Properly use isDisabled

* Remove experiments flicker for unauthenticated users

* Decrease size of NewScenarioButton spinner

package.json

@@ -73,7 +73,6 @@
     "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",

pnpm-lock.yaml

@@ -161,9 +161,6 @@ dependencies:
   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
@@ -6991,11 +6988,6 @@ packages:
       functions-have-names: 1.2.3
     dev: true
 
-  /replicate@0.12.3:
-    resolution: {integrity: sha512-HVWKPoVhWVTONlWk+lUXmq9Vy2J8MxBJMtDBQq3dA5uq71ZzKTh0xvJfvzW4+VLBjhBeL7tkdua6hZJmKfzAPQ==}
-    engines: {git: '>=2.11.0', node: '>=16.6.0', npm: '>=7.19.0', yarn: '>=1.7.0'}
-    dev: false
-
   /require-directory@2.1.1:
     resolution: {integrity: sha512-fGxEI7+wsG9xrvdjsrlmL22OMTTiHRwAMroiEeMgq8gzoLC/PQr7RsRDSTLUg/bZAZtF+TVIkHc6/4RIKrui+Q==}
     engines: {node: '>=0.10.0'}

src/components/AutoResizeTextArea.tsx

@@ -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}

src/components/OutputsTable/FloatingLabelInput.tsx

@@ -18,11 +18,9 @@ export const FloatingLabelInput = ({
         transform={isFocused || !!value ? "translateY(-50%)" : "translateY(0)"}
         fontSize={isFocused || !!value ? "12px" : "16px"}
         transition="all 0.15s"
-        zIndex="100"
+        zIndex="5"
         bg="white"
         px={1}
-        mt={0}
-        mb={2}
         lineHeight="1"
         pointerEvents="none"
         color={isFocused ? "blue.500" : "gray.500"}

src/components/OutputsTable/NewScenarioButton.tsx

@@ -49,7 +49,11 @@ export default function NewScenarioButton() {
         Add Scenario
       </StyledButton>
       <StyledButton onClick={onAutogenerate}>
-        <Icon as={autogenerating ? Spinner : BsPlus} boxSize={6} mr={autogenerating ? 1 : 0} />
+        <Icon
+          as={autogenerating ? Spinner : BsPlus}
+          boxSize={autogenerating ? 4 : 6}
+          mr={autogenerating ? 2 : 0}
+        />
         Autogenerate Scenario
       </StyledButton>
     </HStack>

src/components/OutputsTable/OutputCell/OutputCell.tsx

@@ -88,11 +88,9 @@ export default function OutputCell({
   }
 
   const normalizedOutput = modelOutput
-    ? // @ts-expect-error TODO FIX ASAP
-      provider.normalizeOutput(modelOutput.output as unknown as OutputSchema)
+    ? provider.normalizeOutput(modelOutput.output as unknown as OutputSchema)
     : streamedMessage
-    ? // @ts-expect-error TODO FIX ASAP
-      provider.normalizeOutput(streamedMessage)
+    ? provider.normalizeOutput(streamedMessage)
     : null;
 
   if (modelOutput && normalizedOutput?.type === "json") {

src/components/OutputsTable/styles.ts

@@ -4,5 +4,5 @@ export const stickyHeaderStyle: SystemStyleObject = {
   position: "sticky",
   top: "0",
   backgroundColor: "#fff",
-  zIndex: 1,
+  zIndex: 10,
 };

src/components/RefinePromptModal/CompareFunctions.tsx

@@ -1,4 +1,4 @@
-import { HStack, VStack, useBreakpointValue } 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";
@@ -19,10 +19,15 @@ const highlightSyntax = (str: string) => {
 const CompareFunctions = ({
   originalFunction,
   newFunction = "",
+  leftTitle = "Original",
+  rightTitle = "Modified",
+  ...props
 }: {
   originalFunction: string;
   newFunction?: string;
-}) => {
+  leftTitle?: string;
+  rightTitle?: string;
+} & StackProps) => {
   const showSplitView = useBreakpointValue(
     {
       base: false,
@@ -34,22 +39,20 @@ const CompareFunctions = ({
   );
 
   return (
-    <HStack w="full" spacing={5}>
-      <VStack w="full" spacing={4} maxH="40vh" fontSize={12} lineHeight={1} overflowY="auto">
-        <DiffViewer
-          oldValue={originalFunction}
-          newValue={newFunction || originalFunction}
-          splitView={showSplitView}
-          hideLineNumbers={!showSplitView}
-          leftTitle="Original"
-          rightTitle={newFunction ? "Modified" : "Unmodified"}
-          disableWordDiff={true}
-          compareMethod={DiffMethod.CHARS}
-          renderContent={highlightSyntax}
-          showDiffOnly={false}
-        />
-      </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>
   );
 };
 

src/components/RefinePromptModal/CustomInstructionsInput.tsx

@@ -56,7 +56,6 @@ export const CustomInstructionsInput = ({
           minW="unset"
           size="sm"
           onClick={() => onSubmit()}
-          disabled={!instructions}
           variant={instructions ? "solid" : "ghost"}
           mr={4}
           borderRadius="8"

src/components/RefinePromptModal/RefinePromptModal.tsx

@@ -36,25 +36,25 @@ export const RefinePromptModal = ({
 }) => {
   const utils = api.useContext();
 
-  const { mutateAsync: getRefinedPromptMutateAsync, data: refinedPromptFn } =
-    api.promptVariants.getRefinedPromptFn.useMutation();
+  const { mutateAsync: getModifiedPromptMutateAsync, data: refinedPromptFn } =
+    api.promptVariants.getModifiedPromptFn.useMutation();
   const [instructions, setInstructions] = useState<string>("");
 
   const [activeRefineOptionLabel, setActiveRefineOptionLabel] = useState<
     RefineOptionLabel | undefined
   >(undefined);
 
-  const [getRefinedPromptFn, refiningInProgress] = useHandledAsyncCallback(
+  const [getModifiedPromptFn, modificationInProgress] = useHandledAsyncCallback(
     async (label?: RefineOptionLabel) => {
       if (!variant.experimentId) return;
       const updatedInstructions = label ? refineOptions[label].instructions : instructions;
       setActiveRefineOptionLabel(label);
-      await getRefinedPromptMutateAsync({
+      await getModifiedPromptMutateAsync({
         id: variant.id,
         instructions: updatedInstructions,
       });
     },
-    [getRefinedPromptMutateAsync, onClose, variant, instructions, setActiveRefineOptionLabel],
+    [getModifiedPromptMutateAsync, onClose, variant, instructions, setActiveRefineOptionLabel],
   );
 
   const replaceVariantMutation = api.promptVariants.replaceVariant.useMutation();
@@ -75,7 +75,11 @@ export const RefinePromptModal = ({
   }, [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>
@@ -93,15 +97,15 @@ export const RefinePromptModal = ({
                   label="Convert to function call"
                   activeLabel={activeRefineOptionLabel}
                   icon={VscJson}
-                  onClick={getRefinedPromptFn}
-                  loading={refiningInProgress}
+                  onClick={getModifiedPromptFn}
+                  loading={modificationInProgress}
                 />
                 <RefineOption
                   label="Add chain of thought"
                   activeLabel={activeRefineOptionLabel}
                   icon={TfiThought}
-                  onClick={getRefinedPromptFn}
-                  loading={refiningInProgress}
+                  onClick={getModifiedPromptFn}
+                  loading={modificationInProgress}
                 />
               </SimpleGrid>
               <HStack>
@@ -110,13 +114,14 @@ export const RefinePromptModal = ({
               <CustomInstructionsInput
                 instructions={instructions}
                 setInstructions={setInstructions}
-                loading={refiningInProgress}
-                onSubmit={getRefinedPromptFn}
+                loading={modificationInProgress}
+                onSubmit={getModifiedPromptFn}
               />
             </VStack>
             <CompareFunctions
               originalFunction={variant.constructFn}
               newFunction={isString(refinedPromptFn) ? refinedPromptFn : undefined}
+              maxH="40vh"
             />
           </VStack>
         </ModalBody>
@@ -124,12 +129,10 @@ export const RefinePromptModal = ({
         <ModalFooter>
           <HStack spacing={4}>
             <Button
+              colorScheme="blue"
               onClick={replaceVariant}
               minW={24}
-              disabled={replacementInProgress || !refinedPromptFn}
-              _disabled={{
-                bgColor: "blue.500",
-              }}
+              isDisabled={replacementInProgress || !refinedPromptFn}
             >
               {replacementInProgress ? <Spinner boxSize={4} /> : <Text>Accept</Text>}
             </Button>

src/components/RefinePromptModal/refineOptions.ts

@@ -12,7 +12,7 @@ export const refineOptions: Record<
       
     This is what a prompt looks like before adding chain of thought:
     
-    prompt = {
+    definePrompt("openai/ChatCompletion", {
         model: "gpt-4",
         stream: true,
         messages: [
@@ -25,11 +25,11 @@ export const refineOptions: Record<
             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:
 
-    prompt = {
+    definePrompt("openai/ChatCompletion", {
         model: "gpt-4",
         stream: true,
         messages: [
@@ -42,13 +42,13 @@ export const refineOptions: Record<
             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:
 
-    prompt = {
+    definePrompt("openai/ChatCompletion", {
         model: "gpt-3.5-turbo",
         messages: [
           {
@@ -78,11 +78,11 @@ export const refineOptions: Record<
         function_call: {
           name: "score_post",
         },
-      };
+      });
 
     After:
 
-    prompt = {
+    definePrompt("openai/ChatCompletion", {
         model: "gpt-3.5-turbo",
         messages: [
           {
@@ -115,7 +115,7 @@ export const refineOptions: Record<
         function_call: {
           name: "score_post",
         },
-      };
+      });
 
     Add chain of thought to the original prompt.`,
   },
@@ -125,7 +125,7 @@ export const refineOptions: Record<
     
     This is what a prompt looks like before adding a function:
     
-    prompt = {
+    definePrompt("openai/ChatCompletion", {
       model: "gpt-4",
       stream: true,
       messages: [
@@ -138,11 +138,11 @@ export const refineOptions: Record<
           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:
   
-    prompt = {
+    definePrompt("openai/ChatCompletion", {
       model: "gpt-4",
       stream: true,
       messages: [
@@ -172,13 +172,13 @@ export const refineOptions: Record<
       function_call: {
         name: "extract_sentiment",
       },
-    };
+    });
 
     Here's another example of adding a function:
 
     Before:
 
-    prompt = {
+    definePrompt("openai/ChatCompletion", {
         model: "gpt-3.5-turbo",
         messages: [
           {
@@ -196,11 +196,11 @@ export const refineOptions: Record<
           },
         ],
         temperature: 0,
-    };
+    });
 
     After:
 
-    prompt = {
+    definePrompt("openai/ChatCompletion", {
         model: "gpt-3.5-turbo",
         messages: [
           {
@@ -230,7 +230,7 @@ export const refineOptions: Record<
         function_call: {
           name: "score_post",
         },
-      };
+      });
     
     Add an OpenAI function that takes one or more nested parameters that match the expected output from this prompt.`,
   },

src/components/SelectModelModal/SelectModelModal.tsx

@@ -20,36 +20,60 @@ import { ModelStatsCard } from "./ModelStatsCard";
 import { SelectModelSearch } from "./SelectModelSearch";
 import { api } from "~/utils/api";
 import { useExperiment, useHandledAsyncCallback } from "~/utils/hooks";
+import CompareFunctions from "../RefinePromptModal/CompareFunctions";
+import { type PromptVariant } from "@prisma/client";
+import { isObject, isString } from "lodash-es";
 
 export const SelectModelModal = ({
-  originalModel,
-  variantId,
+  variant,
   onClose,
 }: {
-  originalModel: SupportedModel;
-  variantId: string;
+  variant: PromptVariant;
   onClose: () => void;
 }) => {
+  const originalModel = variant.model as SupportedModel;
   const [selectedModel, setSelectedModel] = useState<SupportedModel>(originalModel);
+  const [convertedModel, setConvertedModel] = useState<SupportedModel | undefined>(undefined);
   const utils = api.useContext();
 
   const experiment = useExperiment();
 
-  const createMutation = api.promptVariants.create.useMutation();
+  const { mutateAsync: getModifiedPromptMutateAsync, data: modifiedPromptFn } =
+    api.promptVariants.getModifiedPromptFn.useMutation();
 
-  const [createNewVariant, creationInProgress] = useHandledAsyncCallback(async () => {
-    if (!experiment?.data?.id) return;
-    await createMutation.mutateAsync({
-      experimentId: experiment?.data?.id,
-      variantId,
+  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,
+    });
     await utils.promptVariants.list.invalidate();
     onClose();
-  }, [createMutation, experiment?.data?.id, variantId, onClose]);
+  }, [replaceVariantMutation, variant, onClose, modifiedPromptFn]);
 
   return (
-    <Modal isOpen onClose={onClose} size={{ base: "xl", sm: "2xl", md: "3xl" }}>
+    <Modal
+      isOpen
+      onClose={onClose}
+      size={{ base: "xl", sm: "2xl", md: "3xl", lg: "5xl", xl: "7xl" }}
+    >
       <ModalOverlay />
       <ModalContent w={1200}>
         <ModalHeader>
@@ -66,18 +90,36 @@ export const SelectModelModal = ({
               <ModelStatsCard label="New Model" model={selectedModel} />
             )}
             <SelectModelSearch selectedModel={selectedModel} setSelectedModel={setSelectedModel} />
+            {isString(modifiedPromptFn) && (
+              <CompareFunctions
+                originalFunction={variant.constructFn}
+                newFunction={modifiedPromptFn}
+                leftTitle={originalModel}
+                rightTitle={convertedModel}
+              />
+            )}
           </VStack>
         </ModalBody>
 
         <ModalFooter>
-          <Button
-            colorScheme="blue"
-            onClick={createNewVariant}
-            minW={24}
-            disabled={originalModel === selectedModel}
-          >
-            {creationInProgress ? <Spinner boxSize={4} /> : <Text>Continue</Text>}
-          </Button>
+          <HStack>
+            <Button
+              colorScheme="gray"
+              onClick={getModifiedPromptFn}
+              minW={24}
+              isDisabled={originalModel === selectedModel || 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>

src/components/VariantHeader/VariantHeaderMenuButton.tsx

@@ -18,7 +18,6 @@ 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";
 
 export default function VariantHeaderMenuButton({
   variant,
@@ -99,11 +98,7 @@ export default function VariantHeaderMenuButton({
         </MenuList>
       </Menu>
       {selectModelModalOpen && (
-        <SelectModelModal
-          originalModel={variant.model as SupportedModel}
-          variantId={variant.id}
-          onClose={() => setSelectModelModalOpen(false)}
-        />
+        <SelectModelModal variant={variant} onClose={() => setSelectModelModalOpen(false)} />
       )}
       {refinePromptModalOpen && (
         <RefinePromptModal variant={variant} onClose={() => setRefinePromptModalOpen(false)} />

src/env.mjs

@@ -17,7 +17,6 @@ export const env = createEnv({
       .transform((val) => val.toLowerCase() === "true"),
     GITHUB_CLIENT_ID: z.string().min(1),
     GITHUB_CLIENT_SECRET: z.string().min(1),
-    REPLICATE_API_TOKEN: z.string().min(1),
   },
 
   /**
@@ -43,7 +42,6 @@ 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.

src/modelProviders/modelProviders.ts

@@ -1,9 +1,7 @@
 import openaiChatCompletion from "./openai-ChatCompletion";
-import replicateLlama2 from "./replicate-llama2";
 
 const modelProviders = {
   "openai/ChatCompletion": openaiChatCompletion,
-  "replicate/llama2": replicateLlama2,
 } as const;
 
 export default modelProviders;

src/modelProviders/modelProvidersFrontend.ts

@@ -1,14 +1,10 @@
-import openaiChatCompletionFrontend from "./openai-ChatCompletion/frontend";
-import replicateLlama2Frontend from "./replicate-llama2/frontend";
-
-// TODO: make sure we get a typescript error if you forget to add a provider here
+import modelProviderFrontend from "./openai-ChatCompletion/frontend";
 
 // 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 modelProvidersFrontend = {
-  "openai/ChatCompletion": openaiChatCompletionFrontend,
-  "replicate/llama2": replicateLlama2Frontend,
+  "openai/ChatCompletion": modelProviderFrontend,
 } as const;
 
 export default modelProvidersFrontend;

src/modelProviders/replicate-llama2/frontend.ts

@@ -1,13 +0,0 @@
-import { type ReplicateLlama2Provider } from ".";
-import { type ModelProviderFrontend } from "../types";
-
-const modelProviderFrontend: ModelProviderFrontend<ReplicateLlama2Provider> = {
-  normalizeOutput: (output) => {
-    return {
-      type: "text",
-      value: output.join(""),
-    };
-  },
-};
-
-export default modelProviderFrontend;

src/modelProviders/replicate-llama2/getCompletion.ts

@@ -1,62 +0,0 @@
-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": "3725a659b5afff1a0ba9bead5fac3899d998feaad00e07032ca2b0e35eb14f8a",
-  "13b-chat": "5c785d117c5bcdd1928d5a9acb1ffa6272d6cf13fcb722e90886a0196633f9d3",
-  "70b-chat": "e951f18578850b652510200860fc4ea62b3b16fac280f83ff32282f87bbd2e48",
-};
-
-export async function getCompletion(
-  input: ReplicateLlama2Input,
-  onStream: ((partialOutput: string[]) => void) | null,
-): Promise<CompletionResponse<ReplicateLlama2Output>> {
-  const start = Date.now();
-
-  const { model, stream, ...rest } = input;
-
-  try {
-    const prediction = await replicate.predictions.create({
-      version: modelIds[model],
-      input: rest,
-    });
-
-    console.log("stream?", onStream);
-
-    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,
-    };
-  }
-}

src/modelProviders/replicate-llama2/index.ts

@@ -1,74 +0,0 @@
-import { type ModelProvider } from "../types";
-import { getCompletion } from "./getCompletion";
-
-const supportedModels = ["7b-chat", "13b-chat", "70b-chat"] as const;
-
-type SupportedModel = (typeof supportedModels)[number];
-
-export type ReplicateLlama2Input = {
-  model: SupportedModel;
-  prompt: string;
-  stream?: boolean;
-  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 = {
-  name: "OpenAI ChatCompletion",
-  models: {
-    "7b-chat": {},
-    "13b-chat": {},
-    "70b-chat": {},
-  },
-  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[],
-      },
-      prompt: {
-        type: "string",
-      },
-      stream: {
-        type: "boolean",
-      },
-      max_length: {
-        type: "number",
-      },
-      temperature: {
-        type: "number",
-      },
-      top_p: {
-        type: "number",
-      },
-      repetition_penalty: {
-        type: "number",
-      },
-      debug: {
-        type: "boolean",
-      },
-    },
-    required: ["model", "prompt"],
-  },
-  shouldStream: (input) => input.stream ?? false,
-  getCompletion,
-};
-
-export default modelProvider;

src/modelProviders/types.ts

@@ -2,8 +2,8 @@ import { type JSONSchema4 } from "json-schema";
 import { type JsonValue } from "type-fest";
 
 type ModelProviderModel = {
-  name?: string;
-  learnMore?: string;
+  name: string;
+  learnMore: string;
 };
 
 export type CompletionResponse<T> =

src/pages/experiments/index.tsx

@@ -20,22 +20,25 @@ 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>
     );

src/server/api/routers/experiments.router.ts

@@ -98,7 +98,7 @@ 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,
@@ -109,7 +109,8 @@ export const experimentsRouter = createTRPCRouter({
           constructFn: dedent`
           /**
            * Use Javascript to define an OpenAI chat completion
-           * (https://platform.openai.com/docs/api-reference/chat/create).
+           * (https://platform.openai.com/docs/api-reference/chat/create) and
+           * assign it to the \`prompt\` variable.
            *
            * You have access to the current scenario in the \`scenario\`
            * variable.
@@ -121,7 +122,7 @@ export const experimentsRouter = createTRPCRouter({
             messages: [
               {
                 role: "system",
-                content: \`"Return 'this is output for the scenario "${"$"}{scenario.text}"'\`,
+                content: \`Write 'Start experimenting!' in ${"$"}{scenario.language}\`,
               },
             ],
           });`,
@@ -133,20 +134,38 @@ export const experimentsRouter = createTRPCRouter({
       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;
   }),

src/server/api/routers/promptVariants.router.ts

@@ -284,11 +284,12 @@ 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.string().optional(),
       }),
     )
     .mutation(async ({ input, ctx }) => {
@@ -307,7 +308,7 @@ export const promptVariantsRouter = createTRPCRouter({
 
       const promptConstructionFn = await deriveNewConstructFn(
         existing,
-        constructedPrompt.model as SupportedModel,
+        input.newModel as SupportedModel | undefined,
         input.instructions,
       );
 

src/server/scripts/replicate-test.ts

@@ -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: "3725a659b5afff1a0ba9bead5fac3899d998feaad00e07032ca2b0e35eb14f8a",
-  input: {
-    prompt: "...",
-  },
-});
+// console.log("going to run");
+// const prediction = await replicate.predictions.create({
+//   version: "e951f18578850b652510200860fc4ea62b3b16fac280f83ff32282f87bbd2e48",
+//   input: {
+//     prompt: "...",
+//   },
+// });
 
-console.log("waiting");
-setInterval(() => {
-  replicate.predictions.get(prediction.id).then((prediction) => {
-    console.log(prediction);
-  });
-}, 500);
-// const output = await replicate.wait(prediction, {});
+// console.log("waiting");
+// setInterval(() => {
+//   replicate.predictions.get(prediction.id).then((prediction) => {
+//     console.log(prediction.output);
+//   });
+// }, 500);
+// // const output = await replicate.wait(prediction, {});
 
-// console.log(output);
+// // console.log(output);

src/server/tasks/queryLLM.task.ts

@@ -99,7 +99,6 @@ export const queryLLM = defineTask<queryLLMJob>("queryLLM", async (task) => {
 
   const provider = modelProviders[prompt.modelProvider];
 
-  // @ts-expect-error TODO FIX ASAP
   const streamingChannel = provider.shouldStream(prompt.modelInput) ? generateChannel() : null;
 
   if (streamingChannel) {
@@ -116,8 +115,6 @@ export const queryLLM = defineTask<queryLLMJob>("queryLLM", async (task) => {
     : null;
 
   for (let i = 0; true; i++) {
-    // @ts-expect-error TODO FIX ASAP
-
     const response = await provider.getCompletion(prompt.modelInput, onStream);
     if (response.type === "success") {
       const inputHash = hashPrompt(prompt);

src/server/utils/parseConstructFn.ts

@@ -70,7 +70,6 @@ export default async function parseConstructFn(
     // We've validated the JSON schema so this should be safe
     const input = prompt.input as Parameters<(typeof provider)["getModel"]>[0];
 
-    // @ts-expect-error TODO FIX ASAP
     const model = provider.getModel(input);
     if (!model) {
       return {
@@ -80,8 +79,6 @@ export default async function parseConstructFn(
 
     return {
       modelProvider: prompt.modelProvider as keyof typeof modelProviders,
-      // @ts-expect-error TODO FIX ASAP
-
       model,
       modelInput: input,
     };