test: crypto compatity with node18

2026-07-02 20:13:52 -04:00 · 2025-03-19 07:42:58 +07:00
242 changed files with 516 additions and 10923 deletions
@@ -0,0 +1,7 @@
+---
+"@llamaindex/readers": patch
+"@llamaindex/core": patch
+"@llamaindex/doc": patch
+---
+
+Expose more content to fix the issue with unavailable documentation links, and adjust the documentation based on the latest code.
@@ -0,0 +1,5 @@
+---
+"@llamaindex/google": patch
+---
+
+Added saftey setting parameter for gemini
@@ -0,0 +1,5 @@
+---
+"@llamaindex/pinecone": minor
+---
+
+Fix deleting of document by id in PineconeVectorStore
@@ -0,0 +1,13 @@
+---
+"@llamaindex/huggingface": minor
+"@llamaindex/anthropic": minor
+"@llamaindex/mistral": minor
+"@llamaindex/google": minor
+"@llamaindex/ollama": minor
+"@llamaindex/openai": minor
+"@llamaindex/core": minor
+"@llamaindex/examples": minor
+---
+
+Added support for structured output in the chat api of openai and ollama
+Added structured output parameter in the provider
@@ -0,0 +1,5 @@
+---
+"@llamaindex/cloud": patch
+---
+
+chore: bump sdk openapi.json
@@ -0,0 +1,5 @@
+---
+"@llamaindex/azure": patch
+---
+
+Add `fromConnectionString` method to azure storage libs to track the usage vCore.
@@ -0,0 +1,5 @@
+---
+"@llamaindex/tools": patch
+---
+
+feat: @llamaindex/tools
@@ -0,0 +1,8 @@
+---
+"@llamaindex/mistral": minor
+"@llamaindex/examples": minor
+---
+
+Added support for function calling in mistral provider
+Update model list for mistral provider
+Added example for the tool call in mistral
@@ -0,0 +1,8 @@
+---
+"@llamaindex/cloud": patch
+"@llamaindex/community": patch
+"@llamaindex/core": patch
+"@llamaindex/readers": patch
+---
+
+fix: add retry handling logic to parser reader and fix lint issues
@@ -1,75 +1,5 @@
 # @llamaindex/doc

-## 0.2.4
-
-### Patch Changes
-
- 9c63f3f: Add support for openai responses api
- Updated dependencies [9c63f3f]
- Updated dependencies [c515a32]
-  - @llamaindex/openai@0.3.0
-  - @llamaindex/core@0.6.2
-  - @llamaindex/workflow@1.0.2
-  - llamaindex@0.9.15
-  - @llamaindex/cloud@4.0.2
-  - @llamaindex/node-parser@2.0.2
-  - @llamaindex/readers@3.0.2
-
-## 0.2.3
-
-### Patch Changes
-
- 648cfb5: Add support for supabase vector store
-  Added doc for the supbase vector store
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
- Updated dependencies [9d951b2]
-  - @llamaindex/core@0.6.1
-  - llamaindex@0.9.14
-  - @llamaindex/cloud@4.0.1
-  - @llamaindex/node-parser@2.0.1
-  - @llamaindex/openai@0.2.1
-  - @llamaindex/readers@3.0.1
-  - @llamaindex/workflow@1.0.1
-
-## 0.2.2
-
-### Patch Changes
-
- e98033e: docs: correct the number of indexes
-
-## 0.2.1
-
-### Patch Changes
-
- Updated dependencies [75d6e29]
-  - llamaindex@0.9.13
-
-## 0.2.0
-
-### Minor Changes
-
- f1db9b3: Adding an options parameter to vercel tool to tailor responses
-
-### Patch Changes
-
- 21bebfc: Expose more content to fix the issue with unavailable documentation links, and adjust the documentation based on the latest code.
- 2b39cef: Added documentation for structured output in openai and ollama
- Updated dependencies [21bebfc]
- Updated dependencies [93bc0ff]
- Updated dependencies [91a18e7]
- Updated dependencies [bf56fc0]
- Updated dependencies [f8a86e4]
- Updated dependencies [5189b44]
- Updated dependencies [58a9446]
-  - @llamaindex/readers@3.0.0
-  - @llamaindex/core@0.6.0
-  - @llamaindex/openai@0.2.0
-  - @llamaindex/cloud@4.0.0
-  - @llamaindex/workflow@1.0.0
-  - llamaindex@0.9.12
-  - @llamaindex/node-parser@2.0.0
-
 ## 0.1.11

 ### Patch Changes
@@ -4,8 +4,6 @@ const withMDX = createMDX();

 /** @type {import('next').NextConfig} */
 const config = {
-  // default timeout for static generation is 60s, but we need to increase it to 10 minutes due to the large number of document pages
-  staticPageGenerationTimeout: 600,
  reactStrictMode: true,
  eslint: {
    ignoreDuringBuilds: true,
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/doc",
-  "version": "0.2.4",
+  "version": "0.1.11",
  "private": true,
  "scripts": {
    "postinstall": "fumadocs-mdx",
@@ -84,7 +84,6 @@ const queryTool = llamaindex({
  model: openai("gpt-4"),
  index,
  description: "Search through the documents",
-  options: { fields: ["sourceNodes", "messages"]}
 });

 // Use the tool with Vercel's AI SDK
@@ -2,7 +2,7 @@
 title: Index
 ---

-An index is the basic container and organization for your data. LlamaIndex.TS supports three indexes:
+An index is the basic container and organization for your data. LlamaIndex.TS supports two indexes:

 - `VectorStoreIndex` - will send the top-k `Node`s to the LLM when generating a response. The default top-k is 2.
 - `SummaryIndex` - will send every `Node` in the index to the LLM in order to generate a response
@@ -56,10 +56,10 @@ const vectorStore = new QdrantVectorStore({

 ```ts
 const document = new Document({ text: essay, id_: path });
-const storageContext = await storageContextFromDefaults({ vectorStore });
-  const index = await VectorStoreIndex.fromDocuments([document], {
-    storageContext,
-  });
+
+const index = await VectorStoreIndex.fromDocuments([document], {
+  vectorStore,
+});
 ```

 ## Query the index
@@ -91,11 +91,11 @@ async function main() {
  });

  const document = new Document({ text: essay, id_: path });
-  const storageContext = await storageContextFromDefaults({ vectorStore });
+
  const index = await VectorStoreIndex.fromDocuments([document], {
-    storageContext,
+    vectorStore,
  });
-  
+
  const queryEngine = index.asQueryEngine();

  const response = await queryEngine.query({
@@ -1,166 +0,0 @@
---
-title: Supabase Vector Store
---
-
-[supabase.com](https://supabase.com/)
-
-To use this vector store, you need a Supabase project. You can create one at [supabase.com](https://supabase.com/).
-
-## Installation
-
-import { Tab, Tabs } from "fumadocs-ui/components/tabs";
-
-<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
-  ```shell tab="npm"
-  npm install llamaindex @llamaindex/supabase
-  ```
-
-  ```shell tab="yarn"
-  yarn add llamaindex @llamaindex/supabase
-  ```
-
-  ```shell tab="pnpm"
-  pnpm add llamaindex @llamaindex/supabase
-  ```
-</Tabs>
-
-## Database Setup
-
-Before using the vector store, you need to:
-1. Enable the `pgvector` extension
-2. Create a table for storing vectors
-3. Create a vector similarity search function
-
-```sql
-create table documents (
-id uuid primary key,
-content text,
-metadata jsonb,
-embedding vector(1536)
-);
-```
-
-- Create a function for similarity search
-```sql
-create function match_documents (
-query_embedding vector(1536),
-match_count int
-) returns table (
-id uuid,
-content text,
-metadata jsonb,
-embedding vector(1536),
-similarity float
-)
-language plpgsql
-as $$
-begin
-return query
-select
-id,
-content,
-metadata,
-embedding,
-1 - (embedding <=> query_embedding) as similarity
-from documents
-order by embedding <=> query_embedding
-limit match_count;
-end;
-$$;
-```
-
-## Importing the modules
-
-```ts
-import { Document, VectorStoreIndex } from "llamaindex";
-import { SupabaseVectorStore } from "@llamaindex/supabase";
-```
-
-## Setup Supabase
-
-```ts
-const vectorStore = new SupabaseVectorStore({
-  supabaseUrl: process.env.SUPABASE_URL,
-  supabaseKey: process.env.SUPABASE_KEY,
-  table: "documents",
-});
-```
-
-## Setup the index
-
-```ts
-const documents = [
-  new Document({ 
-    text: "Sample document text",
-    metadata: { source: "example" }
-  })
-];
-
-const storageContext = await storageContextFromDefaults({ vectorStore });
-const index = await VectorStoreIndex.fromDocuments(documents, {
-  storageContext,
-});
-```
-
-## Query the index
-
-```ts
-const queryEngine = index.asQueryEngine();
-
-const response = await queryEngine.query({
-  query: "What is in the document?",
-});
-
-// Output response
-console.log(response.toString());
-```
-
-## Full code
-
-```ts
-import { Document, VectorStoreIndex, storageContextFromDefaults } from "llamaindex";
-import { SupabaseVectorStore } from "@llamaindex/supabase";
-
-async function main() {
-  // Initialize the vector store
-  const vectorStore = new SupabaseVectorStore({
-    supabaseUrl: process.env.SUPABASE_URL,
-    supabaseKey: process.env.SUPABASE_KEY,
-    table: "documents",
-  });
-
-  // Create sample documents
-  const documents = [
-    new Document({
-      text: "Vector search enables semantic similarity search",
-      metadata: {
-        source: "research_paper",
-        author: "Jane Smith",
-      },
-    }),
-  ];
-
-  // Create storage context
-  const storageContext = await storageContextFromDefaults({ vectorStore });
-
-  // Create and store embeddings
-  const index = await VectorStoreIndex.fromDocuments(documents, {
-    storageContext,
-  });
-
-  // Query the index
-  const queryEngine = index.asQueryEngine();
-  const response = await queryEngine.query({
-    query: "What is vector search?",
-  });
-
-  // Output response
-  console.log(response.toString());
-}
-
-main().catch(console.error);
-```
-
-## API Reference
-
- [SupabaseVectorStore](/docs/api/classes/SupabaseVectorStore)
@@ -55,35 +55,6 @@ const results = await queryEngine.query({
 });
 ```

-## Using JSON Response Format
-
-You can configure Ollama to return responses in JSON format:
-
-```ts
-import { Ollama } from "@llamaindex/llms/ollama";
-import { z } from "zod";
-
-// Simple JSON format
-const llm = new Ollama({ 
-  model: "llama2", 
-  temperature: 0,
-  responseFormat: { type: "json_object" }
-});
-
-// Using Zod schema for validation
-const responseSchema = z.object({
-  summary: z.string(),
-  topics: z.array(z.string()),
-  sentiment: z.enum(["positive", "negative", "neutral"])
-});
-
-const llm = new Ollama({ 
-  model: "llama2", 
-  temperature: 0,
-  responseFormat: responseSchema  
-});
-```
-
 ## Full Example

 ```ts
@@ -46,289 +46,6 @@ or
 Settings.llm = new OpenAI({ model: "gpt-3.5-turbo", temperature: 0, apiKey: <YOUR_API_KEY>, baseURL: "https://api.scaleway.ai/v1" });
 ```

-## Using OpenAI Responses API
-
-The OpenAI Responses API provides enhanced functionality for handling complex interactions, including built-in tools, annotations, and streaming responses. Here's how to use it:
-
-### Basic Setup
-
-```ts
-import { openaiResponses } from "@llamaindex/openai";
-
-const llm = openaiResponses({
-  model: "gpt-4o",
-  temperature: 0.1,
-  maxOutputTokens: 1000
-});
-```
-
-### Message Content Types
-
-The API supports different types of message content, including text and images:
-
-```ts
-const response = await llm.chat({
-  messages: [
-    {
-      role: "user",
-      content: [
-        {
-          type: "input_text",
-          text: "What's in this image?"
-        },
-        {
-          type: "input_image",
-          image_url: "https://example.com/image.jpg",
-          detail: "auto" // Optional: can be "auto", "low", or "high"
-        }
-      ]
-    }
-  ]
-});
-```
-
-### Advanced Features
-
-#### Built-in Tools
-
-```ts
-const llm = openaiResponses({
-  model: "gpt-4o",
-  builtInTools: [
-    {
-      type: "function",
-      name: "search_files",
-      description: "Search through available files"
-    }
-  ],
-  strict: true // Enable strict mode for tool calls
-});
-```
-
-#### Response Tracking and Storage
-
-```ts
-const llm = openaiResponses({
-  trackPreviousResponses: true, // Enable response tracking
-  store: true, // Store responses for future reference
-  user: "user-123", // Associate responses with a user
-  callMetadata: { // Add custom metadata
-    sessionId: "session-123",
-    context: "customer-support"
-  }
-});
-```
-
-#### Streaming Responses
-
-```ts
-const response = await llm.chat({
-  messages: [
-    {
-      role: "user",
-      content: "Generate a long response"
-    }
-  ],
-  stream: true // Enable streaming
-});
-
-for await (const chunk of response) {
-  console.log(chunk.delta); // Process each chunk of the response
-}
-```
-
-### Configuration Options
-
-The OpenAI Responses API supports various configuration options:
-
-```ts
-const llm = openaiResponses({
-  // Model and basic settings
-  model: "gpt-4o",
-  temperature: 0.1,
-  topP: 1,
-  maxOutputTokens: 1000,
-  
-  // API configuration
-  apiKey: "your-api-key",
-  baseURL: "custom-endpoint",
-  maxRetries: 10,
-  timeout: 60000,
-  
-  // Response handling
-  trackPreviousResponses: false,
-  store: false,
-  strict: false,
-  
-  // Additional options
-  instructions: "Custom instructions for the model",
-  truncation: "auto", // Can be "auto", "disabled", or null
-  include: ["citations", "reasoning"] // Specify what to include in responses
-});
-```
-
-### Response Structure
-
-The API returns responses with rich metadata and optional annotations:
-
-```ts
-interface ResponseStructure {
-  message: {
-    content: string;
-    role: "assistant";
-    options: {
-      built_in_tool_calls: Array<ToolCall>;
-      annotations?: Array<Citation | URLCitation | FilePath>;
-      refusal?: string;
-      reasoning?: ReasoningItem;
-      usage?: ResponseUsage;
-      toolCall?: Array<PartialToolCall>;
-    }
-  }
-}
-```
-
-### Best Practices
-
-1. Use `trackPreviousResponses` when you need conversation continuity
-2. Enable `strict` mode when using tools to ensure accurate function calls
-3. Set appropriate `maxOutputTokens` to control response length
-4. Use `annotations` to track citations and references in responses
-5. Implement error handling for potential API failures and retries
-
-## Using JSON Response Format
-
-You can configure OpenAI to return responses in JSON format:
-
-```ts
-Settings.llm = new OpenAI({ 
-  model: "gpt-4o", 
-  temperature: 0,
-  responseFormat: { type: "json_object" }  
-});
-
-// You can also use a Zod schema to validate the response structure
-import { z } from "zod";
-
-const responseSchema = z.object({
-  summary: z.string(),  
-  topics: z.array(z.string()),
-  sentiment: z.enum(["positive", "negative", "neutral"])
-});
-
-Settings.llm = new OpenAI({ 
-  model: "gpt-4o", 
-  temperature: 0,
-  responseFormat: responseSchema  
-});
-```
-
-## Response Formats
-
-The OpenAI LLM supports different response formats to structure the output in specific ways. There are two main approaches to formatting responses:
-
-### 1. JSON Object Format
-
-The simplest way to get structured JSON responses is using the `json_object` response format:
-
-```ts
-Settings.llm = new OpenAI({ 
-  model: "gpt-4o", 
-  temperature: 0,
-  responseFormat: { type: "json_object" }  
-});
-
-const response = await llm.chat({
-  messages: [
-    {
-      role: "system",
-      content: "You are a helpful assistant that outputs JSON."
-    },
-    {
-      role: "user", 
-      content: "Summarize this meeting transcript"
-    }
-  ]
-});
-
-// Response will be valid JSON
-console.log(response.message.content);
-```
-
-### 2. Schema Validation with Zod
-
-For more robust type safety and validation, you can use Zod schemas to define the expected response structure:
-
-```ts
-import { z } from "zod";
-
-// Define the response schema
-const meetingSchema = z.object({
-  summary: z.string(),
-  participants: z.array(z.string()),
-  actionItems: z.array(z.string()),
-  nextSteps: z.string()
-});
-
-// Configure the LLM with the schema
-Settings.llm = new OpenAI({ 
-  model: "gpt-4o", 
-  temperature: 0,
-  responseFormat: meetingSchema
-});
-
-const response = await llm.chat({
-  messages: [
-    {
-      role: "user",
-      content: "Summarize this meeting transcript" 
-    }
-  ]
-});
-
-// Response will be typed and validated according to the schema
-const result = response.message.content;
-console.log(result.summary);
-console.log(result.actionItems);
-```
-
-### Response Format Options
-
-The response format can be configured in two ways:
-
-1. At LLM initialization:
-```ts
-const llm = new OpenAI({
-  model: "gpt-4o",
-  responseFormat: { type: "json_object" } // or a Zod schema
-});
-```
-
-2. Per request:
-```ts
-const response = await llm.chat({
-  messages: [...],
-  responseFormat: { type: "json_object" } // or a Zod schema
-});
-```
-
-The response format options are:
-
- `{ type: "json_object" }` - Returns responses as JSON objects
- `zodSchema` - A Zod schema that defines and validates the response structure
-
-### Best Practices
-
-1. Use JSON object format for simple structured responses
-2. Use Zod schemas when you need:
-   - Type safety
-   - Response validation
-   - Complex nested structures
-   - Specific field constraints
-3. Set a low temperature (e.g. 0) when using structured outputs for more reliable formatting
-4. Include clear instructions in system or user messages about the expected response format
-5. Handle potential parsing errors when working with JSON responses
-
 ## 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.
@@ -7,59 +7,9 @@ A tool can be called to perform custom actions, or retrieve extra information ba
 A result from a tool call can be used by subsequent steps in a workflow, or to compute a final answer.
 For example, a "weather tool" could fetch some live weather information from a geographical location.

-## Tool Function
-
-The `tool` function is a utility provided to define a tool that can be used by an agent. It takes a function and a configuration object as arguments. The configuration object includes the tool's name, description, and parameters.
-
-### Parameters with Zod
-
-The `parameters` field in the tool configuration is defined using `zod`, a TypeScript-first schema declaration and validation library. `zod` allows you to specify the expected structure and types of the input parameters, ensuring that the data passed to the tool is valid.
-
-Example:
-```ts
-import { agent, tool } from "llamaindex";
-import { z } from "zod";
-
-// first arg is LLM input, second is bound arg
-const queryKnowledgeBase = async ({ question }, { userToken }) => {
-  const response = await fetch(`https://knowledge-base.com?token=${userToken}&query=${question}`);
-  // ...
-};
-
-// define tool with zod validation
-const kbTool = tool(queryKnowledgeBase, {
-  name: 'queryKnowledgeBase',
-  description: 'Query knowledge base',
-  parameters: z.object({
-    question: z.string({
-      description: 'The user question',
-    }),
-  }),
-});
-
-```
-In this example, `z.object` is used to define a schema for the `parameters` where `question` is expected to be a string. This ensures that any input to the tool adheres to the specified structure, providing a layer of type safety and validation.
-
-
-## Built-in tools
-
-You can import built-in tools from the `@llamaindex/tools` package.
-
-```ts
-import { agent } from "llamaindex";
-import { wiki } from "@llamaindex/tools";
-
-const researchAgent = agent({
-  name: "WikiAgent",
-  description: "Gathering information from the internet",
-  systemPrompt: `You are a research agent. Your role is to gather information from the internet using the provided tools.`,
-  tools: [wiki()],
-});
-```
-
 ## Function tool

-You can still use the `FunctionTool` class to define a tool.
+Function tools are implemented with the `FunctionTool` class.
 A `FunctionTool` is constructed from a function with signature
 ```ts
 (input: T, additionalArg?: AdditionalToolArgument) => R
@@ -1,31 +1,5 @@
 # @llamaindex/cloudflare-worker-agent-test

-## 0.0.149
-
-### Patch Changes
-
- llamaindex@0.9.15
-
-## 0.0.148
-
-### Patch Changes
-
- Updated dependencies [9d951b2]
-  - llamaindex@0.9.14
-
-## 0.0.147
-
-### Patch Changes
-
- Updated dependencies [75d6e29]
-  - llamaindex@0.9.13
-
-## 0.0.146
-
-### Patch Changes
-
- llamaindex@0.9.12
-
 ## 0.0.145

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/cloudflare-worker-agent-test",
-  "version": "0.0.149",
+  "version": "0.0.145",
  "type": "module",
  "private": true,
  "scripts": {
@@ -1,25 +1,5 @@
 # @llamaindex/llama-parse-browser-test

-## 0.0.57
-
-### Patch Changes
-
- @llamaindex/cloud@4.0.2
-
-## 0.0.56
-
-### Patch Changes
-
- @llamaindex/cloud@4.0.1
-
-## 0.0.55
-
-### Patch Changes
-
- Updated dependencies [bf56fc0]
- Updated dependencies [5189b44]
-  - @llamaindex/cloud@4.0.0
-
 ## 0.0.54

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/llama-parse-browser-test",
  "private": true,
-  "version": "0.0.57",
+  "version": "0.0.54",
  "type": "module",
  "scripts": {
    "dev": "vite",
@@ -10,7 +10,7 @@
  },
  "devDependencies": {
    "typescript": "^5.7.3",
-    "vite": "^5.4.16",
+    "vite": "^5.4.12",
    "vite-plugin-wasm": "^3.3.0"
  },
  "dependencies": {
@@ -1,31 +1,5 @@
 # @llamaindex/next-agent-test

-## 0.1.149
-
-### Patch Changes
-
- llamaindex@0.9.15
-
-## 0.1.148
-
-### Patch Changes
-
- Updated dependencies [9d951b2]
-  - llamaindex@0.9.14
-
-## 0.1.147
-
-### Patch Changes
-
- Updated dependencies [75d6e29]
-  - llamaindex@0.9.13
-
-## 0.1.146
-
-### Patch Changes
-
- llamaindex@0.9.12
-
 ## 0.1.145

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/next-agent-test",
-  "version": "0.1.149",
+  "version": "0.1.145",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -1,31 +1,5 @@
 # test-edge-runtime

-## 0.1.148
-
-### Patch Changes
-
- llamaindex@0.9.15
-
-## 0.1.147
-
-### Patch Changes
-
- Updated dependencies [9d951b2]
-  - llamaindex@0.9.14
-
-## 0.1.146
-
-### Patch Changes
-
- Updated dependencies [75d6e29]
-  - llamaindex@0.9.13
-
-## 0.1.145
-
-### Patch Changes
-
- llamaindex@0.9.12
-
 ## 0.1.144

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/nextjs-edge-runtime-test",
-  "version": "0.1.148",
+  "version": "0.1.144",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -1,40 +1,5 @@
 # @llamaindex/next-node-runtime

-## 0.1.15
-
-### Patch Changes
-
- llamaindex@0.9.15
- @llamaindex/huggingface@0.1.2
- @llamaindex/readers@3.0.2
-
-## 0.1.14
-
-### Patch Changes
-
- Updated dependencies [9d951b2]
-  - llamaindex@0.9.14
-  - @llamaindex/huggingface@0.1.1
-  - @llamaindex/readers@3.0.1
-
-## 0.1.13
-
-### Patch Changes
-
- Updated dependencies [75d6e29]
-  - llamaindex@0.9.13
-
-## 0.1.12
-
-### Patch Changes
-
- Updated dependencies [21bebfc]
- Updated dependencies [91a18e7]
- Updated dependencies [5189b44]
-  - @llamaindex/readers@3.0.0
-  - @llamaindex/huggingface@0.1.0
-  - llamaindex@0.9.12
-
 ## 0.1.11

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/next-node-runtime-test",
-  "version": "0.1.15",
+  "version": "0.1.11",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -1,31 +1,5 @@
 # vite-import-llamaindex

-## 0.0.15
-
-### Patch Changes
-
- llamaindex@0.9.15
-
-## 0.0.14
-
-### Patch Changes
-
- Updated dependencies [9d951b2]
-  - llamaindex@0.9.14
-
-## 0.0.13
-
-### Patch Changes
-
- Updated dependencies [75d6e29]
-  - llamaindex@0.9.13
-
-## 0.0.12
-
-### Patch Changes
-
- llamaindex@0.9.12
-
 ## 0.0.11

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "vite-import-llamaindex",
  "private": true,
-  "version": "0.0.15",
+  "version": "0.0.11",
  "type": "module",
  "scripts": {
    "build": "vite build",
@@ -16,7 +16,7 @@
    "@size-limit/preset-big-lib": "^11.1.6",
    "size-limit": "^11.1.6",
    "typescript": "^5.7.3",
-    "vite": "^5.4.16"
+    "vite": "^6.1.0"
  },
  "dependencies": {
    "llamaindex": "workspace:*"
@@ -1,31 +1,5 @@
 # @llamaindex/waku-query-engine-test

-## 0.0.149
-
-### Patch Changes
-
- llamaindex@0.9.15
-
-## 0.0.148
-
-### Patch Changes
-
- Updated dependencies [9d951b2]
-  - llamaindex@0.9.14
-
-## 0.0.147
-
-### Patch Changes
-
- Updated dependencies [75d6e29]
-  - llamaindex@0.9.13
-
-## 0.0.146
-
-### Patch Changes
-
- llamaindex@0.9.12
-
 ## 0.0.145

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/waku-query-engine-test",
-  "version": "0.0.149",
+  "version": "0.0.145",
  "type": "module",
  "private": true,
  "scripts": {
@@ -1 +0,0 @@
-20
@@ -1,178 +1,5 @@
 # examples

-## 0.3.2
-
-### Patch Changes
-
- 9c63f3f: Add support for openai responses api
- Updated dependencies [9c63f3f]
- Updated dependencies [c515a32]
-  - @llamaindex/openai@0.3.0
-  - @llamaindex/google@0.2.2
-  - @llamaindex/core@0.6.2
-  - @llamaindex/workflow@1.0.2
-  - llamaindex@0.9.15
-  - @llamaindex/clip@0.0.48
-  - @llamaindex/deepinfra@0.0.48
-  - @llamaindex/deepseek@0.0.8
-  - @llamaindex/fireworks@0.0.8
-  - @llamaindex/groq@0.0.63
-  - @llamaindex/huggingface@0.1.2
-  - @llamaindex/jinaai@0.0.8
-  - @llamaindex/perplexity@0.0.5
-  - @llamaindex/azure@0.1.11
-  - @llamaindex/elastic-search@0.1.2
-  - @llamaindex/milvus@0.1.11
-  - @llamaindex/qdrant@0.1.11
-  - @llamaindex/supabase@0.1.1
-  - @llamaindex/together@0.0.8
-  - @llamaindex/vllm@0.0.34
-  - @llamaindex/cloud@4.0.2
-  - @llamaindex/node-parser@2.0.2
-  - @llamaindex/anthropic@0.3.2
-  - @llamaindex/cohere@0.0.16
-  - @llamaindex/mistral@0.1.2
-  - @llamaindex/mixedbread@0.0.16
-  - @llamaindex/ollama@0.1.2
-  - @llamaindex/portkey-ai@0.0.44
-  - @llamaindex/replicate@0.0.44
-  - @llamaindex/astra@0.0.16
-  - @llamaindex/chroma@0.0.16
-  - @llamaindex/firestore@1.0.9
-  - @llamaindex/mongodb@0.0.16
-  - @llamaindex/pinecone@0.1.2
-  - @llamaindex/postgres@0.0.44
-  - @llamaindex/upstash@0.0.16
-  - @llamaindex/weaviate@0.0.16
-  - @llamaindex/vercel@0.1.2
-  - @llamaindex/voyage-ai@1.0.8
-  - @llamaindex/readers@3.0.2
-  - @llamaindex/tools@0.0.4
-
-## 0.3.1
-
-### Patch Changes
-
- 648cfb5: Add support for supabase vector store
-  Added doc for the supbase vector store
- Updated dependencies [648cfb5]
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
- Updated dependencies [9d951b2]
-  - @llamaindex/supabase@0.1.0
-  - @llamaindex/core@0.6.1
-  - llamaindex@0.9.14
-  - @llamaindex/tools@0.0.3
-  - @llamaindex/cloud@4.0.1
-  - @llamaindex/node-parser@2.0.1
-  - @llamaindex/anthropic@0.3.1
-  - @llamaindex/clip@0.0.47
-  - @llamaindex/cohere@0.0.15
-  - @llamaindex/deepinfra@0.0.47
-  - @llamaindex/google@0.2.1
-  - @llamaindex/huggingface@0.1.1
-  - @llamaindex/jinaai@0.0.7
-  - @llamaindex/mistral@0.1.1
-  - @llamaindex/mixedbread@0.0.15
-  - @llamaindex/ollama@0.1.1
-  - @llamaindex/openai@0.2.1
-  - @llamaindex/perplexity@0.0.4
-  - @llamaindex/portkey-ai@0.0.43
-  - @llamaindex/replicate@0.0.43
-  - @llamaindex/astra@0.0.15
-  - @llamaindex/azure@0.1.10
-  - @llamaindex/chroma@0.0.15
-  - @llamaindex/elastic-search@0.1.1
-  - @llamaindex/firestore@1.0.8
-  - @llamaindex/milvus@0.1.10
-  - @llamaindex/mongodb@0.0.15
-  - @llamaindex/pinecone@0.1.1
-  - @llamaindex/postgres@0.0.43
-  - @llamaindex/qdrant@0.1.10
-  - @llamaindex/upstash@0.0.15
-  - @llamaindex/weaviate@0.0.15
-  - @llamaindex/vercel@0.1.1
-  - @llamaindex/voyage-ai@1.0.7
-  - @llamaindex/readers@3.0.1
-  - @llamaindex/workflow@1.0.1
-  - @llamaindex/deepseek@0.0.7
-  - @llamaindex/fireworks@0.0.7
-  - @llamaindex/groq@0.0.62
-  - @llamaindex/together@0.0.7
-  - @llamaindex/vllm@0.0.33
-
-## 0.3.0
-
-### Minor Changes
-
- 91a18e7: Added support for structured output in the chat api of openai and ollama
-  Added structured output parameter in the provider
- d1c1f99: Added support for function calling in mistral provider
-  Update model list for mistral provider
-  Added example for the tool call in mistral
-
-### Patch Changes
-
- 2509353: Added support for elastic search vector store
- Updated dependencies [21bebfc]
- Updated dependencies [77e24ce]
- Updated dependencies [93bc0ff]
- Updated dependencies [2509353]
- Updated dependencies [da06e45]
- Updated dependencies [2a0a899]
- Updated dependencies [050cd53]
- Updated dependencies [91a18e7]
- Updated dependencies [bf56fc0]
- Updated dependencies [f1db9b3]
- Updated dependencies [da8068e]
- Updated dependencies [c7ff323]
- Updated dependencies [f8a86e4]
- Updated dependencies [d1c1f99]
- Updated dependencies [5189b44]
- Updated dependencies [3fd4cc3]
- Updated dependencies [04f8c96]
- Updated dependencies [58a9446]
-  - @llamaindex/readers@3.0.0
-  - @llamaindex/core@0.6.0
-  - @llamaindex/tools@0.0.2
-  - @llamaindex/elastic-search@0.1.0
-  - @llamaindex/google@0.2.0
-  - @llamaindex/pinecone@0.1.0
-  - @llamaindex/huggingface@0.1.0
-  - @llamaindex/anthropic@0.3.0
-  - @llamaindex/mistral@0.1.0
-  - @llamaindex/ollama@0.1.0
-  - @llamaindex/openai@0.2.0
-  - @llamaindex/cloud@4.0.0
-  - @llamaindex/vercel@0.1.0
-  - @llamaindex/azure@0.1.9
-  - @llamaindex/workflow@1.0.0
-  - @llamaindex/mongodb@0.0.14
-  - llamaindex@0.9.12
-  - @llamaindex/node-parser@2.0.0
-  - @llamaindex/clip@0.0.46
-  - @llamaindex/cohere@0.0.14
-  - @llamaindex/deepinfra@0.0.46
-  - @llamaindex/jinaai@0.0.6
-  - @llamaindex/mixedbread@0.0.14
-  - @llamaindex/perplexity@0.0.3
-  - @llamaindex/portkey-ai@0.0.42
-  - @llamaindex/replicate@0.0.42
-  - @llamaindex/astra@0.0.14
-  - @llamaindex/chroma@0.0.14
-  - @llamaindex/firestore@1.0.7
-  - @llamaindex/milvus@0.1.9
-  - @llamaindex/postgres@0.0.42
-  - @llamaindex/qdrant@0.1.9
-  - @llamaindex/upstash@0.0.14
-  - @llamaindex/weaviate@0.0.14
-  - @llamaindex/voyage-ai@1.0.6
-  - @llamaindex/deepseek@0.0.6
-  - @llamaindex/fireworks@0.0.6
-  - @llamaindex/groq@0.0.61
-  - @llamaindex/together@0.0.6
-  - @llamaindex/vllm@0.0.32
-
 ## 0.2.10

 ### Patch Changes
@@ -1,51 +0,0 @@
-import {
-  AgentStream,
-  AgentToolCallResult,
-  Document,
-  VectorStoreIndex,
-  agent,
-  openai,
-} from "llamaindex";
-
-async function main() {
-  const index = await VectorStoreIndex.fromDocuments([
-    new Document({
-      text: "Cats have a specialized collarbone that allows them to always land on their feet when they fall.",
-    }),
-    new Document({
-      text: "Dogs have a sense of smell that is 10,000 to 100,000 times more acute than humans.",
-    }),
-    new Document({
-      text: "Cats are known for their agility and ability to jump high.",
-    }),
-  ]);
-
-  const myAgent = agent({
-    llm: openai({ model: "gpt-4o" }),
-    tools: [
-      index.queryTool({
-        options: { similarityTopK: 2 },
-        includeSourceNodes: true,
-      }),
-    ],
-  });
-
-  const context = myAgent.run("The fact about cats");
-
-  for await (const event of context) {
-    if (event instanceof AgentToolCallResult) {
-      console.log(
-        "Using these retrieved information to answer the question:\n",
-        event.data.toolOutput.result,
-      );
-    } else if (event instanceof AgentStream) {
-      for (const chunk of event.data.delta) {
-        process.stdout.write(chunk);
-      }
-    }
-  }
-}
-
-void main().then(() => {
-  console.log("Done");
-});
@@ -1,30 +0,0 @@
-import { openaiResponses } from "@llamaindex/openai";
-import { wiki } from "@llamaindex/tools";
-import { agent, tool } from "llamaindex";
-import { z } from "zod";
-
-const workflow = agent({
-  tools: [
-    tool({
-      name: "weather",
-      description: "Get the weather",
-      parameters: z.object({
-        location: z.string().describe("The location to get the weather for"),
-      }),
-      execute: ({ location }) => `The weather in ${location} is sunny`,
-    }),
-    wiki(),
-  ],
-  llm: openaiResponses({
-    model: "gpt-4o-mini",
-  }),
-});
-
-async function main() {
-  const result = await workflow.run(
-    "What is the weather in New York? What's the history of New York from Wikipedia in 3 sentences?",
-  );
-  console.log(result.data);
-}
-
-void main();
@@ -1,33 +0,0 @@
-import { openaiResponses } from "@llamaindex/openai";
-
-async function main() {
-  const llm = openaiResponses({
-    model: "gpt-4o",
-    maxOutputTokens: 1000,
-    apiKey: process.env.MY_OPENAI_API_KEY,
-  });
-
-  const response = await llm.chat({
-    messages: [
-      {
-        role: "user",
-        content: [
-          {
-            type: "text",
-            text: "What's in this image? Describe it in detail.",
-          },
-          {
-            type: "image_url",
-            image_url: {
-              url: "https://storage.googleapis.com/cloud-samples-data/vision/face/faces.jpeg",
-            },
-          },
-        ],
-      },
-    ],
-  });
-
-  console.log("Single Image Analysis:", response.message.content);
-}
-
-main().catch(console.error);
@@ -1,22 +0,0 @@
-import { openaiResponses } from "@llamaindex/openai";
-
-async function main() {
-  const llm = openaiResponses({
-    model: "gpt-4o-mini",
-    temperature: 0.1,
-  });
-
-  // Basic chat example
-  const response = await llm.chat({
-    messages: [
-      {
-        role: "user",
-        content: "What is the capital of France?",
-      },
-    ],
-  });
-
-  console.log(response.message.content);
-}
-
-main().catch(console.error);
@@ -1,26 +0,0 @@
-import { openaiResponses } from "@llamaindex/openai";
-
-async function main() {
-  const llm = openaiResponses({
-    model: "gpt-4o-mini",
-    temperature: 0.1,
-  });
-
-  const stream = await llm.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);
-  }
-}
-
-main().catch(console.error);
@@ -1,37 +0,0 @@
-import { openaiResponses } from "@llamaindex/openai";
-import { tool } from "llamaindex";
-
-import { z } from "zod";
-async function main() {
-  const weatherTool = tool({
-    name: "weather",
-    description: "Get the weather",
-    parameters: z.object({
-      location: z.string({
-        description: "The location to get the weather for",
-      }),
-    }),
-    execute: ({ location }) => {
-      return `The weather in ${location} is sunny`;
-    },
-  });
-
-  const llm = openaiResponses({
-    model: "gpt-4o-mini",
-    temperature: 0.1,
-  });
-
-  const response = await llm.chat({
-    messages: [
-      {
-        role: "user",
-        content: "What is the weather in New York?",
-      },
-    ],
-    tools: [weatherTool],
-  });
-
-  console.log(response.message.options);
-}
-
-main().catch(console.error);
@@ -1,23 +0,0 @@
-import { openaiResponses } from "@llamaindex/openai";
-
-async function main() {
-  const llm = openaiResponses({
-    model: "gpt-4o",
-    temperature: 0.1,
-    builtInTools: [{ type: "web_search_preview" }],
-  });
-
-  // Streaming chat example
-  const response = await llm.chat({
-    messages: [
-      {
-        role: "user",
-        content: "What are the latest developments in AI?",
-      },
-    ],
-  });
-
-  console.log(response.message.content);
-}
-
-main().catch(console.error);
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/examples",
-  "version": "0.3.2",
+  "version": "0.2.10",
  "private": true,
  "scripts": {
    "lint": "eslint .",
@@ -11,47 +11,45 @@
    "@azure/cosmos": "^4.1.1",
    "@azure/identity": "^4.4.1",
    "@azure/search-documents": "^12.1.0",
-    "@llamaindex/anthropic": "^0.3.2",
-    "@llamaindex/astra": "^0.0.16",
-    "@llamaindex/azure": "^0.1.11",
-    "@llamaindex/chroma": "^0.0.16",
-    "@llamaindex/clip": "^0.0.48",
-    "@llamaindex/cloud": "^4.0.2",
-    "@llamaindex/cohere": "^0.0.16",
-    "@llamaindex/core": "^0.6.2",
-    "@llamaindex/deepinfra": "^0.0.48",
+    "@llamaindex/anthropic": "^0.2.6",
+    "@llamaindex/astra": "^0.0.13",
+    "@llamaindex/azure": "^0.1.8",
+    "@llamaindex/chroma": "^0.0.13",
+    "@llamaindex/clip": "^0.0.45",
+    "@llamaindex/cloud": "^3.0.9",
+    "@llamaindex/cohere": "^0.0.13",
+    "@llamaindex/core": "^0.5.8",
+    "@llamaindex/deepinfra": "^0.0.45",
    "@llamaindex/env": "^0.1.29",
-    "@llamaindex/firestore": "^1.0.9",
-    "@llamaindex/google": "^0.2.2",
-    "@llamaindex/groq": "^0.0.63",
-    "@llamaindex/huggingface": "^0.1.2",
-    "@llamaindex/milvus": "^0.1.11",
-    "@llamaindex/mistral": "^0.1.2",
-    "@llamaindex/mixedbread": "^0.0.16",
-    "@llamaindex/mongodb": "^0.0.16",
-    "@llamaindex/elastic-search": "^0.1.2",
-    "@llamaindex/node-parser": "^2.0.2",
-    "@llamaindex/ollama": "^0.1.2",
-    "@llamaindex/openai": "^0.3.0",
-    "@llamaindex/pinecone": "^0.1.2",
-    "@llamaindex/portkey-ai": "^0.0.44",
-    "@llamaindex/postgres": "^0.0.44",
-    "@llamaindex/qdrant": "^0.1.11",
-    "@llamaindex/readers": "^3.0.2",
-    "@llamaindex/replicate": "^0.0.44",
-    "@llamaindex/upstash": "^0.0.16",
-    "@llamaindex/vercel": "^0.1.2",
-    "@llamaindex/vllm": "^0.0.34",
-    "@llamaindex/voyage-ai": "^1.0.8",
-    "@llamaindex/weaviate": "^0.0.16",
-    "@llamaindex/workflow": "^1.0.2",
-    "@llamaindex/deepseek": "^0.0.8",
-    "@llamaindex/fireworks": "^0.0.8",
-    "@llamaindex/together": "^0.0.8",
-    "@llamaindex/jinaai": "^0.0.8",
-    "@llamaindex/perplexity": "^0.0.5",
-    "@llamaindex/supabase": "^0.1.1",
-    "@llamaindex/tools": "^0.0.4",
+    "@llamaindex/firestore": "^1.0.6",
+    "@llamaindex/google": "^0.1.2",
+    "@llamaindex/groq": "^0.0.60",
+    "@llamaindex/huggingface": "^0.0.45",
+    "@llamaindex/milvus": "^0.1.8",
+    "@llamaindex/mistral": "^0.0.14",
+    "@llamaindex/mixedbread": "^0.0.13",
+    "@llamaindex/mongodb": "^0.0.13",
+    "@llamaindex/node-parser": "^1.0.8",
+    "@llamaindex/ollama": "^0.0.48",
+    "@llamaindex/openai": "^0.1.61",
+    "@llamaindex/pinecone": "^0.0.13",
+    "@llamaindex/portkey-ai": "^0.0.41",
+    "@llamaindex/postgres": "^0.0.41",
+    "@llamaindex/qdrant": "^0.1.8",
+    "@llamaindex/readers": "^2.0.8",
+    "@llamaindex/replicate": "^0.0.41",
+    "@llamaindex/upstash": "^0.0.13",
+    "@llamaindex/vercel": "^0.0.19",
+    "@llamaindex/vllm": "^0.0.31",
+    "@llamaindex/voyage-ai": "^1.0.5",
+    "@llamaindex/weaviate": "^0.0.13",
+    "@llamaindex/workflow": "^0.0.16",
+    "@llamaindex/deepseek": "^0.0.5",
+    "@llamaindex/fireworks": "^0.0.5",
+    "@llamaindex/together": "^0.0.5",
+    "@llamaindex/jinaai": "^0.0.5",
+    "@llamaindex/perplexity": "^0.0.2",
+    "@llamaindex/tools": "^0.0.1",
    "@notionhq/client": "^2.2.15",
    "@pinecone-database/pinecone": "^4.0.0",
    "@vercel/postgres": "^0.10.0",
@@ -60,7 +58,7 @@
    "commander": "^12.1.0",
    "dotenv": "^16.4.5",
    "js-tiktoken": "^1.0.14",
-    "llamaindex": "^0.9.15",
+    "llamaindex": "^0.9.11",
    "mongodb": "6.7.0",
    "postgres": "^3.4.4",
    "wikipedia": "^2.1.2",
@@ -1,73 +0,0 @@
-import { ElasticSearchVectorStore } from "@llamaindex/elastic-search";
-import {
-  gemini,
-  GEMINI_EMBEDDING_MODEL,
-  GEMINI_MODEL,
-  GeminiEmbedding,
-} from "@llamaindex/google";
-import {
-  Document,
-  Settings,
-  storageContextFromDefaults,
-  VectorStoreIndex,
-} from "llamaindex";
-async function main() {
-  Settings.embedModel = new GeminiEmbedding({
-    model: GEMINI_EMBEDDING_MODEL.TEXT_EMBEDDING_004,
-  });
-  Settings.llm = gemini({
-    model: GEMINI_MODEL.GEMINI_PRO_1_5_FLASH,
-  });
-  // Create sample documents
-  const documents = [
-    new Document({
-      text: "Elastic search is a powerful search engine",
-      metadata: {
-        source: "tech_docs",
-        author: "John Doe",
-      },
-    }),
-    new Document({
-      text: "Vector search enables semantic similarity search",
-      metadata: {
-        source: "research_paper",
-        author: "Jane Smith",
-      },
-    }),
-    new Document({
-      text: "Elasticsearch supports various distance metrics for vector search",
-      metadata: {
-        source: "tech_docs",
-        author: "Bob Wilson",
-      },
-    }),
-  ];
-
-  // Initialize ElasticSearch Vector Store
-  const vectorStore = new ElasticSearchVectorStore({
-    indexName: "llamaindex-demo",
-    esCloudId: process.env.ES_CLOUD_ID,
-    esApiKey: process.env.ES_API_KEY,
-  });
-
-  // Create storage context with the vector store
-  const storageContext = await storageContextFromDefaults({
-    vectorStore,
-  });
-
-  // Create and store embeddings in ElasticSearch
-  const index = await VectorStoreIndex.fromDocuments(documents, {
-    storageContext,
-  });
-
-  // Query the index
-  const queryEngine = index.asQueryEngine();
-
-  // Simple query
-  const response = await queryEngine.query({
-    query: "What is vector search?",
-  });
-  console.log("Basic Query Response:", response.toString());
-}
-
-main().catch(console.error);
@@ -1,8 +0,0 @@
-{
-  "name": "elastic-search-vector-store",
-  "type": "module",
-  "private": true,
-  "scripts": {
-    "start": "npx tsx index.ts"
-  }
-}
@@ -1,75 +0,0 @@
-import {
-  gemini,
-  GEMINI_EMBEDDING_MODEL,
-  GEMINI_MODEL,
-  GeminiEmbedding,
-} from "@llamaindex/google";
-import { SupabaseVectorStore } from "@llamaindex/supabase";
-import {
-  Document,
-  Settings,
-  storageContextFromDefaults,
-  VectorStoreIndex,
-} from "llamaindex";
-async function main() {
-  Settings.embedModel = new GeminiEmbedding({
-    model: GEMINI_EMBEDDING_MODEL.TEXT_EMBEDDING_004,
-  });
-  Settings.llm = gemini({
-    model: GEMINI_MODEL.GEMINI_PRO_1_5_FLASH,
-  });
-  // Create sample documents
-  const documents = [
-    new Document({
-      text: "Supbase is a powerful Database engine",
-      metadata: {
-        source: "tech_docs",
-        author: "John Doe",
-      },
-    }),
-    new Document({
-      text: "Vector search enables semantic similarity search",
-      metadata: {
-        source: "research_paper",
-        author: "Jane Smith",
-      },
-    }),
-    new Document({
-      text: "Supbase vector store supports various distance metrics for vector search",
-      metadata: {
-        source: "tech_docs",
-        author: "Bob Wilson",
-      },
-    }),
-  ];
-
-  // Initialize ElasticSearch Vector Store
-  const vectorStore = new SupabaseVectorStore({
-    supabaseUrl: process.env.SUPABASE_URL,
-    supabaseKey: process.env.SUPABASE_KEY,
-    table: "document",
-  });
-
-  // await vectorStore.delete("fc079c38-2af4-4782-96e4-955c28608fcf");
-
-  // Create storage context with the vector store
-  const storageContext = await storageContextFromDefaults({
-    vectorStore,
-  });
-
-  // Create and store embeddings in ElasticSearch
-  const index = await VectorStoreIndex.fromDocuments(documents, {
-    storageContext,
-  });
-
-  // Query the index
-  const queryEngine = index.asQueryEngine();
-
-  // Simple query
-  const response = await queryEngine.query({
-    query: "What is vector search?",
-  });
-  console.log("Basic Query Response:", response.toString());
-}
-
-main().catch(console.error);
@@ -1,8 +0,0 @@
-{
-  "name": "vector-store-supabase",
-  "type": "module",
-  "private": true,
-  "scripts": {
-    "start": "npx tsx index.ts"
-  }
-}
@@ -35,8 +35,7 @@
    "prettier-plugin-tailwindcss": "^0.6.11",
    "turbo": "^2.4.4",
    "typescript": "^5.7.3",
-    "typescript-eslint": "^8.18.0",
-    "vitest": "^3.1.1"
+    "typescript-eslint": "^8.18.0"
  },
  "packageManager": "pnpm@9.12.3",
  "lint-staged": {
@@ -1,31 +1,5 @@
 # @llamaindex/autotool

-## 6.0.15
-
-### Patch Changes
-
- llamaindex@0.9.15
-
-## 6.0.14
-
-### Patch Changes
-
- Updated dependencies [9d951b2]
-  - llamaindex@0.9.14
-
-## 6.0.13
-
-### Patch Changes
-
- Updated dependencies [75d6e29]
-  - llamaindex@0.9.13
-
-## 6.0.12
-
-### Patch Changes
-
- llamaindex@0.9.12
-
 ## 6.0.11

 ### Patch Changes
@@ -1,35 +1,5 @@
 # @llamaindex/autotool-01-node-example

-## 0.0.96
-
-### Patch Changes
-
- llamaindex@0.9.15
- @llamaindex/autotool@6.0.15
-
-## 0.0.95
-
-### Patch Changes
-
- Updated dependencies [9d951b2]
-  - llamaindex@0.9.14
-  - @llamaindex/autotool@6.0.14
-
-## 0.0.94
-
-### Patch Changes
-
- Updated dependencies [75d6e29]
-  - llamaindex@0.9.13
-  - @llamaindex/autotool@6.0.13
-
-## 0.0.93
-
-### Patch Changes
-
- llamaindex@0.9.12
- @llamaindex/autotool@6.0.12
-
 ## 0.0.92

 ### Patch Changes
@@ -13,5 +13,5 @@
  "scripts": {
    "start": "node --import tsx --import @llamaindex/autotool/node ./src/index.ts"
  },
-  "version": "0.0.96"
+  "version": "0.0.92"
 }
@@ -6,7 +6,7 @@
    "url": "git+https://github.com/run-llama/LlamaIndexTS.git",
    "directory": "packages/autotool"
  },
-  "version": "6.0.15",
+  "version": "6.0.11",
  "description": "auto transpile your JS function to LLM Agent compatible",
  "files": [
    "dist",
@@ -1,32 +1,5 @@
 # @llamaindex/cloud

-## 4.0.2
-
-### Patch Changes
-
- Updated dependencies [9c63f3f]
-  - @llamaindex/core@0.6.2
-
-## 4.0.1
-
-### Patch Changes
-
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
-  - @llamaindex/core@0.6.1
-
-## 4.0.0
-
-### Patch Changes
-
- bf56fc0: chore: bump sdk openapi.json
- 5189b44: fix: add retry handling logic to parser reader and fix lint issues
- Updated dependencies [21bebfc]
- Updated dependencies [93bc0ff]
- Updated dependencies [91a18e7]
- Updated dependencies [5189b44]
-  - @llamaindex/core@0.6.0
-
 ## 3.0.9

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/cloud",
-  "version": "4.0.2",
+  "version": "3.0.9",
  "type": "module",
  "license": "MIT",
  "scripts": {
@@ -1,38 +1,5 @@
 # @llamaindex/community

-## 0.0.94
-
-### Patch Changes
-
- Updated dependencies [9c63f3f]
-  - @llamaindex/core@0.6.2
-
-## 0.0.93
-
-### Patch Changes
-
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
-  - @llamaindex/core@0.6.1
-
-## 0.0.92
-
-### Patch Changes
-
- 1325178: fix: stringify all tool results for anthropic on bedrock
-
-## 0.0.91
-
-### Patch Changes
-
- 5189b44: fix: add retry handling logic to parser reader and fix lint issues
- 3fd4cc3: feat: use google's new gen ai library to support multimodal output
- Updated dependencies [21bebfc]
- Updated dependencies [93bc0ff]
- Updated dependencies [91a18e7]
- Updated dependencies [5189b44]
-  - @llamaindex/core@0.6.0
-
 ## 0.0.90

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/community",
  "description": "Community package for LlamaIndexTS",
-  "version": "0.0.94",
+  "version": "0.0.90",
  "type": "module",
  "types": "dist/type/index.d.ts",
  "main": "dist/cjs/index.js",
@@ -10,10 +10,12 @@ import type {
  MessageContentDetail,
  ToolCallLLMMessageOptions,
 } from "@llamaindex/core/llms";
-import { extractDataUrlComponents } from "../utils";
+import {
+  extractDataUrlComponents,
+  mapMessageContentToMessageContentDetails,
+} from "../utils";

 import type { JSONObject } from "@llamaindex/core/global";
-import { mapMessageContentToMessageContentDetails } from "../../utils";
 import type { AmazonMessage, AmazonMessages } from "./types";

 const ACCEPTED_IMAGE_MIME_TYPES = [
@@ -6,8 +6,10 @@ import type {
  MessageContentDetail,
  ToolCallLLMMessageOptions,
 } from "@llamaindex/core/llms";
-import { mapMessageContentToMessageContentDetails } from "../../utils";
-import { extractDataUrlComponents } from "../utils";
+import {
+  extractDataUrlComponents,
+  mapMessageContentToMessageContentDetails,
+} from "../utils";
 import type {
  AnthropicContent,
  AnthropicImageContent,
@@ -111,7 +113,7 @@ export const mapChatMessagesToAnthropicMessages = <
              {
                type: "tool_result",
                tool_use_id: msg.options.toolResult.id,
-                content: JSON.stringify(msg.options.toolResult.result),
+                content: msg.options.toolResult.result,
              },
            ],
          },
@@ -22,9 +22,9 @@ import {
  type BedrockChatStreamResponse,
  Provider,
 } from "./provider";
+import { mapMessageContentToMessageContentDetails } from "./utils";

 import { wrapLLMEvent } from "@llamaindex/core/decorator";
-import { mapMessageContentToMessageContentDetails } from "../utils";
 import { AmazonProvider } from "./amazon/provider";
 import { AnthropicProvider } from "./anthropic/provider";
 import { MetaProvider } from "./meta/provider";
@@ -1,3 +1,14 @@
+import type {
+  MessageContent,
+  MessageContentDetail,
+} from "@llamaindex/core/llms";
+
+export const mapMessageContentToMessageContentDetails = (
+  content: MessageContent,
+): MessageContentDetail[] => {
+  return Array.isArray(content) ? content : [{ type: "text", text: content }];
+};
+
 export const toUtf8 = (input: Uint8Array): string =>
  new TextDecoder("utf-8").decode(input);

@@ -1,10 +0,0 @@
-import type {
-  MessageContent,
-  MessageContentDetail,
-} from "@llamaindex/core/llms";
-
-export const mapMessageContentToMessageContentDetails = (
-  content: MessageContent,
-): MessageContentDetail[] => {
-  return Array.isArray(content) ? content : [{ type: "text", text: content }];
-};
@@ -1,31 +1,5 @@
 # @llamaindex/core

-## 0.6.2
-
-### Patch Changes
-
- 9c63f3f: Add support for openai responses api
-
-## 0.6.1
-
-### Patch Changes
-
- 1b6f368: Support loading from URLs for all readers extending FileReader
- eaf326e: Fix passing right llm setting from SimpleChatEngine to ChatMemoryBuffer
-
-## 0.6.0
-
-### Minor Changes
-
- 91a18e7: Added support for structured output in the chat api of openai and ollama
-  Added structured output parameter in the provider
-
-### Patch Changes
-
- 21bebfc: Expose more content to fix the issue with unavailable documentation links, and adjust the documentation based on the latest code.
- 93bc0ff: fix: include additional options for context chat engine
- 5189b44: fix: add retry handling logic to parser reader and fix lint issues
-
 ## 0.5.8

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/core",
  "type": "module",
-  "version": "0.6.2",
+  "version": "0.5.8",
  "description": "LlamaIndex Core Module",
  "exports": {
    "./agent": {
@@ -102,7 +102,6 @@ export class ContextChatEngine extends PromptMixin implements BaseChatEngine {
      const stream = await this.chatModel.chat({
        messages: requestMessages.messages,
        stream: true,
-        additionalChatOptions: params.chatOptions as object,
      });
      return streamConverter(
        streamReducer({
@@ -118,7 +117,6 @@ export class ContextChatEngine extends PromptMixin implements BaseChatEngine {
    }
    const response = await this.chatModel.chat({
      messages: requestMessages.messages,
-      additionalChatOptions: params.chatOptions as object,
    });
    chatHistory.put(response.message);
    return EngineResponse.fromChatResponse(response, requestMessages.nodes);
@@ -24,12 +24,8 @@ export class SimpleChatEngine implements BaseChatEngine {
  }

  constructor(init?: Partial<SimpleChatEngine>) {
+    this.memory = init?.memory ?? new ChatMemoryBuffer();
    this.llm = init?.llm ?? Settings.llm;
-    this.memory =
-      init?.memory ??
-      new ChatMemoryBuffer({
-        llm: this.llm,
-      });
  }

  chat(params: NonStreamingChatEngineParams): Promise<EngineResponse>;
@@ -44,7 +40,6 @@ export class SimpleChatEngine implements BaseChatEngine {

    const chatHistory = params.chatHistory
      ? new ChatMemoryBuffer({
-          llm: this.llm,
          chatHistory:
            params.chatHistory instanceof BaseMemory
              ? await params.chatHistory.getMessages()
@@ -2,6 +2,7 @@ import type { Tokenizers } from "@llamaindex/env/tokenizers";
 import type { JSONSchemaType } from "ajv";
 import { z } from "zod";
 import type { JSONObject, JSONValue } from "../global";
+
 /**
 * @internal
 */
@@ -54,12 +55,7 @@ export interface LLM<
  ): Promise<CompletionResponse>;
 }

-export type MessageType =
-  | "user"
-  | "assistant"
-  | "system"
-  | "memory"
-  | "developer";
+export type MessageType = "user" | "assistant" | "system" | "memory";

 export type TextChatMessage<AdditionalMessageOptions extends object = object> =
  {
@@ -160,7 +156,6 @@ export type MessageContentTextDetail = {
 export type MessageContentImageDetail = {
  type: "image_url";
  image_url: { url: string };
-  detail?: "high" | "low" | "auto";
 };

 export type MessageContentDetail =
@@ -63,29 +63,8 @@ export abstract class FileReader<T extends BaseNode = Document>
  ): Promise<T[]>;

  async loadData(filePath: string): Promise<T[]> {
-    let fileContent: Uint8Array;
-    let filename: string;
-
-    // Check if filePath is a URL
-    if (filePath.startsWith("http://") || filePath.startsWith("https://")) {
-      // Handle URL
-      const response = await fetch(filePath);
-      if (!response.ok) {
-        throw new Error(
-          `Failed to fetch URL: ${filePath}, status: ${response.status}`,
-        );
-      }
-      const buffer = await response.arrayBuffer();
-      fileContent = new Uint8Array(buffer);
-      // Extract filename from URL
-      const url = new URL(filePath);
-      filename = path.basename(url.pathname) || "url_document";
-    } else {
-      // Handle local file
-      fileContent = await fs.readFile(filePath);
-      filename = path.basename(filePath);
-    }
-
+    const fileContent = await fs.readFile(filePath);
+    const filename = path.basename(filePath);
    const docs = await this.loadDataAsContent(fileContent, filename);
    docs.forEach(FileReader.addMetaData(filePath));
    return docs;
@@ -1,91 +0,0 @@
-/* eslint-disable @typescript-eslint/no-explicit-any */
-import { Document, FileReader } from "@llamaindex/core/schema";
-import { fs, path } from "@llamaindex/env";
-import { TextDecoder, TextEncoder } from "util";
-import { afterEach, beforeEach, describe, expect, test, vi } from "vitest";
-
-// Mock implementation of FileReader for testing
-class TestFileReader extends FileReader<Document> {
-  async loadDataAsContent(
-    fileContent: Uint8Array,
-    filename?: string,
-  ): Promise<Document[]> {
-    const text = new TextDecoder().decode(fileContent);
-    return [new Document({ text, metadata: { filename } })];
-  }
-}
-
-describe("FileReader", () => {
-  let reader: TestFileReader;
-  let mockFetch: any;
-  let mockFsReadFile: any;
-
-  beforeEach(() => {
-    reader = new TestFileReader();
-
-    // Mock fetch for URL tests
-    mockFetch = vi.fn();
-    global.fetch = mockFetch;
-
-    // Mock fs.readFile for local file tests
-    mockFsReadFile = vi.spyOn(fs, "readFile");
-  });
-
-  afterEach(() => {
-    vi.restoreAllMocks();
-  });
-
-  test("loadData should load content from a local file", async () => {
-    const testFilePath = "/path/to/test.txt";
-    const testContent = "Test file content";
-    const testContentBuffer = new TextEncoder().encode(testContent);
-
-    mockFsReadFile.mockResolvedValue(testContentBuffer);
-
-    const result = await reader.loadData(testFilePath);
-
-    expect(mockFsReadFile).toHaveBeenCalledWith(testFilePath);
-    expect(result).toHaveLength(1);
-    expect(result[0]).toBeInstanceOf(Document);
-    expect(result[0]?.getText()).toBe(testContent);
-    expect(result[0]?.metadata.file_path).toBe(path.resolve(testFilePath));
-    expect(result[0]?.metadata.file_name).toBe("test.txt");
-  });
-
-  test("loadData should load content from a URL", async () => {
-    const testUrl = "https://example.com/test.txt";
-    const testContent = "Test URL content";
-    const testContentBuffer = new TextEncoder().encode(testContent);
-
-    // Mock fetch response
-    mockFetch.mockResolvedValue({
-      ok: true,
-      arrayBuffer: () => Promise.resolve(testContentBuffer.buffer),
-    });
-
-    const result = await reader.loadData(testUrl);
-
-    expect(mockFetch).toHaveBeenCalledWith(testUrl);
-    expect(result).toHaveLength(1);
-    expect(result[0]).toBeInstanceOf(Document);
-    expect(result[0]?.getText()).toBe(testContent);
-    expect(result[0]?.metadata.file_path).toBe(path.resolve(testUrl));
-    expect(result[0]?.metadata.file_name).toBe("test.txt");
-  });
-
-  test("loadData should throw an error for failed URL fetch", async () => {
-    const testUrl = "https://example.com/not-found.txt";
-
-    // Mock failed fetch response
-    mockFetch.mockResolvedValue({
-      ok: false,
-      status: 404,
-    });
-
-    await expect(reader.loadData(testUrl)).rejects.toThrow(
-      `Failed to fetch URL: ${testUrl}, status: 404`,
-    );
-
-    expect(mockFetch).toHaveBeenCalledWith(testUrl);
-  });
-});
@@ -1,14 +0,0 @@
-import { SimpleChatEngine } from "@llamaindex/core/chat-engine";
-import { ChatMemoryBuffer } from "@llamaindex/core/memory";
-import { MockLLM } from "@llamaindex/core/utils";
-import { describe, expect, test } from "vitest";
-
-describe("SimpleChatEngine", () => {
-  test("constructor initializes with provided LLM", () => {
-    const llm = new MockLLM();
-    const engine = new SimpleChatEngine({ llm });
-    expect(engine.llm).toBe(llm);
-    expect(engine.memory).toBeInstanceOf(ChatMemoryBuffer);
-    expect((engine.memory as ChatMemoryBuffer).tokenLimit).toBe(768);
-  });
-});
@@ -1,31 +1,5 @@
 # @llamaindex/experimental

-## 0.0.165
-
-### Patch Changes
-
- llamaindex@0.9.15
-
-## 0.0.164
-
-### Patch Changes
-
- Updated dependencies [9d951b2]
-  - llamaindex@0.9.14
-
-## 0.0.163
-
-### Patch Changes
-
- Updated dependencies [75d6e29]
-  - llamaindex@0.9.13
-
-## 0.0.162
-
-### Patch Changes
-
- llamaindex@0.9.12
-
 ## 0.0.161

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/experimental",
  "description": "Experimental package for LlamaIndexTS",
-  "version": "0.0.165",
+  "version": "0.0.161",
  "type": "module",
  "types": "dist/type/index.d.ts",
  "main": "dist/cjs/index.js",
@@ -1,53 +1,5 @@
 # llamaindex

-## 0.9.15
-
-### Patch Changes
-
- Updated dependencies [9c63f3f]
- Updated dependencies [c515a32]
-  - @llamaindex/openai@0.3.0
-  - @llamaindex/core@0.6.2
-  - @llamaindex/workflow@1.0.2
-  - @llamaindex/cloud@4.0.2
-  - @llamaindex/node-parser@2.0.2
-
-## 0.9.14
-
-### Patch Changes
-
- 9d951b2: feat: support llamacloud in @llamaindex/server
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
-  - @llamaindex/core@0.6.1
-  - @llamaindex/cloud@4.0.1
-  - @llamaindex/node-parser@2.0.1
-  - @llamaindex/openai@0.2.1
-  - @llamaindex/workflow@1.0.1
-
-## 0.9.13
-
-### Patch Changes
-
- 75d6e29: feat: response source nodes in query tool output
-
-## 0.9.12
-
-### Patch Changes
-
- Updated dependencies [21bebfc]
- Updated dependencies [93bc0ff]
- Updated dependencies [91a18e7]
- Updated dependencies [bf56fc0]
- Updated dependencies [f8a86e4]
- Updated dependencies [5189b44]
- Updated dependencies [58a9446]
-  - @llamaindex/core@0.6.0
-  - @llamaindex/openai@0.2.0
-  - @llamaindex/cloud@4.0.0
-  - @llamaindex/workflow@1.0.0
-  - @llamaindex/node-parser@2.0.0
-
 ## 0.9.11

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "llamaindex",
-  "version": "0.9.15",
+  "version": "0.9.11",
  "license": "MIT",
  "type": "module",
  "keywords": [
@@ -25,9 +25,7 @@ import {
 } from "@llamaindex/cloud/api";
 import type { BaseRetriever } from "@llamaindex/core/retriever";
 import { getEnv } from "@llamaindex/env";
-import type { QueryToolParams } from "../indices/BaseIndex.js";
 import { Settings } from "../Settings.js";
-import { QueryEngineTool } from "../tools/QueryEngineTool.js";

 export class LlamaCloudIndex {
  params: CloudConstructorParams;
@@ -274,22 +272,6 @@ export class LlamaCloudIndex {
    );
  }

-  asQueryTool(params: QueryToolParams): QueryEngineTool {
-    if (params.options) {
-      params.retriever = this.asRetriever(params.options);
-    }
-
-    return new QueryEngineTool({
-      queryEngine: this.asQueryEngine(params),
-      metadata: params?.metadata,
-      includeSourceNodes: params?.includeSourceNodes ?? false,
-    });
-  }
-
-  queryTool(params: QueryToolParams): QueryEngineTool {
-    return this.asQueryTool(params);
-  }
-
  async insert(document: Document) {
    const pipelineId = await this.getPipelineId();

@@ -41,7 +41,6 @@ export type QueryToolParams = (
 ) & {
  responseSynthesizer?: BaseSynthesizer;
  metadata?: ToolMetadata<JSONSchemaType<QueryEngineParam>> | undefined;
-  includeSourceNodes?: boolean;
 };

 /**
@@ -99,7 +98,6 @@ export abstract class BaseIndex<T> {
    return new QueryEngineTool({
      queryEngine: this.asQueryEngine(params),
      metadata: params?.metadata,
-      includeSourceNodes: params?.includeSourceNodes ?? false,
    });
  }

@@ -1,4 +1,3 @@
-import type { JSONValue } from "@llamaindex/core/global";
 import type { BaseTool, ToolMetadata } from "@llamaindex/core/llms";
 import type { BaseQueryEngine } from "@llamaindex/core/query-engine";
 import type { JSONSchemaType } from "ajv";
@@ -21,7 +20,6 @@ const DEFAULT_PARAMETERS: JSONSchemaType<QueryEngineParam> = {
 export type QueryEngineToolParams = {
  queryEngine: BaseQueryEngine;
  metadata?: ToolMetadata<JSONSchemaType<QueryEngineParam>> | undefined;
-  includeSourceNodes?: boolean;
 };

 export type QueryEngineParam = {
@@ -31,32 +29,19 @@ export type QueryEngineParam = {
 export class QueryEngineTool implements BaseTool<QueryEngineParam> {
  private queryEngine: BaseQueryEngine;
  metadata: ToolMetadata<JSONSchemaType<QueryEngineParam>>;
-  includeSourceNodes: boolean;

-  constructor({
-    queryEngine,
-    metadata,
-    includeSourceNodes,
-  }: QueryEngineToolParams) {
+  constructor({ queryEngine, metadata }: QueryEngineToolParams) {
    this.queryEngine = queryEngine;
    this.metadata = {
      name: metadata?.name ?? DEFAULT_NAME,
      description: metadata?.description ?? DEFAULT_DESCRIPTION,
      parameters: metadata?.parameters ?? DEFAULT_PARAMETERS,
    };
-    this.includeSourceNodes = includeSourceNodes ?? false;
  }

  async call({ query }: QueryEngineParam) {
    const response = await this.queryEngine.query({ query });

-    if (!this.includeSourceNodes) {
-      return { content: response.message.content };
-    }
-
-    return {
-      content: response.message.content,
-      sourceNodes: response.sourceNodes,
-    } as unknown as JSONValue;
+    return response.message.content;
  }
 }
@@ -1,30 +1,5 @@
 # @llamaindex/node-parser

-## 2.0.2
-
-### Patch Changes
-
- Updated dependencies [9c63f3f]
-  - @llamaindex/core@0.6.2
-
-## 2.0.1
-
-### Patch Changes
-
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
-  - @llamaindex/core@0.6.1
-
-## 2.0.0
-
-### Patch Changes
-
- Updated dependencies [21bebfc]
- Updated dependencies [93bc0ff]
- Updated dependencies [91a18e7]
- Updated dependencies [5189b44]
-  - @llamaindex/core@0.6.0
-
 ## 1.0.8

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/node-parser",
-  "version": "2.0.2",
+  "version": "1.0.8",
  "description": "Node parser for LlamaIndex",
  "type": "module",
  "exports": {
@@ -1,35 +1,5 @@
 # @llamaindex/anthropic

-## 0.3.2
-
-### Patch Changes
-
- Updated dependencies [9c63f3f]
-  - @llamaindex/core@0.6.2
-
-## 0.3.1
-
-### Patch Changes
-
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
-  - @llamaindex/core@0.6.1
-
-## 0.3.0
-
-### Minor Changes
-
- 91a18e7: Added support for structured output in the chat api of openai and ollama
-  Added structured output parameter in the provider
-
-### Patch Changes
-
- Updated dependencies [21bebfc]
- Updated dependencies [93bc0ff]
- Updated dependencies [91a18e7]
- Updated dependencies [5189b44]
-  - @llamaindex/core@0.6.0
-
 ## 0.2.6

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/anthropic",
  "description": "Anthropic Adapter for LlamaIndex",
-  "version": "0.3.2",
+  "version": "0.2.6",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,33 +1,5 @@
 # @llamaindex/clip

-## 0.0.48
-
-### Patch Changes
-
- Updated dependencies [9c63f3f]
-  - @llamaindex/openai@0.3.0
-  - @llamaindex/core@0.6.2
-
-## 0.0.47
-
-### Patch Changes
-
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
-  - @llamaindex/core@0.6.1
-  - @llamaindex/openai@0.2.1
-
-## 0.0.46
-
-### Patch Changes
-
- Updated dependencies [21bebfc]
- Updated dependencies [93bc0ff]
- Updated dependencies [91a18e7]
- Updated dependencies [5189b44]
-  - @llamaindex/core@0.6.0
-  - @llamaindex/openai@0.2.0
-
 ## 0.0.45

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/clip",
  "description": "Clip Embedding Adapter for LlamaIndex",
-  "version": "0.0.48",
+  "version": "0.0.45",
  "type": "module",
  "types": "dist/index.d.ts",
  "main": "dist/index.cjs",
@@ -1,30 +1,5 @@
 # @llamaindex/cohere

-## 0.0.16
-
-### Patch Changes
-
- Updated dependencies [9c63f3f]
-  - @llamaindex/core@0.6.2
-
-## 0.0.15
-
-### Patch Changes
-
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
-  - @llamaindex/core@0.6.1
-
-## 0.0.14
-
-### Patch Changes
-
- Updated dependencies [21bebfc]
- Updated dependencies [93bc0ff]
- Updated dependencies [91a18e7]
- Updated dependencies [5189b44]
-  - @llamaindex/core@0.6.0
-
 ## 0.0.13

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/cohere",
  "description": "Cohere Adapter for LlamaIndex",
-  "version": "0.0.16",
+  "version": "0.0.13",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,33 +1,5 @@
 # @llamaindex/deepinfra

-## 0.0.48
-
-### Patch Changes
-
- Updated dependencies [9c63f3f]
-  - @llamaindex/openai@0.3.0
-  - @llamaindex/core@0.6.2
-
-## 0.0.47
-
-### Patch Changes
-
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
-  - @llamaindex/core@0.6.1
-  - @llamaindex/openai@0.2.1
-
-## 0.0.46
-
-### Patch Changes
-
- Updated dependencies [21bebfc]
- Updated dependencies [93bc0ff]
- Updated dependencies [91a18e7]
- Updated dependencies [5189b44]
-  - @llamaindex/core@0.6.0
-  - @llamaindex/openai@0.2.0
-
 ## 0.0.45

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/deepinfra",
  "description": "Deepinfra Adapter for LlamaIndex",
-  "version": "0.0.48",
+  "version": "0.0.45",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,25 +1,5 @@
 # @llamaindex/deepseek

-## 0.0.8
-
-### Patch Changes
-
- Updated dependencies [9c63f3f]
-  - @llamaindex/openai@0.3.0
-
-## 0.0.7
-
-### Patch Changes
-
- @llamaindex/openai@0.2.1
-
-## 0.0.6
-
-### Patch Changes
-
- Updated dependencies [91a18e7]
-  - @llamaindex/openai@0.2.0
-
 ## 0.0.5

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/deepseek",
  "description": "DeepSeek Adapter for LlamaIndex",
-  "version": "0.0.8",
+  "version": "0.0.5",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,25 +1,5 @@
 # @llamaindex/fireworks

-## 0.0.8
-
-### Patch Changes
-
- Updated dependencies [9c63f3f]
-  - @llamaindex/openai@0.3.0
-
-## 0.0.7
-
-### Patch Changes
-
- @llamaindex/openai@0.2.1
-
-## 0.0.6
-
-### Patch Changes
-
- Updated dependencies [91a18e7]
-  - @llamaindex/openai@0.2.0
-
 ## 0.0.5

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/fireworks",
  "description": "Fireworks Adapter for LlamaIndex",
-  "version": "0.0.8",
+  "version": "0.0.5",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,39 +1,5 @@
 # @llamaindex/google

-## 0.2.2
-
-### Patch Changes
-
- 9c63f3f: Add support for openai responses api
- Updated dependencies [9c63f3f]
-  - @llamaindex/core@0.6.2
-
-## 0.2.1
-
-### Patch Changes
-
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
-  - @llamaindex/core@0.6.1
-
-## 0.2.0
-
-### Minor Changes
-
- 91a18e7: Added support for structured output in the chat api of openai and ollama
-  Added structured output parameter in the provider
-
-### Patch Changes
-
- da06e45: fix: don't ignore parts that only have inline data for google studio
- 2a0a899: Added saftey setting parameter for gemini
- 3fd4cc3: feat: use google's new gen ai library to support multimodal output
- Updated dependencies [21bebfc]
- Updated dependencies [93bc0ff]
- Updated dependencies [91a18e7]
- Updated dependencies [5189b44]
-  - @llamaindex/core@0.6.0
-
 ## 0.1.2

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/google",
  "description": "Google Adapter for LlamaIndex",
-  "version": "0.2.2",
+  "version": "0.1.2",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -34,7 +34,6 @@
  },
  "dependencies": {
    "@google-cloud/vertexai": "1.9.0",
-    "@google/genai": "^0.4.0",
    "@google/generative-ai": "0.21.0",
    "@llamaindex/core": "workspace:*",
    "@llamaindex/env": "workspace:*"
@@ -63,7 +63,7 @@ export const GEMINI_MODEL_INFO_MAP: Record<GEMINI_MODEL, GeminiModelInfo> = {
  [GEMINI_MODEL.GEMINI_2_0_PRO_EXPERIMENTAL]: { contextWindow: 2 * 10 ** 6 },
 };

-export const SUPPORT_TOOL_CALL_MODELS: GEMINI_MODEL[] = [
+const SUPPORT_TOOL_CALL_MODELS: GEMINI_MODEL[] = [
  GEMINI_MODEL.GEMINI_PRO,
  GEMINI_MODEL.GEMINI_PRO_VISION,
  GEMINI_MODEL.GEMINI_PRO_1_5_PRO_PREVIEW,
@@ -79,7 +79,7 @@ export const SUPPORT_TOOL_CALL_MODELS: GEMINI_MODEL[] = [
  GEMINI_MODEL.GEMINI_2_0_PRO_EXPERIMENTAL,
 ];

-export const DEFAULT_GEMINI_PARAMS = {
+const DEFAULT_GEMINI_PARAMS = {
  model: GEMINI_MODEL.GEMINI_PRO,
  temperature: 0.1,
  topP: 1,
@@ -3,10 +3,4 @@ export * from "./types";
 export * from "./utils";
 export * from "./vertex";

-export {
-  GoogleStudio,
-  Modality,
-  getGoogleStudioInlineData,
-} from "./studio/index.js";
-
 export * from "./GeminiEmbedding";
@@ -1,262 +0,0 @@
-import {
-  GenerateContentResponse,
-  GoogleGenAI,
-  Modality,
-  type Blob,
-  type GenerateContentConfig,
-  type GoogleGenAIOptions,
-} from "@google/genai";
-import {
-  ToolCallLLM,
-  type ChatResponse,
-  type ChatResponseChunk,
-  type CompletionResponse,
-  type LLMChatParamsNonStreaming,
-  type LLMChatParamsStreaming,
-  type LLMCompletionParamsNonStreaming,
-  type LLMCompletionParamsStreaming,
-  type LLMMetadata,
-  type ToolCall,
-  type ToolCallLLMMessageOptions,
-} from "@llamaindex/core/llms";
-export { Modality };
-
-import { streamConverter } from "@llamaindex/core/utils";
-
-import { wrapLLMEvent } from "@llamaindex/core/decorator";
-import type { JSONObject } from "@llamaindex/core/global";
-import { DEFAULT_GEMINI_PARAMS, SUPPORT_TOOL_CALL_MODELS } from "../base";
-import type { GEMINI_MODEL } from "../types";
-import {
-  mapChatMessagesToGoogleFunctions,
-  mapChatMessagesToGoogleMessages,
-  mapMessageContentDetailToGooglePart,
-  mapMessageContentToMessageContentDetails,
-} from "./utils";
-
-export type GoogleAdditionalChatOptions = { config: GenerateContentConfig };
-
-export type GoogleChatStreamResponse = AsyncIterable<
-  ChatResponseChunk<
-    ToolCallLLMMessageOptions & {
-      data?: Blob[];
-    }
-  >
->;
-
-export type GoogleChatParamsStreaming = LLMChatParamsStreaming<
-  GoogleAdditionalChatOptions,
-  ToolCallLLMMessageOptions
->;
-
-export type GoogleChatParamsNonStreaming = LLMChatParamsNonStreaming<
-  GoogleAdditionalChatOptions,
-  ToolCallLLMMessageOptions
->;
-
-export type GoogleChatNonStreamResponse =
-  ChatResponse<ToolCallLLMMessageOptions>;
-
-export const getGoogleStudioInlineData = (
-  response: GenerateContentResponse,
-): Blob[] => {
-  return response.candidates
-    ?.flatMap((candidate) => candidate.content?.parts)
-    .map((part) => part?.inlineData)
-    .filter((data) => data) as Blob[];
-};
-
-export type GoogleModelParams = {
-  model: GEMINI_MODEL;
-  temperature?: number;
-  topP?: number;
-  maxTokens?: number;
-};
-
-export type GoogleParams = GoogleGenAIOptions & GoogleModelParams;
-
-export class GoogleStudio extends ToolCallLLM<GoogleAdditionalChatOptions> {
-  client: GoogleGenAI;
-  model: GEMINI_MODEL;
-  temperature: number;
-  topP: number;
-  maxTokens?: number | undefined;
-  topK?: number;
-
-  constructor({
-    temperature,
-    topP,
-    maxTokens,
-    model,
-    ...params
-  }: GoogleParams) {
-    super();
-    this.model = model;
-    this.maxTokens = maxTokens ?? DEFAULT_GEMINI_PARAMS.maxTokens;
-    this.temperature = temperature ?? DEFAULT_GEMINI_PARAMS.temperature;
-    this.topP = topP ?? DEFAULT_GEMINI_PARAMS.topP;
-    this.client = new GoogleGenAI(params);
-  }
-
-  get supportToolCall(): boolean {
-    return SUPPORT_TOOL_CALL_MODELS.includes(this.model);
-  }
-
-  get metadata(): LLMMetadata {
-    return {
-      model: this.model,
-      temperature: this.temperature,
-      topP: this.topP,
-      maxTokens: this.maxTokens,
-      contextWindow: 128000,
-      tokenizer: undefined,
-      structuredOutput: false,
-    };
-  }
-
-  getToolCallsFromResponse(response: GenerateContentResponse): ToolCall[] {
-    if (!response.functionCalls) return [];
-    return response.functionCalls.map((call) => ({
-      id: call.id ?? "",
-      name: call.name ?? "",
-      input: call.args as JSONObject,
-    }));
-  }
-
-  protected async nonStreamChat(
-    params: GoogleChatParamsNonStreaming,
-  ): Promise<GoogleChatNonStreamResponse> {
-    if (!this.supportToolCall && params.tools?.length) {
-      console.warn(`The model "${this.model}" doesn't support ToolCall`);
-    }
-
-    const config: GenerateContentConfig =
-      params.additionalChatOptions?.config ?? {};
-    if (params.tools?.length) {
-      if (config.responseModalities?.includes(Modality.IMAGE)) {
-        console.warn("Tools are currently not supported with Modality.IMAGE");
-      } else {
-        config.tools = mapChatMessagesToGoogleFunctions(params.tools);
-      }
-    }
-    const response = await this.client.models.generateContent({
-      model: this.model,
-      contents: mapChatMessagesToGoogleMessages(params.messages),
-      config,
-    });
-
-    if (this.supportToolCall) {
-      const tools = this.getToolCallsFromResponse(response);
-      if (tools.length) {
-        return {
-          raw: response,
-          message: {
-            role: "assistant",
-            content: "",
-            options: { toolCall: tools },
-          },
-        };
-      }
-    }
-    return {
-      raw: response,
-      message: {
-        role: "assistant",
-        content: response.text ?? "",
-        options: {
-          inlineData: getGoogleStudioInlineData(response),
-        },
-      },
-    };
-  }
-
-  protected async *streamChat(
-    params: GoogleChatParamsStreaming,
-  ): GoogleChatStreamResponse {
-    if (!this.supportToolCall && params.tools?.length) {
-      console.warn(`The model "${this.model}" doesn't support ToolCall`);
-    }
-    const config: GenerateContentConfig =
-      params.additionalChatOptions?.config ?? {};
-    if (params.tools?.length) {
-      if (config.responseModalities?.includes(Modality.IMAGE)) {
-        console.warn("Tools are currently not supported with Modality.IMAGE");
-      } else {
-        config.tools = mapChatMessagesToGoogleFunctions(params.tools);
-      }
-    }
-    const response = await this.client.models.generateContentStream({
-      model: this.model,
-      contents: mapChatMessagesToGoogleMessages(params.messages),
-      config,
-    });
-    yield* streamConverter(response, (response) => {
-      if (response.functionCalls?.length) {
-        return {
-          delta: "",
-          raw: response,
-          options: {
-            toolCall: this.getToolCallsFromResponse(response),
-          },
-        };
-      }
-
-      return {
-        delta: response.text ?? "",
-        raw: response,
-        options: {
-          inlineData: getGoogleStudioInlineData(response),
-        },
-      };
-    });
-  }
-
-  chat(params: GoogleChatParamsStreaming): Promise<GoogleChatStreamResponse>;
-  chat(
-    params: GoogleChatParamsNonStreaming,
-  ): Promise<GoogleChatNonStreamResponse>;
-  @wrapLLMEvent
-  async chat(
-    params: GoogleChatParamsStreaming | GoogleChatParamsNonStreaming,
-  ): Promise<GoogleChatStreamResponse | GoogleChatNonStreamResponse> {
-    if (params.stream) {
-      return this.streamChat(params);
-    }
-    return this.nonStreamChat(params);
-  }
-
-  complete(
-    params: LLMCompletionParamsStreaming,
-  ): Promise<AsyncIterable<CompletionResponse>>;
-  complete(
-    params: LLMCompletionParamsNonStreaming,
-  ): Promise<CompletionResponse>;
-  async complete(
-    params: LLMCompletionParamsStreaming | LLMCompletionParamsNonStreaming,
-  ): Promise<CompletionResponse | AsyncIterable<CompletionResponse>> {
-    const contents = mapMessageContentToMessageContentDetails(
-      params.prompt,
-    ).map(mapMessageContentDetailToGooglePart);
-    if (params.stream) {
-      const response = await this.client.models.generateContentStream({
-        model: this.model,
-        contents,
-      });
-      return streamConverter(response, (response) => {
-        return {
-          text: response.text ?? "",
-          raw: response,
-        };
-      });
-    }
-    const response = await this.client.models.generateContent({
-      model: this.model,
-      contents,
-    });
-
-    return {
-      text: response.text || "",
-      raw: response,
-    };
-  }
-}
@@ -1,136 +0,0 @@
-import type {
-  ContentListUnion,
-  ContentUnion,
-  Part,
-  Schema,
-  ToolListUnion,
-} from "@google/genai";
-import type {
-  BaseTool,
-  ChatMessage,
-  MessageContentDetail,
-  ToolCallLLMMessageOptions,
-} from "@llamaindex/core/llms";
-import { extractDataUrlComponents } from "@llamaindex/core/utils";
-
-import type { MessageContent } from "@llamaindex/core/llms";
-
-export const mapMessageContentToMessageContentDetails = (
-  content: MessageContent,
-): MessageContentDetail[] => {
-  return Array.isArray(content) ? content : [{ type: "text", text: content }];
-};
-
-const ACCEPTED_IMAGE_MIME_TYPES = ["image/jpeg", "image/png"];
-
-export const mapTextPart = (text: string): Part => {
-  return { text };
-};
-
-export const mapImagePart = (imageUrl: string): Part => {
-  if (!imageUrl.startsWith("data:"))
-    throw new Error(
-      "For Google please only use base64 data url, e.g.: data:image/jpeg;base64,SGVsbG8sIFdvcmxkIQ==",
-    );
-  const { mimeType, base64: data } = extractDataUrlComponents(imageUrl);
-  if (!ACCEPTED_IMAGE_MIME_TYPES.includes(mimeType))
-    throw new Error(
-      `Anthropic only accepts the following mimeTypes: ${ACCEPTED_IMAGE_MIME_TYPES.join("\n")}`,
-    );
-
-  return {
-    inlineData: {
-      mimeType,
-      data,
-    },
-  };
-};
-
-export const mapMessageContentDetailToGooglePart = <
-  T extends MessageContentDetail,
->(
-  detail: T,
-): Part => {
-  let part: Part;
-
-  if (detail.type === "text") {
-    part = mapTextPart(detail.text);
-  } else if (detail.type === "image_url") {
-    part = mapImagePart(detail.image_url.url);
-  } else {
-    throw new Error("Unsupported content detail type");
-  }
-  return part;
-};
-export const mapChatMessagesToGoogleFunctions = (
-  tools: BaseTool[],
-): ToolListUnion => {
-  return [
-    {
-      functionDeclarations: tools.map((tool) => ({
-        response: tool.metadata.parameters as Schema,
-        description: tool.metadata.description,
-        name: tool.metadata.name,
-      })),
-    },
-  ];
-};
-
-export const mapChatMessagesToGoogleMessages = <
-  T extends ChatMessage<ToolCallLLMMessageOptions>,
->(
-  messages: T[],
-): ContentListUnion => {
-  const functionNames: Record<string, string> = {};
-  messages.forEach((msg: T) => {
-    if (msg.options && "toolCall" in msg.options) {
-      const mapped = msg.options.toolCall.reduce(
-        (result, item) => {
-          result[item.id] = item.name;
-          return result;
-        },
-        {} as Record<string, string>,
-      );
-
-      Object.assign(functionNames, mapped);
-    }
-  });
-  return messages.flatMap((msg: T): ContentListUnion => {
-    if (msg.options && "toolResult" in msg.options) {
-      return {
-        role: "user",
-        parts: [
-          {
-            functionResponse: {
-              name: functionNames[msg.options.toolResult.id] ?? "",
-              response: msg.options.toolResult,
-            },
-          },
-        ],
-      };
-    }
-
-    if (msg.options && "toolCall" in msg.options) {
-      return {
-        role: "model",
-        parts: msg.options.toolCall.map((call) => ({
-          functionCall: {
-            name: call.name,
-            args: call.input as Record<string, unknown>,
-          },
-        })),
-      };
-    }
-    return mapMessageContentToMessageContentDetails(msg.content)
-      .map((detail: MessageContentDetail): ContentUnion | null => {
-        const part = mapMessageContentDetailToGooglePart(detail);
-        if (!part.text && !part.inlineData) return null;
-
-        return {
-          role: msg.role === "assistant" ? "model" : "user",
-          parts: [part],
-        };
-      })
-      .filter((content) => content) as ContentUnion;
-  });
-};
@@ -181,7 +181,7 @@ export const mapBaseToolToGeminiFunctionDeclaration = (
 export class GeminiHelper {
  // Gemini only has user and model roles. Put the rest in user role.
  public static readonly ROLES_TO_GEMINI: Record<
-    Exclude<MessageType, "developer">,
+    MessageType,
    GeminiMessageRole
  > = {
    user: "user",
@@ -285,9 +285,7 @@ export class GeminiHelper {
    if (message.options && "toolResult" in message.options) {
      return "function";
    }
-    return GeminiHelper.ROLES_TO_GEMINI[
-      message.role as Exclude<MessageType, "developer">
-    ];
+    return GeminiHelper.ROLES_TO_GEMINI[message.role];
  }

  public static chatMessageToGemini(
@@ -1,25 +1,5 @@
 # @llamaindex/groq

-## 0.0.63
-
-### Patch Changes
-
- Updated dependencies [9c63f3f]
-  - @llamaindex/openai@0.3.0
-
-## 0.0.62
-
-### Patch Changes
-
- @llamaindex/openai@0.2.1
-
-## 0.0.61
-
-### Patch Changes
-
- Updated dependencies [91a18e7]
-  - @llamaindex/openai@0.2.0
-
 ## 0.0.60

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/groq",
  "description": "Groq Adapter for LlamaIndex",
-  "version": "0.0.63",
+  "version": "0.0.60",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
--- a/Show More
+++ b/Show More