}
|
||||
</SimpleGrid>
|
||||
</VStack>
|
||||
</AppShell>
|
||||
|
||||
@@ -1,5 +1,7 @@
|
||||
import { z } from "zod";
|
||||
import { v4 as uuidv4 } from "uuid";
|
||||
import { createTRPCRouter, protectedProcedure, publicProcedure } from "~/server/api/trpc";
|
||||
import { type Prisma } from "@prisma/client";
|
||||
import { prisma } from "~/server/db";
|
||||
import dedent from "dedent";
|
||||
import { generateNewCell } from "~/server/utils/generateNewCell";
|
||||
@@ -10,6 +12,7 @@ import {
|
||||
requireNothing,
|
||||
} from "~/utils/accessControl";
|
||||
import userOrg from "~/server/utils/userOrg";
|
||||
import generateTypes from "~/modelProviders/generateTypes";
|
||||
|
||||
export const experimentsRouter = createTRPCRouter({
|
||||
list: protectedProcedure.query(async ({ ctx }) => {
|
||||
@@ -19,7 +22,7 @@ export const experimentsRouter = createTRPCRouter({
|
||||
const experiments = await prisma.experiment.findMany({
|
||||
where: {
|
||||
organization: {
|
||||
OrganizationUser: {
|
||||
organizationUsers: {
|
||||
some: { userId: ctx.session.user.id },
|
||||
},
|
||||
},
|
||||
@@ -76,6 +79,189 @@ export const experimentsRouter = createTRPCRouter({
|
||||
};
|
||||
}),
|
||||
|
||||
fork: protectedProcedure.input(z.object({ id: z.string() })).mutation(async ({ input, ctx }) => {
|
||||
await requireCanViewExperiment(input.id, ctx);
|
||||
|
||||
const [
|
||||
existingExp,
|
||||
existingVariants,
|
||||
existingScenarios,
|
||||
existingCells,
|
||||
evaluations,
|
||||
templateVariables,
|
||||
] = await prisma.$transaction([
|
||||
prisma.experiment.findUniqueOrThrow({
|
||||
where: {
|
||||
id: input.id,
|
||||
},
|
||||
}),
|
||||
prisma.promptVariant.findMany({
|
||||
where: {
|
||||
experimentId: input.id,
|
||||
visible: true,
|
||||
},
|
||||
}),
|
||||
prisma.testScenario.findMany({
|
||||
where: {
|
||||
experimentId: input.id,
|
||||
visible: true,
|
||||
},
|
||||
}),
|
||||
prisma.scenarioVariantCell.findMany({
|
||||
where: {
|
||||
testScenario: {
|
||||
visible: true,
|
||||
},
|
||||
promptVariant: {
|
||||
experimentId: input.id,
|
||||
visible: true,
|
||||
},
|
||||
},
|
||||
include: {
|
||||
modelOutput: {
|
||||
include: {
|
||||
outputEvaluations: true,
|
||||
},
|
||||
},
|
||||
},
|
||||
}),
|
||||
prisma.evaluation.findMany({
|
||||
where: {
|
||||
experimentId: input.id,
|
||||
},
|
||||
}),
|
||||
prisma.templateVariable.findMany({
|
||||
where: {
|
||||
experimentId: input.id,
|
||||
},
|
||||
}),
|
||||
]);
|
||||
|
||||
const newExperimentId = uuidv4();
|
||||
|
||||
const existingToNewVariantIds = new Map<string, string>();
|
||||
const variantsToCreate: Prisma.PromptVariantCreateManyInput[] = [];
|
||||
for (const variant of existingVariants) {
|
||||
const newVariantId = uuidv4();
|
||||
existingToNewVariantIds.set(variant.id, newVariantId);
|
||||
variantsToCreate.push({
|
||||
...variant,
|
||||
id: newVariantId,
|
||||
experimentId: newExperimentId,
|
||||
});
|
||||
}
|
||||
|
||||
const existingToNewScenarioIds = new Map<string, string>();
|
||||
const scenariosToCreate: Prisma.TestScenarioCreateManyInput[] = [];
|
||||
for (const scenario of existingScenarios) {
|
||||
const newScenarioId = uuidv4();
|
||||
existingToNewScenarioIds.set(scenario.id, newScenarioId);
|
||||
scenariosToCreate.push({
|
||||
...scenario,
|
||||
id: newScenarioId,
|
||||
experimentId: newExperimentId,
|
||||
variableValues: scenario.variableValues as Prisma.InputJsonValue,
|
||||
});
|
||||
}
|
||||
|
||||
const existingToNewEvaluationIds = new Map<string, string>();
|
||||
const evaluationsToCreate: Prisma.EvaluationCreateManyInput[] = [];
|
||||
for (const evaluation of evaluations) {
|
||||
const newEvaluationId = uuidv4();
|
||||
existingToNewEvaluationIds.set(evaluation.id, newEvaluationId);
|
||||
evaluationsToCreate.push({
|
||||
...evaluation,
|
||||
id: newEvaluationId,
|
||||
experimentId: newExperimentId,
|
||||
});
|
||||
}
|
||||
|
||||
const cellsToCreate: Prisma.ScenarioVariantCellCreateManyInput[] = [];
|
||||
const modelOutputsToCreate: Prisma.ModelOutputCreateManyInput[] = [];
|
||||
const outputEvaluationsToCreate: Prisma.OutputEvaluationCreateManyInput[] = [];
|
||||
for (const cell of existingCells) {
|
||||
const newCellId = uuidv4();
|
||||
const { modelOutput, ...cellData } = cell;
|
||||
cellsToCreate.push({
|
||||
...cellData,
|
||||
id: newCellId,
|
||||
promptVariantId: existingToNewVariantIds.get(cell.promptVariantId) ?? "",
|
||||
testScenarioId: existingToNewScenarioIds.get(cell.testScenarioId) ?? "",
|
||||
prompt: (cell.prompt as Prisma.InputJsonValue) ?? undefined,
|
||||
});
|
||||
if (modelOutput) {
|
||||
const newModelOutputId = uuidv4();
|
||||
const { outputEvaluations, ...modelOutputData } = modelOutput;
|
||||
modelOutputsToCreate.push({
|
||||
...modelOutputData,
|
||||
id: newModelOutputId,
|
||||
scenarioVariantCellId: newCellId,
|
||||
output: (modelOutput.output as Prisma.InputJsonValue) ?? undefined,
|
||||
});
|
||||
for (const evaluation of outputEvaluations) {
|
||||
outputEvaluationsToCreate.push({
|
||||
...evaluation,
|
||||
id: uuidv4(),
|
||||
modelOutputId: newModelOutputId,
|
||||
evaluationId: existingToNewEvaluationIds.get(evaluation.evaluationId) ?? "",
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const templateVariablesToCreate: Prisma.TemplateVariableCreateManyInput[] = [];
|
||||
for (const templateVariable of templateVariables) {
|
||||
templateVariablesToCreate.push({
|
||||
...templateVariable,
|
||||
id: uuidv4(),
|
||||
experimentId: newExperimentId,
|
||||
});
|
||||
}
|
||||
|
||||
const maxSortIndex =
|
||||
(
|
||||
await prisma.experiment.aggregate({
|
||||
_max: {
|
||||
sortIndex: true,
|
||||
},
|
||||
})
|
||||
)._max?.sortIndex ?? 0;
|
||||
|
||||
await prisma.$transaction([
|
||||
prisma.experiment.create({
|
||||
data: {
|
||||
id: newExperimentId,
|
||||
sortIndex: maxSortIndex + 1,
|
||||
label: `${existingExp.label} (forked)`,
|
||||
organizationId: (await userOrg(ctx.session.user.id)).id,
|
||||
},
|
||||
}),
|
||||
prisma.promptVariant.createMany({
|
||||
data: variantsToCreate,
|
||||
}),
|
||||
prisma.testScenario.createMany({
|
||||
data: scenariosToCreate,
|
||||
}),
|
||||
prisma.scenarioVariantCell.createMany({
|
||||
data: cellsToCreate,
|
||||
}),
|
||||
prisma.modelOutput.createMany({
|
||||
data: modelOutputsToCreate,
|
||||
}),
|
||||
prisma.evaluation.createMany({
|
||||
data: evaluationsToCreate,
|
||||
}),
|
||||
prisma.outputEvaluation.createMany({
|
||||
data: outputEvaluationsToCreate,
|
||||
}),
|
||||
prisma.templateVariable.createMany({
|
||||
data: templateVariablesToCreate,
|
||||
}),
|
||||
]);
|
||||
|
||||
return newExperimentId;
|
||||
}),
|
||||
|
||||
create: protectedProcedure.input(z.object({})).mutation(async ({ ctx }) => {
|
||||
// Anyone can create an experiment
|
||||
requireNothing(ctx);
|
||||
@@ -97,7 +283,7 @@ export const experimentsRouter = createTRPCRouter({
|
||||
},
|
||||
});
|
||||
|
||||
const [variant, _, scenario] = await prisma.$transaction([
|
||||
const [variant, _, scenario1, scenario2, scenario3] = await prisma.$transaction([
|
||||
prisma.promptVariant.create({
|
||||
data: {
|
||||
experimentId: exp.id,
|
||||
@@ -108,43 +294,62 @@ export const experimentsRouter = createTRPCRouter({
|
||||
constructFn: dedent`
|
||||
/**
|
||||
* Use Javascript to define an OpenAI chat completion
|
||||
* (https://platform.openai.com/docs/api-reference/chat/create) and
|
||||
* assign it to the \`prompt\` variable.
|
||||
* (https://platform.openai.com/docs/api-reference/chat/create).
|
||||
*
|
||||
* You have access to the current scenario in the \`scenario\`
|
||||
* variable.
|
||||
*/
|
||||
|
||||
prompt = {
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
stream: true,
|
||||
messages: [
|
||||
{
|
||||
role: "system",
|
||||
content: \`"Return 'this is output for the scenario "${"$"}{scenario.text}"'\`,
|
||||
content: \`Write 'Start experimenting!' in ${"$"}{scenario.language}\`,
|
||||
},
|
||||
],
|
||||
};`,
|
||||
});`,
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
modelProvider: "openai/ChatCompletion",
|
||||
constructFnVersion: 2,
|
||||
},
|
||||
}),
|
||||
prisma.templateVariable.create({
|
||||
data: {
|
||||
experimentId: exp.id,
|
||||
label: "text",
|
||||
label: "language",
|
||||
},
|
||||
}),
|
||||
prisma.testScenario.create({
|
||||
data: {
|
||||
experimentId: exp.id,
|
||||
variableValues: {
|
||||
text: "This is a test scenario.",
|
||||
language: "English",
|
||||
},
|
||||
},
|
||||
}),
|
||||
prisma.testScenario.create({
|
||||
data: {
|
||||
experimentId: exp.id,
|
||||
variableValues: {
|
||||
language: "Spanish",
|
||||
},
|
||||
},
|
||||
}),
|
||||
prisma.testScenario.create({
|
||||
data: {
|
||||
experimentId: exp.id,
|
||||
variableValues: {
|
||||
language: "German",
|
||||
},
|
||||
},
|
||||
}),
|
||||
]);
|
||||
|
||||
await generateNewCell(variant.id, scenario.id);
|
||||
await generateNewCell(variant.id, scenario1.id);
|
||||
await generateNewCell(variant.id, scenario2.id);
|
||||
await generateNewCell(variant.id, scenario3.id);
|
||||
|
||||
return exp;
|
||||
}),
|
||||
@@ -174,4 +379,10 @@ export const experimentsRouter = createTRPCRouter({
|
||||
},
|
||||
});
|
||||
}),
|
||||
|
||||
// Keeping these on `experiment` for now because we might want to limit the
|
||||
// providers based on your account/experiment
|
||||
promptTypes: publicProcedure.query(async () => {
|
||||
return await generateTypes();
|
||||
}),
|
||||
});
|
||||
|
||||
@@ -1,16 +1,16 @@
|
||||
import { isObject } from "lodash-es";
|
||||
import { z } from "zod";
|
||||
import { createTRPCRouter, protectedProcedure, publicProcedure } from "~/server/api/trpc";
|
||||
import { prisma } from "~/server/db";
|
||||
import { generateNewCell } from "~/server/utils/generateNewCell";
|
||||
import { OpenAIChatModel, type SupportedModel } from "~/server/types";
|
||||
import { constructPrompt } from "~/server/utils/constructPrompt";
|
||||
import userError from "~/server/utils/error";
|
||||
import { recordExperimentUpdated } from "~/server/utils/recordExperimentUpdated";
|
||||
import { reorderPromptVariants } from "~/server/utils/reorderPromptVariants";
|
||||
import { type PromptVariant } from "@prisma/client";
|
||||
import { deriveNewConstructFn } from "~/server/utils/deriveNewContructFn";
|
||||
import { requireCanModifyExperiment, requireCanViewExperiment } from "~/utils/accessControl";
|
||||
import parseConstructFn from "~/server/utils/parseConstructFn";
|
||||
import modelProviders from "~/modelProviders/modelProviders";
|
||||
import { ZodSupportedProvider } from "~/modelProviders/types";
|
||||
|
||||
export const promptVariantsRouter = createTRPCRouter({
|
||||
list: publicProcedure
|
||||
@@ -145,7 +145,7 @@ export const promptVariantsRouter = createTRPCRouter({
|
||||
z.object({
|
||||
experimentId: z.string(),
|
||||
variantId: z.string().optional(),
|
||||
newModel: z.string().optional(),
|
||||
streamScenarios: z.array(z.string()),
|
||||
}),
|
||||
)
|
||||
.mutation(async ({ input, ctx }) => {
|
||||
@@ -187,10 +187,7 @@ export const promptVariantsRouter = createTRPCRouter({
|
||||
? `${originalVariant?.label} Copy`
|
||||
: `Prompt Variant ${largestSortIndex + 2}`;
|
||||
|
||||
const newConstructFn = await deriveNewConstructFn(
|
||||
originalVariant,
|
||||
input.newModel as SupportedModel,
|
||||
);
|
||||
const newConstructFn = await deriveNewConstructFn(originalVariant);
|
||||
|
||||
const createNewVariantAction = prisma.promptVariant.create({
|
||||
data: {
|
||||
@@ -198,7 +195,9 @@ export const promptVariantsRouter = createTRPCRouter({
|
||||
label: newVariantLabel,
|
||||
sortIndex: (originalVariant?.sortIndex ?? 0) + 1,
|
||||
constructFn: newConstructFn,
|
||||
constructFnVersion: 2,
|
||||
model: originalVariant?.model ?? "gpt-3.5-turbo",
|
||||
modelProvider: originalVariant?.modelProvider ?? "openai/ChatCompletion",
|
||||
},
|
||||
});
|
||||
|
||||
@@ -220,7 +219,9 @@ export const promptVariantsRouter = createTRPCRouter({
|
||||
});
|
||||
|
||||
for (const scenario of scenarios) {
|
||||
await generateNewCell(newVariant.id, scenario.id);
|
||||
await generateNewCell(newVariant.id, scenario.id, {
|
||||
stream: input.streamScenarios.includes(scenario.id),
|
||||
});
|
||||
}
|
||||
|
||||
return newVariant;
|
||||
@@ -283,11 +284,17 @@ export const promptVariantsRouter = createTRPCRouter({
|
||||
return updatedPromptVariant;
|
||||
}),
|
||||
|
||||
getRefinedPromptFn: protectedProcedure
|
||||
getModifiedPromptFn: protectedProcedure
|
||||
.input(
|
||||
z.object({
|
||||
id: z.string(),
|
||||
instructions: z.string(),
|
||||
instructions: z.string().optional(),
|
||||
newModel: z
|
||||
.object({
|
||||
provider: ZodSupportedProvider,
|
||||
model: z.string(),
|
||||
})
|
||||
.optional(),
|
||||
}),
|
||||
)
|
||||
.mutation(async ({ input, ctx }) => {
|
||||
@@ -298,14 +305,17 @@ export const promptVariantsRouter = createTRPCRouter({
|
||||
});
|
||||
await requireCanModifyExperiment(existing.experimentId, ctx);
|
||||
|
||||
const constructedPrompt = await constructPrompt({ constructFn: existing.constructFn }, null);
|
||||
const constructedPrompt = await parseConstructFn(existing.constructFn);
|
||||
|
||||
const promptConstructionFn = await deriveNewConstructFn(
|
||||
existing,
|
||||
// @ts-expect-error TODO clean this up
|
||||
constructedPrompt?.model as SupportedModel,
|
||||
input.instructions,
|
||||
);
|
||||
if ("error" in constructedPrompt) {
|
||||
return userError(constructedPrompt.error);
|
||||
}
|
||||
|
||||
const model = input.newModel
|
||||
? modelProviders[input.newModel.provider].models[input.newModel.model]
|
||||
: undefined;
|
||||
|
||||
const promptConstructionFn = await deriveNewConstructFn(existing, model, input.instructions);
|
||||
|
||||
// TODO: Validate promptConstructionFn
|
||||
// TODO: Record in some sort of history
|
||||
@@ -318,6 +328,7 @@ export const promptVariantsRouter = createTRPCRouter({
|
||||
z.object({
|
||||
id: z.string(),
|
||||
constructFn: z.string(),
|
||||
streamScenarios: z.array(z.string()),
|
||||
}),
|
||||
)
|
||||
.mutation(async ({ input, ctx }) => {
|
||||
@@ -332,25 +343,10 @@ export const promptVariantsRouter = createTRPCRouter({
|
||||
throw new Error(`Prompt Variant with id ${input.id} does not exist`);
|
||||
}
|
||||
|
||||
let model = existing.model;
|
||||
try {
|
||||
const contructedPrompt = await constructPrompt({ constructFn: input.constructFn }, null);
|
||||
const parsedPrompt = await parseConstructFn(input.constructFn);
|
||||
|
||||
if (!isObject(contructedPrompt)) {
|
||||
return userError("Prompt is not an object");
|
||||
}
|
||||
if (!("model" in contructedPrompt)) {
|
||||
return userError("Prompt does not define a model");
|
||||
}
|
||||
if (
|
||||
typeof contructedPrompt.model !== "string" ||
|
||||
!(contructedPrompt.model in OpenAIChatModel)
|
||||
) {
|
||||
return userError("Prompt defines an invalid model");
|
||||
}
|
||||
model = contructedPrompt.model;
|
||||
} catch (e) {
|
||||
return userError((e as Error).message);
|
||||
if ("error" in parsedPrompt) {
|
||||
return userError(parsedPrompt.error);
|
||||
}
|
||||
|
||||
// Create a duplicate with only the config changed
|
||||
@@ -361,7 +357,9 @@ export const promptVariantsRouter = createTRPCRouter({
|
||||
sortIndex: existing.sortIndex,
|
||||
uiId: existing.uiId,
|
||||
constructFn: input.constructFn,
|
||||
model,
|
||||
constructFnVersion: 2,
|
||||
modelProvider: parsedPrompt.modelProvider,
|
||||
model: parsedPrompt.model,
|
||||
},
|
||||
});
|
||||
|
||||
@@ -388,7 +386,9 @@ export const promptVariantsRouter = createTRPCRouter({
|
||||
});
|
||||
|
||||
for (const scenario of scenarios) {
|
||||
await generateNewCell(newVariant.id, scenario.id);
|
||||
await generateNewCell(newVariant.id, scenario.id, {
|
||||
stream: input.streamScenarios.includes(scenario.id),
|
||||
});
|
||||
}
|
||||
|
||||
return { status: "ok" } as const;
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
import { z } from "zod";
|
||||
import { createTRPCRouter, protectedProcedure, publicProcedure } from "~/server/api/trpc";
|
||||
import { prisma } from "~/server/db";
|
||||
import { queueQueryModel } from "~/server/tasks/queryModel.task";
|
||||
import { generateNewCell } from "~/server/utils/generateNewCell";
|
||||
import { queueLLMRetrievalTask } from "~/server/utils/queueLLMRetrievalTask";
|
||||
import { requireCanModifyExperiment, requireCanViewExperiment } from "~/utils/accessControl";
|
||||
|
||||
export const scenarioVariantCellsRouter = createTRPCRouter({
|
||||
@@ -29,7 +29,7 @@ export const scenarioVariantCellsRouter = createTRPCRouter({
|
||||
include: {
|
||||
modelOutput: {
|
||||
include: {
|
||||
outputEvaluation: {
|
||||
outputEvaluations: {
|
||||
include: {
|
||||
evaluation: {
|
||||
select: { label: true },
|
||||
@@ -62,14 +62,12 @@ export const scenarioVariantCellsRouter = createTRPCRouter({
|
||||
testScenarioId: input.scenarioId,
|
||||
},
|
||||
},
|
||||
include: {
|
||||
modelOutput: true,
|
||||
},
|
||||
include: { modelOutput: true },
|
||||
});
|
||||
|
||||
if (!cell) {
|
||||
await generateNewCell(input.variantId, input.scenarioId);
|
||||
return true;
|
||||
await generateNewCell(input.variantId, input.scenarioId, { stream: true });
|
||||
return;
|
||||
}
|
||||
|
||||
if (cell.modelOutput) {
|
||||
@@ -79,12 +77,6 @@ export const scenarioVariantCellsRouter = createTRPCRouter({
|
||||
});
|
||||
}
|
||||
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: cell.id },
|
||||
data: { retrievalStatus: "PENDING" },
|
||||
});
|
||||
|
||||
await queueLLMRetrievalTask(cell.id);
|
||||
return true;
|
||||
await queueQueryModel(cell.id, true);
|
||||
}),
|
||||
});
|
||||
|
||||
@@ -7,21 +7,39 @@ import { runAllEvals } from "~/server/utils/evaluations";
|
||||
import { generateNewCell } from "~/server/utils/generateNewCell";
|
||||
import { requireCanModifyExperiment, requireCanViewExperiment } from "~/utils/accessControl";
|
||||
|
||||
const PAGE_SIZE = 10;
|
||||
|
||||
export const scenariosRouter = createTRPCRouter({
|
||||
list: publicProcedure
|
||||
.input(z.object({ experimentId: z.string() }))
|
||||
.input(z.object({ experimentId: z.string(), page: z.number() }))
|
||||
.query(async ({ input, ctx }) => {
|
||||
await requireCanViewExperiment(input.experimentId, ctx);
|
||||
|
||||
return await prisma.testScenario.findMany({
|
||||
const { experimentId, page } = input;
|
||||
|
||||
const scenarios = await prisma.testScenario.findMany({
|
||||
where: {
|
||||
experimentId: input.experimentId,
|
||||
experimentId,
|
||||
visible: true,
|
||||
},
|
||||
orderBy: {
|
||||
sortIndex: "asc",
|
||||
orderBy: { sortIndex: "asc" },
|
||||
skip: (page - 1) * PAGE_SIZE,
|
||||
take: PAGE_SIZE,
|
||||
});
|
||||
|
||||
const count = await prisma.testScenario.count({
|
||||
where: {
|
||||
experimentId,
|
||||
visible: true,
|
||||
},
|
||||
});
|
||||
|
||||
return {
|
||||
scenarios,
|
||||
startIndex: (page - 1) * PAGE_SIZE + 1,
|
||||
lastPage: Math.ceil(count / PAGE_SIZE),
|
||||
count,
|
||||
};
|
||||
}),
|
||||
|
||||
create: protectedProcedure
|
||||
@@ -34,22 +52,21 @@ export const scenariosRouter = createTRPCRouter({
|
||||
.mutation(async ({ input, ctx }) => {
|
||||
await requireCanModifyExperiment(input.experimentId, ctx);
|
||||
|
||||
const maxSortIndex =
|
||||
(
|
||||
await prisma.testScenario.aggregate({
|
||||
where: {
|
||||
experimentId: input.experimentId,
|
||||
},
|
||||
_max: {
|
||||
sortIndex: true,
|
||||
},
|
||||
})
|
||||
)._max.sortIndex ?? 0;
|
||||
await prisma.testScenario.updateMany({
|
||||
where: {
|
||||
experimentId: input.experimentId,
|
||||
},
|
||||
data: {
|
||||
sortIndex: {
|
||||
increment: 1,
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
const createNewScenarioAction = prisma.testScenario.create({
|
||||
data: {
|
||||
experimentId: input.experimentId,
|
||||
sortIndex: maxSortIndex + 1,
|
||||
sortIndex: 0,
|
||||
variableValues: input.autogenerate
|
||||
? await autogenerateScenarioValues(input.experimentId)
|
||||
: {},
|
||||
@@ -69,7 +86,7 @@ export const scenariosRouter = createTRPCRouter({
|
||||
});
|
||||
|
||||
for (const variant of promptVariants) {
|
||||
await generateNewCell(variant.id, scenario.id);
|
||||
await generateNewCell(variant.id, scenario.id, { stream: true });
|
||||
}
|
||||
}),
|
||||
|
||||
@@ -213,7 +230,7 @@ export const scenariosRouter = createTRPCRouter({
|
||||
});
|
||||
|
||||
for (const variant of promptVariants) {
|
||||
await generateNewCell(variant.id, newScenario.id);
|
||||
await generateNewCell(variant.id, newScenario.id, { stream: true });
|
||||
}
|
||||
|
||||
return newScenario;
|
||||
|
||||
@@ -1,77 +0,0 @@
|
||||
import { type SupportedModel } from "./types";
|
||||
|
||||
interface ModelStats {
|
||||
contextLength: number;
|
||||
promptTokenPrice: number;
|
||||
completionTokenPrice: number;
|
||||
speed: "fast" | "medium" | "slow";
|
||||
provider: "OpenAI";
|
||||
learnMoreUrl: string;
|
||||
}
|
||||
|
||||
export const modelStats: Record<SupportedModel, ModelStats> = {
|
||||
"gpt-4": {
|
||||
contextLength: 8192,
|
||||
promptTokenPrice: 0.00003,
|
||||
completionTokenPrice: 0.00006,
|
||||
speed: "medium",
|
||||
provider: "OpenAI",
|
||||
learnMoreUrl: "https://openai.com/gpt-4",
|
||||
},
|
||||
"gpt-4-0613": {
|
||||
contextLength: 8192,
|
||||
promptTokenPrice: 0.00003,
|
||||
completionTokenPrice: 0.00006,
|
||||
speed: "medium",
|
||||
provider: "OpenAI",
|
||||
learnMoreUrl: "https://openai.com/gpt-4",
|
||||
},
|
||||
"gpt-4-32k": {
|
||||
contextLength: 32768,
|
||||
promptTokenPrice: 0.00006,
|
||||
completionTokenPrice: 0.00012,
|
||||
speed: "medium",
|
||||
provider: "OpenAI",
|
||||
learnMoreUrl: "https://openai.com/gpt-4",
|
||||
},
|
||||
"gpt-4-32k-0613": {
|
||||
contextLength: 32768,
|
||||
promptTokenPrice: 0.00006,
|
||||
completionTokenPrice: 0.00012,
|
||||
speed: "medium",
|
||||
provider: "OpenAI",
|
||||
learnMoreUrl: "https://openai.com/gpt-4",
|
||||
},
|
||||
"gpt-3.5-turbo": {
|
||||
contextLength: 4096,
|
||||
promptTokenPrice: 0.0000015,
|
||||
completionTokenPrice: 0.000002,
|
||||
speed: "fast",
|
||||
provider: "OpenAI",
|
||||
learnMoreUrl: "https://platform.openai.com/docs/guides/gpt/chat-completions-api",
|
||||
},
|
||||
"gpt-3.5-turbo-0613": {
|
||||
contextLength: 4096,
|
||||
promptTokenPrice: 0.0000015,
|
||||
completionTokenPrice: 0.000002,
|
||||
speed: "fast",
|
||||
provider: "OpenAI",
|
||||
learnMoreUrl: "https://platform.openai.com/docs/guides/gpt/chat-completions-api",
|
||||
},
|
||||
"gpt-3.5-turbo-16k": {
|
||||
contextLength: 16384,
|
||||
promptTokenPrice: 0.000003,
|
||||
completionTokenPrice: 0.000004,
|
||||
speed: "fast",
|
||||
provider: "OpenAI",
|
||||
learnMoreUrl: "https://platform.openai.com/docs/guides/gpt/chat-completions-api",
|
||||
},
|
||||
"gpt-3.5-turbo-16k-0613": {
|
||||
contextLength: 16384,
|
||||
promptTokenPrice: 0.000003,
|
||||
completionTokenPrice: 0.000004,
|
||||
speed: "fast",
|
||||
provider: "OpenAI",
|
||||
learnMoreUrl: "https://platform.openai.com/docs/guides/gpt/chat-completions-api",
|
||||
},
|
||||
};
|
||||
45
src/server/scripts/migrateConstructFns.test.ts
Normal file
45
src/server/scripts/migrateConstructFns.test.ts
Normal file
@@ -0,0 +1,45 @@
|
||||
import "dotenv/config";
|
||||
import dedent from "dedent";
|
||||
import { expect, test } from "vitest";
|
||||
import { migrate1to2 } from "./migrateConstructFns";
|
||||
|
||||
test("migrate1to2", () => {
|
||||
const constructFn = dedent`
|
||||
// Test comment
|
||||
|
||||
prompt = {
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "What is the capital of China?"
|
||||
}
|
||||
]
|
||||
}
|
||||
`;
|
||||
|
||||
const migrated = migrate1to2(constructFn);
|
||||
expect(migrated).toBe(dedent`
|
||||
// Test comment
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "What is the capital of China?"
|
||||
}
|
||||
]
|
||||
})
|
||||
`);
|
||||
|
||||
// console.log(
|
||||
// migrateConstructFn(dedent`definePrompt(
|
||||
// "openai/ChatCompletion",
|
||||
// {
|
||||
// model: 'gpt-3.5-turbo-0613',
|
||||
// messages: []
|
||||
// }
|
||||
// )`),
|
||||
// );
|
||||
});
|
||||
58
src/server/scripts/migrateConstructFns.ts
Normal file
58
src/server/scripts/migrateConstructFns.ts
Normal file
@@ -0,0 +1,58 @@
|
||||
import * as recast from "recast";
|
||||
import { type ASTNode } from "ast-types";
|
||||
import { prisma } from "../db";
|
||||
import { fileURLToPath } from "url";
|
||||
const { builders: b } = recast.types;
|
||||
|
||||
export const migrate1to2 = (fnBody: string): string => {
|
||||
const ast: ASTNode = recast.parse(fnBody);
|
||||
|
||||
recast.visit(ast, {
|
||||
visitAssignmentExpression(path) {
|
||||
const node = path.node;
|
||||
if ("name" in node.left && node.left.name === "prompt") {
|
||||
const functionCall = b.callExpression(b.identifier("definePrompt"), [
|
||||
b.literal("openai/ChatCompletion"),
|
||||
node.right,
|
||||
]);
|
||||
path.replace(functionCall);
|
||||
}
|
||||
return false;
|
||||
},
|
||||
});
|
||||
|
||||
return recast.print(ast).code;
|
||||
};
|
||||
|
||||
export default async function migrateConstructFns() {
|
||||
const v1Prompts = await prisma.promptVariant.findMany({
|
||||
where: {
|
||||
constructFnVersion: 1,
|
||||
},
|
||||
});
|
||||
console.log(`Migrating ${v1Prompts.length} prompts 1->2`);
|
||||
await Promise.all(
|
||||
v1Prompts.map(async (variant) => {
|
||||
try {
|
||||
await prisma.promptVariant.update({
|
||||
where: {
|
||||
id: variant.id,
|
||||
},
|
||||
data: {
|
||||
constructFn: migrate1to2(variant.constructFn),
|
||||
constructFnVersion: 2,
|
||||
},
|
||||
});
|
||||
} catch (e) {
|
||||
console.error("Error migrating constructFn for variant", variant.id, e);
|
||||
}
|
||||
}),
|
||||
);
|
||||
}
|
||||
|
||||
// If we're running this file directly, run the migration
|
||||
if (process.argv.at(-1) === fileURLToPath(import.meta.url)) {
|
||||
console.log("Running migration");
|
||||
await migrateConstructFns();
|
||||
console.log("Done");
|
||||
}
|
||||
19
src/server/scripts/openai-test.ts
Normal file
19
src/server/scripts/openai-test.ts
Normal file
@@ -0,0 +1,19 @@
|
||||
import "dotenv/config";
|
||||
import { openai } from "../utils/openai";
|
||||
|
||||
const resp = await openai.chat.completions.create({
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
stream: true,
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "count to 20",
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
for await (const part of resp) {
|
||||
console.log("part", part);
|
||||
}
|
||||
|
||||
console.log("final resp", resp);
|
||||
@@ -1,26 +1,26 @@
|
||||
// /* eslint-disable */
|
||||
/* eslint-disable */
|
||||
|
||||
// import "dotenv/config";
|
||||
// import Replicate from "replicate";
|
||||
import "dotenv/config";
|
||||
import Replicate from "replicate";
|
||||
|
||||
// const replicate = new Replicate({
|
||||
// auth: process.env.REPLICATE_API_TOKEN || "",
|
||||
// });
|
||||
const replicate = new Replicate({
|
||||
auth: process.env.REPLICATE_API_TOKEN || "",
|
||||
});
|
||||
|
||||
// console.log("going to run");
|
||||
// const prediction = await replicate.predictions.create({
|
||||
// version: "e951f18578850b652510200860fc4ea62b3b16fac280f83ff32282f87bbd2e48",
|
||||
// input: {
|
||||
// prompt: "...",
|
||||
// },
|
||||
// });
|
||||
console.log("going to run");
|
||||
const prediction = await replicate.predictions.create({
|
||||
version: "3725a659b5afff1a0ba9bead5fac3899d998feaad00e07032ca2b0e35eb14f8a",
|
||||
input: {
|
||||
prompt: "...",
|
||||
},
|
||||
});
|
||||
|
||||
// console.log("waiting");
|
||||
// setInterval(() => {
|
||||
// replicate.predictions.get(prediction.id).then((prediction) => {
|
||||
// console.log(prediction.output);
|
||||
// });
|
||||
// }, 500);
|
||||
// // const output = await replicate.wait(prediction, {});
|
||||
console.log("waiting");
|
||||
setInterval(() => {
|
||||
replicate.predictions.get(prediction.id).then((prediction) => {
|
||||
console.log(prediction);
|
||||
});
|
||||
}, 500);
|
||||
// const output = await replicate.wait(prediction, {});
|
||||
|
||||
// // console.log(output);
|
||||
// console.log(output);
|
||||
|
||||
@@ -1,182 +0,0 @@
|
||||
import crypto from "crypto";
|
||||
import { prisma } from "~/server/db";
|
||||
import defineTask from "./defineTask";
|
||||
import { type CompletionResponse, getOpenAIChatCompletion } from "../utils/getCompletion";
|
||||
import { type JSONSerializable } from "../types";
|
||||
import { sleep } from "../utils/sleep";
|
||||
import { shouldStream } from "../utils/shouldStream";
|
||||
import { generateChannel } from "~/utils/generateChannel";
|
||||
import { runEvalsForOutput } from "../utils/evaluations";
|
||||
import { constructPrompt } from "../utils/constructPrompt";
|
||||
import { type CompletionCreateParams } from "openai/resources/chat";
|
||||
import { type Prisma } from "@prisma/client";
|
||||
|
||||
const MAX_AUTO_RETRIES = 10;
|
||||
const MIN_DELAY = 500; // milliseconds
|
||||
const MAX_DELAY = 15000; // milliseconds
|
||||
|
||||
function calculateDelay(numPreviousTries: number): number {
|
||||
const baseDelay = Math.min(MAX_DELAY, MIN_DELAY * Math.pow(2, numPreviousTries));
|
||||
const jitter = Math.random() * baseDelay;
|
||||
return baseDelay + jitter;
|
||||
}
|
||||
|
||||
const getCompletionWithRetries = async (
|
||||
cellId: string,
|
||||
payload: JSONSerializable,
|
||||
channel?: string,
|
||||
): Promise<CompletionResponse> => {
|
||||
let modelResponse: CompletionResponse | null = null;
|
||||
try {
|
||||
for (let i = 0; i < MAX_AUTO_RETRIES; i++) {
|
||||
modelResponse = await getOpenAIChatCompletion(
|
||||
payload as unknown as CompletionCreateParams,
|
||||
channel,
|
||||
);
|
||||
if (modelResponse.statusCode !== 429 || i === MAX_AUTO_RETRIES - 1) {
|
||||
return modelResponse;
|
||||
}
|
||||
const delay = calculateDelay(i);
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: cellId },
|
||||
data: {
|
||||
errorMessage: "Rate limit exceeded",
|
||||
statusCode: 429,
|
||||
retryTime: new Date(Date.now() + delay),
|
||||
},
|
||||
});
|
||||
// TODO: Maybe requeue the job so other jobs can run in the future?
|
||||
await sleep(delay);
|
||||
}
|
||||
throw new Error("Max retries limit reached");
|
||||
} catch (error: unknown) {
|
||||
return {
|
||||
statusCode: modelResponse?.statusCode ?? 500,
|
||||
errorMessage: modelResponse?.errorMessage ?? (error as Error).message,
|
||||
output: null,
|
||||
timeToComplete: 0,
|
||||
};
|
||||
}
|
||||
};
|
||||
|
||||
export type queryLLMJob = {
|
||||
scenarioVariantCellId: string;
|
||||
};
|
||||
|
||||
export const queryLLM = defineTask<queryLLMJob>("queryLLM", async (task) => {
|
||||
const { scenarioVariantCellId } = task;
|
||||
const cell = await prisma.scenarioVariantCell.findUnique({
|
||||
where: { id: scenarioVariantCellId },
|
||||
include: { modelOutput: true },
|
||||
});
|
||||
if (!cell) {
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: scenarioVariantCellId },
|
||||
data: {
|
||||
statusCode: 404,
|
||||
errorMessage: "Cell not found",
|
||||
retrievalStatus: "ERROR",
|
||||
},
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
// If cell is not pending, then some other job is already processing it
|
||||
if (cell.retrievalStatus !== "PENDING") {
|
||||
return;
|
||||
}
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: scenarioVariantCellId },
|
||||
data: {
|
||||
retrievalStatus: "IN_PROGRESS",
|
||||
},
|
||||
});
|
||||
|
||||
const variant = await prisma.promptVariant.findUnique({
|
||||
where: { id: cell.promptVariantId },
|
||||
});
|
||||
if (!variant) {
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: scenarioVariantCellId },
|
||||
data: {
|
||||
statusCode: 404,
|
||||
errorMessage: "Prompt Variant not found",
|
||||
retrievalStatus: "ERROR",
|
||||
},
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
const scenario = await prisma.testScenario.findUnique({
|
||||
where: { id: cell.testScenarioId },
|
||||
});
|
||||
if (!scenario) {
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: scenarioVariantCellId },
|
||||
data: {
|
||||
statusCode: 404,
|
||||
errorMessage: "Scenario not found",
|
||||
retrievalStatus: "ERROR",
|
||||
},
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
const prompt = await constructPrompt(variant, scenario.variableValues);
|
||||
|
||||
const streamingEnabled = shouldStream(prompt);
|
||||
let streamingChannel;
|
||||
|
||||
if (streamingEnabled) {
|
||||
streamingChannel = generateChannel();
|
||||
// Save streaming channel so that UI can connect to it
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: scenarioVariantCellId },
|
||||
data: {
|
||||
streamingChannel,
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
const modelResponse = await getCompletionWithRetries(
|
||||
scenarioVariantCellId,
|
||||
prompt,
|
||||
streamingChannel,
|
||||
);
|
||||
|
||||
let modelOutput = null;
|
||||
if (modelResponse.statusCode === 200) {
|
||||
const inputHash = crypto.createHash("sha256").update(JSON.stringify(prompt)).digest("hex");
|
||||
|
||||
modelOutput = await prisma.modelOutput.create({
|
||||
data: {
|
||||
scenarioVariantCellId,
|
||||
inputHash,
|
||||
output: modelResponse.output as unknown as Prisma.InputJsonObject,
|
||||
timeToComplete: modelResponse.timeToComplete,
|
||||
promptTokens: modelResponse.promptTokens,
|
||||
completionTokens: modelResponse.completionTokens,
|
||||
cost: modelResponse.cost,
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: scenarioVariantCellId },
|
||||
data: {
|
||||
statusCode: modelResponse.statusCode,
|
||||
errorMessage: modelResponse.errorMessage,
|
||||
streamingChannel: null,
|
||||
retrievalStatus: modelOutput ? "COMPLETE" : "ERROR",
|
||||
modelOutput: {
|
||||
connect: {
|
||||
id: modelOutput?.id,
|
||||
},
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
if (modelOutput) {
|
||||
await runEvalsForOutput(variant.experimentId, scenario, modelOutput);
|
||||
}
|
||||
});
|
||||
175
src/server/tasks/queryModel.task.ts
Normal file
175
src/server/tasks/queryModel.task.ts
Normal file
@@ -0,0 +1,175 @@
|
||||
import { type Prisma } from "@prisma/client";
|
||||
import { type JsonObject } from "type-fest";
|
||||
import modelProviders from "~/modelProviders/modelProviders";
|
||||
import { prisma } from "~/server/db";
|
||||
import { wsConnection } from "~/utils/wsConnection";
|
||||
import { runEvalsForOutput } from "../utils/evaluations";
|
||||
import hashPrompt from "../utils/hashPrompt";
|
||||
import parseConstructFn from "../utils/parseConstructFn";
|
||||
import { sleep } from "../utils/sleep";
|
||||
import defineTask from "./defineTask";
|
||||
|
||||
export type QueryModelJob = {
|
||||
cellId: string;
|
||||
stream: boolean;
|
||||
};
|
||||
|
||||
const MAX_AUTO_RETRIES = 10;
|
||||
const MIN_DELAY = 500; // milliseconds
|
||||
const MAX_DELAY = 15000; // milliseconds
|
||||
|
||||
function calculateDelay(numPreviousTries: number): number {
|
||||
const baseDelay = Math.min(MAX_DELAY, MIN_DELAY * Math.pow(2, numPreviousTries));
|
||||
const jitter = Math.random() * baseDelay;
|
||||
return baseDelay + jitter;
|
||||
}
|
||||
|
||||
export const queryModel = defineTask<QueryModelJob>("queryModel", async (task) => {
|
||||
console.log("RUNNING TASK", task);
|
||||
const { cellId, stream } = task;
|
||||
const cell = await prisma.scenarioVariantCell.findUnique({
|
||||
where: { id: cellId },
|
||||
include: { modelOutput: true },
|
||||
});
|
||||
if (!cell) {
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: cellId },
|
||||
data: {
|
||||
statusCode: 404,
|
||||
errorMessage: "Cell not found",
|
||||
retrievalStatus: "ERROR",
|
||||
},
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
// If cell is not pending, then some other job is already processing it
|
||||
if (cell.retrievalStatus !== "PENDING") {
|
||||
return;
|
||||
}
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: cellId },
|
||||
data: {
|
||||
retrievalStatus: "IN_PROGRESS",
|
||||
},
|
||||
});
|
||||
|
||||
const variant = await prisma.promptVariant.findUnique({
|
||||
where: { id: cell.promptVariantId },
|
||||
});
|
||||
if (!variant) {
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: cellId },
|
||||
data: {
|
||||
statusCode: 404,
|
||||
errorMessage: "Prompt Variant not found",
|
||||
retrievalStatus: "ERROR",
|
||||
},
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
const scenario = await prisma.testScenario.findUnique({
|
||||
where: { id: cell.testScenarioId },
|
||||
});
|
||||
if (!scenario) {
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: cellId },
|
||||
data: {
|
||||
statusCode: 404,
|
||||
errorMessage: "Scenario not found",
|
||||
retrievalStatus: "ERROR",
|
||||
},
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
const prompt = await parseConstructFn(variant.constructFn, scenario.variableValues as JsonObject);
|
||||
|
||||
if ("error" in prompt) {
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: cellId },
|
||||
data: {
|
||||
statusCode: 400,
|
||||
errorMessage: prompt.error,
|
||||
retrievalStatus: "ERROR",
|
||||
},
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
const provider = modelProviders[prompt.modelProvider];
|
||||
|
||||
const onStream = stream
|
||||
? (partialOutput: (typeof provider)["_outputSchema"]) => {
|
||||
wsConnection.emit("message", { channel: cell.id, payload: partialOutput });
|
||||
}
|
||||
: null;
|
||||
|
||||
for (let i = 0; true; i++) {
|
||||
const response = await provider.getCompletion(prompt.modelInput, onStream);
|
||||
if (response.type === "success") {
|
||||
const inputHash = hashPrompt(prompt);
|
||||
|
||||
const modelOutput = await prisma.modelOutput.create({
|
||||
data: {
|
||||
scenarioVariantCellId: cellId,
|
||||
inputHash,
|
||||
output: response.value as Prisma.InputJsonObject,
|
||||
timeToComplete: response.timeToComplete,
|
||||
promptTokens: response.promptTokens,
|
||||
completionTokens: response.completionTokens,
|
||||
cost: response.cost,
|
||||
},
|
||||
});
|
||||
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: cellId },
|
||||
data: {
|
||||
statusCode: response.statusCode,
|
||||
retrievalStatus: "COMPLETE",
|
||||
},
|
||||
});
|
||||
|
||||
await runEvalsForOutput(variant.experimentId, scenario, modelOutput);
|
||||
break;
|
||||
} else {
|
||||
const shouldRetry = response.autoRetry && i < MAX_AUTO_RETRIES;
|
||||
const delay = calculateDelay(i);
|
||||
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: cellId },
|
||||
data: {
|
||||
errorMessage: response.message,
|
||||
statusCode: response.statusCode,
|
||||
retryTime: shouldRetry ? new Date(Date.now() + delay) : null,
|
||||
retrievalStatus: "ERROR",
|
||||
},
|
||||
});
|
||||
|
||||
if (shouldRetry) {
|
||||
await sleep(delay);
|
||||
} else {
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
export const queueQueryModel = async (cellId: string, stream: boolean) => {
|
||||
console.log("queueQueryModel", cellId, stream);
|
||||
await Promise.all([
|
||||
prisma.scenarioVariantCell.update({
|
||||
where: {
|
||||
id: cellId,
|
||||
},
|
||||
data: {
|
||||
retrievalStatus: "PENDING",
|
||||
errorMessage: null,
|
||||
},
|
||||
}),
|
||||
|
||||
await queryModel.enqueue({ cellId, stream }),
|
||||
console.log("queued"),
|
||||
]);
|
||||
};
|
||||
@@ -2,39 +2,27 @@ import { type TaskList, run } from "graphile-worker";
|
||||
import "dotenv/config";
|
||||
|
||||
import { env } from "~/env.mjs";
|
||||
import { queryLLM } from "./queryLLM.task";
|
||||
import { queryModel } from "./queryModel.task";
|
||||
|
||||
const registeredTasks = [queryLLM];
|
||||
console.log("Starting worker");
|
||||
|
||||
const registeredTasks = [queryModel];
|
||||
|
||||
const taskList = registeredTasks.reduce((acc, task) => {
|
||||
acc[task.task.identifier] = task.task.handler;
|
||||
return acc;
|
||||
}, {} as TaskList);
|
||||
|
||||
async function main() {
|
||||
// Run a worker to execute jobs:
|
||||
const runner = await run({
|
||||
connectionString: env.DATABASE_URL,
|
||||
concurrency: 20,
|
||||
// Install signal handlers for graceful shutdown on SIGINT, SIGTERM, etc
|
||||
noHandleSignals: false,
|
||||
pollInterval: 1000,
|
||||
// you can set the taskList or taskDirectory but not both
|
||||
taskList,
|
||||
// or:
|
||||
// taskDirectory: `${__dirname}/tasks`,
|
||||
});
|
||||
|
||||
// Immediately await (or otherwise handled) the resulting promise, to avoid
|
||||
// "unhandled rejection" errors causing a process crash in the event of
|
||||
// something going wrong.
|
||||
await runner.promise;
|
||||
|
||||
// If the worker exits (whether through fatal error or otherwise), the above
|
||||
// promise will resolve/reject.
|
||||
}
|
||||
|
||||
main().catch((err) => {
|
||||
console.error("Unhandled error occurred running worker: ", err);
|
||||
process.exit(1);
|
||||
// Run a worker to execute jobs:
|
||||
const runner = await run({
|
||||
connectionString: env.DATABASE_URL,
|
||||
concurrency: 20,
|
||||
// Install signal handlers for graceful shutdown on SIGINT, SIGTERM, etc
|
||||
noHandleSignals: false,
|
||||
pollInterval: 1000,
|
||||
taskList,
|
||||
});
|
||||
|
||||
console.log("Worker successfully started");
|
||||
|
||||
await runner.promise;
|
||||
|
||||
@@ -1,23 +0,0 @@
|
||||
export type JSONSerializable =
|
||||
| string
|
||||
| number
|
||||
| boolean
|
||||
| null
|
||||
| JSONSerializable[]
|
||||
| { [key: string]: JSONSerializable };
|
||||
|
||||
// Placeholder for now
|
||||
export type OpenAIChatConfig = NonNullable<JSONSerializable>;
|
||||
|
||||
export enum OpenAIChatModel {
|
||||
"gpt-4" = "gpt-4",
|
||||
"gpt-4-0613" = "gpt-4-0613",
|
||||
"gpt-4-32k" = "gpt-4-32k",
|
||||
"gpt-4-32k-0613" = "gpt-4-32k-0613",
|
||||
"gpt-3.5-turbo" = "gpt-3.5-turbo",
|
||||
"gpt-3.5-turbo-0613" = "gpt-3.5-turbo-0613",
|
||||
"gpt-3.5-turbo-16k" = "gpt-3.5-turbo-16k",
|
||||
"gpt-3.5-turbo-16k-0613" = "gpt-3.5-turbo-16k-0613",
|
||||
}
|
||||
|
||||
export type SupportedModel = keyof typeof OpenAIChatModel;
|
||||
@@ -1,15 +0,0 @@
|
||||
import { test } from "vitest";
|
||||
import { constructPrompt } from "./constructPrompt";
|
||||
|
||||
test.skip("constructPrompt", async () => {
|
||||
const constructed = await constructPrompt(
|
||||
{
|
||||
constructFn: `prompt = { "fooz": "bar" }`,
|
||||
},
|
||||
{
|
||||
foo: "bar",
|
||||
},
|
||||
);
|
||||
|
||||
console.log(constructed);
|
||||
});
|
||||
@@ -1,35 +0,0 @@
|
||||
import { type PromptVariant, type TestScenario } from "@prisma/client";
|
||||
import ivm from "isolated-vm";
|
||||
import { type JSONSerializable } from "../types";
|
||||
|
||||
const isolate = new ivm.Isolate({ memoryLimit: 128 });
|
||||
|
||||
export async function constructPrompt(
|
||||
variant: Pick<PromptVariant, "constructFn">,
|
||||
scenario: TestScenario["variableValues"],
|
||||
): Promise<JSONSerializable> {
|
||||
const code = `
|
||||
const scenario = ${JSON.stringify(scenario ?? {}, null, 2)};
|
||||
let prompt
|
||||
|
||||
${variant.constructFn}
|
||||
|
||||
global.prompt = prompt;
|
||||
`;
|
||||
|
||||
console.log("code is", code);
|
||||
|
||||
const context = await isolate.createContext();
|
||||
|
||||
const jail = context.global;
|
||||
await jail.set("global", jail.derefInto());
|
||||
|
||||
const script = await isolate.compileScript(code);
|
||||
|
||||
await script.run(context);
|
||||
const promptReference = (await context.global.get("prompt")) as ivm.Reference;
|
||||
|
||||
const prompt = await promptReference.copy(); // Get the actual value from the isolate
|
||||
|
||||
return prompt as JSONSerializable;
|
||||
}
|
||||
@@ -1,17 +1,18 @@
|
||||
import { type PromptVariant } from "@prisma/client";
|
||||
import { type SupportedModel } from "../types";
|
||||
import ivm from "isolated-vm";
|
||||
import dedent from "dedent";
|
||||
import { openai } from "./openai";
|
||||
import { getApiShapeForModel } from "./getTypesForModel";
|
||||
import { isObject } from "lodash-es";
|
||||
import { type CompletionCreateParams } from "openai/resources/chat/completions";
|
||||
import formatPromptConstructor from "~/utils/formatPromptConstructor";
|
||||
import { type SupportedProvider, type Model } from "~/modelProviders/types";
|
||||
import modelProviders from "~/modelProviders/modelProviders";
|
||||
|
||||
const isolate = new ivm.Isolate({ memoryLimit: 128 });
|
||||
|
||||
export async function deriveNewConstructFn(
|
||||
originalVariant: PromptVariant | null,
|
||||
newModel?: SupportedModel,
|
||||
newModel?: Model,
|
||||
instructions?: string,
|
||||
) {
|
||||
if (originalVariant && !newModel && !instructions) {
|
||||
@@ -35,10 +36,11 @@ export async function deriveNewConstructFn(
|
||||
const NUM_RETRIES = 5;
|
||||
const requestUpdatedPromptFunction = async (
|
||||
originalVariant: PromptVariant,
|
||||
newModel?: SupportedModel,
|
||||
newModel?: Model,
|
||||
instructions?: string,
|
||||
) => {
|
||||
const originalModel = originalVariant.model as SupportedModel;
|
||||
const originalModelProvider = modelProviders[originalVariant.modelProvider as SupportedProvider];
|
||||
const originalModel = originalModelProvider.models[originalVariant.model] as Model;
|
||||
let newContructionFn = "";
|
||||
for (let i = 0; i < NUM_RETRIES; i++) {
|
||||
try {
|
||||
@@ -46,29 +48,45 @@ const requestUpdatedPromptFunction = async (
|
||||
{
|
||||
role: "system",
|
||||
content: `Your job is to update prompt constructor functions. Here is the api shape for the current model:\n---\n${JSON.stringify(
|
||||
getApiShapeForModel(originalModel),
|
||||
originalModelProvider.inputSchema,
|
||||
null,
|
||||
2,
|
||||
)}`,
|
||||
)}\n\nDo not add any assistant messages.`,
|
||||
},
|
||||
{
|
||||
role: "user",
|
||||
content: `This is the current prompt constructor function:\n---\n${originalVariant.constructFn}`,
|
||||
},
|
||||
];
|
||||
if (newModel) {
|
||||
messages.push({
|
||||
role: "user",
|
||||
content: `Return the prompt constructor function for ${newModel} given the following prompt constructor function for ${originalModel}:\n---\n${originalVariant.constructFn}`,
|
||||
content: `Return the prompt constructor function for ${newModel.name} given the existing prompt constructor function for ${originalModel.name}`,
|
||||
});
|
||||
if (newModel.provider !== originalModel.provider) {
|
||||
messages.push({
|
||||
role: "user",
|
||||
content: `The old provider was ${originalModel.provider}. The new provider is ${
|
||||
newModel.provider
|
||||
}. Here is the schema for the new model:\n---\n${JSON.stringify(
|
||||
modelProviders[newModel.provider].inputSchema,
|
||||
null,
|
||||
2,
|
||||
)}`,
|
||||
});
|
||||
} else {
|
||||
messages.push({
|
||||
role: "user",
|
||||
content: `The provider is the same as the old provider: ${originalModel.provider}`,
|
||||
});
|
||||
}
|
||||
}
|
||||
if (instructions) {
|
||||
messages.push({
|
||||
role: "user",
|
||||
content: `Follow these instructions: ${instructions}`,
|
||||
content: instructions,
|
||||
});
|
||||
}
|
||||
messages.push({
|
||||
role: "user",
|
||||
content:
|
||||
"The prompt variable has already been declared, so do not declare it again. Rewrite the entire prompt constructor function.",
|
||||
});
|
||||
const completion = await openai.chat.completions.create({
|
||||
model: "gpt-4",
|
||||
messages,
|
||||
@@ -111,7 +129,7 @@ const requestUpdatedPromptFunction = async (
|
||||
const args = await contructPromptFunctionArgs.copy(); // Get the actual value from the isolate
|
||||
|
||||
if (args && isObject(args) && "new_prompt_function" in args) {
|
||||
newContructionFn = args.new_prompt_function as string;
|
||||
newContructionFn = await formatPromptConstructor(args.new_prompt_function as string);
|
||||
break;
|
||||
}
|
||||
} catch (e) {
|
||||
|
||||
@@ -56,7 +56,7 @@ export const runAllEvals = async (experimentId: string) => {
|
||||
testScenario: true,
|
||||
},
|
||||
},
|
||||
outputEvaluation: true,
|
||||
outputEvaluations: true,
|
||||
},
|
||||
});
|
||||
const evals = await prisma.evaluation.findMany({
|
||||
@@ -66,7 +66,7 @@ export const runAllEvals = async (experimentId: string) => {
|
||||
await Promise.all(
|
||||
outputs.map(async (output) => {
|
||||
const unrunEvals = evals.filter(
|
||||
(evaluation) => !output.outputEvaluation.find((e) => e.evaluationId === evaluation.id),
|
||||
(evaluation) => !output.outputEvaluations.find((e) => e.evaluationId === evaluation.id),
|
||||
);
|
||||
|
||||
await Promise.all(
|
||||
|
||||
@@ -1,5 +1,3 @@
|
||||
import { type JSONSerializable } from "../types";
|
||||
|
||||
export type VariableMap = Record<string, string>;
|
||||
|
||||
// Escape quotes to match the way we encode JSON
|
||||
@@ -15,24 +13,3 @@ export function escapeRegExp(str: string) {
|
||||
export function fillTemplate(template: string, variables: VariableMap): string {
|
||||
return template.replace(/{{\s*(\w+)\s*}}/g, (_, key: string) => variables[key] || "");
|
||||
}
|
||||
|
||||
export function fillTemplateJson<T extends JSONSerializable>(
|
||||
template: T,
|
||||
variables: VariableMap,
|
||||
): T {
|
||||
if (typeof template === "string") {
|
||||
return fillTemplate(template, variables) as T;
|
||||
} else if (Array.isArray(template)) {
|
||||
return template.map((item) => fillTemplateJson(item, variables)) as T;
|
||||
} else if (typeof template === "object" && template !== null) {
|
||||
return Object.keys(template).reduce(
|
||||
(acc, key) => {
|
||||
acc[key] = fillTemplateJson(template[key] as JSONSerializable, variables);
|
||||
return acc;
|
||||
},
|
||||
{} as { [key: string]: JSONSerializable } & T,
|
||||
);
|
||||
} else {
|
||||
return template;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,10 +1,18 @@
|
||||
import crypto from "crypto";
|
||||
import { type Prisma } from "@prisma/client";
|
||||
import { prisma } from "../db";
|
||||
import { queueLLMRetrievalTask } from "./queueLLMRetrievalTask";
|
||||
import { constructPrompt } from "./constructPrompt";
|
||||
import parseConstructFn from "./parseConstructFn";
|
||||
import { type JsonObject } from "type-fest";
|
||||
import hashPrompt from "./hashPrompt";
|
||||
import { omit } from "lodash-es";
|
||||
import { queueQueryModel } from "../tasks/queryModel.task";
|
||||
|
||||
export const generateNewCell = async (
|
||||
variantId: string,
|
||||
scenarioId: string,
|
||||
options?: { stream?: boolean },
|
||||
): Promise<void> => {
|
||||
const stream = options?.stream ?? false;
|
||||
|
||||
export const generateNewCell = async (variantId: string, scenarioId: string) => {
|
||||
const variant = await prisma.promptVariant.findUnique({
|
||||
where: {
|
||||
id: variantId,
|
||||
@@ -17,11 +25,7 @@ export const generateNewCell = async (variantId: string, scenarioId: string) =>
|
||||
},
|
||||
});
|
||||
|
||||
if (!variant || !scenario) return null;
|
||||
|
||||
const prompt = await constructPrompt(variant, scenario.variableValues);
|
||||
|
||||
const inputHash = crypto.createHash("sha256").update(JSON.stringify(prompt)).digest("hex");
|
||||
if (!variant || !scenario) return;
|
||||
|
||||
let cell = await prisma.scenarioVariantCell.findUnique({
|
||||
where: {
|
||||
@@ -35,12 +39,34 @@ export const generateNewCell = async (variantId: string, scenarioId: string) =>
|
||||
},
|
||||
});
|
||||
|
||||
if (cell) return cell;
|
||||
if (cell) return;
|
||||
|
||||
const parsedConstructFn = await parseConstructFn(
|
||||
variant.constructFn,
|
||||
scenario.variableValues as JsonObject,
|
||||
);
|
||||
|
||||
if ("error" in parsedConstructFn) {
|
||||
await prisma.scenarioVariantCell.create({
|
||||
data: {
|
||||
promptVariantId: variantId,
|
||||
testScenarioId: scenarioId,
|
||||
statusCode: 400,
|
||||
errorMessage: parsedConstructFn.error,
|
||||
retrievalStatus: "ERROR",
|
||||
},
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
const inputHash = hashPrompt(parsedConstructFn);
|
||||
|
||||
cell = await prisma.scenarioVariantCell.create({
|
||||
data: {
|
||||
promptVariantId: variantId,
|
||||
testScenarioId: scenarioId,
|
||||
prompt: parsedConstructFn.modelInput as unknown as Prisma.InputJsonValue,
|
||||
retrievalStatus: "PENDING",
|
||||
},
|
||||
include: {
|
||||
modelOutput: true,
|
||||
@@ -48,30 +74,36 @@ export const generateNewCell = async (variantId: string, scenarioId: string) =>
|
||||
});
|
||||
|
||||
const matchingModelOutput = await prisma.modelOutput.findFirst({
|
||||
where: {
|
||||
inputHash,
|
||||
},
|
||||
where: { inputHash },
|
||||
});
|
||||
|
||||
let newModelOutput;
|
||||
|
||||
if (matchingModelOutput) {
|
||||
newModelOutput = await prisma.modelOutput.create({
|
||||
const newModelOutput = await prisma.modelOutput.create({
|
||||
data: {
|
||||
...omit(matchingModelOutput, ["id"]),
|
||||
scenarioVariantCellId: cell.id,
|
||||
inputHash,
|
||||
output: matchingModelOutput.output as Prisma.InputJsonValue,
|
||||
timeToComplete: matchingModelOutput.timeToComplete,
|
||||
cost: matchingModelOutput.cost,
|
||||
promptTokens: matchingModelOutput.promptTokens,
|
||||
completionTokens: matchingModelOutput.completionTokens,
|
||||
createdAt: matchingModelOutput.createdAt,
|
||||
updatedAt: matchingModelOutput.updatedAt,
|
||||
},
|
||||
});
|
||||
} else {
|
||||
cell = await queueLLMRetrievalTask(cell.id);
|
||||
}
|
||||
await prisma.scenarioVariantCell.update({
|
||||
where: { id: cell.id },
|
||||
data: { retrievalStatus: "COMPLETE" },
|
||||
});
|
||||
|
||||
return { ...cell, modelOutput: newModelOutput };
|
||||
// Copy over all eval results as well
|
||||
await Promise.all(
|
||||
(
|
||||
await prisma.outputEvaluation.findMany({ where: { modelOutputId: matchingModelOutput.id } })
|
||||
).map(async (evaluation) => {
|
||||
await prisma.outputEvaluation.create({
|
||||
data: {
|
||||
...omit(evaluation, ["id"]),
|
||||
modelOutputId: newModelOutput.id,
|
||||
},
|
||||
});
|
||||
}),
|
||||
);
|
||||
} else {
|
||||
await queueQueryModel(cell.id, stream);
|
||||
}
|
||||
};
|
||||
|
||||
@@ -1,107 +0,0 @@
|
||||
/* eslint-disable @typescript-eslint/no-unsafe-call */
|
||||
import { isObject } from "lodash-es";
|
||||
import { streamChatCompletion } from "./openai";
|
||||
import { wsConnection } from "~/utils/wsConnection";
|
||||
import { type ChatCompletion, type CompletionCreateParams } from "openai/resources/chat";
|
||||
import { type SupportedModel, type OpenAIChatModel } from "../types";
|
||||
import { env } from "~/env.mjs";
|
||||
import { countOpenAIChatTokens } from "~/utils/countTokens";
|
||||
import { rateLimitErrorMessage } from "~/sharedStrings";
|
||||
import { modelStats } from "../modelStats";
|
||||
|
||||
export type CompletionResponse = {
|
||||
output: ChatCompletion | null;
|
||||
statusCode: number;
|
||||
errorMessage: string | null;
|
||||
timeToComplete: number;
|
||||
promptTokens?: number;
|
||||
completionTokens?: number;
|
||||
cost?: number;
|
||||
};
|
||||
|
||||
export async function getOpenAIChatCompletion(
|
||||
payload: CompletionCreateParams,
|
||||
channel?: string,
|
||||
): Promise<CompletionResponse> {
|
||||
// If functions are enabled, disable streaming so that we get the full response with token counts
|
||||
if (payload.functions?.length) payload.stream = false;
|
||||
const start = Date.now();
|
||||
const response = await fetch("https://api.openai.com/v1/chat/completions", {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${env.OPENAI_API_KEY}`,
|
||||
},
|
||||
body: JSON.stringify(payload),
|
||||
});
|
||||
|
||||
const resp: CompletionResponse = {
|
||||
output: null,
|
||||
errorMessage: null,
|
||||
statusCode: response.status,
|
||||
timeToComplete: 0,
|
||||
};
|
||||
|
||||
try {
|
||||
if (payload.stream) {
|
||||
const completion = streamChatCompletion(payload as unknown as CompletionCreateParams);
|
||||
let finalOutput: ChatCompletion | null = null;
|
||||
await (async () => {
|
||||
for await (const partialCompletion of completion) {
|
||||
finalOutput = partialCompletion;
|
||||
wsConnection.emit("message", { channel, payload: partialCompletion });
|
||||
}
|
||||
})().catch((err) => console.error(err));
|
||||
if (finalOutput) {
|
||||
resp.output = finalOutput;
|
||||
resp.timeToComplete = Date.now() - start;
|
||||
}
|
||||
} else {
|
||||
resp.timeToComplete = Date.now() - start;
|
||||
resp.output = await response.json();
|
||||
}
|
||||
|
||||
if (!response.ok) {
|
||||
if (response.status === 429) {
|
||||
resp.errorMessage = rateLimitErrorMessage;
|
||||
} else if (
|
||||
isObject(resp.output) &&
|
||||
"error" in resp.output &&
|
||||
isObject(resp.output.error) &&
|
||||
"message" in resp.output.error
|
||||
) {
|
||||
// If it's an object, try to get the error message
|
||||
resp.errorMessage = resp.output.error.message?.toString() ?? "Unknown error";
|
||||
}
|
||||
}
|
||||
|
||||
if (isObject(resp.output) && "usage" in resp.output) {
|
||||
const usage = resp.output.usage as unknown as ChatCompletion.Usage;
|
||||
resp.promptTokens = usage.prompt_tokens;
|
||||
resp.completionTokens = usage.completion_tokens;
|
||||
} else if (isObject(resp.output) && "choices" in resp.output) {
|
||||
const model = payload.model as unknown as OpenAIChatModel;
|
||||
resp.promptTokens = countOpenAIChatTokens(model, payload.messages);
|
||||
const choices = resp.output.choices as unknown as ChatCompletion.Choice[];
|
||||
const message = choices[0]?.message;
|
||||
if (message) {
|
||||
const messages = [message];
|
||||
resp.completionTokens = countOpenAIChatTokens(model, messages);
|
||||
}
|
||||
}
|
||||
|
||||
const stats = modelStats[resp.output?.model as SupportedModel];
|
||||
if (stats && resp.promptTokens && resp.completionTokens) {
|
||||
resp.cost =
|
||||
resp.promptTokens * stats.promptTokenPrice +
|
||||
resp.completionTokens * stats.completionTokenPrice;
|
||||
}
|
||||
} catch (e) {
|
||||
console.error(e);
|
||||
if (response.ok) {
|
||||
resp.errorMessage = "Failed to parse response";
|
||||
}
|
||||
}
|
||||
|
||||
return resp;
|
||||
}
|
||||
@@ -1,7 +0,0 @@
|
||||
import { OpenAIChatModel, type SupportedModel } from "../types";
|
||||
import openAIChatApiShape from "~/codegen/openai.types.ts.txt";
|
||||
|
||||
export const getApiShapeForModel = (model: SupportedModel) => {
|
||||
if (model in OpenAIChatModel) return openAIChatApiShape;
|
||||
return "";
|
||||
};
|
||||
37
src/server/utils/hashPrompt.ts
Normal file
37
src/server/utils/hashPrompt.ts
Normal file
@@ -0,0 +1,37 @@
|
||||
import crypto from "crypto";
|
||||
import { type JsonValue } from "type-fest";
|
||||
import { type ParsedConstructFn } from "./parseConstructFn";
|
||||
|
||||
function sortKeys(obj: JsonValue): JsonValue {
|
||||
if (typeof obj !== "object" || obj === null) {
|
||||
// Not an object or array, return as is
|
||||
return obj;
|
||||
}
|
||||
|
||||
if (Array.isArray(obj)) {
|
||||
return obj.map(sortKeys);
|
||||
}
|
||||
|
||||
// Get keys and sort them
|
||||
const keys = Object.keys(obj).sort();
|
||||
const sortedObj = {};
|
||||
|
||||
for (const key of keys) {
|
||||
// @ts-expect-error not worth fixing types
|
||||
// eslint-disable-next-line @typescript-eslint/no-unsafe-argument
|
||||
sortedObj[key] = sortKeys(obj[key]);
|
||||
}
|
||||
|
||||
return sortedObj;
|
||||
}
|
||||
|
||||
export default function hashPrompt(prompt: ParsedConstructFn<any>): string {
|
||||
// Sort object keys recursively
|
||||
const sortedObj = sortKeys(prompt as unknown as JsonValue);
|
||||
|
||||
// Convert to JSON and hash it
|
||||
const str = JSON.stringify(sortedObj);
|
||||
const hash = crypto.createHash("sha256");
|
||||
hash.update(str);
|
||||
return hash.digest("hex");
|
||||
}
|
||||
@@ -1,64 +1,5 @@
|
||||
import { omit } from "lodash-es";
|
||||
import { env } from "~/env.mjs";
|
||||
|
||||
import OpenAI from "openai";
|
||||
import {
|
||||
type ChatCompletion,
|
||||
type ChatCompletionChunk,
|
||||
type CompletionCreateParams,
|
||||
} from "openai/resources/chat";
|
||||
|
||||
export const openai = new OpenAI({ apiKey: env.OPENAI_API_KEY });
|
||||
|
||||
export const mergeStreamedChunks = (
|
||||
base: ChatCompletion | null,
|
||||
chunk: ChatCompletionChunk,
|
||||
): ChatCompletion => {
|
||||
if (base === null) {
|
||||
return mergeStreamedChunks({ ...chunk, choices: [] }, chunk);
|
||||
}
|
||||
|
||||
const choices = [...base.choices];
|
||||
for (const choice of chunk.choices) {
|
||||
const baseChoice = choices.find((c) => c.index === choice.index);
|
||||
if (baseChoice) {
|
||||
baseChoice.finish_reason = choice.finish_reason ?? baseChoice.finish_reason;
|
||||
baseChoice.message = baseChoice.message ?? { role: "assistant" };
|
||||
|
||||
if (choice.delta?.content)
|
||||
baseChoice.message.content =
|
||||
((baseChoice.message.content as string) ?? "") + (choice.delta.content ?? "");
|
||||
if (choice.delta?.function_call) {
|
||||
const fnCall = baseChoice.message.function_call ?? {};
|
||||
fnCall.name =
|
||||
((fnCall.name as string) ?? "") + ((choice.delta.function_call.name as string) ?? "");
|
||||
fnCall.arguments =
|
||||
((fnCall.arguments as string) ?? "") +
|
||||
((choice.delta.function_call.arguments as string) ?? "");
|
||||
}
|
||||
} else {
|
||||
choices.push({ ...omit(choice, "delta"), message: { role: "assistant", ...choice.delta } });
|
||||
}
|
||||
}
|
||||
|
||||
const merged: ChatCompletion = {
|
||||
...base,
|
||||
choices,
|
||||
};
|
||||
|
||||
return merged;
|
||||
};
|
||||
|
||||
export const streamChatCompletion = async function* (body: CompletionCreateParams) {
|
||||
// eslint-disable-next-line @typescript-eslint/no-unsafe-call
|
||||
const resp = await openai.chat.completions.create({
|
||||
...body,
|
||||
stream: true,
|
||||
});
|
||||
|
||||
let mergedChunks: ChatCompletion | null = null;
|
||||
for await (const part of resp) {
|
||||
mergedChunks = mergeStreamedChunks(mergedChunks, part);
|
||||
yield mergedChunks;
|
||||
}
|
||||
};
|
||||
|
||||
45
src/server/utils/parseConstructFn.test.ts
Normal file
45
src/server/utils/parseConstructFn.test.ts
Normal file
@@ -0,0 +1,45 @@
|
||||
import { expect, test } from "vitest";
|
||||
import parseConstructFn from "./parseConstructFn";
|
||||
import assert from "assert";
|
||||
|
||||
// Note: this has to be run with `vitest --no-threads` option or else
|
||||
// isolated-vm seems to throw errors
|
||||
test("parseConstructFn", async () => {
|
||||
const constructed = await parseConstructFn(
|
||||
`
|
||||
// These sometimes have a comment
|
||||
|
||||
definePrompt("openai/ChatCompletion", {
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: \`What is the capital of \${scenario.country}?\`
|
||||
}
|
||||
]
|
||||
})
|
||||
`,
|
||||
{ country: "Bolivia" },
|
||||
);
|
||||
|
||||
expect(constructed).toEqual({
|
||||
modelProvider: "openai/ChatCompletion",
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
modelInput: {
|
||||
messages: [
|
||||
{
|
||||
content: "What is the capital of Bolivia?",
|
||||
role: "user",
|
||||
},
|
||||
],
|
||||
model: "gpt-3.5-turbo-0613",
|
||||
},
|
||||
});
|
||||
});
|
||||
|
||||
test("bad syntax", async () => {
|
||||
const parsed = await parseConstructFn(`definePrompt("openai/ChatCompletion", {`);
|
||||
|
||||
assert("error" in parsed);
|
||||
expect(parsed.error).toContain("Unexpected end of input");
|
||||
});
|
||||
92
src/server/utils/parseConstructFn.ts
Normal file
92
src/server/utils/parseConstructFn.ts
Normal file
@@ -0,0 +1,92 @@
|
||||
import modelProviders from "~/modelProviders/modelProviders";
|
||||
import ivm from "isolated-vm";
|
||||
import { isObject, isString } from "lodash-es";
|
||||
import { type JsonObject } from "type-fest";
|
||||
import { validate } from "jsonschema";
|
||||
|
||||
export type ParsedConstructFn<T extends keyof typeof modelProviders> = {
|
||||
modelProvider: T;
|
||||
model: keyof (typeof modelProviders)[T]["models"];
|
||||
modelInput: Parameters<(typeof modelProviders)[T]["getModel"]>[0];
|
||||
};
|
||||
|
||||
const isolate = new ivm.Isolate({ memoryLimit: 128 });
|
||||
|
||||
export default async function parseConstructFn(
|
||||
constructFn: string,
|
||||
scenario: JsonObject | undefined = {},
|
||||
): Promise<ParsedConstructFn<keyof typeof modelProviders> | { error: string }> {
|
||||
try {
|
||||
const modifiedConstructFn = constructFn.replace(
|
||||
"definePrompt(",
|
||||
"global.prompt = definePrompt(",
|
||||
);
|
||||
|
||||
const code = `
|
||||
const scenario = ${JSON.stringify(scenario ?? {}, null, 2)};
|
||||
|
||||
const definePrompt = (modelProvider, input) => ({
|
||||
modelProvider,
|
||||
input
|
||||
})
|
||||
|
||||
${modifiedConstructFn}
|
||||
`;
|
||||
|
||||
const context = await isolate.createContext();
|
||||
const jail = context.global;
|
||||
await jail.set("global", jail.derefInto());
|
||||
|
||||
const script = await isolate.compileScript(code);
|
||||
await script.run(context);
|
||||
const promptReference = (await context.global.get("prompt")) as ivm.Reference;
|
||||
const prompt = await promptReference.copy();
|
||||
|
||||
if (!isObject(prompt)) {
|
||||
return { error: "definePrompt did not return an object" };
|
||||
}
|
||||
if (!("modelProvider" in prompt) || !isString(prompt.modelProvider)) {
|
||||
return { error: "definePrompt did not return a valid modelProvider" };
|
||||
}
|
||||
|
||||
const provider =
|
||||
prompt.modelProvider in modelProviders &&
|
||||
modelProviders[prompt.modelProvider as keyof typeof modelProviders];
|
||||
if (!provider) {
|
||||
return { error: "definePrompt did not return a known modelProvider" };
|
||||
}
|
||||
if (!("input" in prompt) || !isObject(prompt.input)) {
|
||||
return { error: "definePrompt did not return an input" };
|
||||
}
|
||||
|
||||
const validationResult = validate(prompt.input, provider.inputSchema);
|
||||
if (!validationResult.valid)
|
||||
return {
|
||||
error: `definePrompt did not return a valid input: ${validationResult.errors
|
||||
.map((e) => e.stack)
|
||||
.join(", ")}`,
|
||||
};
|
||||
|
||||
// We've validated the JSON schema so this should be safe
|
||||
const input = prompt.input as Parameters<(typeof provider)["getModel"]>[0];
|
||||
|
||||
const model = provider.getModel(input);
|
||||
if (!model) {
|
||||
return {
|
||||
error: `definePrompt did not return a known model for the provider ${prompt.modelProvider}`,
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
modelProvider: prompt.modelProvider as keyof typeof modelProviders,
|
||||
model,
|
||||
modelInput: input,
|
||||
};
|
||||
} catch (e) {
|
||||
const msg =
|
||||
isObject(e) && "message" in e && isString(e.message)
|
||||
? e.message
|
||||
: "unknown error parsing definePrompt script";
|
||||
return { error: msg };
|
||||
}
|
||||
}
|
||||
@@ -1,22 +0,0 @@
|
||||
import { prisma } from "../db";
|
||||
import { queryLLM } from "../tasks/queryLLM.task";
|
||||
|
||||
export const queueLLMRetrievalTask = async (cellId: string) => {
|
||||
const updatedCell = await prisma.scenarioVariantCell.update({
|
||||
where: {
|
||||
id: cellId,
|
||||
},
|
||||
data: {
|
||||
retrievalStatus: "PENDING",
|
||||
errorMessage: null,
|
||||
},
|
||||
include: {
|
||||
modelOutput: true,
|
||||
},
|
||||
});
|
||||
|
||||
// @ts-expect-error we aren't passing the helpers but that's ok
|
||||
void queryLLM.task.handler({ scenarioVariantCellId: cellId }, { logger: console });
|
||||
|
||||
return updatedCell;
|
||||
};
|
||||
@@ -1,7 +0,0 @@
|
||||
import { isObject } from "lodash-es";
|
||||
import { type JSONSerializable } from "../types";
|
||||
|
||||
export const shouldStream = (config: JSONSerializable): boolean => {
|
||||
const shouldStream = isObject(config) && "stream" in config && config.stream === true;
|
||||
return shouldStream;
|
||||
};
|
||||
@@ -8,7 +8,7 @@ export default async function userOrg(userId: string) {
|
||||
update: {},
|
||||
create: {
|
||||
personalOrgUserId: userId,
|
||||
OrganizationUser: {
|
||||
organizationUsers: {
|
||||
create: {
|
||||
userId: userId,
|
||||
role: "ADMIN",
|
||||
|
||||
@@ -1,7 +1,6 @@
|
||||
import { type RouterOutputs } from "~/utils/api";
|
||||
import { type SliceCreator } from "./store";
|
||||
import loader from "@monaco-editor/loader";
|
||||
import openAITypes from "~/codegen/openai.types.ts.txt";
|
||||
import formatPromptConstructor from "~/utils/formatPromptConstructor";
|
||||
|
||||
export const editorBackground = "#fafafa";
|
||||
@@ -9,9 +8,9 @@ export const editorBackground = "#fafafa";
|
||||
export type SharedVariantEditorSlice = {
|
||||
monaco: null | ReturnType<typeof loader.__getMonacoInstance>;
|
||||
loadMonaco: () => Promise<void>;
|
||||
scenarios: RouterOutputs["scenarios"]["list"];
|
||||
scenarios: RouterOutputs["scenarios"]["list"]["scenarios"];
|
||||
updateScenariosModel: () => void;
|
||||
setScenarios: (scenarios: RouterOutputs["scenarios"]["list"]) => void;
|
||||
setScenarios: (scenarios: RouterOutputs["scenarios"]["list"]["scenarios"]) => void;
|
||||
};
|
||||
|
||||
export const createVariantEditorSlice: SliceCreator<SharedVariantEditorSlice> = (set, get) => ({
|
||||
@@ -20,7 +19,10 @@ export const createVariantEditorSlice: SliceCreator<SharedVariantEditorSlice> =
|
||||
// We only want to run this client-side
|
||||
if (typeof window === "undefined") return;
|
||||
|
||||
const monaco = await loader.init();
|
||||
const [monaco, promptTypes] = await Promise.all([
|
||||
loader.init(),
|
||||
get().api?.client.experiments.promptTypes.query(),
|
||||
]);
|
||||
|
||||
monaco.editor.defineTheme("customTheme", {
|
||||
base: "vs",
|
||||
@@ -37,14 +39,9 @@ export const createVariantEditorSlice: SliceCreator<SharedVariantEditorSlice> =
|
||||
lib: ["esnext"],
|
||||
});
|
||||
|
||||
monaco.editor.createModel(
|
||||
`
|
||||
${openAITypes}
|
||||
|
||||
declare var prompt: components["schemas"]["CreateChatCompletionRequest"];
|
||||
`,
|
||||
"typescript",
|
||||
monaco.Uri.parse("file:///openai.types.ts"),
|
||||
monaco.languages.typescript.typescriptDefaults.addExtraLib(
|
||||
promptTypes ?? "",
|
||||
"file:///PromptTypes.d.ts",
|
||||
);
|
||||
|
||||
monaco.languages.registerDocumentFormattingEditProvider("typescript", {
|
||||
@@ -64,7 +61,6 @@ export const createVariantEditorSlice: SliceCreator<SharedVariantEditorSlice> =
|
||||
get().sharedVariantEditor.updateScenariosModel();
|
||||
},
|
||||
scenarios: [],
|
||||
// scenariosModel: null,
|
||||
setScenarios: (scenarios) => {
|
||||
set((state) => {
|
||||
state.sharedVariantEditor.scenarios = scenarios;
|
||||
|
||||
@@ -5,11 +5,14 @@ import {
|
||||
type SharedVariantEditorSlice,
|
||||
createVariantEditorSlice,
|
||||
} from "./sharedVariantEditor.slice";
|
||||
import { type APIClient } from "~/utils/api";
|
||||
|
||||
export type State = {
|
||||
drawerOpen: boolean;
|
||||
openDrawer: () => void;
|
||||
closeDrawer: () => void;
|
||||
api: APIClient | null;
|
||||
setApi: (api: APIClient) => void;
|
||||
sharedVariantEditor: SharedVariantEditorSlice;
|
||||
};
|
||||
|
||||
@@ -20,6 +23,12 @@ export type GetFn = Parameters<SliceCreator<unknown>>[1];
|
||||
|
||||
const useBaseStore = create<State, [["zustand/immer", never]]>(
|
||||
immer((set, get, ...rest) => ({
|
||||
api: null,
|
||||
setApi: (api) =>
|
||||
set((state) => {
|
||||
state.api = api;
|
||||
}),
|
||||
|
||||
drawerOpen: false,
|
||||
openDrawer: () =>
|
||||
set((state) => {
|
||||
@@ -34,5 +43,3 @@ const useBaseStore = create<State, [["zustand/immer", never]]>(
|
||||
);
|
||||
|
||||
export const useAppStore = createSelectors(useBaseStore);
|
||||
|
||||
useAppStore.getState().sharedVariantEditor.loadMonaco().catch(console.error);
|
||||
|
||||
@@ -1,17 +0,0 @@
|
||||
import { useEffect } from "react";
|
||||
import { api } from "~/utils/api";
|
||||
import { useExperiment } from "~/utils/hooks";
|
||||
import { useAppStore } from "./store";
|
||||
|
||||
export function useSyncVariantEditor() {
|
||||
const experiment = useExperiment();
|
||||
const scenarios = api.scenarios.list.useQuery(
|
||||
{ experimentId: experiment.data?.id ?? "" },
|
||||
{ enabled: !!experiment.data?.id },
|
||||
);
|
||||
useEffect(() => {
|
||||
if (scenarios.data) {
|
||||
useAppStore.getState().sharedVariantEditor.setScenarios(scenarios.data);
|
||||
}
|
||||
}, [scenarios.data]);
|
||||
}
|
||||
26
src/state/sync.tsx
Normal file
26
src/state/sync.tsx
Normal file
@@ -0,0 +1,26 @@
|
||||
import { useEffect } from "react";
|
||||
import { api } from "~/utils/api";
|
||||
import { useScenarios } from "~/utils/hooks";
|
||||
import { useAppStore } from "./store";
|
||||
|
||||
export function useSyncVariantEditor() {
|
||||
const scenarios = useScenarios();
|
||||
|
||||
useEffect(() => {
|
||||
if (scenarios.data) {
|
||||
useAppStore.getState().sharedVariantEditor.setScenarios(scenarios.data.scenarios);
|
||||
}
|
||||
}, [scenarios.data]);
|
||||
}
|
||||
|
||||
export function SyncAppStore() {
|
||||
const utils = api.useContext();
|
||||
|
||||
const setApi = useAppStore((state) => state.setApi);
|
||||
|
||||
useEffect(() => {
|
||||
setApi(utils);
|
||||
}, [utils, setApi]);
|
||||
|
||||
return null;
|
||||
}
|
||||
@@ -1,5 +1,6 @@
|
||||
import { extendTheme } from "@chakra-ui/react";
|
||||
import "@fontsource/inconsolata";
|
||||
import { ChakraProvider } from "@chakra-ui/react";
|
||||
|
||||
const systemFont =
|
||||
'ui-sans-serif, -apple-system, "system-ui", "Segoe UI", Helvetica, "Apple Color Emoji", Arial, sans-serif, "Segoe UI Emoji", "Segoe UI Symbol"';
|
||||
@@ -34,4 +35,6 @@ const theme = extendTheme({
|
||||
},
|
||||
});
|
||||
|
||||
export default theme;
|
||||
export const ChakraThemeProvider = ({ children }: { children: JSX.Element }) => {
|
||||
return <ChakraProvider theme={theme}>{children}</ChakraProvider>;
|
||||
};
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user