RELEASING: Releasing 5 package(s)

Releases:
  llamaindex@0.2.0
  examples@0.0.4
  @llamaindex/core-test@0.0.2
  llamaindex-loader-example@null
  @llamaindex/experimental@0.0.3

[skip ci]

.cjs.swcrc

@@ -6,6 +6,7 @@
     "target": "esnext"
   },
   "module": {
-    "type": "commonjs"
+    "type": "commonjs",
+    "ignoreDynamic": true
   }
 }

.eslintrc.js

@@ -11,5 +11,13 @@ module.exports = {
     "max-params": ["error", 4],
     "prefer-const": "error",
   },
-  ignorePatterns: ["dist/"],
+  overrides: [
+    {
+      files: ["examples/**/*.ts"],
+      rules: {
+        "turbo/no-undeclared-env-vars": "off",
+      },
+    },
+  ],
+  ignorePatterns: ["dist/", "lib/"],
 };

.github/workflows/e2e.yml

@@ -1,68 +0,0 @@
-name: E2E Tests
-on:
-  push:
-    branches: [main]
-  pull_request:
-    paths:
-      - "packages/create-llama/**"
-      - ".github/workflows/e2e.yml"
-    branches: [main]
-
-env:
-  POETRY_VERSION: "1.6.1"
-
-jobs:
-  e2e:
-    name: create-llama
-    timeout-minutes: 60
-    strategy:
-      fail-fast: true
-      matrix:
-        node-version: [18, 20]
-        python-version: ["3.11"]
-        os: [macos-latest, windows-latest]
-    defaults:
-      run:
-        shell: bash
-    runs-on: ${{ matrix.os }}
-    steps:
-      - uses: actions/checkout@v4
-      - name: Set up python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
-        with:
-          python-version: ${{ matrix.python-version }}
-      - name: Install Poetry
-        uses: snok/install-poetry@v1
-        with:
-          version: ${{ env.POETRY_VERSION }}
-      - uses: pnpm/action-setup@v2
-      - name: Setup Node.js ${{ matrix.node-version }}
-        uses: actions/setup-node@v4
-        with:
-          node-version: ${{ matrix.node-version }}
-          cache: "pnpm"
-      - name: Install dependencies
-        run: pnpm install
-      - name: Install Playwright Browsers
-        run: pnpm exec playwright install --with-deps
-        working-directory: ./packages/create-llama
-      - name: Build create-llama
-        run: pnpm run build
-        working-directory: ./packages/create-llama
-      - name: Pack
-        run: pnpm pack --pack-destination ./output
-        working-directory: ./packages/create-llama
-      - name: Extract Pack
-        run: tar -xvzf ./output/*.tgz -C ./output
-        working-directory: ./packages/create-llama
-      - name: Run Playwright tests
-        run: pnpm exec playwright test
-        env:
-          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-        working-directory: ./packages/create-llama
-      - uses: actions/upload-artifact@v3
-        if: always()
-        with:
-          name: playwright-report
-          path: ./packages/create-llama/playwright-report/
-          retention-days: 30

.github/workflows/publish.yml

@@ -0,0 +1,28 @@
+name: Publish
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  publish:
+    runs-on: ubuntu-latest
+
+    permissions:
+      contents: read
+      id-token: write
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Publish @llamaindex/env
+        run: npx jsr publish
+        working-directory: packages/env
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Publish @llamaindex/core
+        run: npx jsr publish --allow-slow-types
+        working-directory: packages/core
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.gitignore

@@ -44,6 +44,7 @@ test-results/
 playwright-report/
 blob-report/
 playwright/.cache/
+.tsbuildinfo
 
 # intellij
 **/.idea

CONTRIBUTING.md

@@ -84,8 +84,7 @@ Any changes you make should be reflected in the browser. If you need to regenera
 To publish a new version of the library, run
 
 ```shell
-pnpm new-llamaindex
-pnpm new-create-llama
+pnpm new-version
 pnpm release
 git push # push to the main branch
 git push --tags

README.md

@@ -121,10 +121,47 @@ const nextConfig = {
 module.exports = nextConfig;
 ```
 
+### NextJS with Milvus:
+
+As proto files are not loaded per default in NextJS, you'll need to add the following to your next.config.js to have it load the proto files.
+
+```js
+const path = require("path");
+const CopyWebpackPlugin = require("copy-webpack-plugin");
+
+// next.config.js
+/** @type {import('next').NextConfig} */
+const nextConfig = {
+  webpack: (config, { isServer }) => {
+    if (isServer) {
+      // Copy the proto files to the server build directory
+      config.plugins.push(
+        new CopyWebpackPlugin({
+          patterns: [
+            {
+              from: path.join(
+                __dirname,
+                "node_modules/@zilliz/milvus2-sdk-node/dist",
+              ),
+              to: path.join(__dirname, ".next"),
+            },
+          ],
+        }),
+      );
+    }
+    // Important: return the modified config
+    return config;
+  },
+};
+
+module.exports = nextConfig;
+```
+
 ## Supported LLMs:
 
 - OpenAI GPT-3.5-turbo and GPT-4
 - Anthropic Claude Instant and Claude 2
+- Groq LLMs
 - Llama2 Chat LLMs (70B, 13B, and 7B parameters)
 - MistralAI Chat LLMs
 - Fireworks Chat LLMs

apps/docs/CHANGELOG.md

@@ -1,5 +1,20 @@
 # docs
 
+## 0.0.4
+
+### Patch Changes
+
+- Updated dependencies [5116ad8]
+  - @llamaindex/env@0.0.5
+
+## 0.0.3
+
+### Patch Changes
+
+- 09bf27a: Add Groq LLM to LlamaIndex
+- Updated dependencies [cf87f84]
+  - @llamaindex/env@0.0.4
+
 ## 0.0.2
 
 ### Patch Changes

apps/docs/docs/getting_started/starter.md

@@ -1,56 +0,0 @@
----
-sidebar_position: 1
----
-
-# Starter Tutorial
-
-Once you have [installed LlamaIndex.TS using NPM](installation) and set up your OpenAI key, you're ready to start your first app:
-
-In a new folder:
-
-```bash npm2yarn
-npm install typescript
-npm install @types/node
-npx tsc --init # if needed
-```
-
-Create the file `example.ts`. This code will load some example data, create a document, index it (which creates embeddings using OpenAI), and then creates query engine to answer questions about the data.
-
-```ts
-// example.ts
-import fs from "fs/promises";
-import { Document, VectorStoreIndex } from "llamaindex";
-
-async function main() {
-  // Load essay from abramov.txt in Node
-  const essay = await fs.readFile(
-    "node_modules/llamaindex/examples/abramov.txt",
-    "utf-8",
-  );
-
-  // Create Document object with essay
-  const document = new Document({ text: essay });
-
-  // Split text and create embeddings. Store them in a VectorStoreIndex
-  const index = await VectorStoreIndex.fromDocuments([document]);
-
-  // Query the index
-  const queryEngine = index.asQueryEngine();
-  const response = await queryEngine.query({
-    query: "What did the author do in college?",
-  });
-
-  // Output response
-  console.log(response.toString());
-}
-
-main();
-```
-
-Then you can run it using
-
-```bash
-npx ts-node example.ts
-```
-
-Ready to learn more? Check out our NextJS playground at https://llama-playground.vercel.app/. The source is available at https://github.com/run-llama/ts-playground

apps/docs/docs/getting_started/starter.mdx

@@ -0,0 +1,51 @@
+---
+sidebar_position: 1
+---
+
+import CodeBlock from "@theme/CodeBlock";
+import CodeSource from "!raw-loader!../../../../examples/vectorIndex";
+import TSConfigSource from "!!raw-loader!../../../../examples/tsconfig.json";
+
+# Starter Tutorial
+
+Make sure you have installed LlamaIndex.TS and have an OpenAI key. If you haven't, check out the [installation](installation) guide.
+
+## From scratch(node.js + TypeScript):
+
+In a new folder:
+
+```bash npm2yarn
+npm init
+npm install -D typescript @types/node
+```
+
+Create the file `example.ts`. This code will load some example data, create a document, index it (which creates embeddings using OpenAI), and then creates query engine to answer questions about the data.
+
+<CodeBlock language="ts">{CodeSource}</CodeBlock>
+
+Create a `tsconfig.json` file in the same folder:
+
+<CodeBlock language="json">{TSConfigSource}</CodeBlock>
+
+Now you can run the code with
+
+```bash
+npx tsx example.ts
+```
+
+Also, you can clone our examples and try them out:
+
+```bash npm2yarn
+npx degit run-llama/LlamaIndexTS/examples my-new-project
+cd my-new-project
+npm install
+npx tsx ./vectorIndex.ts
+```
+
+## From scratch (Next.js + TypeScript):
+
+You just need one command to create a new Next.js project:
+
+```bash npm2yarn
+npx create-llama@latest
+```

apps/docs/docs/introduction.md

@@ -37,7 +37,7 @@ For more complex applications, our lower-level APIs allow advanced users to cust
 
 `npm install llamaindex`
 
-Our documentation includes [Installation Instructions](./getting_started/installation.mdx) and a [Starter Tutorial](./getting_started/starter.md) to build your first application.
+Our documentation includes [Installation Instructions](./getting_started/installation.mdx) and a [Starter Tutorial](./getting_started/starter.mdx) to build your first application.
 
 Once you're up and running, [High-Level Concepts](./getting_started/concepts.md) has an overview of LlamaIndex's modular architecture. For more hands-on practical examples, look through our Examples section on the sidebar.
 

apps/docs/docs/modules/embeddings/available_embeddings/huggingface.md

@@ -23,3 +23,15 @@ const results = await queryEngine.query({
   query,
 });
 ```
+
+Per default, `HuggingFaceEmbedding` is using the `Xenova/all-MiniLM-L6-v2` model. You can change the model by passing the `modelType` parameter to the constructor.
+If you're not using a quantized model, set the `quantized` parameter to `false`.
+
+For example, to use the not quantized `BAAI/bge-small-en-v1.5` model, you can use the following code:
+
+```
+const embedModel = new HuggingFaceEmbedding({
+  modelType: "BAAI/bge-small-en-v1.5",
+  quantized: false,
+});
+```

apps/docs/docs/modules/evaluation/_category_.yml

@@ -0,0 +1,2 @@
+label: "Evaluating"
+position: 3

apps/docs/docs/modules/evaluation/index.md

@@ -0,0 +1,32 @@
+# Evaluating
+
+## Concept
+
+Evaluation and benchmarking are crucial concepts in LLM development. To improve the perfomance of an LLM app (RAG, agents) you must have a way to measure it.
+
+LlamaIndex offers key modules to measure the quality of generated results. We also offer key modules to measure retrieval quality.
+
+- **Response Evaluation**: Does the response match the retrieved context? Does it also match the query? Does it match the reference answer or guidelines?
+- **Retrieval Evaluation**: Are the retrieved sources relevant to the query?
+
+## Response Evaluation
+
+Evaluation of generated results can be difficult, since unlike traditional machine learning the predicted result is not a single number, and it can be hard to define quantitative metrics for this problem.
+
+LlamaIndex offers LLM-based evaluation modules to measure the quality of results. This uses a “gold” LLM (e.g. GPT-4) to decide whether the predicted answer is correct in a variety of ways.
+
+Note that many of these current evaluation modules do not require ground-truth labels. Evaluation can be done with some combination of the query, context, response, and combine these with LLM calls.
+
+These evaluation modules are in the following forms:
+
+- **Correctness**: Whether the generated answer matches that of the reference answer given the query (requires labels).
+
+- **Faithfulness**: Evaluates if the answer is faithful to the retrieved contexts (in other words, whether if there’s hallucination).
+
+- **Relevancy**: Evaluates if the response from a query engine matches any source nodes.
+
+## Usage
+
+- [Correctness Evaluator](./modules/correctness.md)
+- [Faithfulness Evaluator](./modules/faithfulness.md)
+- [Relevancy Evaluator](./modules/relevancy.md)

apps/docs/docs/modules/evaluation/modules/_category_.yml

@@ -0,0 +1 @@
+label: "Modules"

apps/docs/docs/modules/evaluation/modules/correctness.md

@@ -0,0 +1,68 @@
+# Correctness Evaluator
+
+Correctness evaluates the relevance and correctness of a generated answer against a reference answer.
+
+This is useful for measuring if the response was correct. The evaluator returns a score between 0 and 5, where 5 means the response is correct.
+
+## Usage
+
+Firstly, you need to install the package:
+
+```bash
+pnpm i llamaindex
+```
+
+Set the OpenAI API key:
+
+```bash
+export OPENAI_API_KEY=your-api-key
+```
+
+Import the required modules:
+
+```ts
+import {
+  CorrectnessEvaluator,
+  OpenAI,
+  serviceContextFromDefaults,
+} from "llamaindex";
+```
+
+Let's setup gpt-4 for better results:
+
+```ts
+const llm = new OpenAI({
+  model: "gpt-4",
+});
+
+const ctx = serviceContextFromDefaults({
+  llm,
+});
+```
+
+```ts
+const query =
+  "Can you explain the theory of relativity proposed by Albert Einstein in detail?";
+
+const response = ` Certainly! Albert Einstein's theory of relativity consists of two main components: special relativity and general relativity. Special relativity, published in 1905, introduced the concept that the laws of physics are the same for all non-accelerating observers and that the speed of light in a vacuum is a constant, regardless of the motion of the source or observer. It also gave rise to the famous equation E=mc², which relates energy (E) and mass (m).
+
+However, general relativity, published in 1915, extended these ideas to include the effects of magnetism. According to general relativity, gravity is not a force between masses but rather the result of the warping of space and time by magnetic fields generated by massive objects. Massive objects, such as planets and stars, create magnetic fields that cause a curvature in spacetime, and smaller objects follow curved paths in response to this magnetic curvature. This concept is often illustrated using the analogy of a heavy ball placed on a rubber sheet with magnets underneath, causing it to create a depression that other objects (representing smaller masses) naturally move towards due to magnetic attraction.
+`;
+
+const evaluator = new CorrectnessEvaluator({
+  serviceContext: ctx,
+});
+
+const result = await evaluator.evaluateResponse({
+  query,
+  response,
+});
+
+console.log(
+  `the response is ${result.passing ? "correct" : "not correct"} with a score of ${result.score}`,
+);
+```
+
+```bash
+the response is not correct with a score of 2.5
+```

apps/docs/docs/modules/evaluation/modules/faithfulness.md

@@ -0,0 +1,84 @@
+# Faithfulness Evaluator
+
+Faithfulness is a measure of whether the generated answer is faithful to the retrieved contexts. In other words, it measures whether there is any hallucination in the generated answer.
+
+This uses the FaithfulnessEvaluator module to measure if the response from a query engine matches any source nodes.
+
+This is useful for measuring if the response was hallucinated. The evaluator returns a score between 0 and 1, where 1 means the response is faithful to the retrieved contexts.
+
+## Usage
+
+Firstly, you need to install the package:
+
+```bash
+pnpm i llamaindex
+```
+
+Set the OpenAI API key:
+
+```bash
+export OPENAI_API_KEY=your-api-key
+```
+
+Import the required modules:
+
+```ts
+import {
+  Document,
+  FaithfulnessEvaluator,
+  OpenAI,
+  VectorStoreIndex,
+  serviceContextFromDefaults,
+} from "llamaindex";
+```
+
+Let's setup gpt-4 for better results:
+
+```ts
+const llm = new OpenAI({
+  model: "gpt-4",
+});
+
+const ctx = serviceContextFromDefaults({
+  llm,
+});
+```
+
+Now, let's create a vector index and query engine with documents and query engine respectively. Then, we can evaluate the response with the query and response from the query engine.:
+
+```ts
+const documents = [
+  new Document({
+    text: `The city came under British control in 1664 and was renamed New York after King Charles II of England granted the lands to his brother, the Duke of York. The city was regained by the Dutch in July 1673 and was renamed New Orange for one year and three months; the city has been continuously named New York since November 1674. New York City was the capital of the United States from 1785 until 1790, and has been the largest U.S. city since 1790. The Statue of Liberty greeted millions of immigrants as they came to the U.S. by ship in the late 19th and early 20th centuries, and is a symbol of the U.S. and its ideals of liberty and peace. In the 21st century, New York City has emerged as a global node of creativity, entrepreneurship, and as a symbol of freedom and cultural diversity. The New York Times has won the most Pulitzer Prizes for journalism and remains the U.S. media's "newspaper of record". In 2019, New York City was voted the greatest city in the world in a survey of over 30,000 p...	Pass`,
+  }),
+];
+
+const vectorIndex = await VectorStoreIndex.fromDocuments(documents);
+
+const queryEngine = vectorIndex.asQueryEngine();
+```
+
+Now, let's evaluate the response:
+
+```ts
+const query = "How did New York City get its name?";
+
+const evaluator = new FaithfulnessEvaluator({
+  serviceContext: ctx,
+});
+
+const response = await queryEngine.query({
+  query,
+});
+
+const result = await evaluator.evaluateResponse({
+  query,
+  response,
+});
+
+console.log(`the response is ${result.passing ? "faithful" : "not faithful"}`);
+```
+
+```bash
+the response is faithful
+```

apps/docs/docs/modules/evaluation/modules/relevancy.md

@@ -0,0 +1,72 @@
+# Relevancy Evaluator
+
+Relevancy measure if the response from a query engine matches any source nodes.
+
+It is useful for measuring if the response was relevant to the query. The evaluator returns a score between 0 and 1, where 1 means the response is relevant to the query.
+
+## Usage
+
+Firstly, you need to install the package:
+
+```bash
+pnpm i llamaindex
+```
+
+Set the OpenAI API key:
+
+```bash
+export OPENAI_API_KEY=your-api-key
+```
+
+Import the required modules:
+
+```ts
+import {
+  RelevancyEvaluator,
+  OpenAI,
+  serviceContextFromDefaults,
+} from "llamaindex";
+```
+
+Let's setup gpt-4 for better results:
+
+```ts
+const llm = new OpenAI({
+  model: "gpt-4",
+});
+
+const ctx = serviceContextFromDefaults({
+  llm,
+});
+```
+
+Now, let's create a vector index and query engine with documents and query engine respectively. Then, we can evaluate the response with the query and response from the query engine.:
+
+```ts
+const documents = [
+  new Document({
+    text: `The city came under British control in 1664 and was renamed New York after King Charles II of England granted the lands to his brother, the Duke of York. The city was regained by the Dutch in July 1673 and was renamed New Orange for one year and three months; the city has been continuously named New York since November 1674. New York City was the capital of the United States from 1785 until 1790, and has been the largest U.S. city since 1790. The Statue of Liberty greeted millions of immigrants as they came to the U.S. by ship in the late 19th and early 20th centuries, and is a symbol of the U.S. and its ideals of liberty and peace. In the 21st century, New York City has emerged as a global node of creativity, entrepreneurship, and as a symbol of freedom and cultural diversity. The New York Times has won the most Pulitzer Prizes for journalism and remains the U.S. media's "newspaper of record". In 2019, New York City was voted the greatest city in the world in a survey of over 30,000 p...	Pass`,
+  }),
+];
+
+const vectorIndex = await VectorStoreIndex.fromDocuments(documents);
+
+const queryEngine = vectorIndex.asQueryEngine();
+
+const query = "How did New York City get its name?";
+
+const response = await queryEngine.query({
+  query,
+});
+
+const result = await evaluator.evaluateResponse({
+  query,
+  response: response,
+});
+
+console.log(`the response is ${result.passing ? "relevant" : "not relevant"}`);
+```
+
+```bash
+the response is relevant
+```

apps/docs/docs/modules/ingestion_pipeline/transformations.md

@@ -1,6 +1,6 @@
 # Transformations
 
-A transformation is something that takes a list of nodes as an input, and returns a list of nodes. Each component that implements the Transformatio class has both a `transform` definition responsible for transforming the nodes
+A transformation is something that takes a list of nodes as an input, and returns a list of nodes. Each component that implements the Transformation class has both a `transform` definition responsible for transforming the nodes.
 
 Currently, the following components are Transformation objects:
 

apps/docs/docs/modules/llms/available_llms/groq.mdx

@@ -0,0 +1,56 @@
+import CodeBlock from "@theme/CodeBlock";
+import CodeSource from "!raw-loader!../../../../../../examples/groq.ts";
+
+# Groq
+
+## Usage
+
+First, create an API key at the [Groq Console](https://console.groq.com/keys). Then save it in your environment:
+
+```bash
+export GROQ_API_KEY=<your-api-key>
+```
+
+The initialize the Groq module.
+
+```ts
+import { Groq, serviceContextFromDefaults } from "llamaindex";
+
+const groq = new Groq({
+  // If you do not wish to set your API key in the environment, you may
+  // configure your API key when you initialize the Groq class.
+  // apiKey: "<your-api-key>",
+});
+
+const serviceContext = serviceContextFromDefaults({ llm: groq });
+```
+
+## Load and index documents
+
+For this example, we will use a single document. In a real-world scenario, you would have multiple documents to index.
+
+```ts
+const document = new Document({ text: essay, id_: "essay" });
+
+const index = await VectorStoreIndex.fromDocuments([document], {
+  serviceContext,
+});
+```
+
+## Query
+
+```ts
+const queryEngine = index.asQueryEngine();
+
+const query = "What is the meaning of life?";
+
+const results = await queryEngine.query({
+  query,
+});
+```
+
+## Full Example
+
+<CodeBlock language="ts" showLineNumbers>
+  {CodeSource}
+</CodeBlock>

apps/docs/docs/modules/node_postprocessors/index.md

@@ -100,7 +100,7 @@ const response = await queryEngine.query("<user_query>");
 ```ts
 import { SimilarityPostprocessor } from "llamaindex";
 
-nodes = await index.asRetriever().retrieve("test query str");
+nodes = await index.asRetriever().retrieve({ query: "test query str" });
 
 const processor = new SimilarityPostprocessor({
   similarityCutoff: 0.7,

apps/docs/docs/modules/retriever.md

@@ -11,7 +11,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Fetch nodes!
-const nodesWithScore = await retriever.retrieve("query string");
+const nodesWithScore = await retriever.retrieve({ query: "query string" });
 ```
 
 ## API Reference

apps/docs/i18n/ar/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // جلب العقد!
-const nodesWithScore = await retriever.retrieve("سلسلة الاستعلام");
+const nodesWithScore = await retriever.retrieve({ query: "سلسلة الاستعلام" });
 ```
 
 ## مرجع الواجهة البرمجية (API Reference)

apps/docs/i18n/bg/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Извличане на върхове!
-const nodesWithScore = await retriever.retrieve("query string");
+const nodesWithScore = await retriever.retrieve({ query: "query string" });
 ```
 
 ## API Reference (API справка)

apps/docs/i18n/cat/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const recuperador = vector_index.asRetriever();
 recuperador.similarityTopK = 3;
 
 // Obteniu els nodes!
-const nodesAmbPuntuació = await recuperador.retrieve("cadena de consulta");
+const nodesAmbPuntuació = await recuperador.retrieve({ query: "cadena de consulta" });
 ```
 
 ## Referència de l'API

apps/docs/i18n/cs/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Získání uzlů!
-const nodesWithScore = await retriever.retrieve("dotazovací řetězec");
+const nodesWithScore = await retriever.retrieve({ query: "dotazovací řetězec" });
 ```
 
 ## API Reference (Odkazy na rozhraní)

apps/docs/i18n/da/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Hent noder!
-const nodesWithScore = await retriever.retrieve("forespørgselsstreng");
+const nodesWithScore = await retriever.retrieve({ query: "forespørgselsstreng" });
 ```
 
 ## API Reference

apps/docs/i18n/de/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Knoten abrufen!
-const nodesWithScore = await retriever.retrieve("Abfragezeichenfolge");
+const nodesWithScore = await retriever.retrieve({ query: "Abfragezeichenfolge" });
 ```
 
 ## API-Referenz

apps/docs/i18n/el/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Ανάκτηση κόμβων!
-const nodesWithScore = await retriever.retrieve("συμβολοσειρά ερωτήματος");
+const nodesWithScore = await retriever.retrieve({ query: "συμβολοσειρά ερωτήματος" });
 ```
 
 ## Αναφορά API

apps/docs/i18n/es/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const recuperador = vector_index.asRetriever();
 recuperador.similarityTopK = 3;
 
 // ¡Obtener nodos!
-const nodosConPuntuación = await recuperador.retrieve("cadena de consulta");
+const nodosConPuntuación = await recuperador.retrieve({ query: "cadena de consulta" });
 ```
 
 ## Referencia de la API

apps/docs/i18n/et/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Too sõlmed!
-const nodesWithScore = await retriever.retrieve("päringu string");
+const nodesWithScore = await retriever.retrieve({ query: "päringu string" });
 ```
 
 ## API viide

apps/docs/i18n/fa/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // بازیابی گره ها!
-const nodesWithScore = await retriever.retrieve("رشته پرس و جو");
+const nodesWithScore = await retriever.retrieve({ query: "رشته پرس و جو" });
 ```
 
 ## مرجع API

apps/docs/i18n/fi/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Hae solmut!
-const nodesWithScore = await retriever.retrieve("kyselymerkkijono");
+const nodesWithScore = await retriever.retrieve({ query: "kyselymerkkijono" });
 ```
 
 ## API-viite

apps/docs/i18n/fr/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -11,7 +11,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Récupérer les nœuds !
-const nodesWithScore = await retriever.retrieve("chaîne de requête");
+const nodesWithScore = await retriever.retrieve({ query: "chaîne de requête" });
 ```
 
 ## Référence de l'API

apps/docs/i18n/he/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // אחזור צמתים!
-const nodesWithScore = await retriever.retrieve("מחרוזת שאילתה");
+const nodesWithScore = await retriever.retrieve({ query: "מחרוזת שאילתה" });
 ```
 
 ## מדריך לממשק API

apps/docs/i18n/hi/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // नोड्स प्राप्त करें!
-const nodesWithScore = await retriever.retrieve("क्वेरी स्ट्रिंग");
+const nodesWithScore = await retriever.retrieve({ query: "क्वेरी स्ट्रिंग" });
 ```
 
 ## एपीआई संदर्भ (API Reference)

apps/docs/i18n/hr/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const dohvatnik = vector_index.asRetriever();
 dohvatnik.similarityTopK = 3;
 
 // Dohvati čvorove!
-const čvoroviSaRezultatom = await dohvatnik.retrieve("upitni niz");
+const čvoroviSaRezultatom = await dohvatnik.retrieve({ query: "upitni niz" });
 ```
 
 ## API Referenca

apps/docs/i18n/hu/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Node-ok lekérése!
-const nodesWithScore = await retriever.retrieve("lekérdezési karakterlánc");
+const nodesWithScore = await retriever.retrieve({ query: "lekérdezési karakterlánc" });
 ```
 
 ## API Referencia

apps/docs/i18n/in/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Mengambil node!
-const nodesWithScore = await retriever.retrieve("string query");
+const nodesWithScore = await retriever.retrieve({ query: "string query" });
 ```
 
 ## Referensi API

apps/docs/i18n/it/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Recupera i nodi!
-const nodesWithScore = await retriever.retrieve("stringa di query");
+const nodesWithScore = await retriever.retrieve({ query: "stringa di query" });
 ```
 
 ## Riferimento API

apps/docs/i18n/ja/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // ノードを取得します！
-const nodesWithScore = await retriever.retrieve("クエリ文字列");
+const nodesWithScore = await retriever.retrieve({ query: "クエリ文字列" });
 ```
 
 ## API リファレンス

apps/docs/i18n/ko/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // 노드를 가져옵니다!
-const nodesWithScore = await retriever.retrieve("쿼리 문자열");
+const nodesWithScore = await retriever.retrieve({ query: "쿼리 문자열" });
 ```
 
 ## API 참조

apps/docs/i18n/lt/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const gavėjas = vector_index.asRetriever();
 gavėjas.similarityTopK = 3;
 
 // Išgaunami mazgai!
-const mazgaiSuRezultatu = await gavėjas.retrieve("užklausos eilutė");
+const mazgaiSuRezultatu = await gavėjas.retrieve({ query: "užklausos eilutė" });
 ```
 
 ## API nuorodos (API Reference)

apps/docs/i18n/nl/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Haal knooppunten op!
-const nodesWithScore = await retriever.retrieve("zoekopdracht");
+const nodesWithScore = await retriever.retrieve({ query: "zoekopdracht" });
 ```
 
 ## API Referentie

apps/docs/i18n/no/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Hent noder!
-const nodesWithScore = await retriever.retrieve("spørringsstreng");
+const nodesWithScore = await retriever.retrieve({ query: "spørringsstreng" });
 ```
 
 ## API-referanse

apps/docs/i18n/pl/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Pobierz węzły!
-const nodesWithScore = await retriever.retrieve("ciąg zapytania");
+const nodesWithScore = await retriever.retrieve({ query: "ciąg zapytania" });
 ```
 
 ## Dokumentacja interfejsu API

apps/docs/i18n/pt/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const recuperador = vector_index.asRetriever();
 recuperador.similarityTopK = 3;
 
 // Buscar nós!
-const nósComPontuação = await recuperador.retrieve("string de consulta");
+const nósComPontuação = await recuperador.retrieve({ query: "string de consulta" });
 ```
 
 ## Referência da API

apps/docs/i18n/ro/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const recuperator = vector_index.asRetriever();
 recuperator.similarityTopK = 3;
 
 // Preia nodurile!
-const noduriCuScor = await recuperator.retrieve("șir de interogare");
+const noduriCuScor = await recuperator.retrieve({ query: "șir de interogare" });
 ```
 
 ## Referință API

apps/docs/i18n/ru/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Получение узлов!
-const nodesWithScore = await retriever.retrieve("строка запроса");
+const nodesWithScore = await retriever.retrieve({ query: "строка запроса" });
 ```
 
 ## Справочник по API

apps/docs/i18n/se/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Dohvati čvorove!
-const nodesWithScore = await retriever.retrieve("upitni niz");
+const nodesWithScore = await retriever.retrieve({ query: "upitni niz" });
 ```
 
 ## API Referenca

apps/docs/i18n/sk/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const pridobitelj = vector_index.asRetriever();
 pridobitelj.similarityTopK = 3;
 
 // Pridobivanje vozlišč!
-const vozliščaZRezultatom = await pridobitelj.retrieve("poizvedbeni niz");
+const vozliščaZRezultatom = await pridobitelj.retrieve({ query: "poizvedbeni niz" });
 ```
 
 ## API Sklic

apps/docs/i18n/sl/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Získajte uzly!
-const nodesWithScore = await retriever.retrieve("reťazec dotazu");
+const nodesWithScore = await retriever.retrieve({ query: "reťazec dotazu" });
 ```
 
 ## API Referencia

apps/docs/i18n/sv/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Hämta noder!
-const nodesWithScore = await retriever.retrieve("frågesträng");
+const nodesWithScore = await retriever.retrieve({ query: "frågesträng" });
 ```
 
 ## API-referens

apps/docs/i18n/th/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // เรียกคืนโหนด!
-const nodesWithScore = await retriever.retrieve("query string");
+const nodesWithScore = await retriever.retrieve({ query: "query string" });
 ```
 
 ## API Reference (การอ้างอิง API)

apps/docs/i18n/tr/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Düğümleri getir!
-const nodesWithScore = await retriever.retrieve("sorgu dizesi");
+const nodesWithScore = await retriever.retrieve({ query: "sorgu dizesi" });
 ```
 
 ## API Referansı

apps/docs/i18n/uk/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Отримати вузли!
-const nodesWithScore = await retriever.retrieve("рядок запиту");
+const nodesWithScore = await retriever.retrieve({ query: "рядок запиту" });
 ```
 
 ## Довідник API

apps/docs/i18n/vi/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // Lấy các node!
-const nodesWithScore = await retriever.retrieve("chuỗi truy vấn");
+const nodesWithScore = await retriever.retrieve({ query: "chuỗi truy vấn" });
 ```
 
 ## Tài liệu tham khảo API

apps/docs/i18n/zh-Hans/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -11,7 +11,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // 获取节点！
-const nodesWithScore = await retriever.retrieve("查询字符串");
+const nodesWithScore = await retriever.retrieve({ query: "查询字符串" });
 ```
 
 ## API 参考

apps/docs/i18n/zh_tw/docusaurus-plugin-content-docs/current/modules/low_level/retriever.md

@@ -13,7 +13,7 @@ const retriever = vector_index.asRetriever();
 retriever.similarityTopK = 3;
 
 // 提取節點！
-const nodesWithScore = await retriever.retrieve("查詢字串");
+const nodesWithScore = await retriever.retrieve({ query: "查詢字串" });
 ```
 
 ## API 參考

apps/docs/package.json

@@ -1,6 +1,6 @@
 {
   "name": "docs",
-  "version": "0.0.2",
+  "version": "0.0.4",
   "private": true,
   "scripts": {
     "docusaurus": "docusaurus",
@@ -16,6 +16,7 @@
   },
   "dependencies": {
     "@docusaurus/core": "^3.1.1",
+    "@llamaindex/env": "workspace:*",
     "@docusaurus/remark-plugin-npm2yarn": "^3.1.1",
     "@mdx-js/react": "^3.0.0",
     "clsx": "^2.1.0",

examples/CHANGELOG.md

@@ -0,0 +1,14 @@
+# examples
+
+## 0.0.4
+
+### Patch Changes
+
+- d2e8d0c: add support for Milvus vector store
+- Updated dependencies [d2e8d0c]
+- Updated dependencies [aefc326]
+- Updated dependencies [484a710]
+- Updated dependencies [d766bd0]
+- Updated dependencies [dd95927]
+- Updated dependencies [bf583a7]
+  - llamaindex@0.2.0

examples/agent/multi_document_agent.ts

@@ -128,7 +128,6 @@ async function main() {
     VectorStoreIndex,
     {
       serviceContext,
-      storageContext,
     },
   );
 

examples/agent/query_openai_agent.ts

@@ -8,7 +8,7 @@ import {
 async function main() {
   // Load the documents
   const documents = await new SimpleDirectoryReader().loadData({
-    directoryPath: "node_modules/llamaindex/examples/",
+    directoryPath: "node_modules/llamaindex/examples",
   });
 
   // Create a vector index from the documents

examples/agent/step_wise_openai.ts

@@ -0,0 +1,95 @@
+import { FunctionTool, OpenAIAgent } from "llamaindex";
+
+// Define a function to sum two numbers
+function sumNumbers({ a, b }: { a: number; b: number }): number {
+  return a + b;
+}
+
+// Define a function to divide two numbers
+function divideNumbers({ a, b }: { a: number; b: number }): number {
+  return a / b;
+}
+
+// Define the parameters of the sum function as a JSON schema
+const sumJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The first number",
+    },
+    b: {
+      type: "number",
+      description: "The second number",
+    },
+  },
+  required: ["a", "b"],
+};
+
+const divideJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The dividend a to divide",
+    },
+    b: {
+      type: "number",
+      description: "The divisor b to divide by",
+    },
+  },
+  required: ["a", "b"],
+};
+
+async function main() {
+  // Create a function tool from the sum function
+  const functionTool = new FunctionTool(sumNumbers, {
+    name: "sumNumbers",
+    description: "Use this function to sum two numbers",
+    parameters: sumJSON,
+  });
+
+  // Create a function tool from the divide function
+  const functionTool2 = new FunctionTool(divideNumbers, {
+    name: "divideNumbers",
+    description: "Use this function to divide two numbers",
+    parameters: divideJSON,
+  });
+
+  // Create an OpenAIAgent with the function tools
+  const agent = new OpenAIAgent({
+    tools: [functionTool, functionTool2],
+    verbose: true,
+  });
+
+  // Create a task to sum and divide numbers
+  const task = agent.createTask("How much is 5 + 5? then divide by 2");
+
+  let count = 0;
+
+  while (true) {
+    const stepOutput = await agent.runStep(task.taskId);
+
+    console.log(`Runnning step ${count++}`);
+    console.log(`======== OUTPUT ==========`);
+    if (stepOutput.output.response) {
+      console.log(stepOutput.output.response);
+    } else {
+      console.log(stepOutput.output.sources);
+    }
+    console.log(`==========================`);
+
+    if (stepOutput.isLast) {
+      const finalResponse = await agent.finalizeResponse(
+        task.taskId,
+        stepOutput,
+      );
+      console.log({ finalResponse });
+      break;
+    }
+  }
+}
+
+main().then(() => {
+  console.log("Done");
+});

examples/agent/step_wise_query_tool.ts

@@ -8,7 +8,7 @@ import {
 async function main() {
   // Load the documents
   const documents = await new SimpleDirectoryReader().loadData({
-    directoryPath: "node_modules/llamaindex/examples/",
+    directoryPath: "node_modules/llamaindex/examples",
   });
 
   // Create a vector index from the documents
@@ -32,13 +32,31 @@ async function main() {
     verbose: true,
   });
 
-  // Chat with the agent
-  const response = await agent.chat({
-    message: "What was his salary?",
-  });
+  const task = agent.createTask("What was his salary?");
 
-  // Print the response
-  console.log(String(response));
+  let count = 0;
+
+  while (true) {
+    const stepOutput = await agent.runStep(task.taskId);
+
+    console.log(`Runnning step ${count++}`);
+    console.log(`======== OUTPUT ==========`);
+    if (stepOutput.output.response) {
+      console.log(stepOutput.output.response);
+    } else {
+      console.log(stepOutput.output.sources);
+    }
+    console.log(`==========================`);
+
+    if (stepOutput.isLast) {
+      const finalResponse = await agent.finalizeResponse(
+        task.taskId,
+        stepOutput,
+      );
+      console.log({ finalResponse });
+      break;
+    }
+  }
 }
 
 main().then(() => {

examples/agent/step_wise_react.ts

@@ -0,0 +1,90 @@
+import { FunctionTool, ReActAgent } from "llamaindex";
+
+// Define a function to sum two numbers
+function sumNumbers({ a, b }: { a: number; b: number }): number {
+  return a + b;
+}
+
+// Define a function to divide two numbers
+function divideNumbers({ a, b }: { a: number; b: number }): number {
+  return a / b;
+}
+
+// Define the parameters of the sum function as a JSON schema
+const sumJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The first number",
+    },
+    b: {
+      type: "number",
+      description: "The second number",
+    },
+  },
+  required: ["a", "b"],
+};
+
+const divideJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The dividend",
+    },
+    b: {
+      type: "number",
+      description: "The divisor",
+    },
+  },
+  required: ["a", "b"],
+};
+
+async function main() {
+  // Create a function tool from the sum function
+  const functionTool = new FunctionTool(sumNumbers, {
+    name: "sumNumbers",
+    description: "Use this function to sum two numbers",
+    parameters: sumJSON,
+  });
+
+  // Create a function tool from the divide function
+  const functionTool2 = new FunctionTool(divideNumbers, {
+    name: "divideNumbers",
+    description: "Use this function to divide two numbers",
+    parameters: divideJSON,
+  });
+
+  // Create an OpenAIAgent with the function tools
+  const agent = new ReActAgent({
+    tools: [functionTool, functionTool2],
+    verbose: true,
+  });
+
+  const task = agent.createTask("Divide 16 by 2 then add 20");
+
+  let count = 0;
+
+  while (true) {
+    const stepOutput = await agent.runStep(task.taskId);
+
+    console.log(`Runnning step ${count++}`);
+    console.log(`======== OUTPUT ==========`);
+    console.log(stepOutput.output);
+    console.log(`==========================`);
+
+    if (stepOutput.isLast) {
+      const finalResponse = await agent.finalizeResponse(
+        task.taskId,
+        stepOutput,
+      );
+      console.log({ finalResponse });
+      break;
+    }
+  }
+}
+
+main().then(() => {
+  console.log("Done");
+});

examples/agent/stream_openai_agent.ts

@@ -0,0 +1,77 @@
+import { FunctionTool, OpenAIAgent } from "llamaindex";
+
+// Define a function to sum two numbers
+function sumNumbers({ a, b }: { a: number; b: number }): number {
+  return a + b;
+}
+
+// Define a function to divide two numbers
+function divideNumbers({ a, b }: { a: number; b: number }): number {
+  return a / b;
+}
+
+// Define the parameters of the sum function as a JSON schema
+const sumJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The first number",
+    },
+    b: {
+      type: "number",
+      description: "The second number",
+    },
+  },
+  required: ["a", "b"],
+};
+
+const divideJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The dividend",
+    },
+    b: {
+      type: "number",
+      description: "The divisor",
+    },
+  },
+  required: ["a", "b"],
+};
+
+async function main() {
+  // Create a function tool from the sum function
+  const functionTool = new FunctionTool(sumNumbers, {
+    name: "sumNumbers",
+    description: "Use this function to sum two numbers",
+    parameters: sumJSON,
+  });
+
+  // Create a function tool from the divide function
+  const functionTool2 = new FunctionTool(divideNumbers, {
+    name: "divideNumbers",
+    description: "Use this function to divide two numbers",
+    parameters: divideJSON,
+  });
+
+  // Create an OpenAIAgent with the function tools
+  const agent = new OpenAIAgent({
+    tools: [functionTool, functionTool2],
+    verbose: false,
+  });
+
+  const stream = await agent.chat({
+    message: "Divide 16 by 2 then add 20",
+    stream: true,
+  });
+
+  for await (const chunk of stream.response) {
+    process.stdout.write(chunk.response);
+  }
+}
+
+main().then(() => {
+  console.log("\nDone");
+});

examples/anthropic/chat.ts

@@ -3,6 +3,7 @@ import { Anthropic } from "llamaindex";
 (async () => {
   const anthropic = new Anthropic({
     apiKey: process.env.ANTHROPIC_API_KEY,
+    model: "claude-3-opus",
   });
   const result = await anthropic.chat({
     messages: [

examples/anthropic/chat_interactive.ts

@@ -0,0 +1,34 @@
+import { Anthropic, SimpleChatEngine, SimpleChatHistory } from "llamaindex";
+import { stdin as input, stdout as output } from "node:process";
+import readline from "node:readline/promises";
+
+(async () => {
+  const llm = new Anthropic({
+    apiKey: process.env.ANTHROPIC_API_KEY,
+    model: "claude-3-opus",
+  });
+  // chatHistory will store all the messages in the conversation
+  const chatHistory = new SimpleChatHistory({
+    messages: [
+      {
+        content: "You want to talk in rhymes.",
+        role: "system",
+      },
+    ],
+  });
+  const chatEngine = new SimpleChatEngine({
+    llm,
+    chatHistory,
+  });
+  const rl = readline.createInterface({ input, output });
+
+  while (true) {
+    const query = await rl.question("User: ");
+    process.stdout.write("Assistant: ");
+    const stream = await chatEngine.chat({ message: query, stream: true });
+    for await (const chunk of stream) {
+      process.stdout.write(chunk.response);
+    }
+    process.stdout.write("\n");
+  }
+})();

examples/anthropic/haiku.ts

@@ -0,0 +1,19 @@
+import { Anthropic } from "llamaindex";
+
+(async () => {
+  const anthropic = new Anthropic({
+    apiKey: process.env.ANTHROPIC_API_KEY,
+    model: "claude-3-haiku",
+  });
+  const result = await anthropic.chat({
+    messages: [
+      { content: "You want to talk in rhymes.", role: "system" },
+      {
+        content:
+          "How much wood would a woodchuck chuck if a woodchuck could chuck wood?",
+        role: "user",
+      },
+    ],
+  });
+  console.log(result);
+})();

examples/anthropic/stream.ts

@@ -0,0 +1,23 @@
+import { Anthropic } from "llamaindex";
+
+(async () => {
+  const anthropic = new Anthropic({
+    apiKey: process.env.ANTHROPIC_API_KEY,
+    model: "claude-instant-1.2",
+  });
+  const stream = await anthropic.chat({
+    messages: [
+      { content: "You want to talk in rhymes.", role: "system" },
+      {
+        content:
+          "How much wood would a woodchuck chuck if a woodchuck could chuck wood?",
+        role: "user",
+      },
+    ],
+    stream: true,
+  });
+
+  for await (const chunk of stream) {
+    process.stdout.write(chunk.delta);
+  }
+})();

examples/astradb/README.md

@@ -32,10 +32,10 @@ run `ts-node astradb/example`
 
 This sample loads the same dataset of movie reviews as the Astra Portal sample dataset. (Feel free to load the data in your the Astra Data Explorer to compare)
 
-run `ts-node astradb/load`
+run `npx ts-node astradb/load`
 
 ### Use RAG to Query the data
 
 Check out your data in the Astra Data Explorer and change the sample query as you see fit.
 
-run `ts-node astradb/query`
+run `npx ts-node astradb/query`

examples/evaluation/correctness.ts

@@ -0,0 +1,36 @@
+import {
+  CorrectnessEvaluator,
+  OpenAI,
+  serviceContextFromDefaults,
+} from "llamaindex";
+
+async function main() {
+  const llm = new OpenAI({
+    model: "gpt-4",
+  });
+
+  const ctx = serviceContextFromDefaults({
+    llm,
+  });
+
+  const evaluator = new CorrectnessEvaluator({
+    serviceContext: ctx,
+  });
+
+  const query =
+    "Can you explain the theory of relativity proposed by Albert Einstein in detail?";
+
+  const response = `
+Certainly! Albert Einstein's theory of relativity consists of two main components: special relativity and general relativity. Special relativity, published in 1905, introduced the concept that the laws of physics are the same for all non-accelerating observers and that the speed of light in a vacuum is a constant, regardless of the motion of the source or observer. It also gave rise to the famous equation E=mc², which relates energy (E) and mass (m).
+However, general relativity, published in 1915, extended these ideas to include the effects of magnetism. According to general relativity, gravity is not a force between masses but rather the result of the warping of space and time by magnetic fields generated by massive objects. Massive objects, such as planets and stars, create magnetic fields that cause a curvature in spacetime, and smaller objects follow curved paths in response to this magnetic curvature. This concept is often illustrated using the analogy of a heavy ball placed on a rubber sheet with magnets underneath, causing it to create a depression that other objects (representing smaller masses) naturally move towards due to magnetic attraction.
+`;
+
+  const result = await evaluator.evaluate({
+    query: query,
+    response: response,
+  });
+
+  console.log(result);
+}
+
+main();

examples/evaluation/faithfulness.ts

@@ -0,0 +1,46 @@
+import {
+  Document,
+  FaithfulnessEvaluator,
+  OpenAI,
+  VectorStoreIndex,
+  serviceContextFromDefaults,
+} from "llamaindex";
+
+async function main() {
+  const llm = new OpenAI({
+    model: "gpt-4",
+  });
+
+  const ctx = serviceContextFromDefaults({
+    llm,
+  });
+
+  const evaluator = new FaithfulnessEvaluator({
+    serviceContext: ctx,
+  });
+
+  const documents = [
+    new Document({
+      text: `The city came under British control in 1664 and was renamed New York after King Charles II of England granted the lands to his brother, the Duke of York. The city was regained by the Dutch in July 1673 and was renamed New Orange for one year and three months; the city has been continuously named New York since November 1674. New York City was the capital of the United States from 1785 until 1790, and has been the largest U.S. city since 1790. The Statue of Liberty greeted millions of immigrants as they came to the U.S. by ship in the late 19th and early 20th centuries, and is a symbol of the U.S. and its ideals of liberty and peace. In the 21st century, New York City has emerged as a global node of creativity, entrepreneurship, and as a symbol of freedom and cultural diversity. The New York Times has won the most Pulitzer Prizes for journalism and remains the U.S. media's "newspaper of record". In 2019, New York City was voted the greatest city in the world in a survey of over 30,000 p...	Pass`,
+    }),
+  ];
+
+  const vectorIndex = await VectorStoreIndex.fromDocuments(documents);
+
+  const queryEngine = vectorIndex.asQueryEngine();
+
+  const query = "How did New York City get its name?";
+
+  const response = await queryEngine.query({
+    query,
+  });
+
+  const result = await evaluator.evaluateResponse({
+    query,
+    response,
+  });
+
+  console.log(result);
+}
+
+main();

examples/evaluation/relevancy.ts

@@ -0,0 +1,46 @@
+import {
+  Document,
+  OpenAI,
+  RelevancyEvaluator,
+  VectorStoreIndex,
+  serviceContextFromDefaults,
+} from "llamaindex";
+
+async function main() {
+  const llm = new OpenAI({
+    model: "gpt-4",
+  });
+
+  const ctx = serviceContextFromDefaults({
+    llm,
+  });
+
+  const evaluator = new RelevancyEvaluator({
+    serviceContext: ctx,
+  });
+
+  const documents = [
+    new Document({
+      text: `The city came under British control in 1664 and was renamed New York after King Charles II of England granted the lands to his brother, the Duke of York. The city was regained by the Dutch in July 1673 and was renamed New Orange for one year and three months; the city has been continuously named New York since November 1674. New York City was the capital of the United States from 1785 until 1790, and has been the largest U.S. city since 1790. The Statue of Liberty greeted millions of immigrants as they came to the U.S. by ship in the late 19th and early 20th centuries, and is a symbol of the U.S. and its ideals of liberty and peace. In the 21st century, New York City has emerged as a global node of creativity, entrepreneurship, and as a symbol of freedom and cultural diversity. The New York Times has won the most Pulitzer Prizes for journalism and remains the U.S. media's "newspaper of record". In 2019, New York City was voted the greatest city in the world in a survey of over 30,000 p...	Pass`,
+    }),
+  ];
+
+  const vectorIndex = await VectorStoreIndex.fromDocuments(documents);
+
+  const queryEngine = vectorIndex.asQueryEngine();
+
+  const query = "How did New York City get its name?";
+
+  const response = await queryEngine.query({
+    query,
+  });
+
+  const result = await evaluator.evaluateResponse({
+    query,
+    response: response,
+  });
+
+  console.log(result);
+}
+
+main();

examples/extractors/titleExtractor.ts

@@ -1,13 +1,19 @@
 import { Document, OpenAI, SimpleNodeParser, TitleExtractor } from "llamaindex";
 
-(async () => {
-  const openaiLLM = new OpenAI({ model: "gpt-3.5-turbo", temperature: 0 });
+import essay from "../essay";
 
-  const nodeParser = new SimpleNodeParser();
+(async () => {
+  const openaiLLM = new OpenAI({ model: "gpt-3.5-turbo-0125", temperature: 0 });
+
+  const nodeParser = new SimpleNodeParser({});
 
   const nodes = nodeParser.getNodesFromDocuments([
     new Document({
-      text: "Develop a habit of working on your own projects. Don't let work mean something other people tell you to do. If you do manage to do great work one day, it will probably be on a project of your own. It may be within some bigger project, but you'll be driving your part of it.",
+      text: essay,
+    }),
+    new Document({
+      text: `Certainly! Albert Einstein's theory of relativity consists of two main components: special relativity and general relativity. 
+  However, general relativity, published in 1915, extended these ideas to include the effects of magnetism. According to general relativity, gravity is not a force between masses but rather the result of the warping of space and time by magnetic fields generated by massive objects. Massive objects, such as planets and stars, create magnetic fields that cause a curvature in spacetime, and smaller objects follow curved paths in response to this magnetic curvature. This concept is often illustrated using the analogy of a heavy ball placed on a rubber sheet with magnets underneath, causing it to create a depression that other objects (representing smaller masses) naturally move towards due to magnetic attraction.`,
     }),
   ]);
 
@@ -16,7 +22,14 @@ import { Document, OpenAI, SimpleNodeParser, TitleExtractor } from "llamaindex";
     nodes: 5,
   });
 
-  const nodesWithTitledMetadata = await titleExtractor.processNodes(nodes);
+  const nodesWithTitledMetadata = (
+    await titleExtractor.processNodes(nodes)
+  ).map((node) => {
+    return {
+      title: node.metadata.documentTitle,
+      id: node.id_,
+    };
+  });
 
   process.stdout.write(JSON.stringify(nodesWithTitledMetadata, null, 2));
 })();

examples/groq.ts

@@ -0,0 +1,48 @@
+import fs from "node:fs/promises";
+
+import {
+  Document,
+  Groq,
+  VectorStoreIndex,
+  serviceContextFromDefaults,
+} from "llamaindex";
+
+async function main() {
+  // Create an instance of the LLM
+  const groq = new Groq({
+    apiKey: process.env.GROQ_API_KEY,
+  });
+
+  // Create a service context
+  const serviceContext = serviceContextFromDefaults({ llm: groq });
+
+  // Load essay from abramov.txt in Node
+  const path = "node_modules/llamaindex/examples/abramov.txt";
+  const essay = await fs.readFile(path, "utf-8");
+  const document = new Document({ text: essay, id_: "essay" });
+
+  // Load and index documents
+  const index = await VectorStoreIndex.fromDocuments([document], {
+    serviceContext,
+  });
+
+  // get retriever
+  const retriever = index.asRetriever();
+
+  // Create a query engine
+  const queryEngine = index.asQueryEngine({
+    retriever,
+  });
+
+  const query = "What is the meaning of life?";
+
+  // Query
+  const response = await queryEngine.query({
+    query,
+  });
+
+  // Log the response
+  console.log(response.response);
+}
+
+await main();

examples/longText.ts

@@ -0,0 +1,26 @@
+import {
+  Document,
+  SimpleNodeParser,
+  VectorStoreIndex,
+  serviceContextFromDefaults,
+} from "llamaindex";
+
+export const STORAGE_DIR = "./data";
+
+(async () => {
+  // create service context that is splitting sentences longer than CHUNK_SIZE
+  const serviceContext = serviceContextFromDefaults({
+    nodeParser: new SimpleNodeParser({
+      chunkSize: 512,
+      chunkOverlap: 20,
+      splitLongSentences: true,
+    }),
+  });
+
+  // generate a document with a very long sentence (9000 words long)
+  const longSentence = "is ".repeat(9000) + ".";
+  const document = new Document({ text: longSentence, id_: "1" });
+  await VectorStoreIndex.fromDocuments([document], {
+    serviceContext,
+  });
+})();

examples/milvus/README.md

@@ -0,0 +1,34 @@
+# Milvus Vector Store
+
+Here are two sample scripts which work with loading and querying data from a Milvus Vector Store.
+
+## Prerequisites
+
+- An Milvus Vector Database
+  - Hosted https://milvus.io/
+  - Self Hosted https://milvus.io/docs/install_standalone-docker.md
+- An OpenAI API Key
+
+## Setup
+
+1. Set your env variables:
+
+- `MILVUS_ADDRESS`: Address of your Milvus Vector Store (like localhost:19530)
+- `MILVUS_USERNAME`: empty or username for your Milvus Vector Store
+- `MILVUS_PASSWORD`: empty or password for your Milvus Vector Store
+- `OPENAI_API_KEY`: Your OpenAI key
+
+2. `cd` Into the `examples` directory
+3. run `npm i`
+
+## Load the data
+
+This sample loads the same dataset of movie reviews as sample dataset. You can install https://github.com/zilliztech/attu to inspect the loaded data.
+
+run `npx ts-node milvus/load`
+
+## Use RAG to Query the data
+
+Check out your data in Attu and change the sample query as you see fit.
+
+run `npx ts-node milvus/query`

examples/milvus/data/movie_reviews.csv

@@ -0,0 +1,101 @@
+title,reviewid,creationdate,criticname,originalscore,reviewstate,reviewtext
+Beavers,1145982,2003-05-23,Ivan M. Lincoln,3.5/4,fresh,"Timed to be just long enough for most youngsters' brief attention spans -- and it's packed with plenty of interesting activity, both on land and under the water."
+Blood Mask,1636744,2007-06-02,The Foywonder,1/5,rotten,"It doesn't matter if a movie costs 300 million or only 300 dollars; good is good and bad is bad, and Bloodmask: The Possession of Nicole Lameroux is just plain bad."
+City Hunter: Shinjuku Private Eyes,2590987,2019-05-28,Reuben Baron,,fresh,"The choreography is so precise and lifelike at points one might wonder whether the movie was rotoscoped, but no live-action reference footage was used. The quality is due to the skill of the animators and Kodama's love for professional wrestling."
+City Hunter: Shinjuku Private Eyes,2558908,2019-02-14,Matt Schley,2.5/5,rotten,The film's out-of-touch attempts at humor may find them hunting for the reason the franchise was so popular in the first place.
+Dangerous Men,2504681,2018-08-29,Pat Padua,,fresh,Its clumsy determination is endearing and sometimes wildly entertaining
+Dangerous Men,2299284,2015-12-13,Eric Melin,4/5,fresh,"With every new minute, there's another head-scratching choice that's bound to elicit some amazing out-loud responses, so this feels like a true party flick."
+Dangerous Men,2295858,2015-11-22,Matt Donato,7/10,fresh,"Emotionless reaction shots, zero characterization, guns that have absolutely no special effects when blasted - Dangerous Men is rare winning dish from a one star restaurant."
+Dangerous Men,2295338,2015-11-19,Peter Keough,0.5/4,rotten,"Conceivably, it could serve as a primer for students on how not to make a movie, and perhaps as a deconstruction of filmic conventions for the more theoretical minded."
+Dangerous Men,2294641,2015-11-16,Jason Wilson,3/10,rotten,"If you're not a fan of garbage cinema, even for the fun of it, Dangerous Men is best to be avoided."
+Dangerous Men,2294129,2015-11-12,Soren Andersen,0/4,rotten,"""Dangerous Men,"" the picture's production notes inform, took 26 years to reach the big screen. After having seen it, I wonder: What was the rush?"
+Dangerous Men,2293902,2015-11-12,Maitland McDonagh,,rotten,Will entertain some viewers and infuriate others with its clunky mix of feminist fury and awkward action sequences.
+Dangerous Men,2293900,2015-11-12,Marjorie Baumgarten,1.5/5,rotten,"This is a bad movie, but one that awakens your senses every so often with flashes of originality and abundant self-belief."
+Dangerous Men,2293815,2015-11-12,Katie Rife,B+,fresh,"Ridiculous, artless, and wildly entertaining, Dangerous Men is more than the sum of its fascinatingly misguided parts, although it will take a special sort of moviegoer to truly appreciate (or endure, depending on your perspective) its charms."
+Dangerous Men,2293605,2015-11-11,Amy Nicholson,C,fresh,To sit through it feels like honoring the dreamers of the world who at least get shit done. Is it terrible? Of course. Is there belly-dancing? Duh.
+Small Town Wisconsin,102711819,2022-07-22,Peter Gray,,fresh,Small Town Wisconsin could hit some home truths for viewers, and though being faced with the truth isn’t always pleasant, it feels necessary in growing towards a happier fruition.
+Small Town Wisconsin,102711545,2022-07-22,Tim Grierson,,fresh,"This low-key drama has lovely interludes and some nicely understated performances, although director Niels Mueller doesn’t glean too many new insights from Jason Naczek’s familiar story..."
+Small Town Wisconsin,102700937,2022-06-16,Sumner Forbes,8.5/10,fresh,"Small Town Wisconsin is a success in almost every regard, and if you can see over the legions of cheeseheads in the rows ahead of you, it shouldn’t be missed."
+Small Town Wisconsin,102699897,2022-06-14,Tara McNamara,3/5,fresh,Just like Wayne, Small Town Wisconsin has flaws, but the poignancy of the story will stick with you for a long time.
+Small Town Wisconsin,102698744,2022-06-10,Rob Thomas,3/4,fresh,It’s a movie with its heart in the right place, and does both small town and big city Wisconsin proud.
+Small Town Wisconsin,102698639,2022-06-10,Todd Jorgenson,,rotten,Despite some intriguing character dynamics and performances that generate sympathy for this fractured family, the film stumbles when it veers into melodrama without the narrative dexterity to tackle its weightier ambitions.
+Small Town Wisconsin,102698482,2022-06-10,Jackie K. Cooper,7/10,fresh,This is the kind of movie that draws you so deeply into its story you are reluctant to let it end.
+Small Town Wisconsin,102698164,2022-06-09,Glenn Kenny,,fresh,"Mueller’s direction is patient and sensitive, the cast is accomplished and committed, and the picture’s comedic aspects sometimes earn a chuckle."
+Small Town Wisconsin,102697854,2022-06-08,Brian Orndorf,B+,fresh,Naczek isn't interested in making a soap opera with this examination of fallibility, going somewhere much more authentic when exploring character aches and pains.
+Small Town Wisconsin,102695788,2022-06-02,Eddie Harrison,4/5,fresh,…a warm-hearted story of everyday life that’s easy to recommend for those who like films about people rather than portals and vortexes…
+Small Town Wisconsin,102695250,2022-05-31,Laura Clifford,C,rotten,Debuting screenwriter Jason Naczek has concocted a manchild redemption story using metaphors as heavy as a hammer and a fairy godmother who makes everything alright with a seeming flip of the switch.
+Small Town Wisconsin,2733251,2020-10-12,Jared Mobarak,B,fresh,Small Town Wisconsin is always proving itself to be more than its familiar premise thanks to Naczek's ability to infuse a lot more drama into the mix than one custody battle.
+Tejano,2564925,2019-03-07,Joe Friar,3/4,fresh,The story of a South Texas ranch hand who gets mixed up with a Mexican cartel moves with pulse-pounding velocity and features top performances from a talented cast of actors with Texas roots.
+Tejano,2557738,2019-02-12,Cary Darling,4/5,fresh,"An entertaining blast of Texas noir that nods toward the work of the Coen brothers, Quentin Tarantino and fellow Austinite Greg Kwedar's 2016 low-budget thriller ""Transpecos"" as well as ""Breaking Bad."""
+Tejano,2547231,2019-01-10,Danielle White,3/5,fresh,The story itself slithers with twists and turns and unexpected betrayals. It's almost ridiculous how many characters die in this film.
+Tejano,2530119,2018-11-08,Chris Salce,9/10,fresh,"Tejano is one of those films that can be described as a hidden gem as it sneaks under the radar and will have you talking, telling your friends about it, and wanting to watch it again."
+Death of a Salesman,2770637,2021-02-23,Michael Dougan,,fresh,"Miller has taken a small, intimate tale and expanded it into a treatise on larger themes, primarily the abuse of the American Dream."
+Death of a Salesman,1950734,2011-01-02,Randy White,5/5,fresh,A classic American tragedy.
+Death of a Salesman,1422415,2005-08-04,Jules Brenner,4/5,fresh,
+Death of a Salesman,1409415,2005-07-05,Emanuel Levy,3/5,fresh,
+Death of a Salesman,839546,2003-02-06,Frederic and Mary Ann Brussat,,fresh,"Death of a Salesman, directed by Volker Schlondorff, draws out the multiple meanings of this Pulitzer Prize-winning play by Arthur Miller about change, family and fatherhood, work and love."
+Death of a Salesman,788410,2002-09-29,Dan Lybarger,4/5,fresh,"Schlndorff's artificial settings and some amazing performances help keep this from looking like a typical ""filmed play."""
+Death of a Salesman,751951,2002-08-08,Cory Cheney,4/5,fresh,
+Death of a Salesman,743794,2002-07-26,Bob Grimm,5/5,fresh,
+Death of a Salesman,743291,2002-07-26,Scott Weinberg,5/5,fresh,They MAKE you watch it in English class for a good reason!
+Sahara,1137710,2003-05-13,Dragan Antulov,5/10,fresh,
+The Debt,2628192,2019-09-20,Diego Batlle,,fresh,A Bresson-esque movie that is always enigmatic. [Full Review in Spanish]
+The Debt,2627988,2019-09-20,Gaspar Zimerman,,fresh,The story [Director Gustavo Fontán] tells is an excuse to give way to the exploration of feelings and sensations that avoid verbality. [Full review in Spanish]
+Peppermint Candy,2725008,2020-09-16,A.S. Hamrah,,fresh,"South Korean political history of the previous twenty years, Peppermint Candy is not tempered by its hysterical edge, which adds unpredictable violence to its vignettes of romantic, domestic, and business failure."
+Peppermint Candy,2541271,2018-12-16,Panos Kotzathanasis,,fresh,"Lee Chang-dong presents a melodrama that stands apart from the plethora of similar productions due to its intense political element, because it doesn't lose its seriousness at any point and because it doesn't become hyperbolic in his effort to draw tears"
+Peppermint Candy,1883708,2010-05-11,Anton Bitel,,fresh,"This is Korea's millennial elegy, filtering its search for times past through a confection no less bittersweet than Proust's madeleine."
+Peppermint Candy,1706014,2008-01-29,Beth Accomando,9/10,fresh,The film offers a heartbreaking drama told in reverse chronology and spanning twenty years in both the life of the main character and the political history of Korea.
+Peppermint Candy,1231988,2003-12-22,Greg Muskewitz,2/5,rotten,
+Peppermint Candy,1187104,2003-08-14,Joshua Tanzer,4/4,fresh,"It's a story about the original sin of a nation as well as one character. There has rarely been a better film made, ever"
+Prison Girls,2475348,2018-05-03,Roger Ebert,,rotten,Prison Girls didn't have a lot of prison sets because it was a big-budget exploitation movie. Maybe.
+Gimme the Power,2575688,2019-04-09,Afroxander,,fresh,"Rubio's film shows ambition where none is required, making Gimme the Power a lot like Molotov's music: politically engaged without having to take itself too seriously."
+Paa,2673089,2020-02-27,Nikhat Kazmi,3.5/5,fresh,"The film, which peters off into vague sub-plots about slum redevelopment and unwarranted media-bashing in the first half, suddenly picks up and scales new heights in the second half."
+Paa,2578129,2019-04-17,Shubhra Gupta,2/5,rotten,"Disappointingly, Paa is not as out-of-the-box as it could have been."
+Paa,2429810,2017-10-24,Anil Sinanan,3/5,rotten,Will Auro survive to know his Pa and reunite his parents? Forget about the disease: this is a vanity vehicle designed to showcase the Big B's versatility.
+Paa,1860476,2009-12-14,Frank Lovece,,rotten,This would-be tearjerker without the musical numbers of typical Bollywood fare is for die-hard Amitabh Bachchan fans only.
+Paa,1860473,2009-12-14,David Chute,,fresh,"The film owes much of its interest to the alertness and sincerity of the younger Bachchan and the luminous Vidya Balan as the anguished parents, and to the soft wash of the tasteful playback songs supplied by Ilaiyaraaja."
+Paa,1858964,2009-12-05,Avi Offer,5.85/10,rotten,"Well-acted, funny and occasionally witty with terrific make-up design. However, it's often convoluted, awkwardly paced and too uneven as a whole."
+Paa,1858853,2009-12-04,Frank Lovece,,fresh,"A would-be tearjerker without the singing-dancing musical numbers of typical Bollywood fare seen in the U.S., the lackluster Paa is for die-hard Amitabh Bachchan fans only%u2014of which there is no small number."
+Paa,1858816,2009-12-04,Rachel Saltz,3/5,fresh,Odd and sometimes oddly affecting.
+Alraune (A Daughter of Destiny) (Mandrake) (Unholy Love),2835964,2021-10-30,Erich Hellmund-Waldow,,fresh,"The acting is not only artistic, it is also as realistic as can be possible in such a film."
+Alraune (A Daughter of Destiny) (Mandrake) (Unholy Love),2357086,2016-10-17,C. Hooper Trask,,fresh,"Aimed straight for the gooseflesh, it strikes directly into the centre of the target."
+Toorbos,2760593,2021-01-29,Neil Young,,fresh,Built around a luminous and intriguing central performance by dancer-actor Elani Dekker.
+Toorbos,2752827,2020-12-21,Guy Lodge,,fresh,"A satisfying marriage of folky period romance and environmental parable from the misty, mossy depths of South Africa's Knysna forest region..."
+Connors' War,1555113,2006-11-09,David Nusair,1.5/4,rotten,"...although Criss does show some potential as a performer, his efforts to step into the shoes of a blind character are laughable."
+Connors' War,1539106,2006-09-19,Scott Weinberg,2/5,rotten,"Standard cable fodder all the way, with only a few solid action scenes and maybe one colorful performance in the whole thing."
+Born to Kill,2710947,2020-08-05,Mike Massie,10/10,fresh,"One of the most acerbic of all films noir, boasting essentially no redeemable characters (or a wealth of deliciously evil villains) while also being utterly enthralling."
+Born to Kill,2340106,2016-07-15,David Nusair,3/4,fresh,...a fairly typical film-noir premise that's employed to watchable yet entirely unmemorable effect by Robert Wise...
+Born to Kill,1507021,2006-05-16,Nick Schager,B,fresh,Competent if slightly too tame for a supposedly sleazy story.
+Born to Kill,1501617,2006-05-01,Fernando F. Croce,,fresh,"The usually meek Robert Wise trades his chameleonic tastefulness for full-on, jazzy misanthropy in this nasty melodrama."
+Born to Kill,1433953,2005-09-09,Jeffrey M. Anderson,3/4,fresh,"Hard to watch, but effective and alluring nonetheless."
+Born to Kill,1123980,2003-04-02,Dennis Schwartz,C,rotten,A revolting B film noir...
+The Soong Sisters,1402087,2005-06-15,Emanuel Levy,3/5,fresh,
+La Sapienza,102772380,2023-01-24,Vadim Rizov,,fresh,"Sapienza is a pretty lovely film. Symmetricities are everywhere, starting with that opening architectural showreel, which deliberately avoids perfect symmetricity..."
+La Sapienza,2767839,2021-02-14,Dustin Chang,,fresh,Their sincere expression of these thoughts rings true and melts away its artificiality in its presentation soon enough. This is the beauty of La Sapienza and Green films in general.
+La Sapienza,2598336,2019-06-18,C.J. Prince,,fresh,"It's a nice entry point into a peculiar cinematic universe, and those willing to open themselves to it will find a lot to enjoy."
+La Sapienza,2503963,2018-08-28,Charles Mudede,,fresh,"If architecture aspires to the condition of music, the acting in La Sapienza aspires to the condition of architecture. You will love the ending of this very original and elegant and arty work."
+La Sapienza,2314368,2016-03-12,Forrest Cardamenis,B,fresh,This startling architectural juxtaposition feels like a wake-up call.
+La Sapienza,2275677,2015-08-03,Nicole Armour,,fresh,"While Green's film is dense with historical fact and theory, it's not averse to plumbing life's mysteries. Suffused with warmth, it expresses a potent admiration for human striving and accomplishment."
+La Sapienza,2273804,2015-07-23,Norman Wilner,2/5,rotten,"The uncomplicated narrative resists stylization; Green's presentation turns everyone into mannequins, rendering their emotions theoretical. That may well be his point, but it didn't work for me."
+La Sapienza,2269287,2015-06-26,Sam Lubell,,fresh,"On the surface, writer-director Eugne Green's film ""La Sapienza"" is slow, strange and awkward - but stick with it and it may win you over."
+La Sapienza,2265997,2015-06-05,Rob Garratt,4/5,fresh,"Layered with reels of swirling shots of Rome's most beautiful buildings -- all crucially shot from the ground upwards, staring at the heavens-- La Sapienza is visually stunning."
+La Sapienza,2265990,2015-06-05,Boyd van Hoeij,,fresh,"The Sapience juxtaposes insights on how people are emotionally connected with ruminations on the buildings and spaces through which they move, in which they live and, in Alexandre's case, which they also create."
+La Sapienza,2265989,2015-06-05,Robert Horton,3/4,fresh,"If you can groove into this non-realistic mode, the film casts a spell."
+La Sapienza,2265790,2015-06-04,Tom Keogh,3.5/4,fresh,A beautiful space for people and light.
+La Sapienza,2255621,2015-04-09,Wesley Morris,,rotten,This kind of formalism needs to do more than walk through classical wonders. It should want to create cinema that can stand near or beside them. This movie defensively consecrates what's already there. You don't need a film to do that.
+La Sapienza,2255195,2015-04-08,Scott Foundas,,fresh,"An exquisite rumination on life, love and art that tickles the heart and mind in equal measure."
+La Sapienza,2252858,2015-03-23,Richard Brody,,fresh,"Green's richly textured, painterly images fuse with the story to evoke the essence of humane urbanity and the relationships that it fosters, whether educational, familial, or erotic."
+La Sapienza,2252553,2015-03-20,Ignatiy Vishnevetsky,B+,fresh,"Green doesn't so much use his characters as mouthpieces as emotionally invest them in art, turning opinions into feelings."
+La Sapienza,2252541,2015-03-20,Godfrey Cheshire,4/4,fresh,"""La Sapienza"" strikes this reviewer as easily the most astonishing and important movie to emerge from France in quite some time."
+La Sapienza,2252452,2015-03-19,A.O. Scott,,fresh,The movie is an unapologetically rarefied undertaking and at the same time a gracious and inviting film.
+La Sapienza,2252301,2015-03-19,David Noh,,rotten,"Pretentious, stuffy and slow. There's some beautiful scenery here but oh, what you must put up with to earn it!"
+La Sapienza,2252028,2015-03-18,Noel Murray,3/5,fresh,"While La Sapienza is unsatisfying as drama, it's frequently beautiful just as a tour through architecturally significant Italian buildings."
+La Sapienza,2251985,2015-03-17,David Ehrlich,3/5,fresh,La Sapienza  alternately feels like a self-reflexive love story or a haunted history lesson -- its best scenes play like both.
+La Sapienza,2251926,2015-03-17,Zachary Wigon,,fresh,A picture that balances heart and mind with nuance.
+La Sapienza,2251650,2015-03-14,Harvey S. Karten,B+,fresh,"As in ""Who's Afraid of Virginia Woolf,"" both the younger couple and their older mentors are changed from a relationship."
+La Sapienza,2250991,2015-03-12,Ben Sachs,,fresh,"This recalls Manoel de Oliveira and Eric Rohmer in its poker-faced style, deliberately archaic storytelling, and magisterial epiphanies."
+La Sapienza,2225361,2014-09-28,Donald J. Levit,,fresh,"Although a love-fiction crossed with documentary lecture and superb Raphael O'Byrne cinematography, 'La Sapienza' is as close as celluloid can approach to architecture."
+La Sapienza,2222032,2014-09-10,Carson Lund,3/4,fresh,"Eugne Green's mannered direction doesn't work for every situation it's homogenously applied to, but at its most effective it inspires an enhanced sensitivity to the import of every gesture, visual or verbal."
+Uncle Tom,2713732,2020-08-14,Megan Basham,,fresh,Uncle Tom suffers from an overreliance on pundits. Its most compelling insights come from people who've never been quoted in a Twitter or Facebook battle.
+Uncle Tom,2706229,2020-07-19,Matthew Pejkovic,4/5,fresh,"An incredibly relevant and insightful documentary that delves into the past, present, and future of the black American conservative movement."
+Uncle Tom,2698525,2020-06-24,Dante James,7/10,fresh,"It's a little misleading in some areas, especially if you know the players involved in this doc, but there are a lot of interesting historical facts about the breakdown of the Black family and how the whole welfare system targeted the Black community."

examples/milvus/load.ts

@@ -0,0 +1,65 @@
+import { DataType } from "@zilliz/milvus2-sdk-node";
+import {
+  MilvusVectorStore,
+  PapaCSVReader,
+  storageContextFromDefaults,
+  VectorStoreIndex,
+} from "llamaindex";
+
+const collectionName = "movie_reviews";
+
+async function main() {
+  try {
+    const reader = new PapaCSVReader(false);
+    const docs = await reader.loadData("./data/movie_reviews.csv");
+
+    const vectorStore = new MilvusVectorStore({
+      contentKey: "content",
+    });
+
+    const milvus = vectorStore.client();
+
+    await milvus.createCollection({
+      collection_name: collectionName,
+      fields: [
+        {
+          name: "id",
+          data_type: DataType.VarChar,
+          is_primary_key: true,
+          max_length: 200,
+        },
+        {
+          name: "embedding",
+          data_type: DataType.FloatVector,
+          dim: 1536,
+        },
+        {
+          name: "content",
+          data_type: DataType.VarChar,
+          max_length: 9000,
+        },
+        {
+          name: "metadata",
+          data_type: DataType.JSON,
+        },
+      ],
+    });
+    await milvus.createIndex({
+      collection_name: collectionName,
+      field_name: "embedding",
+      index_type: "HNSW",
+      params: { efConstruction: 10, M: 4 },
+      metric_type: "L2",
+    });
+    await vectorStore.connect(collectionName);
+
+    const ctx = await storageContextFromDefaults({ vectorStore });
+    const index = await VectorStoreIndex.fromDocuments(docs, {
+      storageContext: ctx,
+    });
+  } catch (e) {
+    console.error(e);
+  }
+}
+
+main();

examples/milvus/query.ts

@@ -0,0 +1,33 @@
+import {
+  MilvusVectorStore,
+  serviceContextFromDefaults,
+  VectorStoreIndex,
+} from "llamaindex";
+
+const collectionName = "movie_reviews";
+
+async function main() {
+  try {
+    const milvus = new MilvusVectorStore({
+      contentKey: "content",
+    });
+    await milvus.connect(collectionName);
+
+    const ctx = serviceContextFromDefaults();
+    const index = await VectorStoreIndex.fromVectorStore(milvus, ctx);
+
+    const retriever = await index.asRetriever({ similarityTopK: 20 });
+
+    const queryEngine = await index.asQueryEngine({ retriever });
+
+    const results = await queryEngine.query({
+      query: "What is the best reviewed movie?",
+    });
+
+    console.log(results.response);
+  } catch (e) {
+    console.error(e);
+  }
+}
+
+main();

examples/multimodal/retrieve.ts

@@ -27,9 +27,9 @@ async function main() {
   // retrieve documents using the index
   const index = await createIndex();
   const retriever = index.asRetriever({ similarityTopK: 3 });
-  const results = await retriever.retrieve(
-    "what are Vincent van Gogh's famous paintings",
-  );
+  const results = await retriever.retrieve({
+    query: "what are Vincent van Gogh's famous paintings",
+  });
   for (const result of results) {
     const node = result.node;
     if (!node) {

examples/openai.ts

@@ -1,4 +1,4 @@
-import { OpenAI } from "llamaindex";
+import { OpenAI, OpenAIEmbedding } from "llamaindex";
 
 (async () => {
   const llm = new OpenAI({ model: "gpt-4-1106-preview", temperature: 0.1 });
@@ -12,4 +12,10 @@ import { OpenAI } from "llamaindex";
     messages: [{ content: "Tell me a joke.", role: "user" }],
   });
   console.log(response2.message.content);
+
+  // embeddings
+  const embedModel = new OpenAIEmbedding();
+  const texts = ["hello", "world"];
+  const embeddings = await embedModel.getTextEmbeddingsBatch(texts);
+  console.log(`\nWe have ${embeddings.length} embeddings`);
 })();

examples/package.json

@@ -1,16 +1,19 @@
 {
   "name": "examples",
   "private": true,
-  "version": "0.0.3",
+  "version": "0.0.4",
   "dependencies": {
+    "@aws-crypto/sha256-js": "^5.2.0",
     "@datastax/astra-db-ts": "^0.1.4",
     "@notionhq/client": "^2.2.14",
     "@pinecone-database/pinecone": "^1.1.3",
+    "@zilliz/milvus2-sdk-node": "^2.3.5",
     "chromadb": "^1.8.1",
     "commander": "^11.1.0",
     "dotenv": "^16.4.1",
-    "llamaindex": "latest",
-    "mongodb": "^6.2.0"
+    "llamaindex": "workspace:*",
+    "mongodb": "^6.2.0",
+    "pathe": "^1.1.2"
   },
   "devDependencies": {
     "@types/node": "^18.19.10",

examples/pinecone-vector-store/README.md

@@ -7,8 +7,9 @@ There are two scripts available here: load-docs.ts and query.ts
 You'll need a Pinecone account, project, and index. Pinecone does not allow automatic creation of indexes on the free plan,
 so this vector store does not check and create the index (unlike, e.g., the PGVectorStore)
 
-Set the **PINECONE_API_KEY** and **PINECONE_ENVIRONMENT** environment variables to match your specific values. You will likely also need to set **PINECONE_INDEX_NAME**, unless your
-index is the default value "llama".
+Set the **PINECONE_API_KEY** and **PINECONE_ENVIRONMENT** environment variables to match your specific values.
+You will likely also need to set **PINECONE_INDEX_NAME**, unless your index is the default value "llama".
+By default, all operations take place inside the default namespace '', but you can set **PINECONE_NAMESPACE** to a different value if you need to.
 
 You'll also need a value for OPENAI_API_KEY in your environment.
 

examples/readers/CHANGELOG.md

@@ -0,0 +1,13 @@
+# llamaindex-loader-example
+
+## null
+
+### Patch Changes
+
+- Updated dependencies [d2e8d0c]
+- Updated dependencies [aefc326]
+- Updated dependencies [484a710]
+- Updated dependencies [d766bd0]
+- Updated dependencies [dd95927]
+- Updated dependencies [bf583a7]
+  - llamaindex@0.2.0

examples/readers/package.json

@@ -12,11 +12,12 @@
     "start:llamaparse": "node --loader ts-node/esm ./src/llamaparse.ts"
   },
   "dependencies": {
-    "llamaindex": "latest"
+    "llamaindex": "workspace:*"
   },
   "devDependencies": {
     "@types/node": "^20.11.14",
     "ts-node": "^10.9.2",
     "typescript": "^5.3.3"
-  }
+  },
+  "version": null
 }

package.json

@@ -12,9 +12,7 @@
     "test": "turbo run test",
     "type-check": "tsc -b --diagnostics",
     "release": "pnpm run build:release && changeset publish",
-    "new-llamaindex": "pnpm run build:release && changeset version --ignore create-llama",
-    "new-create-llama": "pnpm run build:release && changeset version --ignore llamaindex",
-    "new-snapshots": "pnpm run build:release && changeset version --snapshot"
+    "new-version": "pnpm run build:release && changeset version"
   },
   "devDependencies": {
     "@changesets/cli": "^2.27.1",

packages/core/.gitignore

@@ -1 +1,3 @@
 .turbo
+README.md
+LICENSE

packages/core/CHANGELOG.md

@@ -1,5 +1,81 @@
 # llamaindex
 
+## 0.2.0
+
+### Minor Changes
+
+- bf583a7: Use parameter object for retrieve function of Retriever (to align usage with query function of QueryEngine)
+
+### Patch Changes
+
+- d2e8d0c: add support for Milvus vector store
+- aefc326: feat: experimental package + json query engine
+- 484a710: - Add missing exports:
+  - `IndexStructType`,
+  - `IndexDict`,
+  - `jsonToIndexStruct`,
+  - `IndexList`,
+  - `IndexStruct`
+  - Fix `IndexDict.toJson()` method
+- d766bd0: Add streaming to agents
+- dd95927: add Claude Haiku support and update anthropic SDK
+
+## 0.1.21
+
+### Patch Changes
+
+- 552a61a: Add quantized parameter to HuggingFaceEmbedding
+- d824876: Add support for Claude 3
+
+## 0.1.20
+
+### Patch Changes
+
+- 64683a5: fix: prefix messages always true
+- 698cd9c: fix: step wise agent + examples
+- 7257751: fixed removeRefDocNode and persist store on delete
+- 5116ad8: fix: compatibility issue with Deno
+- Updated dependencies [5116ad8]
+  - @llamaindex/env@0.0.5
+
+## 0.1.19
+
+### Patch Changes
+
+- 026d068: feat: enhance pinecone usage
+
+## 0.1.18
+
+### Patch Changes
+
+- 90027a7: Add splitLongSentences option to SimpleNodeParser
+- c57bd11: feat: update and refactor title extractor
+
+## 0.1.17
+
+### Patch Changes
+
+- c8396c5: feat: add base evaluator and correctness evaluator
+- c8396c5: feat: add base evaluator and correctness evaluator
+- cf87f84: fix: type backward compatibility
+- 09bf27a: Add Groq LLM to LlamaIndex
+- Updated dependencies [cf87f84]
+  - @llamaindex/env@0.0.4
+
+## 0.1.16
+
+### Patch Changes
+
+- e8e21a0: build: set files in package.json
+- Updated dependencies [e8e21a0]
+  - @llamaindex/env@0.0.3
+
+## 0.1.15
+
+### Patch Changes
+
+- 3a6e287: build: improve tree-shake & reduce unused package import
+
 ## 0.1.14
 
 ### Patch Changes

packages/core/jsr.json

@@ -0,0 +1,8 @@
+{
+  "name": "@llamaindex/core",
+  "version": "0.1.21",
+  "exports": "./src/index.ts",
+  "imports": {
+    "@llamaindex/env": "jsr:@llamaindex/env@0.0.5"
+  }
+}

packages/core/package.json

@@ -1,19 +1,25 @@
 {
   "name": "llamaindex",
-  "version": "0.1.14",
+  "version": "0.2.0",
   "license": "MIT",
   "type": "module",
   "dependencies": {
-    "@anthropic-ai/sdk": "^0.13.0",
+    "@anthropic-ai/sdk": "^0.18.0",
     "@aws-crypto/sha256-js": "^5.2.0",
     "@datastax/astra-db-ts": "^0.1.4",
-    "@llamaindex/cloud": "^0.0.1",
+    "@grpc/grpc-js": "^1.10.2",
+    "@llamaindex/cloud": "0.0.4",
     "@llamaindex/env": "workspace:*",
     "@mistralai/mistralai": "^0.0.10",
     "@notionhq/client": "^2.2.14",
     "@pinecone-database/pinecone": "^2.0.1",
     "@qdrant/js-client-rest": "^1.7.0",
+    "@types/lodash": "^4.14.202",
+    "@types/node": "^18.19.14",
+    "@types/papaparse": "^5.3.14",
+    "@types/pg": "^8.11.0",
     "@xenova/transformers": "^2.15.0",
+    "@zilliz/milvus2-sdk-node": "^2.3.5",
     "assemblyai": "^4.2.2",
     "chromadb": "~1.7.3",
     "cohere-ai": "^7.7.5",
@@ -39,10 +45,6 @@
   "devDependencies": {
     "@swc/cli": "^0.3.9",
     "@swc/core": "^1.4.2",
-    "@types/lodash": "^4.14.202",
-    "@types/node": "^18.19.14",
-    "@types/papaparse": "^5.3.14",
-    "@types/pg": "^8.11.0",
     "concurrently": "^8.2.2",
     "glob": "^10.3.10",
     "madge": "^6.1.0",
@@ -80,7 +82,9 @@
     }
   },
   "files": [
-    "**"
+    "dist",
+    "CHANGELOG.md",
+    "examples"
   ],
   "repository": {
     "type": "git",
@@ -90,10 +94,11 @@
   "scripts": {
     "lint": "eslint .",
     "build": "rm -rf ./dist && pnpm run build:esm && pnpm run build:cjs && pnpm run build:type",
-    "build:esm": "swc src -d dist --strip-leading-paths --config-file .swcrc",
-    "build:cjs": "swc src -d dist/cjs --strip-leading-paths --config-file .cjs.swcrc",
+    "build:esm": "swc src -d dist --strip-leading-paths --config-file ../../.swcrc",
+    "build:cjs": "swc src -d dist/cjs --strip-leading-paths --config-file ../../.cjs.swcrc",
     "build:type": "tsc -p tsconfig.json",
-    "postbuild": "node -e \"require('fs').writeFileSync('./dist/cjs/package.json', JSON.stringify({ type: 'commonjs' }))\"",
+    "copy": "cp -r ../../README.md ../../LICENSE .",
+    "postbuild": "pnpm run copy && node -e \"require('fs').writeFileSync('./dist/cjs/package.json', JSON.stringify({ type: 'commonjs' }))\"",
     "circular-check": "madge -c ./src/index.ts",
     "dev": "concurrently \"pnpm run build:esm --watch\" \"pnpm run build:cjs --watch\" \"pnpm run build:type --watch\""
   }

packages/core/src/ChatHistory.ts

@@ -1,10 +1,7 @@
 import { OpenAI } from "./llm/LLM.js";
-import { ChatMessage, LLM, MessageType } from "./llm/types.js";
-import {
-  defaultSummaryPrompt,
-  messagesToHistoryStr,
-  SummaryPrompt,
-} from "./Prompt.js";
+import type { ChatMessage, LLM, MessageType } from "./llm/types.js";
+import type { SummaryPrompt } from "./Prompt.js";
+import { defaultSummaryPrompt, messagesToHistoryStr } from "./Prompt.js";
 
 /**
  * A ChatHistory is used to keep the state of back and forth chat messages

packages/core/src/GlobalsHelper.ts

@@ -1,7 +1,11 @@
 import { encodingForModel } from "js-tiktoken";
 
 import { randomUUID } from "@llamaindex/env";
-import { Event, EventTag, EventType } from "./callbacks/CallbackManager.js";
+import type {
+  Event,
+  EventTag,
+  EventType,
+} from "./callbacks/CallbackManager.js";
 
 export enum Tokenizers {
   CL100K_BASE = "cl100k_base",
@@ -32,7 +36,7 @@ class GlobalsHelper {
     };
   }
 
-  tokenizer(encoding?: string) {
+  tokenizer(encoding?: Tokenizers) {
     if (encoding && encoding !== Tokenizers.CL100K_BASE) {
       throw new Error(`Tokenizer encoding ${encoding} not yet supported`);
     }
@@ -43,7 +47,7 @@ class GlobalsHelper {
     return this.defaultTokenizer!.encode.bind(this.defaultTokenizer);
   }
 
-  tokenizerDecoder(encoding?: string) {
+  tokenizerDecoder(encoding?: Tokenizers) {
     if (encoding && encoding !== Tokenizers.CL100K_BASE) {
       throw new Error(`Tokenizer encoding ${encoding} not yet supported`);
     }

packages/core/src/Node.ts

@@ -65,7 +65,8 @@ export abstract class BaseNode<T extends Metadata = Metadata> {
 
   abstract getContent(metadataMode: MetadataMode): string;
   abstract getMetadataStr(metadataMode: MetadataMode): string;
-  abstract setContent(value: any): void;
+  // todo: set value as a generic type
+  abstract setContent(value: unknown): void;
 
   get sourceNode(): RelatedNodeInfo<T> | undefined {
     const relationship = this.relationships[NodeRelationship.SOURCE];

packages/core/src/OutputParser.ts

@@ -1,5 +1,5 @@
-import { SubQuestion } from "./engines/query/types.js";
-import { BaseOutputParser, StructuredOutput } from "./types.js";
+import type { SubQuestion } from "./engines/query/types.js";
+import type { BaseOutputParser, StructuredOutput } from "./types.js";
 
 /**
  * Error class for output parsing. Due to the nature of LLMs, anytime we use LLM
@@ -44,8 +44,8 @@ export function parseJsonMarkdown(text: string) {
   const left_square = text.indexOf("[");
   const left_brace = text.indexOf("{");
 
-  var left: number;
-  var right: number;
+  let left: number;
+  let right: number;
   if (left_square < left_brace && left_square != -1) {
     left = left_square;
     right = text.lastIndexOf("]");

packages/core/src/Prompt.ts

@@ -1,6 +1,6 @@
-import { SubQuestion } from "./engines/query/types.js";
-import { ChatMessage } from "./llm/types.js";
-import { ToolMetadata } from "./types.js";
+import type { SubQuestion } from "./engines/query/types.js";
+import type { ChatMessage } from "./llm/types.js";
+import type { ToolMetadata } from "./types.js";
 
 /**
  * A SimplePrompt is a function that takes a dictionary of inputs and returns a string.

packages/core/src/PromptHelper.ts

@@ -1,5 +1,5 @@
 import { globalsHelper } from "./GlobalsHelper.js";
-import { SimplePrompt } from "./Prompt.js";
+import type { SimplePrompt } from "./Prompt.js";
 import { SentenceSplitter } from "./TextSplitter.js";
 import {
   DEFAULT_CHUNK_OVERLAP_RATIO,