Record updated version number

Publish updated README to npm
Update npm lib README
2023-08-31 22:12:29 -07:00 · 2023-08-31 22:09:03 -07:00 · 2023-08-31 21:57:30 -07:00 · 2023-08-31 19:31:28 -07:00 · 2023-08-31 18:49:03 -07:00 · 2023-08-31 18:48:56 -07:00
90 changed files with 2016 additions and 1023 deletions
--- a/.github/ISSUE_TEMPLATE/sweep-fast-template.yml
+++ b/.github/ISSUE_TEMPLATE/sweep-fast-template.yml
@@ -0,0 +1,14 @@
+name: Sweep Fast Issue
+title: 'Sweep (fast): '
+description: For few-line fixes to be handled by Sweep, an AI-powered junior developer. Sweep will use GPT-3.5 to quickly create a PR for very small changes.
+labels: sweep
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: Details
+      description: Tell Sweep where and what to edit and provide enough context for a new developer to the codebase
+      placeholder: |
+        Bugs: The bug might be in ... file. Here are the logs: ...
+        Features: the new endpoint should use the ... class from ... file because it contains ... logic.
+        Refactors: We are migrating this function to ... version because ...
--- a/.github/ISSUE_TEMPLATE/sweep-slow-template.yml
+++ b/.github/ISSUE_TEMPLATE/sweep-slow-template.yml
@@ -0,0 +1,14 @@
+name: Sweep Slow Issue
+title: 'Sweep (slow): '
+description: For larger bugs, features, refactors, and tests to be handled by Sweep, an AI-powered junior developer. Sweep will perform a deeper search and more self-reviews but will take longer.
+labels: sweep
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: Details
+      description: Tell Sweep where and what to edit and provide enough context for a new developer to the codebase
+      placeholder: |
+        Bugs: The bug might be in ... file. Here are the logs: ...
+        Features: the new endpoint should use the ... class from ... file because it contains ... logic.
+        Refactors: We are migrating this function to ... version because ...
--- a/.github/ISSUE_TEMPLATE/sweep-template.yml
+++ b/.github/ISSUE_TEMPLATE/sweep-template.yml
@@ -0,0 +1,14 @@
+name: Sweep Issue
+title: 'Sweep: '
+description: For small bugs, features, refactors, and tests to be handled by Sweep, an AI-powered junior developer.
+labels: sweep
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: Details
+      description: Tell Sweep where and what to edit and provide enough context for a new developer to the codebase
+      placeholder: |
+        Bugs: The bug might be in ... file. Here are the logs: ...
+        Features: the new endpoint should use the ... class from ... file because it contains ... logic.
+        Refactors: We are migrating this function to ... version because ...
--- a/app/LICENSE
+++ b/app/LICENSE
--- a/README.md
+++ b/README.md
@@ -1,14 +1,53 @@
-# OpenPipe
+ <p align="center">
+  <a href="https://openpipe.ai">
+    <img height="70" src="https://github.com/openpipe/openpipe/assets/41524992/70af25fb-1f90-42d9-8a20-3606e3b5aaba" alt="logo">
+  </a>
+</p>
+<h1 align="center">
+  OpenPipe
+</h1>

-OpenPipe is a flexible playground for comparing and optimizing LLM prompts. It lets you quickly generate, test and compare candidate prompts, and can automatically [translate](#-translate-between-model-apis) those prompts between models.
+<p align="center">
+  <i>Turn expensive prompts into cheap fine-tuned models.</i>
+</p>

-<img src="https://github.com/openpipe/openpipe/assets/41524992/66bb1843-cb72-4130-a369-eec2df3b8201" alt="demo">
+<p align="center">
+  <a href="/LICENSE"><img alt="License Apache-2.0" src="https://img.shields.io/github/license/openpipe/openpipe?style=flat-square"></a>
+  <a href='http://makeapullrequest.com'><img alt='PRs Welcome' src='https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square'/></a>
+  <a href="https://github.com/openpipe/openpipe/graphs/commit-activity"><img alt="GitHub commit activity" src="https://img.shields.io/github/commit-activity/m/openpipe/openpipe?style=flat-square"/></a>
+  <a href="https://github.com/openpipe/openpipe/issues"><img alt="GitHub closed issues" src="https://img.shields.io/github/issues-closed/openpipe/openpipe?style=flat-square"/></a>
+ <img src="https://img.shields.io/badge/Y%20Combinator-S23-orange?style=flat-square" alt="Y Combinator S23">
+</p>
+
+<p align="center">
+  <a href="https://app.openpipe.ai/">Hosted App</a> - <a href="#running-locally">Running Locally</a> - <a href="#sample-experiments">Experiments</a>
+</p>
+
+<br>
+Use powerful but expensive LLMs to fine-tune smaller and cheaper models suited to your exact needs. Evaluate model and prompt combinations in the playground. Query your past requests and export optimized training data. Try it out at https://app.openpipe.ai or <a href="#running-locally">run it locally</a>.
+<br>
+
+
+## Features
+
+ * <b>Experiment</b>
+   * Bulk-test wide-reaching scenarios using code templating.
+   * Seamlessly translate prompts across different model APIs.
+   * Tap into autogenerated scenarios for fresh test perspectives.
+
+ * <b>Fine-Tune (Beta)</b>
+   * Easy integration with OpenPipe's SDK in both Python and JS.
+   * Swiftly query logs using intuitive built-in filters.
+   * Export data in multiple training formats, including Alpaca and ChatGPT, with deduplication.
+   
+<img src="https://github.com/openpipe/openpipe/assets/41524992/eaa8b92d-4536-4f63-bbef-4b0b1a60f6b5" alt="fine-tune demo">
+
+<!-- <img height="400px" src="https://github.com/openpipe/openpipe/assets/41524992/66bb1843-cb72-4130-a369-eec2df3b8201" alt="playground demo"> -->

-You can use our hosted version of OpenPipe at https://openpipe.ai. You can also clone this repository and [run it locally](#running-locally).

 ## Sample Experiments

-These are simple experiments users have created that show how OpenPipe works. Feel free to fork them and start experimenting yourself.
+These are sample experiments users have created that show how OpenPipe works. Feel free to fork them and start experimenting yourself.

 - [Twitter Sentiment Analysis](https://app.openpipe.ai/experiments/62c20a73-2012-4a64-973c-4b665ad46a57)
 - [Reddit User Needs](https://app.openpipe.ai/experiments/22222222-2222-2222-2222-222222222222)
@@ -17,37 +56,25 @@ These are simple experiments users have created that show how OpenPipe works. Fe

 ## Supported Models

- 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).
- Anthropic's [Claude 1 Instant](https://www.anthropic.com/index/introducing-claude) and [Claude 2](https://www.anthropic.com/index/claude-2)
-
-## Features
-
-### 🔍 Visualize Responses
-
-Inspect prompt completions side-by-side.
-
-### 🧪 Bulk-Test
-
-OpenPipe lets you _template_ a prompt. Use the templating feature to run the prompts you're testing against many potential inputs for broad coverage of your problem space.
-
-### 📟 Translate between Model APIs
-
-Write your prompt in one format and automatically convert it to work with any other model.
-
-<!-- <img width="480" alt="Screenshot 2023-08-01 at 11 55 38 PM" src="https://github.com/OpenPipe/OpenPipe/assets/41524992/1e19ccf2-96b6-4e93-a3a5-1449710d1b5b" alt="translate between models"> -->
-
-### 🛠️ Refine Your Prompts Automatically
-
-Use a growing database of best-practice refinements to improve your prompts automatically.
-
-<!-- <img width="480" alt="Screenshot 2023-08-01 at 11 55 38 PM" src="https://github.com/OpenPipe/OpenPipe/assets/41524992/87a27fe7-daef-445c-a5e2-1c82b23f9f99" alt="add function call"> -->
-
-### 🪄 Auto-generate Test Scenarios
-
-OpenPipe includes a tool to generate new test scenarios based on your existing prompts and scenarios. Just click "Autogenerate Scenario" to try it out!
-
-<!-- <img width="600" src="https://github.com/openpipe/openpipe/assets/41524992/219a844e-3f4e-4f6b-8066-41348b42977b" alt="auto-generate"> -->
+#### OpenAI
+  - [GPT 3.5 Turbo](https://platform.openai.com/docs/guides/gpt/chat-completions-api)
+  - [GPT 3.5 Turbo 16k](https://platform.openai.com/docs/guides/gpt/chat-completions-api)
+  - [GPT 4](https://openai.com/gpt-4)
+#### 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)
+#### Llama2 Fine-Tunes
+  - [Open-Orca/OpenOrcaxOpenChat-Preview2-13B](https://huggingface.co/Open-Orca/OpenOrcaxOpenChat-Preview2-13B)
+  - [Open-Orca/OpenOrca-Platypus2-13B](https://huggingface.co/Open-Orca/OpenOrca-Platypus2-13B)
+  - [NousResearch/Nous-Hermes-Llama2-13b](https://huggingface.co/NousResearch/Nous-Hermes-Llama2-13b)
+  - [jondurbin/airoboros-l2-13b-gpt4-2.0](https://huggingface.co/jondurbin/airoboros-l2-13b-gpt4-2.0)
+  - [lmsys/vicuna-13b-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5)
+  - [Gryphe/MythoMax-L2-13b](https://huggingface.co/Gryphe/MythoMax-L2-13b)
+  - [NousResearch/Nous-Hermes-llama-2-7b](https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b)
+#### Anthropic
+  - [Claude 1 Instant](https://www.anthropic.com/index/introducing-claude)
+  - [Claude 2](https://www.anthropic.com/index/claude-2)

 ## Running Locally

--- a/app/package.json
+++ b/app/package.json
@@ -79,7 +79,8 @@
    "nextjs-routes": "^2.0.1",
    "nodemailer": "^6.9.4",
    "openai": "4.0.0-beta.7",
-    "openpipe": "workspace:*",
+    "openpipe": "^0.3.0",
+    "openpipe-dev": "workspace:^",
    "pg": "^8.11.2",
    "pluralize": "^8.0.0",
    "posthog-js": "^1.75.3",
--- a/app/prisma/deleteOneFineTune.ts
+++ b/app/prisma/deleteOneFineTune.ts
@@ -0,0 +1,12 @@
+import { prisma } from "~/server/db";
+
+// delete most recent fineTune
+const mostRecentFineTune = await prisma.fineTune.findFirst({
+  orderBy: { createdAt: "desc" },
+});
+
+if (mostRecentFineTune) {
+  await prisma.fineTune.delete({
+    where: { id: mostRecentFineTune.id },
+  });
+}
--- a/app/prisma/seedDashboard.ts
+++ b/app/prisma/seedDashboard.ts
@@ -80,7 +80,7 @@ const MODEL_RESPONSE_TEMPLATES: {
    },
    respStatus: 200,
    respPayload: {
-      id: "chatcmpl-7lNspqePJWVyXwXebupxb1eMozo6Q",
+      id: "chatcmpl-7",
      model: "gpt-3.5-turbo-0613",
      usage: {
        total_tokens: 241,
@@ -108,7 +108,7 @@ const MODEL_RESPONSE_TEMPLATES: {
    inputTokens: 236,
    outputTokens: 5,
    finishReason: "stop",
-    tags: [],
+    tags: [{ name: "prompt_id", value: "define_func" }],
  },
  {
    reqPayload: {
@@ -167,7 +167,7 @@ const MODEL_RESPONSE_TEMPLATES: {
    },
    respStatus: 200,
    respPayload: {
-      id: "chatcmpl-7lNifmc5AncyAvleZRDBhAcLFYBIT",
+      id: "chatcmpl-7",
      model: "gpt-3.5-turbo-0613",
      usage: {
        total_tokens: 227,
@@ -210,7 +210,7 @@ const MODEL_RESPONSE_TEMPLATES: {
    },
    respStatus: 200,
    respPayload: {
-      id: "chatcmpl-7lNh1TtrsJVgz3Nj70bKkZZk7xPi7",
+      id: "chatcmpl-7",
      model: "gpt-3.5-turbo-0613",
      usage: {
        total_tokens: 21,
@@ -234,7 +234,7 @@ const MODEL_RESPONSE_TEMPLATES: {
    inputTokens: 14,
    outputTokens: 7,
    finishReason: "stop",
-    tags: [{ name: "prompt_id", value: "id2" }],
+    tags: [{ name: "prompt_id", value: "translate_text" }],
  },
  {
    reqPayload: {
@@ -281,7 +281,7 @@ const MODEL_RESPONSE_TEMPLATES: {
    },
    respStatus: 200,
    respPayload: {
-      id: "chatcmpl-7lQS3MktOT8BTgNEytl9dkyssCQqL",
+      id: "chatcmpl-7",
      model: "gpt-4-0613",
      usage: {
        total_tokens: 2910,
@@ -311,7 +311,7 @@ const MODEL_RESPONSE_TEMPLATES: {
    outputTokens: 108,
    finishReason: "stop",
    tags: [
-      { name: "prompt_id", value: "chatcmpl-7lQS3MktOT8BTgNEytl9dkyssCQqL" },
+      { name: "prompt_id", value: "chatcmpl-7" },
      { name: "some_other_tag", value: "some_other_value" },
    ],
  },
@@ -339,7 +339,7 @@ const loggedCallsToCreate: Prisma.LoggedCallCreateManyInput[] = [];
 const loggedCallModelResponsesToCreate: Prisma.LoggedCallModelResponseCreateManyInput[] = [];
 const loggedCallsToUpdate: Prisma.LoggedCallUpdateArgs[] = [];
 const loggedCallTagsToCreate: Prisma.LoggedCallTagCreateManyInput[] = [];
-for (let i = 0; i < 1437; i++) {
+for (let i = 0; i < 11437; i++) {
  const loggedCallId = uuidv4();
  const loggedCallModelResponseId = uuidv4();
  const template =
--- a/app/src/components/nav/BetaModal.tsx
+++ b/app/src/components/nav/BetaModal.tsx
@@ -13,19 +13,17 @@ import {
  Link,
 } from "@chakra-ui/react";
 import { BsStars } from "react-icons/bs";
-import { useRouter } from "next/router";
 import { useSession } from "next-auth/react";

-export const BetaModal = () => {
-  const router = useRouter();
+export const BetaModal = ({ isOpen, onClose }: { isOpen: boolean; onClose: () => void }) => {
  const session = useSession();

  const email = session.data?.user.email ?? "";

  return (
    <Modal
-      isOpen
-      onClose={router.back}
+      isOpen={isOpen}
+      onClose={onClose}
      closeOnOverlayClick={false}
      size={{ base: "xl", md: "2xl" }}
    >
@@ -56,7 +54,7 @@ export const BetaModal = () => {
            >
              Join Waitlist
            </Button>
-            <Button colorScheme="blue" onClick={router.back}>
+            <Button colorScheme="blue" onClick={onClose}>
              Done
            </Button>
          </HStack>
--- a/app/src/components/ChangeModelModal/ChangeModelModal.tsx
+++ b/app/src/components/ChangeModelModal/ChangeModelModal.tsx
@@ -1,3 +1,4 @@
+import { useState, useMemo, useCallback } from "react";
 import {
  Button,
  HStack,
@@ -14,16 +15,18 @@ import {
  VStack,
 } from "@chakra-ui/react";
 import { type PromptVariant } from "@prisma/client";
-import { isObject, isString } from "lodash-es";
-import { useState } from "react";
+import { isString } from "lodash-es";
 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 { useExperiment, useHandledAsyncCallback } from "~/utils/hooks";
 import { lookupModel, modelLabel } from "~/utils/utils";
 import CompareFunctions from "../RefinePromptModal/CompareFunctions";
 import { ModelSearch } from "./ModelSearch";
 import { ModelStatsCard } from "./ModelStatsCard";
+import { maybeReportError } from "~/utils/errorHandling/maybeReportError";
+import { useAppStore } from "~/state/store";

 export const ChangeModelModal = ({
  variant,
@@ -32,48 +35,43 @@ export const ChangeModelModal = ({
  variant: PromptVariant;
  onClose: () => void;
 }) => {
+  const editorOptionsMap = useAppStore((s) => s.sharedVariantEditor.editorOptionsMap);
+  const originalPromptFn = useMemo(
+    () => editorOptionsMap[variant.uiId]?.getContent() || "",
+    [editorOptionsMap, variant.uiId],
+  );
+
  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 [modifiedPromptFn, setModifiedPromptFn] = useState<string>();

  const experiment = useExperiment();

-  const { mutateAsync: getModifiedPromptMutateAsync, data: modifiedPromptFn } =
+  const { mutateAsync: getModifiedPromptMutateAsync } =
    api.promptVariants.getModifiedPromptFn.useMutation();

  const [getModifiedPromptFn, modificationInProgress] = useHandledAsyncCallback(async () => {
    if (!experiment) return;

-    await getModifiedPromptMutateAsync({
+    const resp = await getModifiedPromptMutateAsync({
      id: variant.id,
+      originalPromptFn,
      newModel: selectedModel,
    });
+    if (maybeReportError(resp)) return;
+    setModifiedPromptFn(resp.payload);
    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,
-      promptConstructor: modifiedPromptFn,
-      streamScenarios: visibleScenarios,
-    });
-    await utils.promptVariants.list.invalidate();
+  const replaceVariant = useCallback(() => {
+    if (!modifiedPromptFn) return;
+    editorOptionsMap[variant.uiId]?.setContent(modifiedPromptFn);
    onClose();
-  }, [replaceVariantMutation, variant, onClose, modifiedPromptFn]);
+  }, [variant.uiId, editorOptionsMap, onClose, modifiedPromptFn]);

  const originalLabel = modelLabel(variant.modelProvider, variant.model);
  const selectedLabel = modelLabel(selectedModel.provider, selectedModel.model);
@@ -130,9 +128,9 @@ export const ChangeModelModal = ({
              colorScheme="blue"
              onClick={replaceVariant}
              minW={24}
-              isDisabled={!convertedModel || modificationInProgress || replacementInProgress}
+              isDisabled={!convertedModel || modificationInProgress}
            >
-              {replacementInProgress ? <Spinner boxSize={4} /> : <Text>Accept</Text>}
+              Accept
            </Button>
          </HStack>
        </ModalFooter>
--- a/app/src/components/ExperimentSettingsDrawer/DeleteButton.tsx
+++ b/app/src/components/ExperimentSettingsDrawer/DeleteButton.tsx
@@ -1,74 +1,41 @@
-import {
-  Button,
-  Icon,
-  AlertDialog,
-  AlertDialogBody,
-  AlertDialogFooter,
-  AlertDialogHeader,
-  AlertDialogContent,
-  AlertDialogOverlay,
-  useDisclosure,
-  Text,
-} from "@chakra-ui/react";
-
+import { Button, Icon, useDisclosure, Text } from "@chakra-ui/react";
 import { useRouter } from "next/router";
-import { useRef } from "react";
 import { BsTrash } from "react-icons/bs";
+
 import { useAppStore } from "~/state/store";
-import { api } from "~/utils/api";
 import { useExperiment, useHandledAsyncCallback } from "~/utils/hooks";
+import DeleteExperimentDialog from "../experiments/DeleteExperimentDialog";

 export const DeleteButton = () => {
  const experiment = useExperiment();
-  const mutation = api.experiments.delete.useMutation();
-  const utils = api.useContext();
  const router = useRouter();

+  const disclosure = useDisclosure();
+
  const closeDrawer = useAppStore((s) => s.closeDrawer);
-
-  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();
+  const [onDelete] = useHandledAsyncCallback(async () => {
    await router.push({ pathname: "/experiments" });
    closeDrawer();
-
-    onClose();
-  }, [mutation, experiment.data?.id, router]);
+  }, [router, closeDrawer]);

  return (
    <>
-      <Button size="sm" variant="ghost" colorScheme="red" fontWeight="normal" onClick={onOpen}>
+      <Button
+        size="sm"
+        variant="ghost"
+        colorScheme="red"
+        fontWeight="normal"
+        onClick={disclosure.onOpen}
+      >
        <Icon as={BsTrash} boxSize={4} />
        <Text 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>
+      <DeleteExperimentDialog
+        experimentId={experiment.data?.id}
+        onDelete={onDelete}
+        disclosure={disclosure}
+      />
    </>
  );
 };
--- a/app/src/components/OutputsTable/OutputCell/OutputCell.tsx
+++ b/app/src/components/OutputsTable/OutputCell/OutputCell.tsx
@@ -147,9 +147,10 @@ export default function OutputCell({
                <ResponseLog
                  time={response.receivedAt}
                  title="Response received from API"
-                  message={`statusCode: ${response.statusCode ?? ""}\n ${
-                    response.errorMessage ?? ""
-                  }`}
+                  message={[
+                    response.statusCode ? `Status: ${response.statusCode}\n` : "",
+                    response.errorMessage ?? "",
+                  ].join("")}
                />
              )}
            </Fragment>
--- a/app/src/components/OutputsTable/VariantEditor.tsx
+++ b/app/src/components/OutputsTable/VariantEditor.tsx
@@ -10,7 +10,7 @@ import {
 } from "@chakra-ui/react";
 import { useCallback, useEffect, useRef, useState } from "react";
 import { FiMaximize, FiMinimize } from "react-icons/fi";
-import { editorBackground } from "~/state/sharedVariantEditor.slice";
+import { type CreatedEditor, editorBackground } from "~/state/sharedVariantEditor.slice";
 import { useAppStore } from "~/state/store";
 import { api } from "~/utils/api";
 import {
@@ -24,8 +24,10 @@ import { type PromptVariant } from "./types";
 export default function VariantEditor(props: { variant: PromptVariant }) {
  const { canModify } = useExperimentAccess();
  const monaco = useAppStore.use.sharedVariantEditor.monaco();
-  const editorRef = useRef<ReturnType<NonNullable<typeof monaco>["editor"]["create"]> | null>(null);
+  const updateOptionsForEditor = useAppStore.use.sharedVariantEditor.updateOptionsForEditor();
+  const editorRef = useRef<CreatedEditor | null>(null);
  const containerRef = useRef<HTMLDivElement | null>(null);
+  const lastSavedFnRef = useRef(props.variant.promptConstructor);
  const [editorId] = useState(() => `editor_${Math.random().toString(36).substring(7)}`);
  const [isChanged, setIsChanged] = useState(false);

@@ -48,22 +50,18 @@ export default function VariantEditor(props: { variant: PromptVariant }) {
  }, [isFullscreen, toggleFullscreen]);

  const lastSavedFn = props.variant.promptConstructor;
+  useEffect(() => {
+    // Store in ref so that we can access it dynamically
+    lastSavedFnRef.current = lastSavedFn;
+  }, [lastSavedFn]);

  const modifierKey = useModifierKeyLabel();

  const checkForChanges = useCallback(() => {
    if (!editorRef.current) return;
    const currentFn = editorRef.current.getValue();
-    setIsChanged(currentFn.length > 0 && currentFn !== lastSavedFn);
-  }, [lastSavedFn]);
-
-  const matchUpdatedSavedFn = useCallback(() => {
-    if (!editorRef.current) return;
-    editorRef.current.setValue(lastSavedFn);
-    setIsChanged(false);
-  }, [lastSavedFn]);
-
-  useEffect(matchUpdatedSavedFn, [matchUpdatedSavedFn, lastSavedFn]);
+    setIsChanged(currentFn.length > 0 && currentFn !== lastSavedFnRef.current);
+  }, [editorRef]);

  const replaceVariant = api.promptVariants.replaceVariant.useMutation();
  const utils = api.useContext();
@@ -136,6 +134,11 @@ export default function VariantEditor(props: { variant: PromptVariant }) {
        readOnly: !canModify,
      });

+      updateOptionsForEditor(props.variant.uiId, {
+        getContent: () => editorRef.current?.getValue() || "",
+        setContent: (content) => editorRef.current?.setValue(content),
+      });
+
      // 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
@@ -155,7 +158,7 @@ export default function VariantEditor(props: { variant: PromptVariant }) {
        });
      });

-      editorRef.current.onDidChangeModelContent(checkForChanges);
+      const checkForChangesListener = editorRef.current.onDidChangeModelContent(checkForChanges);

      const resizeObserver = new ResizeObserver(() => {
        editorRef.current?.layout();
@@ -164,6 +167,7 @@ export default function VariantEditor(props: { variant: PromptVariant }) {

      return () => {
        resizeObserver.disconnect();
+        checkForChangesListener.dispose();
        editorRef.current?.dispose();
      };
    }
@@ -171,7 +175,7 @@ export default function VariantEditor(props: { variant: PromptVariant }) {
    // We intentionally skip the onSave and props.savedConfig dependencies here because
    // we don't want to re-render the editor from scratch
    /* eslint-disable-next-line react-hooks/exhaustive-deps */
-  }, [monaco, editorId]);
+  }, [monaco, editorId, updateOptionsForEditor]);

  useEffect(() => {
    if (!editorRef.current) return;
--- a/app/src/components/RefinePromptModal/RefinePromptModal.tsx
+++ b/app/src/components/RefinePromptModal/RefinePromptModal.tsx
@@ -1,3 +1,4 @@
+import { useState, useMemo, useCallback } from "react";
 import {
  Button,
  Modal,
@@ -9,22 +10,23 @@ import {
  ModalOverlay,
  VStack,
  Text,
-  Spinner,
  HStack,
  Icon,
  SimpleGrid,
 } from "@chakra-ui/react";
 import { BsStars } from "react-icons/bs";
 import { api } from "~/utils/api";
-import { useHandledAsyncCallback, useVisibleScenarioIds } from "~/utils/hooks";
+import { useHandledAsyncCallback } from "~/utils/hooks";
 import { type PromptVariant } from "@prisma/client";
-import { useState } from "react";
+
 import CompareFunctions from "./CompareFunctions";
 import { CustomInstructionsInput } from "../CustomInstructionsInput";
 import { RefineAction } from "./RefineAction";
-import { isObject, isString } from "lodash-es";
+import { isString } from "lodash-es";
 import { type RefinementAction, type SupportedProvider } from "~/modelProviders/types";
 import frontendModelProviders from "~/modelProviders/frontendModelProviders";
+import { useAppStore } from "~/state/store";
+import { maybeReportError } from "~/utils/errorHandling/maybeReportError";

 export const RefinePromptModal = ({
  variant,
@@ -33,19 +35,23 @@ export const RefinePromptModal = ({
  variant: PromptVariant;
  onClose: () => void;
 }) => {
-  const utils = api.useContext();
-  const visibleScenarios = useVisibleScenarioIds();
+  const editorOptionsMap = useAppStore((s) => s.sharedVariantEditor.editorOptionsMap);
+  const originalPromptFn = useMemo(
+    () => editorOptionsMap[variant.uiId]?.getContent() || "",
+    [editorOptionsMap, variant.uiId],
+  );

  const refinementActions =
    frontendModelProviders[variant.modelProvider as SupportedProvider].refinementActions || {};

-  const { mutateAsync: getModifiedPromptMutateAsync, data: refinedPromptFn } =
+  const { mutateAsync: getModifiedPromptMutateAsync } =
    api.promptVariants.getModifiedPromptFn.useMutation();
  const [instructions, setInstructions] = useState<string>("");

  const [activeRefineActionLabel, setActiveRefineActionLabel] = useState<string | undefined>(
    undefined,
  );
+  const [refinedPromptFn, setRefinedPromptFn] = useState<string>();

  const [getModifiedPromptFn, modificationInProgress] = useHandledAsyncCallback(
    async (label?: string) => {
@@ -54,31 +60,22 @@ export const RefinePromptModal = ({
        ? (refinementActions[label] as RefinementAction).instructions
        : instructions;
      setActiveRefineActionLabel(label);
-      await getModifiedPromptMutateAsync({
+      const resp = await getModifiedPromptMutateAsync({
        id: variant.id,
+        originalPromptFn,
        instructions: updatedInstructions,
      });
+      if (maybeReportError(resp)) return;
+      setRefinedPromptFn(resp.payload);
    },
    [getModifiedPromptMutateAsync, onClose, variant, instructions, setActiveRefineActionLabel],
  );

-  const replaceVariantMutation = api.promptVariants.replaceVariant.useMutation();
-
-  const [replaceVariant, replacementInProgress] = useHandledAsyncCallback(async () => {
-    if (
-      !variant.experimentId ||
-      !refinedPromptFn ||
-      (isObject(refinedPromptFn) && "status" in refinedPromptFn)
-    )
-      return;
-    await replaceVariantMutation.mutateAsync({
-      id: variant.id,
-      promptConstructor: refinedPromptFn,
-      streamScenarios: visibleScenarios,
-    });
-    await utils.promptVariants.list.invalidate();
+  const replaceVariant = useCallback(() => {
+    if (!refinedPromptFn) return;
+    editorOptionsMap[variant.uiId]?.setContent(refinedPromptFn);
    onClose();
-  }, [replaceVariantMutation, variant, onClose, refinedPromptFn]);
+  }, [variant.uiId, editorOptionsMap, onClose, refinedPromptFn]);

  return (
    <Modal
@@ -126,7 +123,7 @@ export const RefinePromptModal = ({
              />
            </VStack>
            <CompareFunctions
-              originalFunction={variant.promptConstructor}
+              originalFunction={originalPromptFn}
              newFunction={isString(refinedPromptFn) ? refinedPromptFn : undefined}
              maxH="40vh"
            />
@@ -139,9 +136,9 @@ export const RefinePromptModal = ({
              colorScheme="blue"
              onClick={replaceVariant}
              minW={24}
-              isDisabled={replacementInProgress || !refinedPromptFn}
+              isDisabled={!refinedPromptFn}
            >
-              {replacementInProgress ? <Spinner boxSize={4} /> : <Text>Accept</Text>}
+              Accept
            </Button>
          </HStack>
        </ModalFooter>
--- a/app/src/components/StatsCard.tsx
+++ b/app/src/components/StatsCard.tsx
@@ -1,26 +0,0 @@
-import { VStack, HStack, type StackProps, Text, Divider } from "@chakra-ui/react";
-import Link, { type LinkProps } from "next/link";
-
-const StatsCard = ({
-  title,
-  href,
-  children,
-  ...rest
-}: { title: string; href: string } & StackProps & LinkProps) => {
-  return (
-    <VStack flex={1} borderWidth={1} padding={4} borderRadius={4} borderColor="gray.300" {...rest}>
-      <HStack w="full" justifyContent="space-between">
-        <Text fontSize="md" fontWeight="bold">
-          {title}
-        </Text>
-        <Link href={href}>
-          <Text color="blue">View all</Text>
-        </Link>
-      </HStack>
-      <Divider />
-      {children}
-    </VStack>
-  );
-};
-
-export default StatsCard;
--- a/app/src/components/dashboard/LoggedCallsTable.tsx
+++ b/app/src/components/dashboard/LoggedCallsTable.tsx
@@ -2,11 +2,12 @@ import { Card, CardHeader, Heading, Table, Tbody, HStack, Button, Text } from "@
 import { useState } from "react";
 import Link from "next/link";
 import { useLoggedCalls } from "~/utils/hooks";
-import { TableHeader, TableRow } from "../requestLogs/TableRow";
+import { EmptyTableRow, TableHeader, TableRow } from "../requestLogs/TableRow";

 export default function LoggedCallsTable() {
+  const { data: loggedCalls } = useLoggedCalls(false);
+
  const [expandedRow, setExpandedRow] = useState<string | null>(null);
-  const { data: loggedCalls } = useLoggedCalls();

  return (
    <Card width="100%" overflow="hidden">
@@ -23,22 +24,26 @@ export default function LoggedCallsTable() {
      <Table>
        <TableHeader />
        <Tbody>
-          {loggedCalls?.calls.map((loggedCall) => {
-            return (
-              <TableRow
-                key={loggedCall.id}
-                loggedCall={loggedCall}
-                isExpanded={loggedCall.id === expandedRow}
-                onToggle={() => {
-                  if (loggedCall.id === expandedRow) {
-                    setExpandedRow(null);
-                  } else {
-                    setExpandedRow(loggedCall.id);
-                  }
-                }}
-              />
-            );
-          })}
+          {loggedCalls?.calls.length ? (
+            loggedCalls?.calls.map((loggedCall) => {
+              return (
+                <TableRow
+                  key={loggedCall.id}
+                  loggedCall={loggedCall}
+                  isExpanded={loggedCall.id === expandedRow}
+                  onToggle={() => {
+                    if (loggedCall.id === expandedRow) {
+                      setExpandedRow(null);
+                    } else {
+                      setExpandedRow(loggedCall.id);
+                    }
+                  }}
+                />
+              );
+            })
+          ) : (
+            <EmptyTableRow filtersApplied={false} />
+          )}
        </Tbody>
      </Table>
    </Card>
--- a/app/src/components/experiments/DeleteExperimentDialog.tsx
+++ b/app/src/components/experiments/DeleteExperimentDialog.tsx
@@ -0,0 +1,66 @@
+import { useRef } from "react";
+import {
+  type UseDisclosureReturn,
+  AlertDialog,
+  AlertDialogOverlay,
+  AlertDialogContent,
+  AlertDialogHeader,
+  AlertDialogBody,
+  AlertDialogFooter,
+  Button,
+} from "@chakra-ui/react";
+import { api } from "~/utils/api";
+
+import { useHandledAsyncCallback } from "~/utils/hooks";
+
+const DeleteExperimentDialog = ({
+  experimentId,
+  onDelete,
+  disclosure,
+}: {
+  experimentId?: string;
+  onDelete?: () => void;
+  disclosure: UseDisclosureReturn;
+}) => {
+  const cancelRef = useRef<HTMLButtonElement>(null);
+
+  const mutation = api.experiments.delete.useMutation();
+  const utils = api.useContext();
+
+  const [onDeleteConfirm] = useHandledAsyncCallback(async () => {
+    if (!experimentId) return;
+    await mutation.mutateAsync({ id: experimentId });
+    await utils.experiments.list.invalidate();
+    onDelete?.();
+
+    disclosure.onClose();
+  }, [mutation, experimentId, disclosure.onClose]);
+
+  return (
+    <AlertDialog leastDestructiveRef={cancelRef} {...disclosure}>
+      <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={disclosure.onClose}>
+              Cancel
+            </Button>
+            <Button colorScheme="red" onClick={onDeleteConfirm} ml={3}>
+              Delete
+            </Button>
+          </AlertDialogFooter>
+        </AlertDialogContent>
+      </AlertDialogOverlay>
+    </AlertDialog>
+  );
+};
+
+export default DeleteExperimentDialog;
--- a/app/src/components/experiments/ExperimentCard.tsx
+++ b/app/src/components/experiments/ExperimentCard.tsx
@@ -1,3 +1,4 @@
+import { type MouseEvent, useState } from "react";
 import {
  HStack,
  Icon,
@@ -8,17 +9,29 @@ import {
  AspectRatio,
  SkeletonText,
  Card,
+  useDisclosure,
+  Box,
+  Menu,
+  MenuButton,
+  MenuList,
+  MenuItem,
+  IconButton,
+  useToast,
 } from "@chakra-ui/react";
 import { RiFlaskLine } from "react-icons/ri";
-import { formatTimePast } from "~/utils/dayjs";
 import Link from "next/link";
 import { useRouter } from "next/router";
-import { BsPlusSquare } from "react-icons/bs";
-import { RouterOutputs, api } from "~/utils/api";
+import { BsPlusSquare, BsThreeDotsVertical, BsLink45Deg, BsTrash } from "react-icons/bs";
+
+import { formatTimePast } from "~/utils/dayjs";
+import { type RouterOutputs, api } from "~/utils/api";
 import { useHandledAsyncCallback } from "~/utils/hooks";
 import { useAppStore } from "~/state/store";
+import DeleteExperimentDialog from "./DeleteExperimentDialog";

 export const ExperimentCard = ({ exp }: { exp: RouterOutputs["experiments"]["list"][0] }) => {
+  const [isMenuHovered, setIsMenuHovered] = useState(false);
+
  return (
    <Card
      w="full"
@@ -27,7 +40,7 @@ export const ExperimentCard = ({ exp }: { exp: RouterOutputs["experiments"]["lis
      p={4}
      bg="white"
      borderRadius={4}
-      _hover={{ bg: "gray.100" }}
+      _hover={{ bg: isMenuHovered ? undefined : "gray.100" }}
      transition="background 0.2s"
      aspectRatio={1.2}
    >
@@ -38,9 +51,17 @@ export const ExperimentCard = ({ exp }: { exp: RouterOutputs["experiments"]["lis
        href={{ pathname: "/experiments/[experimentSlug]", query: { experimentSlug: exp.slug } }}
        justify="space-between"
      >
-        <HStack w="full" color="gray.700" justify="center">
-          <Icon as={RiFlaskLine} boxSize={4} />
-          <Text fontWeight="bold">{exp.label}</Text>
+        <HStack w="full" justify="space-between" spacing={0}>
+          <Box w={6} />
+          <HStack color="gray.700" justify="center">
+            <Icon as={RiFlaskLine} boxSize={4} />
+            <Text fontWeight="bold">{exp.label}</Text>
+          </HStack>
+          <CardMenu
+            experimentId={exp.id}
+            experimentSlug={exp.slug}
+            setIsMenuHovered={setIsMenuHovered}
+          />
        </HStack>
        <HStack h="full" spacing={4} flex={1} align="center">
          <CountLabel label="Variants" count={exp.promptVariantCount} />
@@ -57,6 +78,75 @@ export const ExperimentCard = ({ exp }: { exp: RouterOutputs["experiments"]["lis
  );
 };

+const CardMenu = ({
+  experimentId,
+  experimentSlug,
+  setIsMenuHovered,
+}: {
+  experimentId: string;
+  experimentSlug: string;
+  setIsMenuHovered: (isHovered: boolean) => void;
+}) => {
+  const deleteDisclosure = useDisclosure();
+  const menuDisclosure = useDisclosure();
+  const toast = useToast();
+  const [copyShareLink] = useHandledAsyncCallback(
+    async (e: MouseEvent<HTMLButtonElement>) => {
+      if (typeof window === "undefined") return;
+      e.preventDefault();
+      e.stopPropagation();
+      const shareLink = `${window.location.origin}/experiments/${experimentSlug}`;
+      await navigator.clipboard.writeText(shareLink);
+      toast({
+        title: "Share link copied to clipboard",
+        status: "success",
+        duration: 2000,
+        isClosable: true,
+      });
+      menuDisclosure.onClose();
+    },
+    [toast, menuDisclosure.onClose, experimentSlug],
+  );
+  return (
+    <>
+      <Menu isLazy {...menuDisclosure}>
+        <MenuButton
+          as={IconButton}
+          aria-label="Options"
+          icon={<BsThreeDotsVertical />}
+          variant="ghost"
+          onClick={(e) => {
+            e.preventDefault();
+            e.stopPropagation();
+            menuDisclosure.onOpen();
+          }}
+          onMouseEnter={() => setIsMenuHovered(true)}
+          onMouseLeave={() => setIsMenuHovered(false)}
+          boxSize={6}
+          minW={0}
+        />
+        <MenuList>
+          <MenuItem icon={<Icon as={BsLink45Deg} boxSize={5} />} onClick={copyShareLink}>
+            Copy Link
+          </MenuItem>
+          <MenuItem
+            icon={<Icon as={BsTrash} boxSize={5} />}
+            onClick={(e) => {
+              e.preventDefault();
+              e.stopPropagation();
+              deleteDisclosure.onOpen();
+            }}
+            color="red.500"
+          >
+            Delete
+          </MenuItem>
+        </MenuList>
+      </Menu>
+      <DeleteExperimentDialog experimentId={experimentId} disclosure={deleteDisclosure} />
+    </>
+  );
+};
+
 const CountLabel = ({ label, count }: { label: string; count: number }) => {
  return (
    <VStack alignItems="center" flex={1}>
@@ -98,9 +188,7 @@ export const NewExperimentCard = () => {
    >
      <VStack align="center" justify="center" w="full" h="full" p={4} onClick={createExperiment}>
        <Icon as={isLoading ? Spinner : BsPlusSquare} boxSize={8} />
-        <Text display={{ base: "none", md: "block" }} ml={2}>
-          New Experiment
-        </Text>
+        <Text ml={2}>New Experiment</Text>
      </VStack>
    </Card>
  );
--- a/app/src/components/nav/AppShell.tsx
+++ b/app/src/components/nav/AppShell.tsx
@@ -13,15 +13,18 @@ import {
 } from "@chakra-ui/react";
 import Head from "next/head";
 import Link from "next/link";
+import { useRouter } from "next/router";
 import { BsGearFill, BsGithub, BsPersonCircle } from "react-icons/bs";
 import { IoStatsChartOutline } from "react-icons/io5";
 import { RiHome3Line, RiFlaskLine } from "react-icons/ri";
-import { FaRobot } from "react-icons/fa";
+import { AiOutlineThunderbolt } from "react-icons/ai";
+import { FaReadme } from "react-icons/fa";
 import { signIn, useSession } from "next-auth/react";
+
 import ProjectMenu from "./ProjectMenu";
 import NavSidebarOption from "./NavSidebarOption";
 import IconLink from "./IconLink";
-import { BetaModal } from "./BetaModal";
+import { BetaModal } from "../BetaModal";
 import { useAppStore } from "~/state/store";

 const Divider = () => <Box h="1px" bgColor="gray.300" w="full" />;
@@ -73,9 +76,9 @@ const NavSidebar = () => {
            <ProjectMenu />
            <Divider />

-            <IconLink icon={RiHome3Line} label="Dashboard" href="/dashboard" beta />
-            <IconLink icon={IoStatsChartOutline} label="Request Logs" href="/request-logs" beta />
-            <IconLink icon={FaRobot} label="Fine Tunes" href="/fine-tunes" beta />
+            <IconLink icon={RiHome3Line} label="Dashboard" href="/dashboard" />
+            <IconLink icon={IoStatsChartOutline} label="Request Logs" href="/request-logs" />
+            <IconLink icon={AiOutlineThunderbolt} label="Fine Tunes" href="/fine-tunes" beta />
            <IconLink icon={RiFlaskLine} label="Experiments" href="/experiments" />
            <VStack w="full" alignItems="flex-start" spacing={0} pt={8}>
              <Text
@@ -111,7 +114,22 @@ const NavSidebar = () => {
          </NavSidebarOption>
        )}
      </VStack>
-
+      <HStack
+        w="full"
+        px={{ base: 2, md: 4 }}
+        py={{ base: 1, md: 2 }}
+        as={ChakraLink}
+        justifyContent="start"
+        href="https://docs.openpipe.ai"
+        target="_blank"
+        color="gray.500"
+        spacing={1}
+      >
+        <Icon as={FaReadme} boxSize={4} mr={2} />
+        <Text fontWeight="bold" fontSize="sm">
+          Read the Docs
+        </Text>
+      </HStack>
      <Divider />
      <VStack spacing={0} align="center">
        <ChakraLink
@@ -140,6 +158,7 @@ export default function AppShell({
  requireBeta?: boolean;
 }) {
  const [vh, setVh] = useState("100vh"); // Default height to prevent flicker on initial render
+  const router = useRouter();

  useEffect(() => {
    const setHeight = () => {
@@ -181,7 +200,7 @@ export default function AppShell({
          {children}
        </Box>
      </Flex>
-      {requireBeta && flagsLoaded && !flags.betaAccess && <BetaModal />}
+      <BetaModal isOpen={!!requireBeta && flagsLoaded && !flags.betaAccess} onClose={router.back} />
    </>
  );
 }
--- a/app/src/components/nav/ProjectMenu.tsx
+++ b/app/src/components/nav/ProjectMenu.tsx
@@ -57,6 +57,7 @@ export default function ProjectMenu() {
    await utils.projects.list.invalidate();
    setSelectedProjectId(newProj.id);
    await router.push({ pathname: "/project/settings" });
+    popover.onClose();
  }, [createMutation, router]);

  const user = useSession().data;
--- a/app/src/components/requestLogs/ActionButton.tsx
+++ b/app/src/components/requestLogs/ActionButton.tsx
@@ -1,29 +1,50 @@
+import { useState } from "react";
+
 import { Button, HStack, type ButtonProps, Icon, Text } from "@chakra-ui/react";
 import { type IconType } from "react-icons";
+import { useAppStore } from "~/state/store";
+import { BetaModal } from "../BetaModal";

 const ActionButton = ({
  icon,
  label,
+  requireBeta = false,
+  onClick,
  ...buttonProps
-}: { icon: IconType; label: string } & ButtonProps) => {
+}: {
+  icon: IconType;
+  label: string;
+  requireBeta?: boolean;
+  onClick?: () => void;
+} & ButtonProps) => {
+  const flags = useAppStore((s) => s.featureFlags.featureFlags);
+  const flagsLoaded = useAppStore((s) => s.featureFlags.flagsLoaded);
+
+  const [betaModalOpen, setBetaModalOpen] = useState(false);
+
+  const isBetaBlocked = requireBeta && flagsLoaded && !flags.betaAccess;
  return (
-    <Button
-      colorScheme="blue"
-      color="black"
-      bgColor="white"
-      borderColor="gray.300"
-      borderRadius={4}
-      variant="outline"
-      size="sm"
-      fontSize="sm"
-      fontWeight="normal"
-      {...buttonProps}
-    >
-      <HStack spacing={1}>
-        {icon && <Icon as={icon} />}
-        <Text display={{ base: "none", md: "flex" }}>{label}</Text>
-      </HStack>
-    </Button>
+    <>
+      <Button
+        colorScheme="blue"
+        color="black"
+        bgColor="white"
+        borderColor="gray.300"
+        borderRadius={4}
+        variant="outline"
+        size="sm"
+        fontSize="sm"
+        fontWeight="normal"
+        onClick={isBetaBlocked ? () => setBetaModalOpen(true) : onClick}
+        {...buttonProps}
+      >
+        <HStack spacing={1}>
+          {icon && <Icon as={icon} color={requireBeta ? "orange.400" : undefined} />}
+          <Text display={{ base: "none", md: "flex" }}>{label}</Text>
+        </HStack>
+      </Button>
+      <BetaModal isOpen={betaModalOpen} onClose={() => setBetaModalOpen(false)} />
+    </>
  );
 };

--- a/app/src/components/requestLogs/ExportButton.tsx
+++ b/app/src/components/requestLogs/ExportButton.tsx
@@ -47,6 +47,7 @@ const ExportButton = () => {
        label="Export"
        icon={BiExport}
        isDisabled={selectedLogIds.size === 0}
+        requireBeta
      />
      <ExportLogsModal disclosure={disclosure} />
    </>
--- a/app/src/components/requestLogs/FineTuneButton.tsx
+++ b/app/src/components/requestLogs/FineTuneButton.tsx
@@ -16,7 +16,7 @@ import {
  type UseDisclosureReturn,
  Input,
 } from "@chakra-ui/react";
-import { FaRobot } from "react-icons/fa";
+import { AiTwotoneThunderbolt } from "react-icons/ai";
 import humanId from "human-id";
 import { useRouter } from "next/router";

@@ -39,8 +39,9 @@ const FineTuneButton = () => {
      <ActionButton
        onClick={disclosure.onOpen}
        label="Fine Tune"
-        icon={FaRobot}
+        icon={AiTwotoneThunderbolt}
        isDisabled={selectedLogIds.size === 0}
+        requireBeta
      />
      <FineTuneModal disclosure={disclosure} />
    </>
@@ -90,7 +91,7 @@ const FineTuneModal = ({ disclosure }: { disclosure: UseDisclosureReturn }) => {
      <ModalContent w={1200}>
        <ModalHeader>
          <HStack>
-            <Icon as={FaRobot} />
+            <Icon as={AiTwotoneThunderbolt} />
            <Text>Fine Tune</Text>
          </HStack>
        </ModalHeader>
--- a/app/src/components/requestLogs/LoggedCallsTable.tsx
+++ b/app/src/components/requestLogs/LoggedCallsTable.tsx
@@ -1,7 +1,7 @@
 import { Card, Table, Tbody } from "@chakra-ui/react";
 import { useState } from "react";
 import { useLoggedCalls } from "~/utils/hooks";
-import { TableHeader, TableRow } from "./TableRow";
+import { TableHeader, TableRow, EmptyTableRow } from "./TableRow";

 export default function LoggedCallsTable() {
  const [expandedRow, setExpandedRow] = useState<string | null>(null);
@@ -12,23 +12,27 @@ export default function LoggedCallsTable() {
      <Table>
        <TableHeader showOptions />
        <Tbody>
-          {loggedCalls?.calls?.map((loggedCall) => {
-            return (
-              <TableRow
-                key={loggedCall.id}
-                loggedCall={loggedCall}
-                isExpanded={loggedCall.id === expandedRow}
-                onToggle={() => {
-                  if (loggedCall.id === expandedRow) {
-                    setExpandedRow(null);
-                  } else {
-                    setExpandedRow(loggedCall.id);
-                  }
-                }}
-                showOptions
-              />
-            );
-          })}
+          {loggedCalls?.calls.length ? (
+            loggedCalls?.calls?.map((loggedCall) => {
+              return (
+                <TableRow
+                  key={loggedCall.id}
+                  loggedCall={loggedCall}
+                  isExpanded={loggedCall.id === expandedRow}
+                  onToggle={() => {
+                    if (loggedCall.id === expandedRow) {
+                      setExpandedRow(null);
+                    } else {
+                      setExpandedRow(loggedCall.id);
+                    }
+                  }}
+                  showOptions
+                />
+              );
+            })
+          ) : (
+            <EmptyTableRow />
+          )}
        </Tbody>
      </Table>
    </Card>
--- a/app/src/components/requestLogs/TableRow.tsx
+++ b/app/src/components/requestLogs/TableRow.tsx
@@ -13,6 +13,7 @@ import {
  ButtonGroup,
  Text,
  Checkbox,
+  Link as ChakraLink,
 } from "@chakra-ui/react";
 import Link from "next/link";

@@ -198,3 +199,41 @@ export const TableRow = ({
    </>
  );
 };
+
+export const EmptyTableRow = ({ filtersApplied = true }: { filtersApplied?: boolean }) => {
+  const visibleColumns = useAppStore((s) => s.columnVisibility.visibleColumns);
+  const filters = useAppStore((state) => state.logFilters.filters);
+  const { isLoading } = useLoggedCalls();
+
+  if (isLoading) return null;
+
+  if (filters.length && filtersApplied) {
+    return (
+      <Tr>
+        <Td w="full" colSpan={visibleColumns.size + 1}>
+          <Text color="gray.500" textAlign="center" w="full" p={4}>
+            No matching request logs found. Try removing some filters.
+          </Text>
+        </Td>
+      </Tr>
+    );
+  }
+
+  return (
+    <Tr>
+      <Td w="full" colSpan={visibleColumns.size + 1}>
+        <Text color="gray.500" textAlign="center" w="full" p={4}>
+          This project has no request logs. Learn how to add request logs to your project in our{" "}
+          <ChakraLink
+            href="https://docs.openpipe.ai/getting-started/quick-start"
+            target="_blank"
+            color="blue.600"
+          >
+            Quick Start
+          </ChakraLink>{" "}
+          guide.
+        </Text>
+      </Td>
+    </Tr>
+  );
+};
--- a/app/src/modelProviders/openai-ChatCompletion/getCompletion.ts
+++ b/app/src/modelProviders/openai-ChatCompletion/getCompletion.ts
@@ -2,7 +2,7 @@
 import { isArray, isString } from "lodash-es";
 import { APIError } from "openai";
 import { type ChatCompletion, type CompletionCreateParams } from "openai/resources/chat";
-import mergeChunks from "openpipe/src/openai/mergeChunks";
+import mergeChunks from "openpipe/openai/mergeChunks";
 import { openai } from "~/server/utils/openai";
 import { type CompletionResponse } from "../types";

--- a/app/src/modelProviders/openpipe-chat/getCompletion.ts
+++ b/app/src/modelProviders/openpipe-chat/getCompletion.ts
@@ -17,10 +17,23 @@ const modelEndpoints: Record<OpenpipeChatInput["model"], string> = {
  "NousResearch/Nous-Hermes-llama-2-7b": "https://ua1bpc6kv3dgge-8000.proxy.runpod.net/v1",
 };

+const CUSTOM_MODELS_ENABLED = false;
+
 export async function getCompletion(
  input: OpenpipeChatInput,
  onStream: ((partialOutput: OpenpipeChatOutput) => void) | null,
 ): Promise<CompletionResponse<OpenpipeChatOutput>> {
+  // Temporarily disable these models because of GPU constraints
+
+  if (!CUSTOM_MODELS_ENABLED) {
+    return {
+      type: "error",
+      message:
+        "We've disabled this model temporarily because of GPU capacity constraints. Check back later.",
+      autoRetry: false,
+    };
+  }
+
  const { model, messages, ...rest } = input;

  const templatedPrompt = frontendModelProvider.models[model].templatePrompt?.(messages);
--- a/app/src/modelProviders/replicate-llama2/getCompletion.ts
+++ b/app/src/modelProviders/replicate-llama2/getCompletion.ts
@@ -8,8 +8,8 @@ const replicate = new Replicate({
 });

 const modelIds: Record<ReplicateLlama2Input["model"], string> = {
-  "7b-chat": "7b0bfc9aff140d5b75bacbed23e91fd3c34b01a1e958d32132de6e0a19796e2c",
-  "13b-chat": "2a7f981751ec7fdf87b5b91ad4db53683a98082e9ff7bfd12c8cd5ea85980a52",
+  "7b-chat": "d24902e3fa9b698cc208b5e63136c4e26e828659a9f09827ca6ec5bb83014381",
+  "13b-chat": "9dff94b1bed5af738655d4a7cbcdcde2bd503aa85c94334fe1f42af7f3dd5ee3",
  "70b-chat": "2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1",
 };

--- a/app/src/pages/dashboard/index.tsx
+++ b/app/src/pages/dashboard/index.tsx
@@ -33,7 +33,7 @@ export default function Dashboard() {
  );

  return (
-    <AppShell title="Dashboard" requireAuth requireBeta>
+    <AppShell title="Dashboard" requireAuth>
      <VStack px={8} py={8} alignItems="flex-start" spacing={4}>
        <Text fontSize="2xl" fontWeight="bold">
          Dashboard
--- a/app/src/pages/request-logs/index.tsx
+++ b/app/src/pages/request-logs/index.tsx
@@ -19,7 +19,7 @@ export default function LoggedCalls() {
  const [filtersShown, setFiltersShown] = useState(true);

  return (
-    <AppShell title="Request Logs" requireAuth requireBeta>
+    <AppShell title="Request Logs" requireAuth>
      <Box h="100vh" overflowY="scroll">
        <VStack px={8} py={8} alignItems="flex-start" spacing={4} w="full">
          <Text fontSize="2xl" fontWeight="bold">
@@ -35,6 +35,7 @@ export default function LoggedCalls() {
              label="Experiment"
              icon={RiFlaskLine}
              isDisabled={selectedLogIds.size === 0}
+              requireBeta
            />
            <ExportButton />
            <ColumnVisiblityDropdown />
--- a/app/src/server/api/routers/promptVariants.router.ts
+++ b/app/src/server/api/routers/promptVariants.router.ts
@@ -196,7 +196,10 @@ export const promptVariantsRouter = createTRPCRouter({
          ? `${originalVariant?.label} Copy`
          : `Prompt Variant ${largestSortIndex + 2}`;

-      const newConstructFn = await deriveNewConstructFn(originalVariant);
+      const newConstructFn = await deriveNewConstructFn(
+        originalVariant,
+        originalVariant?.promptConstructor,
+      );

      const createNewVariantAction = prisma.promptVariant.create({
        data: {
@@ -298,6 +301,7 @@ export const promptVariantsRouter = createTRPCRouter({
    .input(
      z.object({
        id: z.string(),
+        originalPromptFn: z.string(),
        instructions: z.string().optional(),
        newModel: z
          .object({
@@ -315,22 +319,21 @@ export const promptVariantsRouter = createTRPCRouter({
      });
      await requireCanModifyExperiment(existing.experimentId, ctx);

-      const constructedPrompt = await parsePromptConstructor(existing.promptConstructor);
-
-      if ("error" in constructedPrompt) {
-        return error(constructedPrompt.error);
-      }
-
      const model = input.newModel
        ? modelProviders[input.newModel.provider].models[input.newModel.model]
        : undefined;

-      const promptConstructionFn = await deriveNewConstructFn(existing, model, input.instructions);
+      const promptConstructionFn = await deriveNewConstructFn(
+        existing,
+        input.originalPromptFn,
+        model,
+        input.instructions,
+      );

      // TODO: Validate promptConstructionFn
      // TODO: Record in some sort of history

-      return promptConstructionFn;
+      return success(promptConstructionFn);
    }),

  replaceVariant: protectedProcedure
--- a/app/src/server/utils/deriveNewContructFn.ts
+++ b/app/src/server/utils/deriveNewContructFn.ts
@@ -12,30 +12,37 @@ const isolate = new ivm.Isolate({ memoryLimit: 128 });

 export async function deriveNewConstructFn(
  originalVariant: PromptVariant | null,
+  originalPromptFn?: string,
  newModel?: Model,
  instructions?: string,
 ) {
-  if (originalVariant && !newModel && !instructions) {
-    return originalVariant.promptConstructor;
+  if (originalPromptFn && !newModel && !instructions) {
+    return originalPromptFn;
  }
-  if (originalVariant && (newModel || instructions)) {
-    return await requestUpdatedPromptFunction(originalVariant, newModel, instructions);
+  if (originalVariant && originalPromptFn && (newModel || instructions)) {
+    return await requestUpdatedPromptFunction(
+      originalVariant,
+      originalPromptFn,
+      newModel,
+      instructions,
+    );
  }
  return dedent`
-    prompt = {
-      model: "gpt-3.5-turbo",
-      messages: [
-        {
-          role: "system",
-          content: "Return 'Hello, world!'",
-        }
-      ]
-    }`;
+  definePrompt("openai/ChatCompletion", {
+    model: "gpt-3.5-turbo-0613",
+    messages: [
+      {
+        role: "system",
+        content: \`Hello, world!\`,
+      },
+    ],
+  });`;
 }

 const NUM_RETRIES = 5;
 const requestUpdatedPromptFunction = async (
  originalVariant: PromptVariant,
+  originalPromptFn: string,
  newModel?: Model,
  instructions?: string,
 ) => {
@@ -55,7 +62,7 @@ const requestUpdatedPromptFunction = async (
        },
        {
          role: "user",
-          content: `This is the current prompt constructor function:\n---\n${originalVariant.promptConstructor}`,
+          content: `This is the current prompt constructor function:\n---\n${originalPromptFn}`,
        },
      ];
      if (newModel) {
--- a/app/src/server/utils/openai.ts
+++ b/app/src/server/utils/openai.ts
@@ -1,6 +1,6 @@
 import fs from "fs";
 import path from "path";
-import OpenAI, { type ClientOptions } from "openpipe/src/openai";
+import OpenAI, { type ClientOptions } from "openpipe/openai";

 import { env } from "~/env.mjs";

--- a/app/src/state/sharedVariantEditor.slice.ts
+++ b/app/src/state/sharedVariantEditor.slice.ts
@@ -1,16 +1,26 @@
+import loader, { type Monaco } from "@monaco-editor/loader";
+
 import { type RouterOutputs } from "~/utils/api";
 import { type SliceCreator } from "./store";
-import loader from "@monaco-editor/loader";
 import formatPromptConstructor from "~/promptConstructor/format";

 export const editorBackground = "#fafafa";

+export type CreatedEditor = ReturnType<Monaco["editor"]["create"]>;
+
+type EditorOptions = {
+  getContent: () => string;
+  setContent: (content: string) => void;
+};
+
 export type SharedVariantEditorSlice = {
-  monaco: null | ReturnType<typeof loader.__getMonacoInstance>;
+  monaco: null | Monaco;
  loadMonaco: () => Promise<void>;
  scenarioVars: RouterOutputs["scenarioVars"]["list"];
  updateScenariosModel: () => void;
  setScenarioVars: (scenarioVars: RouterOutputs["scenarioVars"]["list"]) => void;
+  editorOptionsMap: Record<string, EditorOptions>;
+  updateOptionsForEditor: (uiId: string, { getContent, setContent }: EditorOptions) => void;
 };

 export const createVariantEditorSlice: SliceCreator<SharedVariantEditorSlice> = (set, get) => ({
@@ -93,4 +103,10 @@ export const createVariantEditorSlice: SliceCreator<SharedVariantEditorSlice> =
      );
    }
  },
+  editorOptionsMap: {},
+  updateOptionsForEditor: (uiId, options) => {
+    set((state) => {
+      state.sharedVariantEditor.editorOptionsMap[uiId] = options;
+    });
+  },
 });
--- a/app/src/utils/hooks.ts
+++ b/app/src/utils/hooks.ts
@@ -148,13 +148,13 @@ export const useScenarioVars = () => {
  );
 };

-export const useLoggedCalls = () => {
+export const useLoggedCalls = (applyFilters = true) => {
  const selectedProjectId = useAppStore((state) => state.selectedProjectId);
  const { page, pageSize } = usePageParams();
  const filters = useAppStore((state) => state.logFilters.filters);

  const { data, isLoading, ...rest } = api.loggedCalls.list.useQuery(
-    { projectId: selectedProjectId ?? "", page, pageSize, filters },
+    { projectId: selectedProjectId ?? "", page, pageSize, filters: applyFilters ? filters : [] },
    { enabled: !!selectedProjectId },
  );

--- a/client-libs/python/README.md
+++ b/client-libs/python/README.md
@@ -3,6 +3,7 @@
 This client allows you automatically report your OpenAI calls to [OpenPipe](https://openpipe.ai/). OpenPipe

 ## Installation
+
 `pip install openpipe`

 ## Usage
@@ -15,7 +16,7 @@ This client allows you automatically report your OpenAI calls to [OpenPipe](http
 from openpipe import openai, configure_openpipe
 import os

-# Set the OpenPipe API key you got in step (3) above.
+# Set the OpenPipe API key you got in step (2) above.
 # If you have the `OPENPIPE_API_KEY` environment variable set we'll read from it by default.
 configure_openpipe(api_key=os.getenv("OPENPIPE_API_KEY"))

@@ -23,7 +24,7 @@ configure_openpipe(api_key=os.getenv("OPENPIPE_API_KEY"))
 openai.api_key = os.getenv("OPENAI_API_KEY")
 ```

-You can use the OpenPipe client for normal
+You can now use your new OpenAI client, which functions identically to the generic OpenAI client while also reporting calls to your OpenPipe instance.

 ## Special Features

@@ -37,4 +38,4 @@ completion = openai.ChatCompletion.create(
    messages=[{"role": "system", "content": "count to 10"}],
    openpipe={"tags": {"prompt_id": "counting"}},
 )
-```
+```
--- a/client-libs/python/openpipe/shared.py
+++ b/client-libs/python/openpipe/shared.py
@@ -6,11 +6,9 @@ from openpipe.api_client.client import AuthenticatedClient
 from openpipe.api_client.models.report_json_body_tags import (
    ReportJsonBodyTags,
 )
-import toml
 import time
 import os
-
-version = toml.load("pyproject.toml")["tool"]["poetry"]["version"]
+import pkg_resources

 configured_client = AuthenticatedClient(
    base_url="https://app.openpipe.ai/api/v1", token=""
@@ -23,7 +21,7 @@ if os.environ.get("OPENPIPE_API_KEY"):
 def _get_tags(openpipe_options):
    tags = openpipe_options.get("tags") or {}
    tags["$sdk"] = "python"
-    tags["$sdk.version"] = version
+    tags["$sdk.version"] = pkg_resources.get_distribution('openpipe').version

    return ReportJsonBodyTags.from_dict(tags)

--- a/client-libs/python/poetry.lock
+++ b/client-libs/python/poetry.lock
@@ -1056,6 +1056,7 @@ files = [
    {file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:69b023b2b4daa7548bcfbd4aa3da05b3a74b772db9e23b982788168117739938"},
    {file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:81e0b275a9ecc9c0c0c07b4b90ba548307583c125f54d5b6946cfee6360c733d"},
    {file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ba336e390cd8e4d1739f42dfe9bb83a3cc2e80f567d8805e11b46f4a943f5515"},
+    {file = "PyYAML-6.0.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:326c013efe8048858a6d312ddd31d56e468118ad4cdeda36c719bf5bb6192290"},
    {file = "PyYAML-6.0.1-cp310-cp310-win32.whl", hash = "sha256:bd4af7373a854424dabd882decdc5579653d7868b8fb26dc7d0e99f823aa5924"},
    {file = "PyYAML-6.0.1-cp310-cp310-win_amd64.whl", hash = "sha256:fd1592b3fdf65fff2ad0004b5e363300ef59ced41c2e6b3a99d4089fa8c5435d"},
    {file = "PyYAML-6.0.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6965a7bc3cf88e5a1c3bd2e0b5c22f8d677dc88a455344035f03399034eb3007"},
@@ -1063,8 +1064,15 @@ files = [
    {file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42f8152b8dbc4fe7d96729ec2b99c7097d656dc1213a3229ca5383f973a5ed6d"},
    {file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:062582fca9fabdd2c8b54a3ef1c978d786e0f6b3a1510e0ac93ef59e0ddae2bc"},
    {file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d2b04aac4d386b172d5b9692e2d2da8de7bfb6c387fa4f801fbf6fb2e6ba4673"},
+    {file = "PyYAML-6.0.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:e7d73685e87afe9f3b36c799222440d6cf362062f78be1013661b00c5c6f678b"},
    {file = "PyYAML-6.0.1-cp311-cp311-win32.whl", hash = "sha256:1635fd110e8d85d55237ab316b5b011de701ea0f29d07611174a1b42f1444741"},
    {file = "PyYAML-6.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:bf07ee2fef7014951eeb99f56f39c9bb4af143d8aa3c21b1677805985307da34"},
+    {file = "PyYAML-6.0.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:855fb52b0dc35af121542a76b9a84f8d1cd886ea97c84703eaa6d88e37a2ad28"},
+    {file = "PyYAML-6.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:40df9b996c2b73138957fe23a16a4f0ba614f4c0efce1e9406a184b6d07fa3a9"},
+    {file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c22bec3fbe2524cde73d7ada88f6566758a8f7227bfbf93a408a9d86bcc12a0"},
+    {file = "PyYAML-6.0.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8d4e9c88387b0f5c7d5f281e55304de64cf7f9c0021a3525bd3b1c542da3b0e4"},
+    {file = "PyYAML-6.0.1-cp312-cp312-win32.whl", hash = "sha256:d483d2cdf104e7c9fa60c544d92981f12ad66a457afae824d146093b8c294c54"},
+    {file = "PyYAML-6.0.1-cp312-cp312-win_amd64.whl", hash = "sha256:0d3304d8c0adc42be59c5f8a4d9e3d7379e6955ad754aa9d6ab7a398b59dd1df"},
    {file = "PyYAML-6.0.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:50550eb667afee136e9a77d6dc71ae76a44df8b3e51e41b77f6de2932bfe0f47"},
    {file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1fe35611261b29bd1de0070f0b2f47cb6ff71fa6595c077e42bd0c419fa27b98"},
    {file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:704219a11b772aea0d8ecd7058d0082713c3562b4e271b849ad7dc4a5c90c13c"},
@@ -1081,6 +1089,7 @@ files = [
    {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a0cd17c15d3bb3fa06978b4e8958dcdc6e0174ccea823003a106c7d4d7899ac5"},
    {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:28c119d996beec18c05208a8bd78cbe4007878c6dd15091efb73a30e90539696"},
    {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7e07cbde391ba96ab58e532ff4803f79c4129397514e1413a7dc761ccd755735"},
+    {file = "PyYAML-6.0.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:49a183be227561de579b4a36efbb21b3eab9651dd81b1858589f796549873dd6"},
    {file = "PyYAML-6.0.1-cp38-cp38-win32.whl", hash = "sha256:184c5108a2aca3c5b3d3bf9395d50893a7ab82a38004c8f61c258d4428e80206"},
    {file = "PyYAML-6.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:1e2722cc9fbb45d9b87631ac70924c11d3a401b2d7f410cc0e3bbf249f2dca62"},
    {file = "PyYAML-6.0.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9eb6caa9a297fc2c2fb8862bc5370d0303ddba53ba97e71f08023b6cd73d16a8"},
@@ -1088,6 +1097,7 @@ files = [
    {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5773183b6446b2c99bb77e77595dd486303b4faab2b086e7b17bc6bef28865f6"},
    {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b786eecbdf8499b9ca1d697215862083bd6d2a99965554781d0d8d1ad31e13a0"},
    {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc1bf2925a1ecd43da378f4db9e4f799775d6367bdb94671027b73b393a7c42c"},
+    {file = "PyYAML-6.0.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:04ac92ad1925b2cff1db0cfebffb6ffc43457495c9b3c39d3fcae417d7125dc5"},
    {file = "PyYAML-6.0.1-cp39-cp39-win32.whl", hash = "sha256:faca3bdcf85b2fc05d06ff3fbc1f83e1391b3e724afa3feba7d13eeab355484c"},
    {file = "PyYAML-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486"},
    {file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
@@ -1147,17 +1157,6 @@ files = [
    {file = "sniffio-1.3.0.tar.gz", hash = "sha256:e60305c5e5d314f5389259b7f22aaa33d8f7dee49763119234af3755c55b9101"},
 ]

-[[package]]
-name = "toml"
-version = "0.10.2"
-description = "Python Library for Tom's Obvious, Minimal Language"
-optional = false
-python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
-files = [
-    {file = "toml-0.10.2-py2.py3-none-any.whl", hash = "sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b"},
-    {file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
-]
-
 [[package]]
 name = "tomli"
 version = "2.0.1"
@@ -1367,4 +1366,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "e93c2ecac1b81a4fc1f9ad3dcedf03b1126cc6815e084ae233da7d3ece313ade"
+content-hash = "f50c3ee43ebb9510bf42b9a16d8d6a92d561bec40e8f3c11fb2614e92a5b756f"
--- a/client-libs/python/publish.sh
+++ b/client-libs/python/publish.sh
@@ -0,0 +1,11 @@
+#!/bin/bash
+set -e
+
+# Check if PYPI_OPENPIPE_TOKEN is set
+if [[ -z "${PYPI_OPENPIPE_TOKEN}" ]]; then
+    echo "Error: PYPI_OPENPIPE_TOKEN is not set."
+    exit 1
+fi
+
+# If the token is set, proceed with publishing
+poetry publish --build --username=__token__ --password=$PYPI_OPENPIPE_TOKEN
--- a/client-libs/python/pyproject.toml
+++ b/client-libs/python/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "openpipe"
-version = "3.0.1"
+version = "3.1.2"
 description = "Python client library for the OpenPipe service"
 authors = ["Kyle Corbitt <kyle@openpipe.ai>"]
 license = "Apache-2.0"
@@ -14,7 +14,6 @@ openai = "^0.27.8"
 httpx = "^0.24.1"
 attrs = "^23.1.0"
 python-dateutil = "^2.8.2"
-toml = "^0.10.2"

 [tool.poetry.dev-dependencies]

--- a/client-libs/typescript/README.md
+++ b/client-libs/typescript/README.md
@@ -0,0 +1,70 @@
+# OpenPipe Node API Library
+
+[![NPM version](https://img.shields.io/npm/v/openpipe.svg)](https://npmjs.org/package/openpipe)
+
+This library wraps TypeScript or Javascript OpenAI API calls and logs additional data to the configured `OPENPIPE_BASE_URL` for further processing.
+
+It is fully compatible with OpenAI's sdk and logs both streaming and non-streaming requests and responses.
+
+<!-- To learn more about using OpenPipe, check out our [Documentation](https://docs.openpipe.ai/docs/api). -->
+
+## Installation
+
+```sh
+npm install --save openpipe
+# or
+yarn add openpipe
+```
+
+## Usage
+
+1. Create a project at https://app.openpipe.ai
+2. Find your project's API key at https://app.openpipe.ai/project/settings
+3. Configure the OpenPipe client as shown below.
+
+```js
+// import OpenAI from 'openai'
+import OpenAI from "openpipe/openai";
+
+// Fully compatible with original OpenAI initialization
+const openai = new OpenAI({
+  apiKey: "my api key", // defaults to process.env["OPENAI_API_KEY"]
+  // openpipe key is optional
+  openpipe: {
+    apiKey: "my api key", // defaults to process.env["OPENPIPE_API_KEY"]
+    baseUrl: "my url", // defaults to process.env["OPENPIPE_BASE_URL"] or https://app.openpipe.ai/api/v1 if not set
+  },
+});
+
+async function main() {
+  // Allows optional openpipe object
+  const completion = await openai.chat.completions.create({
+    messages: [{ role: "user", content: "Say this is a test" }],
+    model: "gpt-3.5-turbo",
+    // optional
+    openpipe: {
+      // Add custom searchable tags
+      tags: {
+        prompt_id: "getCompletion",
+        any_key: "any_value",
+      },
+    },
+  });
+
+  console.log(completion.choices);
+}
+
+main();
+```
+
+## FAQ
+
+<b><i>How do I report calls to my self-hosted instance?</i></b>
+
+Start an instance by following the instructions on [Running Locally](https://github.com/OpenPipe/OpenPipe#running-locally). Once it's running, point your `OPENPIPE_BASE_URL` to your self-hosted instance.
+
+<b><i>What if my `OPENPIPE_BASE_URL` is misconfigured or my instance goes down? Will my OpenAI calls stop working?</i></b>
+
+Your OpenAI calls will continue to function as expected no matter what. The sdk handles logging errors gracefully without affecting OpenAI inference.
+
+See the [GitHub repo](https://github.com/OpenPipe/OpenPipe) for more details.
--- a/client-libs/typescript/build.sh
+++ b/client-libs/typescript/build.sh
@@ -0,0 +1,27 @@
+#!/usr/bin/env bash
+
+# Adapted from https://github.com/openai/openai-node/blob/master/build
+
+set -exuo pipefail
+
+rm -rf dist /tmp/openpipe-build-dist
+
+mkdir /tmp/openpipe-build-dist
+
+cp -rp * /tmp/openpipe-build-dist
+
+# Rename package name in package.json
+python3 -c "
+import json
+with open('/tmp/openpipe-build-dist/package.json', 'r') as f:
+    data = json.load(f)
+data['name'] = 'openpipe'
+with open('/tmp/openpipe-build-dist/package.json', 'w') as f:
+    json.dump(data, f, indent=4)
+"
+
+rm -rf /tmp/openpipe-build-dist/node_modules
+mv /tmp/openpipe-build-dist dist
+
+# build to .js files
+(cd dist && npm exec tsc -- --noEmit false)
--- a/client-libs/typescript/src/codegen/OPClient.ts
+++ b/client-libs/typescript/src/codegen/OPClient.ts
--- a/client-libs/typescript/src/codegen/core/ApiError.ts
+++ b/client-libs/typescript/src/codegen/core/ApiError.ts
--- a/client-libs/typescript/src/codegen/core/ApiRequestOptions.ts
+++ b/client-libs/typescript/src/codegen/core/ApiRequestOptions.ts
--- a/client-libs/typescript/src/codegen/core/ApiResult.ts
+++ b/client-libs/typescript/src/codegen/core/ApiResult.ts
--- a/client-libs/typescript/src/codegen/core/BaseHttpRequest.ts
+++ b/client-libs/typescript/src/codegen/core/BaseHttpRequest.ts
--- a/client-libs/typescript/src/codegen/core/CancelablePromise.ts
+++ b/client-libs/typescript/src/codegen/core/CancelablePromise.ts
--- a/client-libs/typescript/src/codegen/core/NodeHttpRequest.ts
+++ b/client-libs/typescript/src/codegen/core/NodeHttpRequest.ts
--- a/client-libs/typescript/src/codegen/core/OpenAPI.ts
+++ b/client-libs/typescript/src/codegen/core/OpenAPI.ts
--- a/client-libs/typescript/src/codegen/core/request.ts
+++ b/client-libs/typescript/src/codegen/core/request.ts
--- a/client-libs/typescript/src/codegen/index.ts
+++ b/client-libs/typescript/src/codegen/index.ts
--- a/client-libs/typescript/src/codegen/services/DefaultService.ts
+++ b/client-libs/typescript/src/codegen/services/DefaultService.ts
--- a/client-libs/typescript/index.ts
+++ b/client-libs/typescript/index.ts
@@ -1,3 +1 @@
-// main.ts or index.ts at the root level
-export * as OpenAI from "./src/openai";
-export * as OpenAILegacy from "./src/openai-legacy";
+export * as openai from "./openai";
--- a/client-libs/typescript/src/openai/index.test.ts
+++ b/client-libs/typescript/src/openai/index.test.ts
@@ -80,6 +80,7 @@ test("bad call streaming", async () => {
      stream: true,
    });
  } catch (e) {
+    // @ts-expect-error need to check for error type
    await e.openpipe.reportingFinished;
    const lastLogged = await lastLoggedCall();
    expect(lastLogged?.modelResponse?.errorMessage).toEqual(
@@ -96,7 +97,9 @@ test("bad call", async () => {
      messages: [{ role: "system", content: "count to 10" }],
    });
  } catch (e) {
+    // @ts-expect-error need to check for error type
    assert("openpipe" in e);
+    // @ts-expect-error need to check for error type
    await e.openpipe.reportingFinished;
    const lastLogged = await lastLoggedCall();
    expect(lastLogged?.modelResponse?.errorMessage).toEqual(
@@ -120,7 +123,8 @@ test("caching", async () => {

  await completion.openpipe.reportingFinished;
  const firstLogged = await lastLoggedCall();
-  expect(completion.choices[0].message.content).toEqual(
+
+  expect(completion.choices[0]?.message.content).toEqual(
    firstLogged?.modelResponse?.respPayload.choices[0].message.content,
  );

--- a/client-libs/typescript/src/openai/index.ts
+++ b/client-libs/typescript/src/openai/index.ts
--- a/client-libs/typescript/src/openai/mergeChunks.ts
+++ b/client-libs/typescript/src/openai/mergeChunks.ts
--- a/client-libs/typescript/src/openai/streaming.ts
+++ b/client-libs/typescript/src/openai/streaming.ts
--- a/client-libs/typescript/package.json
+++ b/client-libs/typescript/package.json
@@ -1,14 +1,17 @@
 {
-  "name": "openpipe",
-  "version": "0.1.0",
+  "name": "openpipe-dev",
+  "version": "0.3.5",
  "type": "module",
  "description": "Metrics and auto-evaluation for LLM calls",
  "scripts": {
-    "build": "tsc",
+    "build": "./build.sh",
    "test": "vitest"
  },
-  "main": "dist/index.js",
-  "types": "dist/index.d.ts",
+  "main": "./index.ts",
+  "publishConfig": {
+    "access": "public",
+    "main": "./index.js"
+  },
  "keywords": [],
  "author": "",
  "license": "Apache-2.0",
--- a/client-libs/typescript/publish.sh
+++ b/client-libs/typescript/publish.sh
@@ -0,0 +1,9 @@
+#!/usr/bin/env bash
+
+# Adapted from https://github.com/openai/openai-node/blob/master/build
+
+set -exuo pipefail
+
+./build.sh
+
+(cd dist && pnpm publish --access public)
--- a/client-libs/typescript/src/shared.ts
+++ b/client-libs/typescript/src/shared.ts
@@ -1,4 +1,5 @@
-import pkg from "../package.json";
+import pkg from "./package.json";
+
 import { DefaultService } from "./codegen";

 export type OpenPipeConfig = {
--- a/client-libs/typescript/src/openai-legacy/index.ts
+++ b/client-libs/typescript/src/openai-legacy/index.ts
@@ -1,85 +0,0 @@
-import * as openPipeClient from "../codegen";
-import * as openai from "openai-legacy";
-import { version } from "../../package.json";
-
-// Anything we don't override we want to pass through to openai directly
-export * as openAILegacy from "openai-legacy";
-
-type OPConfigurationParameters = {
-  apiKey?: string;
-  basePath?: string;
-};
-
-export class Configuration extends openai.Configuration {
-  public qkConfig?: openPipeClient.Configuration;
-
-  constructor(
-    config: openai.ConfigurationParameters & {
-      opParameters?: OPConfigurationParameters;
-    }
-  ) {
-    super(config);
-    if (config.opParameters) {
-      this.qkConfig = new openPipeClient.Configuration(config.opParameters);
-    }
-  }
-}
-
-type CreateChatCompletion = InstanceType<typeof openai.OpenAIApi>["createChatCompletion"];
-
-export class OpenAIApi extends openai.OpenAIApi {
-  public openPipeApi?: openPipeClient.DefaultApi;
-
-  constructor(config: Configuration) {
-    super(config);
-    if (config.qkConfig) {
-      this.openPipeApi = new openPipeClient.DefaultApi(config.qkConfig);
-    }
-  }
-
-  public async createChatCompletion(
-    createChatCompletionRequest: Parameters<CreateChatCompletion>[0],
-    options?: Parameters<CreateChatCompletion>[1]
-  ): ReturnType<CreateChatCompletion> {
-    const requestedAt = Date.now();
-    let resp: Awaited<ReturnType<CreateChatCompletion>> | null = null;
-    let respPayload: openai.CreateChatCompletionResponse | null = null;
-    let statusCode: number | undefined = undefined;
-    let errorMessage: string | undefined;
-    try {
-      resp = await super.createChatCompletion(createChatCompletionRequest, options);
-      respPayload = resp.data;
-      statusCode = resp.status;
-    } catch (err) {
-      console.error("Error in createChatCompletion");
-      if ("isAxiosError" in err && err.isAxiosError) {
-        errorMessage = err.response?.data?.error?.message;
-        respPayload = err.response?.data;
-        statusCode = err.response?.status;
-      } else if ("message" in err) {
-        errorMessage = err.message.toString();
-      }
-      throw err;
-    } finally {
-      this.openPipeApi
-        ?.externalApiReport({
-          requestedAt,
-          receivedAt: Date.now(),
-          reqPayload: createChatCompletionRequest,
-          respPayload: respPayload,
-          statusCode: statusCode,
-          errorMessage,
-          tags: {
-            client: "openai-js",
-            clientVersion: version,
-          },
-        })
-        .catch((err) => {
-          console.error("Error reporting to OP", err);
-        });
-    }
-
-    console.log("done");
-    return resp;
-  }
-}
--- a/client-libs/typescript/tsconfig.json
+++ b/client-libs/typescript/tsconfig.json
@@ -14,9 +14,12 @@
    "isolatedModules": true,
    "incremental": true,
    "noUncheckedIndexedAccess": true,
-    "baseUrl": ".",
-    "outDir": "dist"
+    "noEmit": true,
+    "sourceMap": true,
+    "declaration": true,
+    "declarationMap": true,
+    "rootDir": "."
  },
-  "include": ["src/**/*.ts"],
+  "include": ["**/*.ts"],
  "exclude": ["node_modules"]
 }
--- a/docs/faq/how-reporting-works.mdx
+++ b/docs/faq/how-reporting-works.mdx
@@ -0,0 +1,23 @@
+---
+title: "How reporting works"
+description: "Our SDK wraps calls and forwards requests"
+---
+
+### Does reporting calls add latency to streamed requests?
+
+Streamed requests won't have any added latency. The SDK forwards each streamed token as it's received from the server while
+simultaneously collecting it in the response it will report to your OpenPipe instance once the entire response has been received.
+
+#### Your OpenAI key never leaves your machine.
+
+Calls to OpenAI are carried out by our SDK **on your machine**, meaning that your API key is secure, and you'll
+continue getting uninterrupted inference even if your OpenPipe instance goes down.
+
+## <br />
+
+### Want to dig deeper? Take a peek in our open-source code.
+
+We benefit from a growing community of developers and customers who are
+dedicated to improving the OpenPipe experience. Our [open source repo](https://github.com/openpipe/openpipe)
+is an opportunity for developers to confirm the quality of our offering
+and to make improvements when they can.
--- a/docs/favicon.webp
+++ b/docs/favicon.webp
--- a/docs/features/experiments.mdx
+++ b/docs/features/experiments.mdx
@@ -0,0 +1,8 @@
+---
+title: "Experiments"
+description: "
+Template multiple scenarios into combinations of prompts and models to compare their output. Use flexible regex and GPT-4 evaluations to assess completion quality.
+Quickly iterate and spot model shortcomings before deployment."
+---
+
+<Frame>![](/images/features/experiments.png)</Frame>
--- a/docs/features/exporting-data.mdx
+++ b/docs/features/exporting-data.mdx
@@ -0,0 +1,8 @@
+---
+title: "Export Data - Beta"
+sidebarTitle: "Export Data"
+description: "
+Export your past requests as a JSONL file in an Alpaca or OpenAI fine-tuning format or in their raw form."
+---
+
+<Frame>![](/images/features/exporting-data.png)</Frame>
--- a/docs/features/fine-tuning.mdx
+++ b/docs/features/fine-tuning.mdx
@@ -0,0 +1,8 @@
+---
+title: "Fine Tuning - Beta"
+sidebarTitle: "Fine Tuning"
+description: "
+Fine tune your data on specific logs. Filter by prompt id and exclude requests with an undesirable output."
+---
+
+<Frame>![](/images/features/fine-tuning.png)</Frame>
--- a/docs/features/log-filters.mdx
+++ b/docs/features/log-filters.mdx
@@ -0,0 +1,7 @@
+---
+title: "Log Filters"
+description: "
+Search and filter your past LLM requests to inspect your responses and build a training dataset."
+---
+
+<Frame>![](/images/features/log-filters.png)</Frame>
--- a/docs/getting-started/openpipe-sdk.mdx
+++ b/docs/getting-started/openpipe-sdk.mdx
@@ -0,0 +1,114 @@
+---
+title: "Installing the SDK"
+---
+
+Use the OpenPipe SDK as a drop-in replacement for the generic OpenAI package. We currently support logging OpenAI calls and support for more LLM providers will be added soon.
+
+<Tabs>
+  <Tab title="Python">
+
+Find the SDK at https://pypi.org/project/openpipe/
+
+## Simple Integration
+
+Add `OPENPIPE_API_KEY` to your environment variables.
+
+```bash
+export OPENPIPE_API_KEY=opk-<your-api-key>
+# Or you can set it in your code, as shown in the example below
+```
+
+Replace this line
+
+```python
+from openai import openai
+```
+
+with this one
+
+```python
+from openpipe import openai
+```
+
+## Adding Searchable Tags
+
+OpenPipe has a concept of "tagging." This is very useful for grouping a certain set of completions together.
+When you're using a dataset for fine-tuning, you can select all the prompts that match a certain set of tags. Here's how you can use the tagging feature:
+
+```python
+from openpipe import openai, configure_openpipe
+import os
+
+# If you have the `OPENPIPE_API_KEY` environment variable set
+# we'll read from it by default.
+configure_openpipe(api_key=os.getenv("OPENPIPE_API_KEY"))
+
+# Configure OpenAI the same way you would normally
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+completion = openai.ChatCompletion.create(
+    model="gpt-3.5-turbo",
+    messages=[{"role": "system", "content": "count to 10"}],
+    openpipe={"tags": {"prompt_id": "counting", "any_key": "any_value"}},
+)
+
+```
+
+  </Tab>
+  <Tab title="NodeJS">
+
+Find the SDK at https://www.npmjs.com/package/openpipe
+
+## Simple Integration
+
+Add `OPENPIPE_API_KEY` to your environment variables.
+
+```bash
+export OPENPIPE_API_KEY=opk-<your-api-key>
+# Or you can set it in your code, as shown in the example below
+```
+
+Replace this line
+
+```typescript
+import OpenAI from "openai";
+```
+
+with this one
+
+```typescript
+import OpenAI from "openpipe/openai";
+```
+
+## Adding Searchable Tags
+
+OpenPipe has a concept of "tagging." This is very useful for grouping a certain set of completions together.
+When you're using a dataset for fine-tuning, you can select all the prompts that match a certain set of tags. Here's how you can use the tagging feature:
+
+```typescript
+// Fully compatible with original OpenAI initialization
+const openai = new OpenAI({
+  apiKey: "my api key", // defaults to process.env["OPENAI_API_KEY"]
+  // openpipe key is optional
+  openpipe: {
+    apiKey: "my api key", // defaults to process.env["OPENPIPE_API_KEY"]
+    baseUrl: "my url", // defaults to process.env["OPENPIPE_BASE_URL"] or https://app.openpipe.ai/api/v1 if not set
+  },
+});
+
+const completion = await openai.chat.completions.create({
+  messages: [{ role: "user", content: "Count to 10" }],
+  model: "gpt-3.5-turbo",
+  // optional
+  openpipe: {
+    // Add custom searchable tags
+    tags: {
+      prompt_id: "counting",
+      any_key: "any_value",
+    },
+  },
+});
+```
+
+  </Tab>
+</Tabs>
--- a/docs/getting-started/quick-start.mdx
+++ b/docs/getting-started/quick-start.mdx
@@ -0,0 +1,35 @@
+---
+title: "Quick Start"
+description: "Get started with OpenPipe in a few quick steps."
+---
+
+## Step 1: Create your OpenPipe Account
+
+If you don't already have one, create an account with OpenPipe at https://app.openpipe.ai/. You can sign up with GitHub, so you don't need to remember an extra password.
+
+## Step 2: Find your Project API key
+
+In order to capture your calls and fine-tune a model on them, we need an API key to authenticate you and determine which project to store your logs under.
+
+<Note>
+  When you created your account, a project was automatically configured for you as well. Find its
+  API key at https://app.openpipe.ai/project/settings.
+</Note>
+
+## Step 3: Integrate the OpenPipe SDK
+
+You're done with the hard part! Learn how to integrate the OpenPipe SDK on the next page.
+
+<CardGroup cols={2}>
+  <Card
+    title="OpenPipe SDK"
+    icon={
+      <svg role="img" viewBox="0 0 24 24" xmlns="http://www.w3.org/2000/svg">
+        <title>OpenPipe</title>
+        <path d="M22.2819 9.8211a5.9847 5.9847 0 0 0-.5157-4.9108 6.0462 6.0462 0 0 0-6.5098-2.9A6.0651 6.0651 0 0 0 4.9807 4.1818a5.9847 5.9847 0 0 0-3.9977 2.9 6.0462 6.0462 0 0 0 .7427 7.0966 5.98 5.98 0 0 0 .511 4.9107 6.051 6.051 0 0 0 6.5146 2.9001A5.9847 5.9847 0 0 0 13.2599 24a6.0557 6.0557 0 0 0 5.7718-4.2058 5.9894 5.9894 0 0 0 3.9977-2.9001 6.0557 6.0557 0 0 0-.7475-7.0729zm-9.022 12.6081a4.4755 4.4755 0 0 1-2.8764-1.0408l.1419-.0804 4.7783-2.7582a.7948.7948 0 0 0 .3927-.6813v-6.7369l2.02 1.1686a.071.071 0 0 1 .038.052v5.5826a4.504 4.504 0 0 1-4.4945 4.4944zm-9.6607-4.1254a4.4708 4.4708 0 0 1-.5346-3.0137l.142.0852 4.783 2.7582a.7712.7712 0 0 0 .7806 0l5.8428-3.3685v2.3324a.0804.0804 0 0 1-.0332.0615L9.74 19.9502a4.4992 4.4992 0 0 1-6.1408-1.6464zM2.3408 7.8956a4.485 4.485 0 0 1 2.3655-1.9728V11.6a.7664.7664 0 0 0 .3879.6765l5.8144 3.3543-2.0201 1.1685a.0757.0757 0 0 1-.071 0l-4.8303-2.7865A4.504 4.504 0 0 1 2.3408 7.872zm16.5963 3.8558L13.1038 8.364 15.1192 7.2a.0757.0757 0 0 1 .071 0l4.8303 2.7913a4.4944 4.4944 0 0 1-.6765 8.1042v-5.6772a.79.79 0 0 0-.407-.667zm2.0107-3.0231l-.142-.0852-4.7735-2.7818a.7759.7759 0 0 0-.7854 0L9.409 9.2297V6.8974a.0662.0662 0 0 1 .0284-.0615l4.8303-2.7866a4.4992 4.4992 0 0 1 6.6802 4.66zM8.3065 12.863l-2.02-1.1638a.0804.0804 0 0 1-.038-.0567V6.0742a4.4992 4.4992 0 0 1 7.3757-3.4537l-.142.0805L8.704 5.459a.7948.7948 0 0 0-.3927.6813zm1.0976-2.3654l2.602-1.4998 2.6069 1.4998v2.9994l-2.5974 1.4997-2.6067-1.4997Z" />
+      </svg>
+    }
+    iconType="duotone"
+    href="/getting-started/openpipe-sdk"
+  ></Card>
+</CardGroup>
--- a/docs/images/features/experiments.png
+++ b/docs/images/features/experiments.png
--- a/docs/images/features/exporting-data.png
+++ b/docs/images/features/exporting-data.png
--- a/docs/images/features/fine-tuning.png
+++ b/docs/images/features/fine-tuning.png
--- a/docs/images/features/log-filters.png
+++ b/docs/images/features/log-filters.png
--- a/docs/images/intro/request-logs.png
+++ b/docs/images/intro/request-logs.png
--- a/docs/introduction.mdx
+++ b/docs/introduction.mdx
@@ -0,0 +1,18 @@
+---
+title: "OpenPipe Documentation"
+sidebarTitle: "Introduction"
+description: "
+Product-focused teams use OpenPipe's seamless fine-tuning and monitoring services to decrease the cost and latency of their LLM operations. 
+You can use OpenPipe to collect and analyze LLM logs, create fine-tuned models, and compare output from multiple models given the same input."
+---
+
+<Frame>![](/images/intro/request-logs.png)</Frame>
+
+<CardGroup cols={2}>
+  <Card title="Get Started" icon="code">
+    Quickly integrate the OpenPipe SDK into your application and start collecting data.
+  </Card>
+  <Card title="Features" icon="lightbulb">
+    View the platform features OpenPipe provides and learn how to use them.
+  </Card>
+</CardGroup>
--- a/docs/logo/dark.svg
+++ b/docs/logo/dark.svg
--- a/docs/logo/light.svg
+++ b/docs/logo/light.svg
--- a/docs/mint.json
+++ b/docs/mint.json
@@ -0,0 +1,65 @@
+{
+  "name": "OpenPipe",
+  "logo": {
+    "light": "/logo/light.svg",
+    "dark": "/logo/dark.svg"
+  },
+  "favicon": "/favicon.webp",
+  "colors": {
+    "primary": "#FF5733",
+    "light": "#FF5733",
+    "dark": "#FF5733"
+  },
+  "modeToggle": {
+    "default": "light"
+  },
+  "topbarCtaButton": {
+    "name": "Sign In",
+    "url": "https://app.openpipe.ai"
+  },
+  "anchors": [
+    {
+      "name": "GitHub",
+      "icon": "github",
+      "url": "https://github.com/openpipe/openpipe"
+    }
+  ],
+  "feedback": {
+    "suggestEdit": true,
+    "raiseIssue": true
+  },
+  "navigation": [
+    {
+      "group": "Welcome",
+      "pages": ["introduction", "overview"]
+    },
+    {
+      "group": "Getting Started",
+      "pages": ["getting-started/quick-start", "getting-started/openpipe-sdk"]
+    },
+    {
+      "group": "Features",
+      "pages": [
+        "features/log-filters",
+        "features/exporting-data",
+        "features/fine-tuning",
+        "features/experiments"
+      ]
+    },
+    {
+      "group": "FAQ",
+      "pages": ["faq/how-reporting-works"]
+    }
+  ],
+  "topbarLinks": [
+    {
+      "name": "Github",
+      "url": "https://github.com/OpenPipe/OpenPipe"
+    }
+  ],
+  "footerSocials": {
+    "twitter": "https://twitter.com/OpenPipeAI",
+    "linkedin": "https://www.linkedin.com/company/openpipe/about/",
+    "github": "https://github.com/OpenPipe/OpenPipe"
+  }
+}
--- a/docs/overview.mdx
+++ b/docs/overview.mdx
@@ -0,0 +1,30 @@
+---
+title: "Overview"
+description: "OpenPipe is a streamlined platform designed to help product-focused teams train specialized LLM models as replacements for slow and expensive prompts."
+---
+
+## Who We Are
+
+We're a team of full-stack engineers and machine learning researchers working to streamline the process of integrating fine-tuned models into any application. Our goal is to make the fine-tuning process accessible to everyone.
+
+## What We Provide
+
+Here are a few of the features we offer:
+
+- **Data Capture**: OpenPipe automatically captures every request and response sent through our drop-in replacement sdk and stores it for your future use.
+
+- **Monitoring**: OpenPipe provides intuitive tools to view the frequency and cost of your LLM requests, and provides a special tool for viewing requests with error status codes.
+
+- **Searchable Logs**: We enable you to search your past requests, and provide a simple protocol for tagging them by prompt id for easy filtering.
+
+- **Fine-Tuning**: With all your LLM requests and responses in one place, it's easy to select the data you want to fine-tune on and kick off a job.
+
+- **Model Hosting**: After we've trained your model, OpenPipe will automatically begin hosting it. Accessing your model will require an API key from your project.
+
+- **Unified SDK**: Switching requests from your previous LLM provider to your new model is as simple as changing the model name. All our models implement the OpenAI inference format, so you won't have to change how you parse its response.
+
+- **Data Export**: OpenPipe allows you to download your request logs or the fine-tuned models you've trained at any time for easy self-hosting.
+
+- **Experimentation**: The fine-tunes you've created on OpenPipe are immediately available for you to run inference on in our experimentation playground.
+
+Welcome to the OpenPipe community!
--- a/examples/.gitignore
+++ b/examples/.gitignore
@@ -1,6 +1,4 @@
 axolotl/
 models/
 data/
-wandb/
-cache/
-.ipynb_checkpoints/
+wandb/
--- a/examples/classify-recipes/.ipynb_checkpoints/benchmark-checkpoint.ipynb
+++ b/examples/classify-recipes/.ipynb_checkpoints/benchmark-checkpoint.ipynb
@@ -0,0 +1,473 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Current Time: 2023-08-24 21:25:06\n",
+      "Current Time: 2023-08-24 21:25:36\n"
+     ]
+    }
+   ],
+   "source": [
+    "import time\n",
+    "\n",
+    "while True:\n",
+    "    current_time = time.strftime(\"%Y-%m-%d %H:%M:%S\", time.localtime())\n",
+    "    print(f\"Current Time: {current_time}\")\n",
+    "    time.sleep(30)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "I'm pretty happy with my model's accuracy relative to GPT-4. How does it compare cost-wise?\n",
+    "\n",
+    "I'll really push this to its limits -- let's see how quickly our poor model can classify the [full 2-million-recipe dataset](https://huggingface.co/datasets/corbt/all-recipes) 😈."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: datasets==2.14.4 in /usr/local/lib/python3.10/dist-packages (2.14.4)\n",
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+      "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets==2.14.4) (1.24.4)\n",
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+      "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets==2.14.4) (2.0.3)\n",
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+      "Requirement already satisfied: ninja in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (1.11.1)\n",
+      "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (5.9.5)\n",
+      "Requirement already satisfied: ray>=2.5.1 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (2.6.3)\n",
+      "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.1.99)\n",
+      "Requirement already satisfied: torch>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (2.0.1+cu118)\n",
+      "Requirement already satisfied: transformers>=4.31.0 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (4.33.0.dev0)\n",
+      "Requirement already satisfied: xformers>=0.0.19 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.0.21)\n",
+      "Requirement already satisfied: fastapi in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.101.1)\n",
+      "Requirement already satisfied: uvicorn in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.23.2)\n",
+      "Requirement already satisfied: pydantic<2 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (1.10.12)\n",
+      "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (23.1.0)\n",
+      "Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (2.1.1)\n",
+      "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (6.0.4)\n",
+      "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (4.0.3)\n",
+      "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (1.9.2)\n",
+      "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (1.4.0)\n",
+      "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (1.3.1)\n",
+      "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0.0,>=0.14.0->datasets==2.14.4) (3.9.0)\n",
+      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0.0,>=0.14.0->datasets==2.14.4) (4.7.1)\n",
+      "Requirement already satisfied: click>=7.0 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (8.1.7)\n",
+      "Requirement already satisfied: jsonschema in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (4.18.0)\n",
+      "Requirement already satisfied: msgpack<2.0.0,>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (1.0.5)\n",
+      "Requirement already satisfied: protobuf!=3.19.5,>=3.15.3 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (4.24.1)\n",
+      "Requirement already satisfied: grpcio>=1.42.0 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (1.57.0)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets==2.14.4) (3.4)\n",
+      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets==2.14.4) (1.26.13)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets==2.14.4) (2022.12.7)\n",
+      "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (1.11.1)\n",
+      "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (3.0)\n",
+      "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (3.1.2)\n",
+      "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (2.0.0)\n",
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+      "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.31.0->vllm==0.1.3) (0.13.3)\n",
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+      "Requirement already satisfied: starlette<0.28.0,>=0.27.0 in /usr/local/lib/python3.10/dist-packages (from fastapi->vllm==0.1.3) (0.27.0)\n",
+      "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets==2.14.4) (2.8.2)\n",
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+      "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=2.0.0->vllm==0.1.3) (2.1.2)\n",
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+      "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema->ray>=2.5.1->vllm==0.1.3) (0.29.1)\n",
+      "Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema->ray>=2.5.1->vllm==0.1.3) (0.8.10)\n",
+      "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=2.0.0->vllm==0.1.3) (1.2.1)\n",
+      "Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.28.0,>=0.27.0->fastapi->vllm==0.1.3) (1.3.0)\n",
+      "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.28.0,>=0.27.0->fastapi->vllm==0.1.3) (1.1.2)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+      "\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.1.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "%pip install datasets==2.14.4 vllm==0.1.3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of recipes: 2,147,248\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset\n",
+    "\n",
+    "all_recipes = load_dataset(\"corbt/all-recipes\")[\"train\"][\"input\"]\n",
+    "\n",
+    "print(f\"Number of recipes: {len(all_recipes):,}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO 08-24 19:38:29 llm_engine.py:70] Initializing an LLM engine with config: model='./models/run1/merged', tokenizer='./models/run1/merged', tokenizer_mode=auto, trust_remote_code=False, dtype=torch.float16, use_dummy_weights=False, download_dir=None, use_np_weights=False, tensor_parallel_size=1, seed=0)\n",
+      "INFO 08-24 19:39:48 llm_engine.py:196] # GPU blocks: 3419, # CPU blocks: 512\n"
+     ]
+    }
+   ],
+   "source": [
+    "from vllm import LLM, SamplingParams\n",
+    "\n",
+    "llm = LLM(model=\"./models/run1/merged\", max_num_batched_tokens=4096)\n",
+    "\n",
+    "sampling_params = SamplingParams(\n",
+    "    # 120 should be fine for the work we're doing here.\n",
+    "    max_tokens=120,\n",
+    "    # This is a deterministic task so temperature=0 is best.\n",
+    "    temperature=0,\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Start time: 1692906050.3340027\n",
+      "Processing recipes 0 to 10,000...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processed prompts: 100%|██████████| 10000/10000 [04:51<00:00, 34.30it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing recipes 10,000 to 20,000...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processed prompts: 100%|██████████| 10000/10000 [04:54<00:00, 33.98it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing recipes 20,000 to 30,000...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processed prompts: 100%|██████████| 10000/10000 [04:53<00:00, 34.11it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing recipes 30,000 to 40,000...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processed prompts: 100%|██████████| 10000/10000 [04:53<00:00, 34.11it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing recipes 40,000 to 50,000...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processed prompts:  48%|████▊     | 4796/10000 [02:21<03:18, 26.22it/s]"
+     ]
+    },
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[6], line 12\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[39mfor\u001b[39;00m i \u001b[39min\u001b[39;00m \u001b[39mrange\u001b[39m(\u001b[39m0\u001b[39m, \u001b[39mlen\u001b[39m(all_recipes), BATCH_SIZE):\n\u001b[1;32m     11\u001b[0m     \u001b[39mprint\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mProcessing recipes \u001b[39m\u001b[39m{\u001b[39;00mi\u001b[39m:\u001b[39;00m\u001b[39m,\u001b[39m\u001b[39m}\u001b[39;00m\u001b[39m to \u001b[39m\u001b[39m{\u001b[39;00mi\u001b[39m+\u001b[39mBATCH_SIZE\u001b[39m:\u001b[39;00m\u001b[39m,\u001b[39m\u001b[39m}\u001b[39;00m\u001b[39m...\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m---> 12\u001b[0m     outputs \u001b[39m=\u001b[39m llm\u001b[39m.\u001b[39;49mgenerate(all_recipes[i:i\u001b[39m+\u001b[39;49mBATCH_SIZE], sampling_params\u001b[39m=\u001b[39;49msampling_params)\n\u001b[1;32m     14\u001b[0m     all_outputs\u001b[39m.\u001b[39mextend([o\u001b[39m.\u001b[39moutputs[\u001b[39m0\u001b[39m]\u001b[39m.\u001b[39mtext \u001b[39mfor\u001b[39;00m o \u001b[39min\u001b[39;00m outputs])\n\u001b[1;32m     16\u001b[0m end_time \u001b[39m=\u001b[39m time\u001b[39m.\u001b[39mtime()\n",
+      "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/llm.py:130\u001b[0m, in \u001b[0;36mLLM.generate\u001b[0;34m(self, prompts, sampling_params, prompt_token_ids, use_tqdm)\u001b[0m\n\u001b[1;32m    128\u001b[0m         token_ids \u001b[39m=\u001b[39m prompt_token_ids[i]\n\u001b[1;32m    129\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_add_request(prompt, sampling_params, token_ids)\n\u001b[0;32m--> 130\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_run_engine(use_tqdm)\n",
+      "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/llm.py:150\u001b[0m, in \u001b[0;36mLLM._run_engine\u001b[0;34m(self, use_tqdm)\u001b[0m\n\u001b[1;32m    148\u001b[0m outputs: List[RequestOutput] \u001b[39m=\u001b[39m []\n\u001b[1;32m    149\u001b[0m \u001b[39mwhile\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mllm_engine\u001b[39m.\u001b[39mhas_unfinished_requests():\n\u001b[0;32m--> 150\u001b[0m     step_outputs \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mllm_engine\u001b[39m.\u001b[39;49mstep()\n\u001b[1;32m    151\u001b[0m     \u001b[39mfor\u001b[39;00m output \u001b[39min\u001b[39;00m step_outputs:\n\u001b[1;32m    152\u001b[0m         \u001b[39mif\u001b[39;00m output\u001b[39m.\u001b[39mfinished:\n",
+      "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/vllm/engine/llm_engine.py:313\u001b[0m, in \u001b[0;36mLLMEngine.step\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    307\u001b[0m     \u001b[39mreturn\u001b[39;00m [\n\u001b[1;32m    308\u001b[0m         RequestOutput\u001b[39m.\u001b[39mfrom_seq_group(seq_group)\n\u001b[1;32m    309\u001b[0m         \u001b[39mfor\u001b[39;00m seq_group \u001b[39min\u001b[39;00m scheduler_outputs\u001b[39m.\u001b[39mignored_seq_groups\n\u001b[1;32m    310\u001b[0m     ]\n\u001b[1;32m    312\u001b[0m \u001b[39m# Execute the model.\u001b[39;00m\n\u001b[0;32m--> 313\u001b[0m output \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_run_workers(\n\u001b[1;32m    314\u001b[0m     \u001b[39m\"\u001b[39;49m\u001b[39mexecute_model\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m    315\u001b[0m     seq_group_metadata_list\u001b[39m=\u001b[39;49mseq_group_metadata_list,\n\u001b[1;32m    316\u001b[0m     blocks_to_swap_in\u001b[39m=\u001b[39;49mscheduler_outputs\u001b[39m.\u001b[39;49mblocks_to_swap_in,\n\u001b[1;32m    317\u001b[0m     blocks_to_swap_out\u001b[39m=\u001b[39;49mscheduler_outputs\u001b[39m.\u001b[39;49mblocks_to_swap_out,\n\u001b[1;32m    318\u001b[0m     blocks_to_copy\u001b[39m=\u001b[39;49mscheduler_outputs\u001b[39m.\u001b[39;49mblocks_to_copy,\n\u001b[1;32m    319\u001b[0m )\n\u001b[1;32m    320\u001b[0m \u001b[39m# Update the scheduler with the model outputs.\u001b[39;00m\n\u001b[1;32m    321\u001b[0m seq_groups \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mscheduler\u001b[39m.\u001b[39mupdate(output)\n",
+      "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/vllm/engine/llm_engine.py:470\u001b[0m, in \u001b[0;36mLLMEngine._run_workers\u001b[0;34m(self, method, get_all_outputs, *args, **kwargs)\u001b[0m\n\u001b[1;32m    467\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[1;32m    468\u001b[0m         executor \u001b[39m=\u001b[39m \u001b[39mgetattr\u001b[39m(worker, method)\n\u001b[0;32m--> 470\u001b[0m     output \u001b[39m=\u001b[39m executor(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m    471\u001b[0m     all_outputs\u001b[39m.\u001b[39mappend(output)\n\u001b[1;32m    473\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mparallel_config\u001b[39m.\u001b[39mworker_use_ray:\n",
+      "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py:115\u001b[0m, in \u001b[0;36mcontext_decorator.<locals>.decorate_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    112\u001b[0m \u001b[39m@functools\u001b[39m\u001b[39m.\u001b[39mwraps(func)\n\u001b[1;32m    113\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mdecorate_context\u001b[39m(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs):\n\u001b[1;32m    114\u001b[0m     \u001b[39mwith\u001b[39;00m ctx_factory():\n\u001b[0;32m--> 115\u001b[0m         \u001b[39mreturn\u001b[39;00m func(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
+      "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/vllm/worker/worker.py:293\u001b[0m, in \u001b[0;36mWorker.execute_model\u001b[0;34m(self, seq_group_metadata_list, blocks_to_swap_in, blocks_to_swap_out, blocks_to_copy)\u001b[0m\n\u001b[1;32m    289\u001b[0m input_tokens, input_positions, input_metadata \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_prepare_inputs(\n\u001b[1;32m    290\u001b[0m     seq_group_metadata_list)\n\u001b[1;32m    292\u001b[0m \u001b[39m# Execute the model.\u001b[39;00m\n\u001b[0;32m--> 293\u001b[0m output \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mmodel(\n\u001b[1;32m    294\u001b[0m     input_ids\u001b[39m=\u001b[39;49minput_tokens,\n\u001b[1;32m    295\u001b[0m     positions\u001b[39m=\u001b[39;49minput_positions,\n\u001b[1;32m    296\u001b[0m     kv_caches\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mgpu_cache,\n\u001b[1;32m    297\u001b[0m     input_metadata\u001b[39m=\u001b[39;49minput_metadata,\n\u001b[1;32m    298\u001b[0m     cache_events\u001b[39m=\u001b[39;49mcache_events,\n\u001b[1;32m    299\u001b[0m )\n\u001b[1;32m    300\u001b[0m \u001b[39mreturn\u001b[39;00m output\n",
+      "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:1501\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1496\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1497\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1498\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_pre_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m   1499\u001b[0m         \u001b[39mor\u001b[39;00m _global_backward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1500\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1501\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1502\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1503\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
+      "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/vllm/model_executor/models/llama.py:255\u001b[0m, in \u001b[0;36mLlamaForCausalLM.forward\u001b[0;34m(self, input_ids, positions, kv_caches, input_metadata, cache_events)\u001b[0m\n\u001b[1;32m    245\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\n\u001b[1;32m    246\u001b[0m     \u001b[39mself\u001b[39m,\n\u001b[1;32m    247\u001b[0m     input_ids: torch\u001b[39m.\u001b[39mTensor,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    251\u001b[0m     cache_events: Optional[List[torch\u001b[39m.\u001b[39mcuda\u001b[39m.\u001b[39mEvent]],\n\u001b[1;32m    252\u001b[0m ) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m Dict[\u001b[39mint\u001b[39m, SequenceOutputs]:\n\u001b[1;32m    253\u001b[0m     hidden_states \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mmodel(input_ids, positions, kv_caches,\n\u001b[1;32m    254\u001b[0m                                input_metadata, cache_events)\n\u001b[0;32m--> 255\u001b[0m     next_tokens \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49msampler(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mlm_head\u001b[39m.\u001b[39;49mweight, hidden_states,\n\u001b[1;32m    256\u001b[0m                                input_metadata)\n\u001b[1;32m    257\u001b[0m     \u001b[39mreturn\u001b[39;00m next_tokens\n",
+      "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:1501\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1496\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1497\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1498\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_pre_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m   1499\u001b[0m         \u001b[39mor\u001b[39;00m _global_backward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1500\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1501\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1502\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1503\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
+      "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/vllm/model_executor/layers/sampler.py:44\u001b[0m, in \u001b[0;36mSampler.forward\u001b[0;34m(self, embedding, hidden_states, input_metadata, embedding_bias)\u001b[0m\n\u001b[1;32m     36\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\n\u001b[1;32m     37\u001b[0m     \u001b[39mself\u001b[39m,\n\u001b[1;32m     38\u001b[0m     embedding: torch\u001b[39m.\u001b[39mTensor,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     42\u001b[0m ) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m Dict[\u001b[39mint\u001b[39m, SequenceOutputs]:\n\u001b[1;32m     43\u001b[0m     \u001b[39m# Get the hidden states that we use for sampling.\u001b[39;00m\n\u001b[0;32m---> 44\u001b[0m     hidden_states \u001b[39m=\u001b[39m _prune_hidden_states(hidden_states, input_metadata)\n\u001b[1;32m     46\u001b[0m     \u001b[39m# Get the logits for the next tokens.\u001b[39;00m\n\u001b[1;32m     47\u001b[0m     logits \u001b[39m=\u001b[39m torch\u001b[39m.\u001b[39mmatmul(hidden_states, embedding\u001b[39m.\u001b[39mt())\n",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
+     ]
+    }
+   ],
+   "source": [
+    "# We'll process our recipes in batches of 10,000.\n",
+    "\n",
+    "import time\n",
+    "\n",
+    "BATCH_SIZE = 10000\n",
+    "all_outputs = []\n",
+    "\n",
+    "start_time = time.time()\n",
+    "print(f\"Start time: {start_time}\")\n",
+    "for i in range(0, len(all_recipes), BATCH_SIZE):\n",
+    "    print(f\"Processing recipes {i:,} to {i+BATCH_SIZE:,}...\")\n",
+    "    outputs = llm.generate(\n",
+    "        all_recipes[i : i + BATCH_SIZE], sampling_params=sampling_params\n",
+    "    )\n",
+    "\n",
+    "    all_outputs.extend([o.outputs[0].text for o in outputs])\n",
+    "\n",
+    "end_time = time.time()\n",
+    "print(f\"End time: {end_time}\")\n",
+    "print(f\"Total hours: {((end_time - start_time) / 3600):.2f}\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nice! I've processed all 2,147,248 recipes in under 17 hours. Let's do a cost comparison with GPT-3.5 and GPT-4. I'll use the GPT-4 latency/cost numbers based on the 5000 samples used to generate our model's training data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Model</th>\n",
+       "      <th>Cost to Classify One Recipe</th>\n",
+       "      <th>Cost to Classify Entire Dataset</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Llama 2 7B (finetuned)</td>\n",
+       "      <td>0.000009</td>\n",
+       "      <td>18.86</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>GPT-3.5</td>\n",
+       "      <td>0.000481</td>\n",
+       "      <td>1,033.26</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>GPT-3.5 (finetuned)</td>\n",
+       "      <td>0.004044</td>\n",
+       "      <td>8,683.47</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>GPT-4</td>\n",
+       "      <td>0.010800</td>\n",
+       "      <td>23,190.28</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                    Model  Cost to Classify One Recipe  \\\n",
+       "0  Llama 2 7B (finetuned)                     0.000009   \n",
+       "1                 GPT-3.5                     0.000481   \n",
+       "2     GPT-3.5 (finetuned)                     0.004044   \n",
+       "3                   GPT-4                     0.010800   \n",
+       "\n",
+       "  Cost to Classify Entire Dataset  \n",
+       "0                           18.86  \n",
+       "1                        1,033.26  \n",
+       "2                        8,683.47  \n",
+       "3                       23,190.28  "
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# I used an on-demand Nvidia L40 on RunPod for this, at an hourly cost of $1.14.\n",
+    "finetuned_hourly_cost = 1.14\n",
+    "\n",
+    "finetuned_total_hours = 16.54\n",
+    "\n",
+    "finetuned_avg_cost = finetuned_hourly_cost * finetuned_total_hours / len(all_recipes)\n",
+    "\n",
+    "# The average input and output tokens calculated by OpenAI, based on the 5000 recipes I sent them\n",
+    "avg_input_tokens = 276\n",
+    "avg_output_tokens = 42\n",
+    "\n",
+    "# Token pricing from https://openai.com/pricing\n",
+    "gpt_4_avg_cost = avg_input_tokens * 0.03 / 1000 + avg_output_tokens * 0.06 / 1000\n",
+    "\n",
+    "gpt_35_avg_cost = avg_input_tokens * 0.0015 / 1000 + avg_output_tokens * 0.0016 / 1000\n",
+    "\n",
+    "gpt_35_finetuned_avg_cost = (\n",
+    "    avg_input_tokens * 0.012 / 1000 + avg_output_tokens * 0.016 / 1000 + 0.06 / 1000\n",
+    ")\n",
+    "\n",
+    "# Multiply the number of recipes\n",
+    "# gpt_4_cost = len(all_recipes) * gpt_4_avg_cost\n",
+    "# gpt_35_cost = len(all_recipes) * gpt_35_avg_cost\n",
+    "# gpt_35_finetuned_cost = len(all_recipes) * gpt_35_finetuned_avg_cost\n",
+    "\n",
+    "# Let's put this in a dataframe for easier comparison.\n",
+    "\n",
+    "costs = pd.DataFrame(\n",
+    "    {\n",
+    "        \"Model\": [\n",
+    "            \"Llama 2 7B (finetuned)\",\n",
+    "            \"GPT-3.5\",\n",
+    "            \"GPT-3.5 (finetuned)\",\n",
+    "            \"GPT-4\",\n",
+    "        ],\n",
+    "        \"Cost to Classify One Recipe\": [\n",
+    "            finetuned_avg_cost,\n",
+    "            gpt_35_avg_cost,\n",
+    "            gpt_35_finetuned_avg_cost,\n",
+    "            gpt_4_avg_cost,\n",
+    "        ],\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "costs[\"Cost to Classify Entire Dataset\"] = (\n",
+    "    costs[\"Cost to Classify One Recipe\"] * len(all_recipes)\n",
+    ").map(lambda x: f\"{x:,.2f}\")\n",
+    "\n",
+    "\n",
+    "costs\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "...and just for fun, let's figure out how many recipes my pescatarian basement-dwelling brother can make! 😂"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
--- a/examples/classify-recipes/4-benchmark.ipynb
+++ b/examples/classify-recipes/4-benchmark.ipynb
@@ -6,22 +6,104 @@
   "source": [
    "I'm pretty happy with my model's accuracy relative to GPT-4. How does it compare cost-wise?\n",
    "\n",
-    "I'll really push this to its limits -- let's see how quickly our poor model can classify the [full 2-million-recipe dataset](https://huggingface.co/datasets/corbt/all-recipes) 😈.\n"
+    "I'll really push this to its limits -- let's see how quickly our poor model can classify the [full 2-million-recipe dataset](https://huggingface.co/datasets/corbt/all-recipes) 😈."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: datasets==2.14.4 in /usr/local/lib/python3.10/dist-packages (2.14.4)\n",
+      "Requirement already satisfied: vllm==0.1.3 in /usr/local/lib/python3.10/dist-packages (0.1.3)\n",
+      "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets==2.14.4) (1.24.4)\n",
+      "Requirement already satisfied: pyarrow>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets==2.14.4) (12.0.1)\n",
+      "Requirement already satisfied: dill<0.3.8,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from datasets==2.14.4) (0.3.7)\n",
+      "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets==2.14.4) (2.0.3)\n",
+      "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from datasets==2.14.4) (2.28.1)\n",
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+      "Requirement already satisfied: multiprocess in /usr/local/lib/python3.10/dist-packages (from datasets==2.14.4) (0.70.15)\n",
+      "Requirement already satisfied: fsspec[http]>=2021.11.1 in /usr/local/lib/python3.10/dist-packages (from datasets==2.14.4) (2023.6.0)\n",
+      "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets==2.14.4) (3.8.5)\n",
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+      "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets==2.14.4) (23.1)\n",
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+      "Requirement already satisfied: ninja in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (1.11.1)\n",
+      "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (5.9.5)\n",
+      "Requirement already satisfied: ray>=2.5.1 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (2.6.3)\n",
+      "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.1.99)\n",
+      "Requirement already satisfied: torch>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (2.0.1+cu118)\n",
+      "Requirement already satisfied: transformers>=4.31.0 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (4.33.0.dev0)\n",
+      "Requirement already satisfied: xformers>=0.0.19 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.0.21)\n",
+      "Requirement already satisfied: fastapi in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.101.1)\n",
+      "Requirement already satisfied: uvicorn in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.23.2)\n",
+      "Requirement already satisfied: pydantic<2 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (1.10.12)\n",
+      "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (23.1.0)\n",
+      "Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (2.1.1)\n",
+      "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (6.0.4)\n",
+      "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (4.0.3)\n",
+      "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (1.9.2)\n",
+      "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (1.4.0)\n",
+      "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets==2.14.4) (1.3.1)\n",
+      "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0.0,>=0.14.0->datasets==2.14.4) (3.9.0)\n",
+      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0.0,>=0.14.0->datasets==2.14.4) (4.7.1)\n",
+      "Requirement already satisfied: click>=7.0 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (8.1.7)\n",
+      "Requirement already satisfied: jsonschema in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (4.18.0)\n",
+      "Requirement already satisfied: msgpack<2.0.0,>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (1.0.5)\n",
+      "Requirement already satisfied: protobuf!=3.19.5,>=3.15.3 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (4.24.1)\n",
+      "Requirement already satisfied: grpcio>=1.42.0 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (1.57.0)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets==2.14.4) (3.4)\n",
+      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets==2.14.4) (1.26.13)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets==2.14.4) (2022.12.7)\n",
+      "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (1.11.1)\n",
+      "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (3.0)\n",
+      "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (3.1.2)\n",
+      "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (2.0.0)\n",
+      "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=2.0.0->vllm==0.1.3) (3.25.0)\n",
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+      "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.31.0->vllm==0.1.3) (0.13.3)\n",
+      "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.31.0->vllm==0.1.3) (0.3.2)\n",
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+      "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets==2.14.4) (2.8.2)\n",
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+      "Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil>=2.8.2->pandas->datasets==2.14.4) (1.16.0)\n",
+      "Requirement already satisfied: anyio<5,>=3.4.0 in /usr/local/lib/python3.10/dist-packages (from starlette<0.28.0,>=0.27.0->fastapi->vllm==0.1.3) (3.7.1)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=2.0.0->vllm==0.1.3) (2.1.2)\n",
+      "Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema->ray>=2.5.1->vllm==0.1.3) (2023.6.1)\n",
+      "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema->ray>=2.5.1->vllm==0.1.3) (0.29.1)\n",
+      "Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema->ray>=2.5.1->vllm==0.1.3) (0.8.10)\n",
+      "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=2.0.0->vllm==0.1.3) (1.2.1)\n",
+      "Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.28.0,>=0.27.0->fastapi->vllm==0.1.3) (1.3.0)\n",
+      "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.28.0,>=0.27.0->fastapi->vllm==0.1.3) (1.1.2)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+      "\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.1.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
   "source": [
-    "%%capture\n",
    "%pip install datasets==2.14.4 vllm==0.1.3"
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
@@ -194,12 +276,12 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "Nice! I've processed all 2,147,248 recipes in under 17 hours. Let's do a cost comparison with GPT-3.5 and GPT-4. I'll use the GPT-4 latency/cost numbers based on the 5000 samples used to generate our model's training data.\n"
+    "Nice! I've processed all 2,147,248 recipes in under 17 hours. Let's do a cost comparison with GPT-3.5 and GPT-4. I'll use the GPT-4 latency/cost numbers based on the 5000 samples used to generate our model's training data."
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
@@ -231,47 +313,47 @@
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
-       "      <td>Llama2 7B (FT)</td>\n",
+       "      <td>Llama 2 7B (finetuned)</td>\n",
       "      <td>0.000009</td>\n",
-       "      <td>18.81</td>\n",
+       "      <td>18.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>0.000481</td>\n",
-       "      <td>1033.26</td>\n",
+       "      <td>1,033.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
-       "      <td>GPT-3.5 (FT)</td>\n",
+       "      <td>GPT-3.5 (finetuned)</td>\n",
       "      <td>0.004044</td>\n",
-       "      <td>8683.47</td>\n",
+       "      <td>8,683.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>GPT-4</td>\n",
       "      <td>0.010800</td>\n",
-       "      <td>23190.28</td>\n",
+       "      <td>23,190.28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
-       "            Model  Cost to Classify One Recipe  \\\n",
-       "0  Llama2 7B (FT)                     0.000009   \n",
-       "1         GPT-3.5                     0.000481   \n",
-       "2    GPT-3.5 (FT)                     0.004044   \n",
-       "3           GPT-4                     0.010800   \n",
+       "                    Model  Cost to Classify One Recipe  \\\n",
+       "0  Llama 2 7B (finetuned)                     0.000009   \n",
+       "1                 GPT-3.5                     0.000481   \n",
+       "2     GPT-3.5 (finetuned)                     0.004044   \n",
+       "3                   GPT-4                     0.010800   \n",
       "\n",
-       "   Cost to Classify Entire Dataset  \n",
-       "0                            18.81  \n",
-       "1                          1033.26  \n",
-       "2                          8683.47  \n",
-       "3                         23190.28  "
+       "  Cost to Classify Entire Dataset  \n",
+       "0                           18.86  \n",
+       "1                        1,033.26  \n",
+       "2                        8,683.47  \n",
+       "3                       23,190.28  "
      ]
     },
-     "execution_count": 23,
+     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
@@ -300,12 +382,12 @@
    "    avg_input_tokens * 0.012 / 1000 + avg_output_tokens * 0.016 / 1000 + 0.06 / 1000\n",
    ")\n",
    "\n",
-    "models = pd.DataFrame(\n",
+    "costs = pd.DataFrame(\n",
    "    {\n",
    "        \"Model\": [\n",
-    "            \"Llama2 7B (FT)\",\n",
+    "            \"Llama 2 7B (finetuned)\",\n",
    "            \"GPT-3.5\",\n",
-    "            \"GPT-3.5 (FT)\",\n",
+    "            \"GPT-3.5 (finetuned)\",\n",
    "            \"GPT-4\",\n",
    "        ],\n",
    "        \"Cost to Classify One Recipe\": [\n",
@@ -317,11 +399,12 @@
    "    }\n",
    ")\n",
    "\n",
-    "models[\"Cost to Classify Entire Dataset\"] = (\n",
-    "    models[\"Cost to Classify One Recipe\"] * len(all_recipes)\n",
-    ").round(2)\n",
+    "costs[\"Cost to Classify Entire Dataset\"] = (\n",
+    "    costs[\"Cost to Classify One Recipe\"] * len(all_recipes)\n",
+    ").map(lambda x: f\"{x:,.2f}\")\n",
    "\n",
-    "models\n"
+    "\n",
+    "costs\n"
   ]
  }
 ],
--- a/examples/classify-recipes/comparative-benchmarks.ipynb
+++ b/examples/classify-recipes/comparative-benchmarks.ipynb
--- a/examples/classify-recipes/3-evaluate.ipynb
+++ b/examples/classify-recipes/3-evaluate.ipynb
@@ -4,29 +4,96 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "I have a model in `./models/run1/merged` that was trained on GPT-4's outputs to classify recipes. I need to figure out whether it does a good job at classifying recipes. I'll install dependencies first.\n"
+    "I have a model in `./models/run1/merged` that was trained on GPT-4's outputs to classify recipes. I need to figure out whether it does a good job at classifying recipes. I'll install dependencies first."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: vllm==0.1.3 in /usr/local/lib/python3.10/dist-packages (0.1.3)\n",
+      "Requirement already satisfied: pandas==2.0.3 in /usr/local/lib/python3.10/dist-packages (2.0.3)\n",
+      "Requirement already satisfied: ninja in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (1.11.1)\n",
+      "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (5.9.5)\n",
+      "Requirement already satisfied: ray>=2.5.1 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (2.6.3)\n",
+      "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.1.99)\n",
+      "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (1.24.4)\n",
+      "Requirement already satisfied: torch>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (2.0.1+cu118)\n",
+      "Requirement already satisfied: transformers>=4.31.0 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (4.33.0.dev0)\n",
+      "Requirement already satisfied: xformers>=0.0.19 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.0.21)\n",
+      "Requirement already satisfied: fastapi in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.101.1)\n",
+      "Requirement already satisfied: uvicorn in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (0.23.2)\n",
+      "Requirement already satisfied: pydantic<2 in /usr/local/lib/python3.10/dist-packages (from vllm==0.1.3) (1.10.12)\n",
+      "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas==2.0.3) (2.8.2)\n",
+      "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas==2.0.3) (2023.3)\n",
+      "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas==2.0.3) (2023.3)\n",
+      "Requirement already satisfied: typing-extensions>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<2->vllm==0.1.3) (4.7.1)\n",
+      "Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil>=2.8.2->pandas==2.0.3) (1.16.0)\n",
+      "Requirement already satisfied: click>=7.0 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (8.1.7)\n",
+      "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (3.9.0)\n",
+      "Requirement already satisfied: jsonschema in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (4.18.0)\n",
+      "Requirement already satisfied: msgpack<2.0.0,>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (1.0.5)\n",
+      "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (23.1)\n",
+      "Requirement already satisfied: protobuf!=3.19.5,>=3.15.3 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (4.24.1)\n",
+      "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (6.0)\n",
+      "Requirement already satisfied: aiosignal in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (1.3.1)\n",
+      "Requirement already satisfied: frozenlist in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (1.4.0)\n",
+      "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (2.28.1)\n",
+      "Requirement already satisfied: grpcio>=1.42.0 in /usr/local/lib/python3.10/dist-packages (from ray>=2.5.1->vllm==0.1.3) (1.57.0)\n",
+      "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (1.11.1)\n",
+      "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (3.0)\n",
+      "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (3.1.2)\n",
+      "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=2.0.0->vllm==0.1.3) (2.0.0)\n",
+      "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=2.0.0->vllm==0.1.3) (3.25.0)\n",
+      "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=2.0.0->vllm==0.1.3) (15.0.7)\n",
+      "Requirement already satisfied: huggingface-hub<1.0,>=0.15.1 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.31.0->vllm==0.1.3) (0.16.4)\n",
+      "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.31.0->vllm==0.1.3) (2023.8.8)\n",
+      "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.31.0->vllm==0.1.3) (0.13.3)\n",
+      "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.31.0->vllm==0.1.3) (0.3.2)\n",
+      "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.31.0->vllm==0.1.3) (4.66.1)\n",
+      "Requirement already satisfied: starlette<0.28.0,>=0.27.0 in /usr/local/lib/python3.10/dist-packages (from fastapi->vllm==0.1.3) (0.27.0)\n",
+      "Requirement already satisfied: h11>=0.8 in /usr/local/lib/python3.10/dist-packages (from uvicorn->vllm==0.1.3) (0.14.0)\n",
+      "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.15.1->transformers>=4.31.0->vllm==0.1.3) (2023.6.0)\n",
+      "Requirement already satisfied: anyio<5,>=3.4.0 in /usr/local/lib/python3.10/dist-packages (from starlette<0.28.0,>=0.27.0->fastapi->vllm==0.1.3) (3.7.1)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=2.0.0->vllm==0.1.3) (2.1.2)\n",
+      "Requirement already satisfied: attrs>=22.2.0 in /usr/local/lib/python3.10/dist-packages (from jsonschema->ray>=2.5.1->vllm==0.1.3) (23.1.0)\n",
+      "Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema->ray>=2.5.1->vllm==0.1.3) (2023.6.1)\n",
+      "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema->ray>=2.5.1->vllm==0.1.3) (0.29.1)\n",
+      "Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema->ray>=2.5.1->vllm==0.1.3) (0.8.10)\n",
+      "Requirement already satisfied: charset-normalizer<3,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->ray>=2.5.1->vllm==0.1.3) (2.1.1)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->ray>=2.5.1->vllm==0.1.3) (3.4)\n",
+      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->ray>=2.5.1->vllm==0.1.3) (1.26.13)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->ray>=2.5.1->vllm==0.1.3) (2022.12.7)\n",
+      "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=2.0.0->vllm==0.1.3) (1.2.1)\n",
+      "Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.28.0,>=0.27.0->fastapi->vllm==0.1.3) (1.3.0)\n",
+      "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.28.0,>=0.27.0->fastapi->vllm==0.1.3) (1.1.2)\n",
+      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+      "\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.1.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython3.10 -m pip install --upgrade pip\u001b[0m\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
   "source": [
-    "%%capture\n",
-    "%pip install vllm==0.1.3 pandas==2.0.3 joblib==1.3.2"
+    "%pip install vllm==0.1.3 pandas==2.0.3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "Remember I got a \"test.jsonl\" file from OpenPipe back in [./prepare.ipynb](./prepare.ipynb)? That's data from our dataset that we didn't use in training, so we can use it to check our model's performance.\n"
+    "Remember I got a \"test.jsonl\" file from OpenPipe back in [./prepare.ipynb](./prepare.ipynb)? That's data from our dataset that we didn't use in training, so we can use it to check our model's performance."
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
@@ -39,12 +106,12 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "During the training process Axolotl transformed our data into an instruction/response format known as the \"Alpaca format\" based on [the project that introduced it](https://github.com/tatsu-lab/stanford_alpaca). I need to transform my test data into the same format for best results.\n"
+    "During the training process Axolotl transformed our data into an instruction/response format known as the \"Alpaca format\" based on [the project that introduced it](https://github.com/tatsu-lab/stanford_alpaca). I need to transform my test data into the same format for best results."
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
@@ -80,27 +147,27 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "Next up, I'll use [vLLM](https://vllm.readthedocs.io/en/latest/) to efficiently process all the prompts in our test data with our own model.\n"
+    "Next up, I'll use [vLLM](https://vllm.readthedocs.io/en/latest/) to efficiently process all the prompts in our test data with our own model."
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
-      "INFO 08-28 00:26:23 llm_engine.py:70] Initializing an LLM engine with config: model='./models/run1/merged', tokenizer='./models/run1/merged', tokenizer_mode=auto, trust_remote_code=False, dtype=torch.float16, use_dummy_weights=False, download_dir=None, use_np_weights=False, tensor_parallel_size=1, seed=0)\n",
-      "INFO 08-28 00:27:26 llm_engine.py:196] # GPU blocks: 3419, # CPU blocks: 512\n"
+      "INFO 08-25 03:58:49 llm_engine.py:70] Initializing an LLM engine with config: model='./models/run1/merged', tokenizer='./models/run1/merged', tokenizer_mode=auto, trust_remote_code=False, dtype=torch.float16, use_dummy_weights=False, download_dir=None, use_np_weights=False, tensor_parallel_size=1, seed=0)\n",
+      "INFO 08-25 03:59:40 llm_engine.py:196] # GPU blocks: 3419, # CPU blocks: 512\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
-      "Processed prompts: 100%|██████████| 500/500 [00:37<00:00, 13.34it/s]"
+      "Processed prompts: 100%|██████████| 500/500 [00:37<00:00, 13.42it/s]"
     ]
    },
    {
@@ -144,12 +211,12 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "Ok, we have our outputs! There are 5 categories we classify each recipe on, so let's check what percentage of the time our model's output matches GPT-4's. I'll write a quick eval function for that:\n"
+    "Ok, we have our outputs! There are 5 categories we classify each recipe on, so let's check what percentage of the time our model's output matches GPT-4's. I'll write a quick eval function for that:"
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
@@ -172,29 +239,20 @@
    "    return args_dict\n",
    "\n",
    "\n",
-    "test_data[\"output_parsed\"] = test_data[\"output\"].apply(parse_fn_call)\n",
-    "test_data[\"my_outputs_parsed\"] = test_data[\"my_outputs\"].apply(parse_fn_call)\n",
-    "\n",
-    "\n",
-    "def calculate_accuracy(row, labels_col):\n",
+    "def calculate_accuracy(row):\n",
    "    \"\"\"Calculate the fraction of my model's outputs that match the reference outputs\"\"\"\n",
-    "    true_outputs = row[\"output_parsed\"]\n",
-    "    labels_outputs = row[labels_col]\n",
-    "\n",
-    "    # print(f\"true_outputs: {true_outputs}\")\n",
-    "    # print(f\"my_outputs: {row[labels_col]}\")\n",
+    "    true_outputs = parse_fn_call(row[\"output\"])\n",
+    "    my_outputs = parse_fn_call(row[\"my_outputs\"])\n",
    "\n",
    "    num_matching_outputs = 0\n",
    "    for key in true_outputs.keys():\n",
-    "        if key in labels_outputs and true_outputs[key] == labels_outputs[key]:\n",
+    "        if key in my_outputs and true_outputs[key] == my_outputs[key]:\n",
    "            num_matching_outputs += 1\n",
    "\n",
    "    return num_matching_outputs / len(true_outputs)\n",
    "\n",
    "\n",
-    "test_data[\"accuracy\"] = test_data.apply(\n",
-    "    calculate_accuracy, axis=1, labels_col=\"my_outputs_parsed\"\n",
-    ")\n",
+    "test_data[\"accuracy\"] = test_data.apply(calculate_accuracy, axis=1)\n",
    "\n",
    "print(f\"Overall accuracy: {test_data['accuracy'].mean():.2f}\")\n"
   ]
@@ -203,293 +261,12 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "95% seems good! However, we don't have much to compare it to. Let's see how GPT-3.5 would do on the same task as a baseline. We'll use the same prompt we used with GPT-4 to generate the labels.\n"
+    "Not bad! However, there are still a few rows where the model outputs don't match. Let's take a closer look."
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Sample recipe:\n",
-      "--------------\n",
-      "Pan Gravy\n",
-      "\n",
-      "Ingredients:\n",
-      "- 1/3 cup all purpose flour\n",
-      "- 1/3 cup turkey drippings\n",
-      "- 3 cup water or broth\n",
-      "- 1/8 to 1/4 teaspoon salt\n",
-      "- 1/8 tsp pepper\n",
-      "\n",
-      "Directions:\n",
-      "- In a skillet or roasting pan, add flour to drippings; blend well.\n",
-      "- Cook over medium heat 2 to 3 minutes until smooth and light brown, stirring constantly.\n",
-      "- Add water; cook until mixture boils and thickens, stirring constantly.\n",
-      "- Stir in salt and pepper.\n",
-      "- *Flour and drippings can be decreased to 1/4 cup each for thinner gravy.\n",
-      "- *\n"
-     ]
-    }
-   ],
-   "source": [
-    "import json\n",
-    "\n",
-    "\n",
-    "def extract_recipe(row):\n",
-    "    \"\"\"Extract the recipe from the instruction\"\"\"\n",
-    "    return json.loads(row[\"instruction\"])[1][\"content\"]\n",
-    "\n",
-    "\n",
-    "recipes = test_data.apply(extract_recipe, axis=1)\n",
-    "print(f\"Sample recipe:\\n--------------\\n{recipes[0]}\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Classifying first recipe:\n",
-      "------------------\n",
-      "{'has_non_fish_meat': False, 'requires_oven': False, 'requires_stove': True, 'cook_time_over_30_mins': False, 'main_dish': False}\n"
-     ]
-    }
-   ],
-   "source": [
-    "import joblib\n",
-    "import openai\n",
-    "import os\n",
-    "import dotenv\n",
-    "\n",
-    "dotenv.load_dotenv()\n",
-    "openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n",
-    "\n",
-    "memory = joblib.Memory(\"./cache\", verbose=0)\n",
-    "\n",
-    "\n",
-    "@memory.cache\n",
-    "def classify_recipe_35(recipe: str):\n",
-    "    completion = openai.ChatCompletion.create(\n",
-    "        model=\"gpt-3.5-turbo\",\n",
-    "        messages=[\n",
-    "            {\n",
-    "                \"role\": \"system\",\n",
-    "                \"content\": \"Your goal is to classify a recipe along several dimensions.Pay attention to the instructions.\",\n",
-    "            },\n",
-    "            {\n",
-    "                \"role\": \"user\",\n",
-    "                \"content\": recipe,\n",
-    "            },\n",
-    "        ],\n",
-    "        functions=[\n",
-    "            {\n",
-    "                \"name\": \"classify\",\n",
-    "                \"parameters\": {\n",
-    "                    \"type\": \"object\",\n",
-    "                    \"properties\": {\n",
-    "                        \"has_non_fish_meat\": {\n",
-    "                            \"type\": \"boolean\",\n",
-    "                            \"description\": \"True if the recipe contains any meat or meat products (eg. chicken broth) besides fish\",\n",
-    "                        },\n",
-    "                        \"requires_oven\": {\n",
-    "                            \"type\": \"boolean\",\n",
-    "                            \"description\": \"True if the recipe requires an oven\",\n",
-    "                        },\n",
-    "                        \"requires_stove\": {\n",
-    "                            \"type\": \"boolean\",\n",
-    "                            \"description\": \"True if the recipe requires a stove\",\n",
-    "                        },\n",
-    "                        \"cook_time_over_30_mins\": {\n",
-    "                            \"type\": \"boolean\",\n",
-    "                            \"description\": \"True if the recipe takes over 30 minutes to prepare and cook, including waiting time\",\n",
-    "                        },\n",
-    "                        \"main_dish\": {\n",
-    "                            \"type\": \"boolean\",\n",
-    "                            \"description\": \"True if the recipe can be served as a main dish\",\n",
-    "                        },\n",
-    "                    },\n",
-    "                    \"required\": [\n",
-    "                        \"has_non_fish_meat\",\n",
-    "                        \"requires_oven\",\n",
-    "                        \"requires_stove\",\n",
-    "                        \"cook_time_over_30_mins\",\n",
-    "                        \"main_dish\",\n",
-    "                    ],\n",
-    "                },\n",
-    "            }\n",
-    "        ],\n",
-    "        function_call={\n",
-    "            \"name\": \"classify\",\n",
-    "        },\n",
-    "    )\n",
-    "    return json.loads(completion.choices[0].message.function_call.arguments)\n",
-    "\n",
-    "\n",
-    "print(\"Classifying first recipe:\\n------------------\")\n",
-    "print(classify_recipe_35(recipes[0]))\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "\u001b[A\n",
-      "100%|██████████| 500/500 [00:31<00:00, 15.77it/s]\n"
-     ]
-    }
-   ],
-   "source": [
-    "from tqdm import tqdm\n",
-    "\n",
-    "test_data[\"gpt_3.5\"] = [classify_recipe_35(r) for r in tqdm(recipes)]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "GPT-3.5 accuracy: 0.91\n"
-     ]
-    }
-   ],
-   "source": [
-    "test_data[\"gpt_3.5_accuracy\"] = test_data.apply(\n",
-    "    calculate_accuracy, axis=1, labels_col=\"gpt_3.5\"\n",
-    ")\n",
-    "\n",
-    "print(f\"GPT-3.5 accuracy: {test_data['gpt_3.5_accuracy'].mean():.2f}\")\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "And for completeness, let's try a fine-tuned GPT-3.5 model. You can find the fine-tuning code in [finetune-gpt-3.5.ipynb](./finetune-gpt-3.5.ipynb)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'has_non_fish_meat': True,\n",
-       " 'requires_oven': False,\n",
-       " 'requires_stove': True,\n",
-       " 'cook_time_over_30_mins': False,\n",
-       " 'main_dish': False}"
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "@memory.cache\n",
-    "def classify_recipe_35_ft(recipe: str):\n",
-    "    completion = openai.ChatCompletion.create(\n",
-    "        model=\"ft:gpt-3.5-turbo-0613:openpipe::7rZpPqYn\",\n",
-    "        messages=[\n",
-    "            {\n",
-    "                \"role\": \"system\",\n",
-    "                \"content\": \"Your goal is to classify a recipe along several \"\n",
-    "                \"dimensions.Pay attention to the instructions.\",\n",
-    "            },\n",
-    "            {\"role\": \"user\", \"content\": recipe},\n",
-    "        ],\n",
-    "    )\n",
-    "\n",
-    "    return json.loads(completion.choices[0].message.content)\n",
-    "\n",
-    "\n",
-    "classify_recipe_35_ft(recipes[0])\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "100%|██████████| 500/500 [07:31<00:00,  1.11it/s]\n"
-     ]
-    }
-   ],
-   "source": [
-    "test_data[\"gpt_3.5_ft\"] = [classify_recipe_35_ft(r) for r in tqdm(recipes)]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "GPT-3.5 FT accuracy: 0.94\n"
-     ]
-    }
-   ],
-   "source": [
-    "test_data[\"gpt_3.5_ft_accuracy\"] = test_data.apply(\n",
-    "    calculate_accuracy, axis=1, labels_col=\"gpt_3.5_ft\"\n",
-    ")\n",
-    "\n",
-    "print(f\"GPT-3.5 FT accuracy: {test_data['gpt_3.5_ft_accuracy'].mean():.2f}\")\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Not bad! However, there are still a few rows where the model outputs don't match. Let's take a closer look.\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
@@ -848,28 +625,9 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "Looking at the outputs, it's clear that our model still makes some mistakes. But at the same time, there are plenty of examples like \"Rhonda's Butter Chess Pie\" where our model gets it right, even though GPT-4 got it wrong! And there are also cases like the \"Veggie Casserole\", where the \"right\" answer is truly ambiguous and really both answers are defensible.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "A realistic point of comparison here might be GPT-3.5. Let's try to classify the same set of recipes using GPT-3.5 and see how it does. We'll use the same prompt that we used with GPT-4 to generate the initial training data.\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Interested in cost/latency benchmarking? You can check out [./benchmarking.ipynb](./benchmarking.ipynb) for an overview of my findings!\n"
+    "Looking at the outputs, it's clear that our model still makes some mistakes. But at the same time, there are plenty of examples like \"Rhonda's Butter Chess Pie\" where our model gets it right, even though GPT-4 got it wrong! And there are also cases like the \"Veggie Casserole\", where the \"right\" answer is truly ambiguous and really both answers are defensible.\n",
+    "\n",
+    "Interested in cost/latency benchmarking? You can check out [./benchmarking.ipynb](./benchmarking.ipynb) for an overview of my findings!"
   ]
  },
  {
--- a/examples/classify-recipes/finetune-gpt-3.5.ipynb
+++ b/examples/classify-recipes/finetune-gpt-3.5.ipynb
@@ -1,207 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Sample training data:\n",
-      "{'messages': [{'content': 'Your goal is to classify a recipe along several '\n",
-      "                          'dimensions.Pay attention to the instructions.',\n",
-      "               'role': 'system'},\n",
-      "              {'content': 'Homemade Salad Dressing\\n'\n",
-      "                          '\\n'\n",
-      "                          'Ingredients:\\n'\n",
-      "                          \"- 1 pt. Hellmann's mayonnaise\\n\"\n",
-      "                          '- 1 pt. buttermilk\\n'\n",
-      "                          '- 1 tsp. Accent\\n'\n",
-      "                          '- 2 Tbsp. dry parsley\\n'\n",
-      "                          '- 2 pkg. low-calorie Italian salad dressing mix\\n'\n",
-      "                          '- 1 can jalapeno peppers or 4 oz. Jimenez green '\n",
-      "                          'sauce\\n'\n",
-      "                          '\\n'\n",
-      "                          'Directions:\\n'\n",
-      "                          '- Blend well in blender; store in refrigerator.\\n'\n",
-      "                          '- For dip, decrease liquid.',\n",
-      "               'role': 'user'},\n",
-      "              {'content': '{\\n'\n",
-      "                          '\"has_non_fish_meat\": false,\\n'\n",
-      "                          '\"requires_oven\": false,\\n'\n",
-      "                          '\"requires_stove\": false,\\n'\n",
-      "                          '\"cook_time_over_30_mins\": false,\\n'\n",
-      "                          '\"main_dish\": false\\n'\n",
-      "                          '}',\n",
-      "               'role': 'assistant'}]}\n"
-     ]
-    }
-   ],
-   "source": [
-    "import pandas as pd\n",
-    "from pprint import pprint\n",
-    "import json\n",
-    "\n",
-    "df = pd.read_json(\"data/train.jsonl\", lines=True)\n",
-    "\n",
-    "training_data = []\n",
-    "for row in df.itertuples():\n",
-    "    input = json.loads(row.instruction)\n",
-    "    output = json.loads(row.output)\n",
-    "\n",
-    "    output[\"content\"] = output[\"function_call\"][\"arguments\"]\n",
-    "    del output[\"function_call\"]\n",
-    "\n",
-    "    sample = {\"messages\": input.copy() + [output]}\n",
-    "    training_data.append(sample)\n",
-    "\n",
-    "# save the training data to data/train-gpt3.5.jsonl\n",
-    "\n",
-    "with open(\"data/train-gpt3.5.jsonl\", \"w\") as f:\n",
-    "    for sample in training_data:\n",
-    "        f.write(json.dumps(sample) + \"\\n\")\n",
-    "\n",
-    "print(f\"Sample training data:\")\n",
-    "pprint(training_data[0])\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<File file id=file-faAdQ1KPxZH79ThW4Dbu4z1y at 0x7fa55db5c6d0> JSON: {\n",
-       "  \"object\": \"file\",\n",
-       "  \"id\": \"file-faAdQ1KPxZH79ThW4Dbu4z1y\",\n",
-       "  \"purpose\": \"fine-tune\",\n",
-       "  \"filename\": \"recipe-classification\",\n",
-       "  \"bytes\": 4210831,\n",
-       "  \"created_at\": 1693000959,\n",
-       "  \"status\": \"uploaded\",\n",
-       "  \"status_details\": null\n",
-       "}"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import os\n",
-    "import openai\n",
-    "\n",
-    "import dotenv\n",
-    "\n",
-    "dotenv.load_dotenv()\n",
-    "\n",
-    "openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n",
-    "\n",
-    "openai.File.create(\n",
-    "    file=open(\"data/train-gpt3.5.jsonl\", \"rb\"),\n",
-    "    purpose=\"fine-tune\",\n",
-    "    user_provided_filename=\"recipe-classification\",\n",
-    ")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<OpenAIObject list at 0x7fa55dbf6930> JSON: {\n",
-       "  \"object\": \"list\",\n",
-       "  \"data\": [\n",
-       "    {\n",
-       "      \"object\": \"file\",\n",
-       "      \"id\": \"file-faAdQ1KPxZH79ThW4Dbu4z1y\",\n",
-       "      \"purpose\": \"fine-tune\",\n",
-       "      \"filename\": \"recipe-classification\",\n",
-       "      \"bytes\": 4210831,\n",
-       "      \"created_at\": 1693000959,\n",
-       "      \"status\": \"processed\",\n",
-       "      \"status_details\": null\n",
-       "    }\n",
-       "  ]\n",
-       "}"
-      ]
-     },
-     "execution_count": 40,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "openai.File.list()\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<FineTuningJob fine_tuning.job id=ftjob-EjjLxmj9P8apwPRk5s2NPSeB at 0x7fa55ddc4360> JSON: {\n",
-       "  \"object\": \"fine_tuning.job\",\n",
-       "  \"id\": \"ftjob-EjjLxmj9P8apwPRk5s2NPSeB\",\n",
-       "  \"model\": \"gpt-3.5-turbo-0613\",\n",
-       "  \"created_at\": 1693001190,\n",
-       "  \"finished_at\": null,\n",
-       "  \"fine_tuned_model\": null,\n",
-       "  \"organization_id\": \"org-jRz4nVPMoeGHWL5nVR3Mb0kp\",\n",
-       "  \"result_files\": [],\n",
-       "  \"status\": \"created\",\n",
-       "  \"validation_file\": null,\n",
-       "  \"training_file\": \"file-faAdQ1KPxZH79ThW4Dbu4z1y\",\n",
-       "  \"hyperparameters\": {\n",
-       "    \"n_epochs\": 3\n",
-       "  },\n",
-       "  \"trained_tokens\": null\n",
-       "}"
-      ]
-     },
-     "execution_count": 42,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "openai.FineTuningJob.create(\n",
-    "    training_file=\"file-faAdQ1KPxZH79ThW4Dbu4z1y\", model=\"gpt-3.5-turbo\"\n",
-    ")\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.6"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
--- a/examples/classify-recipes/1-generate-data.ipynb
+++ b/examples/classify-recipes/1-generate-data.ipynb
@@ -6,24 +6,61 @@
   "source": [
    "In this notebook I'm using the OpenPipe client to capture a set of calls to the OpenAI API.\n",
    "\n",
-    "For this example I'll blithely throw engineering best practices to the wind and use the notebook itself to manage dependencies. 😁\n"
+    "For this example I'll blithely throw engineering best practices to the wind and use the notebook itself to manage dependencies. 😁"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: openpipe==3.0.3 in /usr/local/lib/python3.10/dist-packages (3.0.3)\n",
+      "Requirement already satisfied: python-dotenv==1.0.0 in /usr/local/lib/python3.10/dist-packages (1.0.0)\n",
+      "Requirement already satisfied: joblib==1.3.2 in /usr/local/lib/python3.10/dist-packages (1.3.2)\n",
+      "Requirement already satisfied: attrs<24.0.0,>=23.1.0 in /usr/local/lib/python3.10/dist-packages (from openpipe==3.0.3) (23.1.0)\n",
+      "Requirement already satisfied: httpx<0.25.0,>=0.24.1 in /usr/local/lib/python3.10/dist-packages (from openpipe==3.0.3) (0.24.1)\n",
+      "Requirement already satisfied: openai<0.28.0,>=0.27.8 in /usr/local/lib/python3.10/dist-packages (from openpipe==3.0.3) (0.27.9)\n",
+      "Requirement already satisfied: python-dateutil<3.0.0,>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from openpipe==3.0.3) (2.8.2)\n",
+      "Requirement already satisfied: toml<0.11.0,>=0.10.2 in /usr/local/lib/python3.10/dist-packages (from openpipe==3.0.3) (0.10.2)\n",
+      "Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from httpx<0.25.0,>=0.24.1->openpipe==3.0.3) (2022.12.7)\n",
+      "Requirement already satisfied: httpcore<0.18.0,>=0.15.0 in /usr/local/lib/python3.10/dist-packages (from httpx<0.25.0,>=0.24.1->openpipe==3.0.3) (0.17.3)\n",
+      "Requirement already satisfied: idna in /usr/local/lib/python3.10/dist-packages (from httpx<0.25.0,>=0.24.1->openpipe==3.0.3) (3.4)\n",
+      "Requirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from httpx<0.25.0,>=0.24.1->openpipe==3.0.3) (1.3.0)\n",
+      "Requirement already satisfied: requests>=2.20 in /usr/local/lib/python3.10/dist-packages (from openai<0.28.0,>=0.27.8->openpipe==3.0.3) (2.28.1)\n",
+      "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from openai<0.28.0,>=0.27.8->openpipe==3.0.3) (4.66.1)\n",
+      "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from openai<0.28.0,>=0.27.8->openpipe==3.0.3) (3.8.5)\n",
+      "Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil<3.0.0,>=2.8.2->openpipe==3.0.3) (1.16.0)\n",
+      "Requirement already satisfied: h11<0.15,>=0.13 in /usr/local/lib/python3.10/dist-packages (from httpcore<0.18.0,>=0.15.0->httpx<0.25.0,>=0.24.1->openpipe==3.0.3) (0.14.0)\n",
+      "Requirement already satisfied: anyio<5.0,>=3.0 in /usr/local/lib/python3.10/dist-packages (from httpcore<0.18.0,>=0.15.0->httpx<0.25.0,>=0.24.1->openpipe==3.0.3) (3.7.1)\n",
+      "Requirement already satisfied: charset-normalizer<3,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai<0.28.0,>=0.27.8->openpipe==3.0.3) (2.1.1)\n",
+      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai<0.28.0,>=0.27.8->openpipe==3.0.3) (1.26.13)\n",
+      "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai<0.28.0,>=0.27.8->openpipe==3.0.3) (6.0.4)\n",
+      "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai<0.28.0,>=0.27.8->openpipe==3.0.3) (4.0.3)\n",
+      "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai<0.28.0,>=0.27.8->openpipe==3.0.3) (1.9.2)\n",
+      "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai<0.28.0,>=0.27.8->openpipe==3.0.3) (1.4.0)\n",
+      "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai<0.28.0,>=0.27.8->openpipe==3.0.3) (1.3.1)\n",
+      "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5.0,>=3.0->httpcore<0.18.0,>=0.15.0->httpx<0.25.0,>=0.24.1->openpipe==3.0.3) (1.1.2)\n",
+      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+      "\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.1.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython3.10 -m pip install --upgrade pip\u001b[0m\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
   "source": [
-    "%%capture\n",
-    "%pip install openpipe==3.0.3 python-dotenv==1.0.0 datasets==2.14.4"
+    "%pip install openpipe==3.0.3 python-dotenv==1.0.0 joblib==1.3.2 datasets==2.14.4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "When working with remote datasets (or any data, really), it's a good idea to visually inspect some samples to make sure it looks like you expect. I'll print a recipe.\n"
+    "When working with remote datasets (or any data, really), it's a good idea to visually inspect some samples to make sure it looks like you expect. I'll print a recipe."
   ]
  },
  {
@@ -95,16 +132,15 @@
    "Mm, delicious. Anyway, we need to generate a training dataset. We'll call GPT-4 on each of our examples.\n",
    "\n",
    "In this case, I'll ask GPT-4 to classify each recipe along 5 dimensions:\n",
-    "\n",
-    "- has_non_fish_meat\n",
-    "- requires_oven\n",
-    "- requires_stove\n",
-    "- cook_time_over_30_mins\n",
-    "- main_dish\n",
+    " - has_non_fish_meat\n",
+    " - requires_oven\n",
+    " - requires_stove\n",
+    " - cook_time_over_30_mins\n",
+    " - main_dish\n",
    "\n",
    "That looks like a pretty random list, but there's actually an important unifying thread: I'm looking for meals that my pescatarian brother/co-founder can make in his kitchen-less, near-window-less basement apartment in San Francisco! (If you haven't tried to get an apartment in SF you probably think I'm joking 😂.)\n",
    "\n",
-    "I'll use [OpenPipe](https://github.com/openpipe/openpipe) to track the API calls and form a training dataset. To follow along you'll need to create a free OpenPipe account, then copy your API key from https://app.openpipe.ai/project/settings into a file called `.env`. You can see an example in [./.env.example](./.env.example).\n"
+    "I'll use [OpenPipe](https://github.com/openpipe/openpipe) to track the API calls and form a training dataset. To follow along you'll need to create a free OpenPipe account, then copy your API key from https://app.openpipe.ai/project/settings into a file called `.env`. You can see an example in [./.env.example](./.env.example)."
   ]
  },
  {
@@ -204,7 +240,7 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "That's working, so I'll go ahead and classify all 5000 recipes with GPT-4. Using GPT-4 for this is slowwww and costs about $40. The model I'm fine-tuning will be much faster -- we'll see if we can make it as good!\n"
+    "That's working, so I'll go ahead and classify all 5000 recipes with GPT-4. Using GPT-4 for this is slowwww and costs about $40. The model I'm fine-tuning will be much faster -- we'll see if we can make it as good!"
   ]
  },
  {
@@ -284,11 +320,11 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "Ok, now that my recipes are classified I'll download the training data.\n",
+    "Ok, now that my recipes are classified I'll download the training data. \n",
    "\n",
    "Next up I'll train the model -- check out [./train.ipynb](./train.ipynb) for details! Just go to https://app.openpipe.ai/request-logs, select all the logs you created, and click \"Export\". The default 10% testing split is fine for this dataset size.\n",
    "\n",
-    "I got two files from that: `train.jsonl` and `test.jsonl`. I moved both of them into this repository under `./data/`.\n"
+    "I got two files from that: `train.jsonl` and `test.jsonl`. I moved both of them into this repository under `./data/`."
   ]
  }
 ],
--- a/examples/classify-recipes/2-train.ipynb
+++ b/examples/classify-recipes/2-train.ipynb
@@ -4,16 +4,142 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "Now let's get to the fun part -- training a model. I'll start by installing the dependencies.\n"
+    "Now let's get to the fun part -- training a model. I'll start by installing the dependencies."
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 4,
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: peft==0.5.0 in /usr/local/lib/python3.10/dist-packages (0.5.0)\n",
+      "\u001b[31mERROR: Could not find a version that satisfies the requirement python-dotenv==2.0.0 (from versions: 0.1.0, 0.1.2, 0.1.3, 0.1.5, 0.2.0, 0.3.0, 0.4.0, 0.5.0, 0.5.1, 0.6.0, 0.6.1, 0.6.2, 0.6.3, 0.6.4, 0.6.5, 0.7.0, 0.7.1, 0.8.0, 0.8.1, 0.8.2, 0.9.0, 0.9.1, 0.10.0, 0.10.1, 0.10.2, 0.10.3, 0.10.4, 0.10.5, 0.11.0, 0.12.0, 0.13.0, 0.14.0, 0.15.0, 0.16.0, 0.17.0, 0.17.1, 0.18.0, 0.19.0, 0.19.1, 0.19.2, 0.20.0, 0.21.0, 0.21.1, 1.0.0)\u001b[0m\u001b[31m\n",
+      "\u001b[0m\u001b[31mERROR: No matching distribution found for python-dotenv==2.0.0\u001b[0m\u001b[31m\n",
+      "\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.1.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython3.10 -m pip install --upgrade pip\u001b[0m\n",
+      "Note: you may need to restart the kernel to use updated packages.\n",
+      "fatal: destination path 'axolotl' already exists and is not an empty directory.\n",
+      "Obtaining file:///workspace/OpenPipe/examples/classify-recipes/axolotl\n",
+      "  Preparing metadata (setup.py) ... \u001b[?25ldone\n",
+      "\u001b[?25hCollecting transformers@ git+https://github.com/huggingface/transformers.git (from axolotl==0.1)\n",
+      "  Cloning https://github.com/huggingface/transformers.git to /tmp/pip-install-ckp96ans/transformers_783779e09ad546a5be81c173eca5fd38\n",
+      "  Running command git clone --filter=blob:none --quiet https://github.com/huggingface/transformers.git /tmp/pip-install-ckp96ans/transformers_783779e09ad546a5be81c173eca5fd38\n",
+      "  Resolved https://github.com/huggingface/transformers.git to commit f26099e7b5cf579f99a42bab6ddd371bf2c8d548\n",
+      "  Installing build dependencies ... \u001b[?25ldone\n",
+      "\u001b[?25h  Getting requirements to build wheel ... \u001b[?25ldone\n",
+      "\u001b[?25h  Preparing metadata (pyproject.toml) ... \u001b[?25ldone\n",
+      "\u001b[?25hCollecting accelerate@ git+https://github.com/huggingface/accelerate@2a289f6108e77a77a4efffb3f6316bc98538413b (from axolotl==0.1)\n",
+      "  Using cached accelerate-0.22.0.dev0-py3-none-any.whl\n",
+      "Requirement already satisfied: bitsandbytes>=0.41.1 in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (0.41.1)\n",
+      "Requirement already satisfied: addict in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (2.4.0)\n",
+      "Requirement already satisfied: fire in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (0.5.0)\n",
+      "Requirement already satisfied: PyYAML==6.0 in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (6.0)\n",
+      "Requirement already satisfied: datasets in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (2.14.4)\n",
+      "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (0.1.99)\n",
+      "Requirement already satisfied: wandb in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (0.15.8)\n",
+      "Requirement already satisfied: einops in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (0.6.1)\n",
+      "Requirement already satisfied: xformers in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (0.0.21)\n",
+      "Requirement already satisfied: optimum in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (1.11.2)\n",
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+      "Requirement already satisfied: numba in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (0.57.1)\n",
+      "Requirement already satisfied: numpy==1.24.4 in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (1.24.4)\n",
+      "Requirement already satisfied: bert-score==0.3.13 in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (0.3.13)\n",
+      "Requirement already satisfied: evaluate==0.4.0 in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (0.4.0)\n",
+      "Requirement already satisfied: rouge-score==0.1.2 in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (0.1.2)\n",
+      "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (1.11.2)\n",
+      "Requirement already satisfied: scikit-learn==1.2.2 in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (1.2.2)\n",
+      "Requirement already satisfied: pynvml in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (11.5.0)\n",
+      "Requirement already satisfied: flash-attn==2.0.8 in /usr/local/lib/python3.10/dist-packages (from axolotl==0.1) (2.0.8)\n",
+      "Requirement already satisfied: torch>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from bert-score==0.3.13->axolotl==0.1) (2.0.1+cu118)\n",
+      "Requirement already satisfied: pandas>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from bert-score==0.3.13->axolotl==0.1) (2.0.3)\n",
+      "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from bert-score==0.3.13->axolotl==0.1) (2.28.1)\n",
+      "Requirement already satisfied: tqdm>=4.31.1 in /usr/local/lib/python3.10/dist-packages (from bert-score==0.3.13->axolotl==0.1) (4.66.1)\n",
+      "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from bert-score==0.3.13->axolotl==0.1) (3.7.2)\n",
+      "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from bert-score==0.3.13->axolotl==0.1) (23.1)\n",
+      "Requirement already satisfied: dill in /usr/local/lib/python3.10/dist-packages (from evaluate==0.4.0->axolotl==0.1) (0.3.7)\n",
+      "Requirement already satisfied: xxhash in /usr/local/lib/python3.10/dist-packages (from evaluate==0.4.0->axolotl==0.1) (3.3.0)\n",
+      "Requirement already satisfied: multiprocess in /usr/local/lib/python3.10/dist-packages (from evaluate==0.4.0->axolotl==0.1) (0.70.15)\n",
+      "Requirement already satisfied: fsspec[http]>=2021.05.0 in /usr/local/lib/python3.10/dist-packages (from evaluate==0.4.0->axolotl==0.1) (2023.6.0)\n",
+      "Requirement already satisfied: huggingface-hub>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from evaluate==0.4.0->axolotl==0.1) (0.16.4)\n",
+      "Requirement already satisfied: responses<0.19 in /usr/local/lib/python3.10/dist-packages (from evaluate==0.4.0->axolotl==0.1) (0.18.0)\n",
+      "Requirement already satisfied: ninja in /usr/local/lib/python3.10/dist-packages (from flash-attn==2.0.8->axolotl==0.1) (1.11.1)\n",
+      "Requirement already satisfied: absl-py in /usr/local/lib/python3.10/dist-packages (from rouge-score==0.1.2->axolotl==0.1) (1.4.0)\n",
+      "Requirement already satisfied: nltk in /usr/local/lib/python3.10/dist-packages (from rouge-score==0.1.2->axolotl==0.1) (3.8.1)\n",
+      "Requirement already satisfied: six>=1.14.0 in /usr/lib/python3/dist-packages (from rouge-score==0.1.2->axolotl==0.1) (1.16.0)\n",
+      "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn==1.2.2->axolotl==0.1) (1.3.2)\n",
+      "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn==1.2.2->axolotl==0.1) (3.2.0)\n",
+      "Requirement already satisfied: pyarrow>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets->axolotl==0.1) (12.0.1)\n",
+      "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets->axolotl==0.1) (3.8.5)\n",
+      "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers@ git+https://github.com/huggingface/transformers.git->axolotl==0.1) (3.9.0)\n",
+      "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers@ git+https://github.com/huggingface/transformers.git->axolotl==0.1) (2023.8.8)\n",
+      "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.10/dist-packages (from transformers@ git+https://github.com/huggingface/transformers.git->axolotl==0.1) (0.13.3)\n",
+      "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from transformers@ git+https://github.com/huggingface/transformers.git->axolotl==0.1) (0.3.2)\n",
+      "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate@ git+https://github.com/huggingface/accelerate@2a289f6108e77a77a4efffb3f6316bc98538413b->axolotl==0.1) (5.9.5)\n",
+      "Requirement already satisfied: termcolor in /usr/local/lib/python3.10/dist-packages (from fire->axolotl==0.1) (2.3.0)\n",
+      "Requirement already satisfied: llvmlite<0.41,>=0.40.0dev0 in /usr/local/lib/python3.10/dist-packages (from numba->axolotl==0.1) (0.40.1)\n",
+      "Requirement already satisfied: coloredlogs in /usr/local/lib/python3.10/dist-packages (from optimum->axolotl==0.1) (15.0.1)\n",
+      "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from optimum->axolotl==0.1) (1.11.1)\n",
+      "Requirement already satisfied: Click!=8.0.0,>=7.1 in /usr/local/lib/python3.10/dist-packages (from wandb->axolotl==0.1) (8.1.7)\n",
+      "Requirement already satisfied: GitPython!=3.1.29,>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from wandb->axolotl==0.1) (3.1.32)\n",
+      "Requirement already satisfied: sentry-sdk>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from wandb->axolotl==0.1) (1.29.2)\n",
+      "Requirement already satisfied: docker-pycreds>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from wandb->axolotl==0.1) (0.4.0)\n",
+      "Requirement already satisfied: pathtools in /usr/local/lib/python3.10/dist-packages (from wandb->axolotl==0.1) (0.1.2)\n",
+      "Requirement already satisfied: setproctitle in /usr/local/lib/python3.10/dist-packages (from wandb->axolotl==0.1) (1.3.2)\n",
+      "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from wandb->axolotl==0.1) (68.0.0)\n",
+      "Requirement already satisfied: appdirs>=1.4.3 in /usr/local/lib/python3.10/dist-packages (from wandb->axolotl==0.1) (1.4.4)\n",
+      "Requirement already satisfied: protobuf!=4.21.0,<5,>=3.19.0 in /usr/local/lib/python3.10/dist-packages (from wandb->axolotl==0.1) (4.24.1)\n",
+      "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch>=1.0.0->bert-score==0.3.13->axolotl==0.1) (4.7.1)\n",
+      "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.0.0->bert-score==0.3.13->axolotl==0.1) (3.0)\n",
+      "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.0.0->bert-score==0.3.13->axolotl==0.1) (3.1.2)\n",
+      "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.0.0->bert-score==0.3.13->axolotl==0.1) (2.0.0)\n",
+      "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.0.0->bert-score==0.3.13->axolotl==0.1) (3.25.0)\n",
+      "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.0.0->bert-score==0.3.13->axolotl==0.1) (15.0.7)\n",
+      "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets->axolotl==0.1) (23.1.0)\n",
+      "Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets->axolotl==0.1) (2.1.1)\n",
+      "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets->axolotl==0.1) (6.0.4)\n",
+      "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets->axolotl==0.1) (4.0.3)\n",
+      "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets->axolotl==0.1) (1.9.2)\n",
+      "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets->axolotl==0.1) (1.4.0)\n",
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+      "Requirement already satisfied: gitdb<5,>=4.0.1 in /usr/local/lib/python3.10/dist-packages (from GitPython!=3.1.29,>=1.0.0->wandb->axolotl==0.1) (4.0.10)\n",
+      "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.0.1->bert-score==0.3.13->axolotl==0.1) (2.8.2)\n",
+      "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.0.1->bert-score==0.3.13->axolotl==0.1) (2023.3)\n",
+      "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.0.1->bert-score==0.3.13->axolotl==0.1) (2023.3)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->bert-score==0.3.13->axolotl==0.1) (3.4)\n",
+      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->bert-score==0.3.13->axolotl==0.1) (1.26.13)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->bert-score==0.3.13->axolotl==0.1) (2022.12.7)\n",
+      "Requirement already satisfied: humanfriendly>=9.1 in /usr/local/lib/python3.10/dist-packages (from coloredlogs->optimum->axolotl==0.1) (10.0)\n",
+      "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->bert-score==0.3.13->axolotl==0.1) (1.1.0)\n",
+      "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib->bert-score==0.3.13->axolotl==0.1) (0.11.0)\n",
+      "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->bert-score==0.3.13->axolotl==0.1) (4.42.1)\n",
+      "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->bert-score==0.3.13->axolotl==0.1) (1.4.4)\n",
+      "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->bert-score==0.3.13->axolotl==0.1) (9.3.0)\n",
+      "Requirement already satisfied: pyparsing<3.1,>=2.3.1 in /usr/lib/python3/dist-packages (from matplotlib->bert-score==0.3.13->axolotl==0.1) (2.4.7)\n",
+      "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->optimum->axolotl==0.1) (1.2.1)\n",
+      "Requirement already satisfied: smmap<6,>=3.0.1 in /usr/local/lib/python3.10/dist-packages (from gitdb<5,>=4.0.1->GitPython!=3.1.29,>=1.0.0->wandb->axolotl==0.1) (5.0.0)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.0.0->bert-score==0.3.13->axolotl==0.1) (2.1.2)\n",
+      "Installing collected packages: axolotl\n",
+      "  Attempting uninstall: axolotl\n",
+      "    Found existing installation: axolotl 0.1\n",
+      "    Uninstalling axolotl-0.1:\n",
+      "      Successfully uninstalled axolotl-0.1\n",
+      "  Running setup.py develop for axolotl\n",
+      "Successfully installed axolotl\n",
+      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+      "\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.1.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython3.10 -m pip install --upgrade pip\u001b[0m\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
   "source": [
-    "%%capture\n",
    "%pip install peft==0.5.0 python-dotenv==2.0.0\n",
    "\n",
    "!git clone https://github.com/OpenAccess-AI-Collective/axolotl\n",
@@ -24,7 +150,7 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "Note to the reader: since we'll be basing our fine-tuned model on Meta's Llama 2, you need to apply for access to the weights (which will be automatically granted). Follow the steps on [HuggingFace](https://huggingface.co/meta-llama/Llama-2-7b-hf), then create a read-only access token [here](https://huggingface.co/settings/tokens) and copy it into your .env file.\n"
+    "Note to the reader: since we'll be basing our fine-tuned model on Meta's Llama 2, you need to apply for access to the weights (which will be automatically granted). Follow the steps on [HuggingFace](https://huggingface.co/meta-llama/Llama-2-7b-hf), then create a read-only access token [here](https://huggingface.co/settings/tokens) and copy it into your .env file."
   ]
  },
  {
@@ -59,7 +185,7 @@
    "\n",
    "In this case I'm using 8-bit training to use less GPU RAM, and sample packing to maximize GPU utilization. You can read more about the available options at https://github.com/OpenAccess-AI-Collective/axolotl.\n",
    "\n",
-    "The training run options are defined in [training-config.yaml](./training-config.yaml).\n"
+    "The training run options are defined in [training-config.yaml](./training-config.yaml)."
   ]
  },
  {
@@ -865,7 +991,7 @@
   "source": [
    "Sweet! I now have a new directory `./models/run1`. This contains my trained model, which I can use to classify more recipes.\n",
    "\n",
-    "There's one more step though. I trained our model using [LoRA](https://huggingface.co/docs/peft/conceptual_guides/lora), which is a memory-efficient training method. But the inference library we'll use for testing doesn't support LoRA models directly yet, so we need to \"merge\" our LoRA model to transform it into a standard Llama2-shaped model. I've defined a small helper to do that called `merge_lora_model` that I'll use below.\n"
+    "There's one more step though. I trained our model using [LoRA](https://huggingface.co/docs/peft/conceptual_guides/lora), which is a memory-efficient training method. But the inference library we'll use for testing doesn't support LoRA models directly yet, so we need to \"merge\" our LoRA model to transform it into a standard Llama2-shaped model. I've defined a small helper to do that called `merge_lora_model` that I'll use below."
   ]
  },
  {
@@ -918,7 +1044,7 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "Ok, I have a model, but is it actually any good? I'll run some evaluations in [./evaluate.ipynb](./evaluate.ipynb) to check.\n"
+    "Ok, I have a model, but is it actually any good? I'll run some evaluations in [./evaluate.ipynb](./evaluate.ipynb) to check."
   ]
  }
 ],
--- a/pnpm-lock.yaml
+++ b/pnpm-lock.yaml
@@ -174,7 +174,10 @@ importers:
        specifier: 4.0.0-beta.7
        version: 4.0.0-beta.7(encoding@0.1.13)
      openpipe:
-        specifier: workspace:*
+        specifier: ^0.3.0
+        version: 0.3.0
+      openpipe-dev:
+        specifier: workspace:^
        version: link:../client-libs/typescript
      pg:
        specifier: ^8.11.2
@@ -7247,6 +7250,19 @@ packages:
      oidc-token-hash: 5.0.3
    dev: false

+  /openpipe@0.3.0:
+    resolution: {integrity: sha512-0hhk3Aq0kUxzvNb36vm9vssxMHYZvgJOg5wKeepRhVthW4ygBWftHZjR4PHyOtvjcRmnJ/v4h8xd/IINu5ypnQ==}
+    dependencies:
+      encoding: 0.1.13
+      form-data: 4.0.0
+      lodash-es: 4.17.21
+      node-fetch: 2.6.12(encoding@0.1.13)
+      openai-beta: /openai@4.0.0-beta.7(encoding@0.1.13)
+      openai-legacy: /openai@3.3.0
+    transitivePeerDependencies:
+      - debug
+    dev: false
+
  /optionator@0.9.3:
    resolution: {integrity: sha512-JjCoypp+jKn1ttEFExxhetCKeJt9zhAgAve5FXHixTvFDW/5aEktX9bufBKLRRMdU7bNtpLfcGu94B3cdEJgjg==}
    engines: {node: '>= 0.8.0'}
Author	SHA1	Message	Date
David Corbitt	83d71c6e9d	Record updated version number	2023-08-31 22:12:29 -07:00
David Corbitt	1693ac1c58	Publish updated README to npm	2023-08-31 22:09:03 -07:00
David Corbitt	8de0c0fc5a	Update npm lib README	2023-08-31 21:57:30 -07:00
David Corbitt	3ed390c941	Close project menu after creating a project	2023-08-31 19:31:28 -07:00
David Corbitt	fa16dd61dc	Add publish script	2023-08-31 18:49:03 -07:00
David Corbitt	cb73598148	Update package version	2023-08-31 18:48:56 -07:00
David Corbitt	2f01e53cf3	Update README	2023-08-31 18:48:44 -07:00
arcticfly	5b8113d8e7	Add links to docs, remove beta block from Dashboard and Request Logs (#208 ) * Remove mission text * Change wording * Add link to Read the Docs * Add links to docs in empty log tables * Remove beta block from Dashboard and Request Logs * Make ActionButton onClick optional	2023-08-31 17:17:20 -07:00
arcticfly	96a589e401	Add docs (#207 ) * Add docs folder with introduction, overview, and getting started * Add feature pages * Remove some of Who We Are	2023-08-31 13:20:08 -07:00
arcticfly	16354d83df	Update README.md	2023-08-31 00:07:23 -07:00
arcticfly	6a5afd0c9b	Update README.md	2023-08-29 23:03:15 -07:00
Kyle Corbitt	1684663ddc	Publish the ingestion library to NPM (#204 ) * Update client libs typescript README * Create index.d.ts files * Publish the ingestion library to NPM Library is now published at https://www.npmjs.com/package/openpipe; see README for details. * Rename package.json in /dist folder * Increment patch version * Increment package version * Add newline to publish.sh --------- Co-authored-by: David Corbitt <davidlcorbitt@gmail.com>	2023-08-29 12:18:57 -07:00
arcticfly	70fae68225	Share and delete experiment from ExperimentCard (#206 ) * Refactor DeleteExperimentDialog into separate component * Add CardMenu to ExperimentCard	2023-08-29 11:53:18 -07:00
sweep-ai[bot]	518c8620d0	Configure Sweep (#202 ) * Create sweep template * Create sweep slow template * Create sweep fast template --------- Co-authored-by: sweep-ai[bot] <128439645+sweep-ai[bot]@users.noreply.github.com>	2023-08-29 11:50:27 -07:00
arcticfly	ab87794192	Fix prompt duplication (#205 ) * Update client libs typescript README * Properly duplicate variant	2023-08-28 16:10:56 -07:00
arcticfly	48aa697002	Update replicate versions (#201 ) * Update client libs typescript README * Update replicate versions	2023-08-28 11:20:09 -07:00
arcticfly	55f2be861e	Minor edits (#196 ) * Add command to delete last fine tune * Change ids in seeded dashboard * Change fine tune icon	2023-08-27 18:53:02 -07:00
arcticfly	fa87887e91	Set contents of editor for refinement modals instead of saving on server (#199 ) * Set contents of editor for refinement modals instead of saving on server * Show New Experiment text on mobile	2023-08-27 18:52:25 -07:00
Kyle Corbitt	28713fb3ef	Merge pull request #197 from OpenPipe:hide-models Disable custom models for the moment	2023-08-25 16:02:39 -07:00
Kyle Corbitt	ead981b900	Disable custom models for the moment We're running into GPU constraints and need to turn off custom models until we find a better provider or can hot-swap them.	2023-08-25 16:01:51 -07:00
Kyle Corbitt	e0d0cc0df1	Merge pull request #193 from OpenPipe/examples classify-recipes example	2023-08-25 12:46:01 -07:00
arcticfly	7df1c59bd3	Update README.md	2023-08-24 22:23:40 -07:00
arcticfly	c83863f468	Update README.md	2023-08-24 20:59:46 -07:00
arcticfly	33ca98b267	Enlarge fine-tune gif	2023-08-24 14:14:38 -07:00
arcticfly	39c943f2ec	Change layout of README.md	2023-08-24 14:13:01 -07:00
arcticfly	2aa4ac1594	Update opening gif in README.md	2023-08-24 12:46:25 -07:00
arcticfly	42ade01f22	Update README.md	2023-08-24 11:14:25 -07:00
David Corbitt	59b79049c1	Move license to top level	2023-08-24 10:41:23 -07:00
arcticfly	0d7433cb7e	Update README.md Include more models	2023-08-24 00:13:24 -07:00