Release 0.9.9 (#1713)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>

apps/next/CHANGELOG.md

@@ -1,5 +1,54 @@
 # @llamaindex/doc
 
+## 0.1.9
+
+### Patch Changes
+
+- 4bac71d: Support binding additional argument to function tool
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+  - @llamaindex/cloud@3.0.8
+  - llamaindex@0.9.9
+  - @llamaindex/node-parser@1.0.7
+  - @llamaindex/openai@0.1.59
+  - @llamaindex/readers@2.0.7
+  - @llamaindex/workflow@0.0.15
+
+## 0.1.8
+
+### Patch Changes
+
+- Updated dependencies [4b49428]
+- Updated dependencies [bbc8c87]
+  - @llamaindex/workflow@0.0.14
+  - llamaindex@0.9.8
+
+## 0.1.7
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/core@0.5.6
+  - llamaindex@0.9.7
+  - @llamaindex/cloud@3.0.7
+  - @llamaindex/node-parser@1.0.6
+  - @llamaindex/openai@0.1.58
+  - @llamaindex/readers@2.0.6
+  - @llamaindex/workflow@0.0.13
+
+## 0.1.6
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+  - @llamaindex/workflow@0.0.12
+  - @llamaindex/cloud@3.0.6
+  - llamaindex@0.9.6
+  - @llamaindex/node-parser@1.0.5
+  - @llamaindex/openai@0.1.57
+  - @llamaindex/readers@2.0.5
+
 ## 0.1.5
 
 ### Patch Changes

apps/next/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/doc",
-  "version": "0.1.5",
+  "version": "0.1.9",
   "private": true,
   "scripts": {
     "build": "pnpm run build:docs && next build",

apps/next/src/content/docs/llamaindex/getting_started/setup/node.mdx

@@ -3,6 +3,8 @@ title: With Node.js/Bun/Deno
 description: In this guide, you'll learn how to use LlamaIndex with Node.js, Bun, and Deno.
 ---
 
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
 ## Adding environment variables
 
 By default, LlamaIndex uses OpenAI provider, which requires an API key. You can set the `OPENAI_API_KEY` environment variable to authenticate with OpenAI.
@@ -22,6 +24,26 @@ node --env-file .env your-script.js
 
 For more information, see the [How to read environment variables from Node.js](https://nodejs.org/en/learn/command-line/how-to-read-environment-variables-from-nodejs).
 
+## Performance Optimization
+
+By the default, we are using `js-tiktoken` for tokenization. You can install `gpt-tokenizer` which is then automatically used by LlamaIndex to get a 60x speedup for tokenization:
+
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install gpt-tokenizer
+	```
+
+	```shell tab="yarn"
+	yarn add gpt-tokenizer
+	```
+
+	```shell tab="pnpm"
+	pnpm add gpt-tokenizer
+	```
+</Tabs>
+
+> Note: This only works for Node.js
+
 ## TypeScript support
 
 <Card

apps/next/src/content/docs/llamaindex/modules/agent_workflow.mdx

@@ -0,0 +1,139 @@
+---
+title: Agent Workflow
+---
+
+import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
+import CodeSource from "!raw-loader!../../../../../../../examples/agentworkflow/blog_writer.ts";
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
+`AgentWorkflow` is a powerful system that enables you to create and orchestrate one or multiple agents with tools to perform specific tasks. It's built on top of the base `Workflow` system and provides a streamlined interface for agent interactions.
+
+## Installation
+
+You'll need to install the `@llamaindex/workflow` package:
+
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install @llamaindex/workflow
+	```
+
+	```shell tab="yarn"
+	yarn add @llamaindex/workflow
+	```
+
+	```shell tab="pnpm"
+	pnpm add @llamaindex/workflow
+	```
+</Tabs>
+
+## Usage
+
+### Single Agent Workflow
+
+The simplest use case is creating a single agent with specific tools. Here's an example of creating an assistant that tells jokes:
+
+```typescript
+import { AgentWorkflow, FunctionTool } from "llamaindex";
+import { OpenAI } from "@llamaindex/openai";
+
+// Define a joke-telling tool
+const jokeTool = FunctionTool.from(
+  () => "Baby Llama is called cria",
+  {
+    name: "joke",
+    description: "Use this tool to get a joke",
+  }
+);
+
+// Create an agent workflow with the tool
+const workflow = AgentWorkflow.fromTools({
+  tools: [jokeTool],
+  llm: new OpenAI({
+    model: "gpt-4o-mini",
+  }),
+});
+
+// Run the workflow
+const result = await workflow.run("Tell me something funny");
+console.log(result); // Baby Llama is called cria
+```
+
+### Event Streaming
+
+`AgentWorkflow` provides a unified interface for event streaming, making it easy to track and respond to different events during execution:
+
+```typescript
+import { AgentToolCall, AgentStream } from "llamaindex";
+
+// Get the workflow execution context
+const context = workflow.run("Tell me something funny");
+
+// Stream and handle events
+for await (const event of context) {
+  if (event instanceof AgentToolCall) {
+    console.log(`Tool being called: ${event.data.toolName}`);
+  }
+  if (event instanceof AgentStream) {
+    process.stdout.write(event.data.delta);
+  }
+}
+```
+
+### Multi-Agent Workflow
+
+`AgentWorkflow` can orchestrate multiple agents, enabling complex interactions and task handoffs. Each agent in a multi-agent workflow requires:
+
+- `name`: Unique identifier for the agent
+- `description`: Purpose description used for task routing
+- `tools`: Array of tools the agent can use
+- `canHandoffTo` (optional): Array of agent names or agent instances that this agent can delegate tasks to
+
+Here's an example of a multi-agent system that combines joke-telling and weather information:
+
+```typescript
+import { AgentWorkflow, FunctionAgent, FunctionTool } from "llamaindex";
+import { OpenAI } from "@llamaindex/openai";
+import { z } from "zod";
+
+// Create a weather agent
+const weatherAgent = new FunctionAgent({
+  name: "WeatherAgent",
+  description: "Provides weather information for any city",
+  tools: [
+    FunctionTool.from(
+      ({ city }: { city: string }) => `The weather in ${city} is sunny`,
+      {
+        name: "fetchWeather",
+        description: "Get weather information for a city",
+        parameters: z.object({
+          city: z.string(),
+        }),
+      }
+    ),
+  ],
+  llm: new OpenAI({ model: "gpt-4o-mini" }),
+});
+
+// Create a joke-telling agent
+const jokeAgent = new FunctionAgent({
+  name: "JokeAgent",
+  description: "Tells jokes and funny stories",
+  tools: [jokeTool], // Using the joke tool defined earlier
+  llm: new OpenAI({ model: "gpt-4o-mini" }),
+  canHandoffTo: [weatherAgent], // Can hand off to the weather agent
+});
+
+// Create the multi-agent workflow
+const workflow = new AgentWorkflow({
+  agents: [jokeAgent, weatherAgent],
+  rootAgent: jokeAgent, // Start with the joke agent
+});
+
+// Run the workflow
+const result = await workflow.run(
+  "Give me a morning greeting with a joke and the weather in San Francisco"
+);
+```
+
+The workflow will coordinate between agents, allowing them to handle different aspects of the request and hand off tasks when appropriate.
+

apps/next/src/content/docs/llamaindex/modules/embeddings/available_embeddings/jinaai.mdx

@@ -2,10 +2,11 @@
 title: Jina AI
 ---
 
-To use Jina AI embeddings, you need to import `JinaAIEmbedding` from `llamaindex`.
+To use Jina AI embeddings, you need to import `JinaAIEmbedding` from `@llamaindex/jinaai`.
 
 ```ts
-import { JinaAIEmbedding, Settings } from "llamaindex";
+import { Settings } from "llamaindex";
+import { JinaAIEmbedding } from "@llamaindex/jinaai";
 
 Settings.embedModel = new JinaAIEmbedding();
 

apps/next/src/content/docs/llamaindex/modules/embeddings/available_embeddings/together.mdx

@@ -2,10 +2,11 @@
 title: Together
 ---
 
-To use together embeddings, you need to import `TogetherEmbedding` from `llamaindex`.
+To use together embeddings, you need to import `TogetherEmbedding` from `@llamaindex/together`.
 
 ```ts
-import { TogetherEmbedding, Settings } from "llamaindex";
+import { Settings } from "llamaindex";
+import { TogetherEmbedding } from "@llamaindex/together";
 
 Settings.embedModel = new TogetherEmbedding({
   apiKey: "<YOUR_API_KEY>",

apps/next/src/content/docs/llamaindex/modules/llms/available_llms/deepseek.mdx

@@ -7,7 +7,8 @@ title: DeepSeek LLM
 ## Usage
 
 ```ts
-import { DeepSeekLLM, Settings } from "llamaindex";
+import { Settings } from "llamaindex";
+import { DeepSeekLLM } from "@llamaindex/deepseek";
 
 Settings.llm = new DeepSeekLLM({
   apiKey: "<YOUR_API_KEY>",
@@ -18,7 +19,8 @@ Settings.llm = new DeepSeekLLM({
 ## Example
 
 ```ts
-import { DeepSeekLLM, Document, VectorStoreIndex, Settings } from "llamaindex";
+import { Document, VectorStoreIndex, Settings } from "llamaindex";
+import { DeepSeekLLM } from "@llamaindex/deepseek";
 
 const deepseekLlm = new DeepSeekLLM({
   apiKey: "<YOUR_API_KEY>",

apps/next/src/content/docs/llamaindex/modules/llms/available_llms/fireworks.mdx

@@ -7,7 +7,8 @@ title: Fireworks LLM
 ## Usage
 
 ```ts
-import { FireworksLLM, Settings } from "llamaindex";
+import { Settings } from "llamaindex";
+import { FireworksLLM } from "@llamaindex/fireworks";
 
 Settings.llm = new FireworksLLM({
   apiKey: "<YOUR_API_KEY>",

apps/next/src/content/docs/llamaindex/modules/llms/available_llms/together.mdx

@@ -23,7 +23,8 @@ import { Tab, Tabs } from "fumadocs-ui/components/tabs";
 ## Usage
 
 ```ts
-import { Settings, TogetherLLM } from "llamaindex";
+import { Settings } from "llamaindex";
+import { TogetherLLM } from "@llamaindex/together";
 
 Settings.llm = new TogetherLLM({
   apiKey: "<YOUR_API_KEY>",

apps/next/src/content/docs/llamaindex/modules/tool/index.mdx

@@ -0,0 +1,60 @@
+---
+title: Tools
+---
+
+A "tool" is a utility that can be called by an agent on behalf of an LLM.
+A tool can be called to perform custom actions, or retrieve extra information based on the LLM-generated input.
+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.
+
+## Function tool
+
+Function tools are implemented with the `FunctionTool` class.
+A `FunctionTool` is constructed from a function with signature
+```ts
+(input: T, additionalArg?: AdditionalToolArgument) => R
+```
+where
+- `input` is generated by the LLM, `T` is the type defined by the tool `parameters`
+- `additionalArg` is an optional extra argument, see "Binding" below
+- `R` is the return type
+
+### Binding
+
+An additional argument can be bound to a tool, each tool call will be passed
+- the input provided by the LLM
+- the additional argument (extends object)
+
+Note: calling the `bind` method will return a new `FunctionTool` instance, without modifying the tool which `bind` is called on.
+
+Example to pass a `userToken` as additional argument:
+```ts
+// 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 as usual
+const kbTool = FunctionTool.from(queryKnowledgeBase, {
+  name: 'queryKnowledgeBase',
+  description: 'Query knowledge base',
+  parameters: {
+    type: 'object',
+    properties: {
+      question: {
+        type: 'string',
+        description: 'The user question',
+      },
+    },
+    required: ['question'],
+  },
+});
+
+// create an agent
+const additionalArg = { userToken: 'abcd1234' };
+const kbAgent = new LLMAgent({
+  tools: [kbTool.bind(additionalArg)],
+  // llm, systemPrompt etc
+})
+```

e2e/examples/cloudflare-worker-agent/CHANGELOG.md

@@ -1,5 +1,31 @@
 # @llamaindex/cloudflare-worker-agent-test
 
+## 0.0.143
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 0.0.142
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.0.141
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+
+## 0.0.140
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
 ## 0.0.139
 
 ### Patch Changes

e2e/examples/cloudflare-worker-agent/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/cloudflare-worker-agent-test",
-  "version": "0.0.139",
+  "version": "0.0.143",
   "type": "module",
   "private": true,
   "scripts": {

e2e/examples/llama-parse-browser/CHANGELOG.md

@@ -1,5 +1,23 @@
 # @llamaindex/llama-parse-browser-test
 
+## 0.0.53
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.8
+
+## 0.0.52
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.7
+
+## 0.0.51
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.6
+
 ## 0.0.50
 
 ### Patch Changes

e2e/examples/llama-parse-browser/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/llama-parse-browser-test",
   "private": true,
-  "version": "0.0.50",
+  "version": "0.0.53",
   "type": "module",
   "scripts": {
     "dev": "vite",

e2e/examples/nextjs-agent/CHANGELOG.md

@@ -1,5 +1,31 @@
 # @llamaindex/next-agent-test
 
+## 0.1.143
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 0.1.142
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.1.141
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+
+## 0.1.140
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
 ## 0.1.139
 
 ### Patch Changes

e2e/examples/nextjs-agent/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-agent-test",
-  "version": "0.1.139",
+  "version": "0.1.143",
   "private": true,
   "scripts": {
     "dev": "next dev",

e2e/examples/nextjs-edge-runtime/CHANGELOG.md

@@ -1,5 +1,31 @@
 # test-edge-runtime
 
+## 0.1.142
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 0.1.141
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.1.140
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+
+## 0.1.139
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
 ## 0.1.138
 
 ### Patch Changes

e2e/examples/nextjs-edge-runtime/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/nextjs-edge-runtime-test",
-  "version": "0.1.138",
+  "version": "0.1.142",
   "private": true,
   "scripts": {
     "dev": "next dev",

e2e/examples/nextjs-node-runtime/CHANGELOG.md

@@ -1,5 +1,37 @@
 # @llamaindex/next-node-runtime
 
+## 0.1.9
+
+### Patch Changes
+
+- llamaindex@0.9.9
+- @llamaindex/huggingface@0.0.43
+- @llamaindex/readers@2.0.7
+
+## 0.1.8
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.1.7
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+  - @llamaindex/huggingface@0.0.42
+  - @llamaindex/readers@2.0.6
+
+## 0.1.6
+
+### Patch Changes
+
+- llamaindex@0.9.6
+- @llamaindex/huggingface@0.0.41
+- @llamaindex/readers@2.0.5
+
 ## 0.1.5
 
 ### Patch Changes

e2e/examples/nextjs-node-runtime/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-node-runtime-test",
-  "version": "0.1.5",
+  "version": "0.1.9",
   "private": true,
   "scripts": {
     "dev": "next dev",

e2e/examples/vite-import-llamaindex/CHANGELOG.md

@@ -1,5 +1,31 @@
 # vite-import-llamaindex
 
+## 0.0.9
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 0.0.8
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.0.7
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+
+## 0.0.6
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
 ## 0.0.5
 
 ### Patch Changes

e2e/examples/vite-import-llamaindex/package.json

@@ -1,7 +1,7 @@
 {
   "name": "vite-import-llamaindex",
   "private": true,
-  "version": "0.0.5",
+  "version": "0.0.9",
   "type": "module",
   "scripts": {
     "build": "vite build",

e2e/examples/waku-query-engine/CHANGELOG.md

@@ -1,5 +1,32 @@
 # @llamaindex/waku-query-engine-test
 
+## 0.0.143
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 0.0.142
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.0.141
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - llamaindex@0.9.7
+
+## 0.0.140
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
 ## 0.0.139
 
 ### Patch Changes

e2e/examples/waku-query-engine/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/waku-query-engine-test",
-  "version": "0.0.139",
+  "version": "0.0.143",
   "type": "module",
   "private": true,
   "scripts": {

examples/CHANGELOG.md

@@ -1,5 +1,145 @@
 # examples
 
+## 0.2.8
+
+### Patch Changes
+
+- Updated dependencies [58b3ee5]
+- Updated dependencies [4bac71d]
+- Updated dependencies [8bf1ca1]
+  - @llamaindex/google@0.1.0
+  - @llamaindex/core@0.5.7
+  - @llamaindex/anthropic@0.2.5
+  - @llamaindex/cloud@3.0.8
+  - llamaindex@0.9.9
+  - @llamaindex/node-parser@1.0.7
+  - @llamaindex/clip@0.0.43
+  - @llamaindex/cohere@0.0.12
+  - @llamaindex/deepinfra@0.0.43
+  - @llamaindex/huggingface@0.0.43
+  - @llamaindex/jinaai@0.0.3
+  - @llamaindex/mistral@0.0.12
+  - @llamaindex/mixedbread@0.0.12
+  - @llamaindex/ollama@0.0.47
+  - @llamaindex/openai@0.1.59
+  - @llamaindex/portkey-ai@0.0.40
+  - @llamaindex/replicate@0.0.40
+  - @llamaindex/astra@0.0.12
+  - @llamaindex/azure@0.1.7
+  - @llamaindex/chroma@0.0.12
+  - @llamaindex/firestore@1.0.5
+  - @llamaindex/milvus@0.1.7
+  - @llamaindex/mongodb@0.0.12
+  - @llamaindex/pinecone@0.0.12
+  - @llamaindex/postgres@0.0.40
+  - @llamaindex/qdrant@0.1.7
+  - @llamaindex/upstash@0.0.12
+  - @llamaindex/weaviate@0.0.12
+  - @llamaindex/vercel@0.0.18
+  - @llamaindex/voyage-ai@1.0.4
+  - @llamaindex/readers@2.0.7
+  - @llamaindex/workflow@0.0.15
+  - @llamaindex/deepseek@0.0.3
+  - @llamaindex/fireworks@0.0.3
+  - @llamaindex/groq@0.0.58
+  - @llamaindex/together@0.0.3
+  - @llamaindex/vllm@0.0.29
+
+## 0.2.7
+
+### Patch Changes
+
+- Updated dependencies [4b49428]
+- Updated dependencies [bbc8c87]
+- Updated dependencies [7ee4968]
+  - @llamaindex/workflow@0.0.14
+  - llamaindex@0.9.8
+  - @llamaindex/deepseek@0.0.2
+  - @llamaindex/fireworks@0.0.2
+  - @llamaindex/together@0.0.2
+  - @llamaindex/jinaai@0.0.2
+  - @llamaindex/google@0.0.14
+
+## 0.2.6
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+  - llamaindex@0.9.7
+  - @llamaindex/cloud@3.0.7
+  - @llamaindex/node-parser@1.0.6
+  - @llamaindex/anthropic@0.2.4
+  - @llamaindex/clip@0.0.42
+  - @llamaindex/cohere@0.0.11
+  - @llamaindex/deepinfra@0.0.42
+  - @llamaindex/google@0.0.13
+  - @llamaindex/groq@0.0.57
+  - @llamaindex/huggingface@0.0.42
+  - @llamaindex/mistral@0.0.11
+  - @llamaindex/mixedbread@0.0.11
+  - @llamaindex/ollama@0.0.46
+  - @llamaindex/openai@0.1.58
+  - @llamaindex/portkey-ai@0.0.39
+  - @llamaindex/replicate@0.0.39
+  - @llamaindex/astra@0.0.11
+  - @llamaindex/azure@0.1.6
+  - @llamaindex/chroma@0.0.11
+  - @llamaindex/firestore@1.0.4
+  - @llamaindex/milvus@0.1.6
+  - @llamaindex/mongodb@0.0.11
+  - @llamaindex/pinecone@0.0.11
+  - @llamaindex/postgres@0.0.39
+  - @llamaindex/qdrant@0.1.6
+  - @llamaindex/upstash@0.0.11
+  - @llamaindex/weaviate@0.0.11
+  - @llamaindex/voyage-ai@1.0.3
+  - @llamaindex/readers@2.0.6
+  - @llamaindex/workflow@0.0.13
+  - @llamaindex/vercel@0.0.17
+  - @llamaindex/vllm@0.0.28
+
+## 0.2.5
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+- Updated dependencies [fd74ba4]
+  - @llamaindex/core@0.5.5
+  - @llamaindex/workflow@0.0.12
+  - @llamaindex/voyage-ai@1.0.2
+  - @llamaindex/cloud@3.0.6
+  - llamaindex@0.9.6
+  - @llamaindex/node-parser@1.0.5
+  - @llamaindex/anthropic@0.2.3
+  - @llamaindex/clip@0.0.41
+  - @llamaindex/cohere@0.0.10
+  - @llamaindex/deepinfra@0.0.41
+  - @llamaindex/google@0.0.12
+  - @llamaindex/huggingface@0.0.41
+  - @llamaindex/mistral@0.0.10
+  - @llamaindex/mixedbread@0.0.10
+  - @llamaindex/ollama@0.0.45
+  - @llamaindex/openai@0.1.57
+  - @llamaindex/portkey-ai@0.0.38
+  - @llamaindex/replicate@0.0.38
+  - @llamaindex/astra@0.0.10
+  - @llamaindex/azure@0.1.5
+  - @llamaindex/chroma@0.0.10
+  - @llamaindex/firestore@1.0.3
+  - @llamaindex/milvus@0.1.5
+  - @llamaindex/mongodb@0.0.10
+  - @llamaindex/pinecone@0.0.10
+  - @llamaindex/postgres@0.0.38
+  - @llamaindex/qdrant@0.1.5
+  - @llamaindex/upstash@0.0.10
+  - @llamaindex/weaviate@0.0.10
+  - @llamaindex/vercel@0.0.16
+  - @llamaindex/readers@2.0.5
+  - @llamaindex/groq@0.0.56
+  - @llamaindex/vllm@0.0.27
+
 ## 0.2.4
 
 ### Patch Changes

examples/agentworkflow/blog_writer.ts

@@ -0,0 +1,83 @@
+import { OpenAI } from "@llamaindex/openai";
+import fs from "fs";
+import {
+  AgentToolCall,
+  AgentToolCallResult,
+  AgentWorkflow,
+  FunctionAgent,
+  FunctionTool,
+} from "llamaindex";
+import os from "os";
+import { z } from "zod";
+
+import { WikipediaTool } from "../wiki";
+const llm = new OpenAI({
+  model: "gpt-4o-mini",
+});
+
+const saveFileTool = FunctionTool.from(
+  ({ content }: { content: string }) => {
+    const filePath = os.tmpdir() + "/report.md";
+    fs.writeFileSync(filePath, content);
+    return `File saved successfully at ${filePath}`;
+  },
+  {
+    name: "saveFile",
+    description:
+      "Save the written content into a file that can be downloaded by the user",
+    parameters: z.object({
+      content: z.string({
+        description: "The content to save into a file",
+      }),
+    }),
+  },
+);
+
+async function main() {
+  const reportAgent = new FunctionAgent({
+    name: "ReportAgent",
+    description:
+      "Responsible for crafting well-written blog posts based on research findings",
+    systemPrompt: `You are a professional writer. Your task is to create an engaging blog post using the research content provided. Once complete, save the post to a file using the saveFile tool.`,
+    tools: [saveFileTool],
+    llm,
+  });
+
+  const researchAgent = new FunctionAgent({
+    name: "ResearchAgent",
+    description:
+      "Responsible for gathering relevant information from the internet",
+    systemPrompt: `You are a research agent. Your role is to gather information from the internet using the provided tools and then transfer this information to the report agent for content creation.`,
+    tools: [new WikipediaTool()],
+    canHandoffTo: [reportAgent],
+    llm,
+  });
+
+  const workflow = new AgentWorkflow({
+    agents: [researchAgent, reportAgent],
+    rootAgent: researchAgent,
+  });
+
+  const context = workflow.run("Write a blog post about history of LLM");
+
+  let finalResult;
+  for await (const event of context) {
+    if (event instanceof AgentToolCall) {
+      console.log(
+        `[Agent ${event.displayName}] executing tool ${event.data.toolName} with parameters ${JSON.stringify(
+          event.data.toolKwargs,
+        )}`,
+      );
+    } else if (event instanceof AgentToolCallResult) {
+      console.log(
+        `[Agent ${event.displayName}] executed tool ${event.data.toolName} with result ${event.data.toolOutput.result}`,
+      );
+    }
+    finalResult = event;
+  }
+  console.log("Final result:", finalResult?.data);
+}
+
+main().catch((error) => {
+  console.error("Error:", error);
+});

examples/agentworkflow/multiple_agents.ts

@@ -0,0 +1,110 @@
+/**
+ * This example shows how to use AgentWorkflow with multiple agents
+ * 1. FetchWeatherAgent - Fetches the weather in a city
+ * 2. TemperatureConverterAgent - Converts the temperature from Fahrenheit to Celsius
+ */
+import { OpenAI } from "@llamaindex/openai";
+import { StopEvent } from "@llamaindex/workflow";
+import {
+  AgentInput,
+  AgentOutput,
+  AgentStream,
+  AgentToolCall,
+  AgentToolCallResult,
+  AgentWorkflow,
+  FunctionAgent,
+  FunctionTool,
+} from "llamaindex";
+import { z } from "zod";
+
+const llm = new OpenAI({
+  model: "gpt-4o-mini",
+});
+
+// Define tools for the agents
+const temperatureConverterTool = FunctionTool.from(
+  ({ temperature }: { temperature: number }) => {
+    return ((temperature - 32) * 5) / 9;
+  },
+  {
+    description: "Convert a temperature from Fahrenheit to Celsius",
+    name: "fahrenheitToCelsius",
+    parameters: z.object({
+      temperature: z.number({
+        description: "The temperature in Fahrenheit",
+      }),
+    }),
+  },
+);
+
+const temperatureFetcherTool = FunctionTool.from(
+  ({ city }: { city: string }) => {
+    const temperature = Math.floor(Math.random() * 58) + 32;
+    return `The current temperature in ${city} is ${temperature}°F`;
+  },
+  {
+    description: "Fetch the temperature (in Fahrenheit) for a city",
+    name: "fetchTemperature",
+    parameters: z.object({
+      city: z.string({
+        description: "The city to fetch the temperature for",
+      }),
+    }),
+  },
+);
+
+// Create agents
+async function multiWeatherAgent() {
+  const converterAgent = new FunctionAgent({
+    name: "TemperatureConverterAgent",
+    description:
+      "An agent that can convert temperatures from Fahrenheit to Celsius.",
+    tools: [temperatureConverterTool],
+    llm,
+  });
+
+  const weatherAgent = new FunctionAgent({
+    name: "FetchWeatherAgent",
+    description: "An agent that can get the weather in a city. ",
+    systemPrompt:
+      "If you can't answer the user question, hand off to other agents.",
+    tools: [temperatureFetcherTool],
+    llm,
+    // Define which next agents can be called next if this agent cannot complete the task
+    // Can be passed as agent name, e.g. "TemperatureConverterAgent"
+    canHandoffTo: [converterAgent],
+  });
+
+  // Create agent workflow with the agents
+  const workflow = new AgentWorkflow({
+    agents: [weatherAgent, converterAgent],
+    rootAgent: weatherAgent,
+    verbose: false,
+  });
+
+  // Ask the agent to get the weather in a city
+  const context = workflow.run(
+    "What is the weather in San Francisco in Celsius?",
+  );
+  // Stream the events
+  for await (const event of context) {
+    // These events might be useful for UI
+    if (
+      event instanceof AgentToolCall ||
+      event instanceof AgentToolCallResult ||
+      event instanceof AgentOutput ||
+      event instanceof AgentInput ||
+      event instanceof StopEvent
+    ) {
+      console.log(event);
+    } else if (event instanceof AgentStream) {
+      for (const chunk of event.data.delta) {
+        process.stdout.write(chunk);
+      }
+    }
+  }
+}
+
+multiWeatherAgent().catch((error) => {
+  console.error("Error:", error);
+});

examples/agentworkflow/single_agent.ts

@@ -0,0 +1,37 @@
+/**
+ * This example shows how to use AgentWorkflow as a single agent with tools
+ */
+import { OpenAI } from "@llamaindex/openai";
+import { AgentWorkflow } from "llamaindex";
+import { getWeatherTool } from "../agent/utils/tools";
+
+const llm = new OpenAI({
+  model: "gpt-4o",
+});
+
+async function singleWeatherAgent() {
+  const workflow = AgentWorkflow.fromTools({
+    tools: [getWeatherTool],
+    llm,
+    verbose: false,
+  });
+
+  const workflowContext = workflow.run(
+    "What's the weather like in San Francisco?",
+  );
+  const sfResult = await workflowContext;
+  // The weather in San Francisco, CA is currently sunny.
+  console.log(`${JSON.stringify(sfResult, null, 2)}`);
+
+  // Reuse the context from the previous run
+  const workflowContext2 = workflow.run("Compare it with California?", {
+    context: workflowContext.data,
+  });
+  const caResult = await workflowContext2;
+  // Both San Francisco and California are currently experiencing sunny weather.
+  console.log(`${JSON.stringify(caResult, null, 2)}`);
+}
+
+singleWeatherAgent().catch((error) => {
+  console.error("Error:", error);
+});

examples/agentworkflow/with-anthropic.ts

@@ -0,0 +1,114 @@
+import fs from "fs";
+import {
+  AgentToolCall,
+  AgentToolCallResult,
+  AgentWorkflow,
+  FunctionAgent,
+  FunctionTool,
+} from "llamaindex";
+import { z } from "zod";
+
+import { Anthropic } from "@llamaindex/anthropic";
+
+const llm = new Anthropic({
+  model: "claude-3-5-sonnet",
+});
+
+const weatherTool = FunctionTool.from(
+  (query: { location: string }) => {
+    return `The weather in ${query.location} is sunny`;
+  },
+  {
+    name: "weather",
+    description: "Get the weather",
+    parameters: z.object({
+      location: z.string({
+        description: "The location to get the weather for",
+      }),
+    }),
+  },
+);
+
+const inflationTool = FunctionTool.from(
+  (query: { location: string }) => {
+    return `The inflation in ${query.location} is 2%`;
+  },
+  {
+    name: "inflation",
+    description: "Get the inflation",
+    parameters: z.object({
+      location: z.string({
+        description: "The location to get the inflation for",
+      }),
+    }),
+  },
+);
+
+const saveFileTool = FunctionTool.from(
+  ({ content }: { content: string }) => {
+    const filePath = "./report.md";
+    fs.writeFileSync(filePath, content);
+    return `File saved successfully at ${filePath}`;
+  },
+  {
+    name: "saveFile",
+    description:
+      "Save the written content into a file that can be downloaded by the user",
+    parameters: z.object({
+      content: z.string({
+        description: "The content to save into a file",
+      }),
+    }),
+  },
+);
+
+async function main() {
+  const reportAgent = new FunctionAgent({
+    name: "ReportAgent",
+    description:
+      "Responsible for creating concise reports about weather and inflation data",
+    systemPrompt: `You are a professional writer. Your task is to create a clear and concise report summarizing the weather and inflation data provided. Once complete, save the report to a file using the saveFile tool.`,
+    tools: [saveFileTool],
+    llm,
+  });
+
+  const researchAgent = new FunctionAgent({
+    name: "ResearchAgent",
+    description:
+      "Responsible for gathering relevant information from the internet",
+    systemPrompt: `You are a research agent. Your role is to gather information about the inflation and weather in the location provided.`,
+    tools: [inflationTool, weatherTool],
+    canHandoffTo: [reportAgent],
+    llm,
+  });
+
+  const workflow = new AgentWorkflow({
+    agents: [researchAgent, reportAgent],
+    rootAgent: researchAgent,
+  });
+
+  const context = workflow.run(
+    "Write a report about New York weather and inflation",
+  );
+
+  let finalResult;
+  for await (const event of context) {
+    if (event instanceof AgentToolCall) {
+      console.log(
+        `[Agent ${event.displayName}] executing tool ${event.data.toolName} with parameters ${JSON.stringify(
+          event.data.toolKwargs,
+        )}`,
+      );
+    } else if (event instanceof AgentToolCallResult) {
+      console.log(
+        `[Agent ${event.displayName}] executed tool ${event.data.toolName} with result ${event.data.toolOutput.result}`,
+      );
+    }
+    finalResult = event;
+  }
+  console.log("Final result:", finalResult?.data);
+}
+
+main().catch((error) => {
+  console.error("Error:", error);
+});

examples/deepseek.ts

@@ -0,0 +1,46 @@
+import { DeepSeekLLM } from "@llamaindex/deepseek";
+
+// process.env.DEEPSEEK_API_KEY is required
+const deepseek = new DeepSeekLLM({
+  apiKey: process.env.DEEPSEEK_API_KEY,
+  model: "deepseek-coder", // or "deepseek-chat"
+});
+
+(async () => {
+  // Example of non-streaming chat
+  const response = await deepseek.chat({
+    messages: [
+      {
+        role: "system",
+        content: "You are an AI assistant",
+      },
+      {
+        role: "user",
+        content: "Tell me about San Francisco",
+      },
+    ],
+    stream: false,
+  });
+  console.log("Response from DeepSeek AI:");
+  console.log(response);
+
+  // Example of streaming chat
+  const generator = await deepseek.chat({
+    messages: [
+      {
+        role: "system",
+        content: "You are an AI assistant",
+      },
+      {
+        role: "user",
+        content: "Write a short poem about San Francisco",
+      },
+    ],
+    stream: true,
+  });
+  console.log("\nStreaming response from DeepSeek AI...");
+  for await (const message of generator) {
+    process.stdout.write(message.delta);
+  }
+  console.log("\n");
+})();

examples/multimodal/jina.ts

@@ -1,10 +1,6 @@
+import { JinaAIEmbedding } from "@llamaindex/jinaai";
 import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
-import {
-  ImageDocument,
-  JinaAIEmbedding,
-  similarity,
-  SimilarityType,
-} from "llamaindex";
+import { ImageDocument, similarity, SimilarityType } from "llamaindex";
 import path from "path";
 
 async function main() {

examples/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/examples",
-  "version": "0.2.4",
+  "version": "0.2.8",
   "private": true,
   "scripts": {
     "lint": "eslint .",
@@ -11,39 +11,43 @@
     "@azure/cosmos": "^4.1.1",
     "@azure/identity": "^4.4.1",
     "@azure/search-documents": "^12.1.0",
-    "@llamaindex/anthropic": "^0.2.2",
-    "@llamaindex/astra": "^0.0.9",
-    "@llamaindex/azure": "^0.1.4",
-    "@llamaindex/chroma": "^0.0.9",
-    "@llamaindex/clip": "^0.0.40",
-    "@llamaindex/cloud": "^3.0.5",
-    "@llamaindex/cohere": "^0.0.9",
-    "@llamaindex/core": "^0.5.4",
-    "@llamaindex/deepinfra": "^0.0.40",
-    "@llamaindex/env": "^0.1.28",
-    "@llamaindex/firestore": "^1.0.2",
-    "@llamaindex/google": "^0.0.11",
-    "@llamaindex/groq": "^0.0.55",
-    "@llamaindex/huggingface": "^0.0.40",
-    "@llamaindex/milvus": "^0.1.4",
-    "@llamaindex/mistral": "^0.0.9",
-    "@llamaindex/mixedbread": "^0.0.9",
-    "@llamaindex/mongodb": "^0.0.9",
-    "@llamaindex/node-parser": "^1.0.4",
-    "@llamaindex/ollama": "^0.0.44",
-    "@llamaindex/openai": "^0.1.56",
-    "@llamaindex/pinecone": "^0.0.9",
-    "@llamaindex/portkey-ai": "^0.0.37",
-    "@llamaindex/postgres": "^0.0.37",
-    "@llamaindex/qdrant": "^0.1.4",
-    "@llamaindex/readers": "^2.0.4",
-    "@llamaindex/replicate": "^0.0.37",
-    "@llamaindex/upstash": "^0.0.9",
-    "@llamaindex/vercel": "^0.0.15",
-    "@llamaindex/vllm": "^0.0.26",
-    "@llamaindex/voyage-ai": "^1.0.1",
-    "@llamaindex/weaviate": "^0.0.9",
-    "@llamaindex/workflow": "^0.0.11",
+    "@llamaindex/anthropic": "^0.2.5",
+    "@llamaindex/astra": "^0.0.12",
+    "@llamaindex/azure": "^0.1.7",
+    "@llamaindex/chroma": "^0.0.12",
+    "@llamaindex/clip": "^0.0.43",
+    "@llamaindex/cloud": "^3.0.8",
+    "@llamaindex/cohere": "^0.0.12",
+    "@llamaindex/core": "^0.5.7",
+    "@llamaindex/deepinfra": "^0.0.43",
+    "@llamaindex/env": "^0.1.29",
+    "@llamaindex/firestore": "^1.0.5",
+    "@llamaindex/google": "^0.1.0",
+    "@llamaindex/groq": "^0.0.58",
+    "@llamaindex/huggingface": "^0.0.43",
+    "@llamaindex/milvus": "^0.1.7",
+    "@llamaindex/mistral": "^0.0.12",
+    "@llamaindex/mixedbread": "^0.0.12",
+    "@llamaindex/mongodb": "^0.0.12",
+    "@llamaindex/node-parser": "^1.0.7",
+    "@llamaindex/ollama": "^0.0.47",
+    "@llamaindex/openai": "^0.1.59",
+    "@llamaindex/pinecone": "^0.0.12",
+    "@llamaindex/portkey-ai": "^0.0.40",
+    "@llamaindex/postgres": "^0.0.40",
+    "@llamaindex/qdrant": "^0.1.7",
+    "@llamaindex/readers": "^2.0.7",
+    "@llamaindex/replicate": "^0.0.40",
+    "@llamaindex/upstash": "^0.0.12",
+    "@llamaindex/vercel": "^0.0.18",
+    "@llamaindex/vllm": "^0.0.29",
+    "@llamaindex/voyage-ai": "^1.0.4",
+    "@llamaindex/weaviate": "^0.0.12",
+    "@llamaindex/workflow": "^0.0.15",
+    "@llamaindex/deepseek": "^0.0.3",
+    "@llamaindex/fireworks": "^0.0.3",
+    "@llamaindex/together": "^0.0.3",
+    "@llamaindex/jinaai": "^0.0.3",
     "@notionhq/client": "^2.2.15",
     "@pinecone-database/pinecone": "^4.0.0",
     "@vercel/postgres": "^0.10.0",
@@ -52,11 +56,11 @@
     "commander": "^12.1.0",
     "dotenv": "^16.4.5",
     "js-tiktoken": "^1.0.14",
-    "llamaindex": "^0.9.5",
+    "llamaindex": "^0.9.9",
     "mongodb": "6.7.0",
-    "pathe": "^1.1.2",
     "postgres": "^3.4.4",
-    "wikipedia": "^2.1.2"
+    "wikipedia": "^2.1.2",
+    "zod": "^3.23.8"
   },
   "devDependencies": {
     "@types/node": "^22.9.0",

examples/qdrantdb/with-gemini.ts

@@ -0,0 +1,33 @@
+import {
+  GEMINI_EMBEDDING_MODEL,
+  GeminiEmbedding,
+  GeminiSession,
+} from "@llamaindex/google";
+import { QdrantVectorStore } from "@llamaindex/qdrant";
+import {
+  Document,
+  storageContextFromDefaults,
+  VectorStoreIndex,
+} from "llamaindex";
+
+const embedding = new GeminiEmbedding({
+  model: GEMINI_EMBEDDING_MODEL.EMBEDDING_001,
+  session: new GeminiSession({
+    apiKey: process.env.GEMINI_API_KEY,
+  }),
+});
+
+async function main() {
+  const docs = [new Document({ text: "Lorem ipsum dolor sit amet" })];
+  const vectorStore = new QdrantVectorStore({
+    url: process.env.QDRANT_URL,
+    apiKey: process.env.QDRANT_API_KEY,
+    embeddingModel: embedding,
+    collectionName: "gemini_test",
+  });
+  const storageContext = await storageContextFromDefaults({ vectorStore });
+  await VectorStoreIndex.fromDocuments(docs, { storageContext });
+  console.log("Inizialized vector store successfully");
+}
+
+void main().catch((err) => console.error(err));

examples/qdrantdb/with-jina.ts

@@ -0,0 +1,27 @@
+import { JinaAIEmbedding } from "@llamaindex/jinaai";
+import { QdrantVectorStore } from "@llamaindex/qdrant";
+import {
+  Document,
+  storageContextFromDefaults,
+  VectorStoreIndex,
+} from "llamaindex";
+
+const embedding = new JinaAIEmbedding({
+  apiKey: process.env.JINAAI_API_KEY,
+  model: "jina-embeddings-v3",
+});
+
+async function main() {
+  const docs = [new Document({ text: "Lorem ipsum dolor sit amet" })];
+  const vectorStore = new QdrantVectorStore({
+    url: process.env.QDRANT_URL,
+    apiKey: process.env.QDRANT_API_KEY,
+    embeddingModel: embedding,
+    collectionName: "jina_test",
+  });
+  const storageContext = await storageContextFromDefaults({ vectorStore });
+  await VectorStoreIndex.fromDocuments(docs, { storageContext });
+  console.log("Inizialized vector store successfully");
+}
+
+void main().catch((err) => console.error(err));

examples/readers/src/pdf_fw.ts

@@ -1,5 +1,6 @@
+import { FireworksEmbedding, FireworksLLM } from "@llamaindex/fireworks";
 import { PDFReader } from "@llamaindex/readers/pdf";
-import { FireworksEmbedding, FireworksLLM, VectorStoreIndex } from "llamaindex";
+import { VectorStoreIndex } from "llamaindex";
 
 import { Settings } from "llamaindex";
 

examples/together-ai.ts

@@ -1,4 +1,4 @@
-import { TogetherEmbedding, TogetherLLM } from "llamaindex";
+import { TogetherEmbedding, TogetherLLM } from "@llamaindex/together";
 
 // process.env.TOGETHER_API_KEY is required
 const together = new TogetherLLM({

examples/together-ai/vector-index.ts

@@ -1,12 +1,7 @@
 import fs from "node:fs/promises";
 
-import {
-  Document,
-  Settings,
-  TogetherEmbedding,
-  TogetherLLM,
-  VectorStoreIndex,
-} from "llamaindex";
+import { TogetherEmbedding, TogetherLLM } from "@llamaindex/together";
+import { Document, Settings, VectorStoreIndex } from "llamaindex";
 
 // Update llm to use TogetherAI
 Settings.llm = new TogetherLLM({

examples/toolsStream.ts

@@ -15,7 +15,7 @@ async function main() {
     tools: [
       {
         metadata: {
-          name: "wikipedia_tool",
+          name: "wikipedia_search",
           description: "A tool that uses a query engine to search Wikipedia.",
           parameters: {
             type: "object",

examples/wiki.ts

@@ -14,7 +14,7 @@ type WikipediaToolParams = {
 };
 
 const DEFAULT_META_DATA: ToolMetadata<JSONSchemaType<WikipediaParameter>> = {
-  name: "wikipedia_tool",
+  name: "wikipedia_search",
   description: "A tool that uses a query engine to search Wikipedia.",
   parameters: {
     type: "object",

packages/autotool/CHANGELOG.md

@@ -1,5 +1,31 @@
 # @llamaindex/autotool
 
+## 6.0.9
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 6.0.8
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 6.0.7
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+
+## 6.0.6
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
 ## 6.0.5
 
 ### Patch Changes

packages/autotool/examples/01_node/CHANGELOG.md

@@ -1,5 +1,35 @@
 # @llamaindex/autotool-01-node-example
 
+## 0.0.90
+
+### Patch Changes
+
+- llamaindex@0.9.9
+- @llamaindex/autotool@6.0.9
+
+## 0.0.89
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+  - @llamaindex/autotool@6.0.8
+
+## 0.0.88
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+  - @llamaindex/autotool@6.0.7
+
+## 0.0.87
+
+### Patch Changes
+
+- llamaindex@0.9.6
+- @llamaindex/autotool@6.0.6
+
 ## 0.0.86
 
 ### Patch Changes

packages/autotool/examples/01_node/package.json

@@ -13,5 +13,5 @@
   "scripts": {
     "start": "node --import tsx --import @llamaindex/autotool/node ./src/index.ts"
   },
-  "version": "0.0.86"
+  "version": "0.0.90"
 }

packages/autotool/examples/02_nextjs/CHANGELOG.md

@@ -1,5 +1,35 @@
 # @llamaindex/autotool-02-next-example
 
+## 0.1.134
+
+### Patch Changes
+
+- llamaindex@0.9.9
+- @llamaindex/autotool@6.0.9
+
+## 0.1.133
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+  - @llamaindex/autotool@6.0.8
+
+## 0.1.132
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+  - @llamaindex/autotool@6.0.7
+
+## 0.1.131
+
+### Patch Changes
+
+- llamaindex@0.9.6
+- @llamaindex/autotool@6.0.6
+
 ## 0.1.130
 
 ### Patch Changes

packages/autotool/examples/02_nextjs/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/autotool-02-next-example",
   "private": true,
-  "version": "0.1.130",
+  "version": "0.1.134",
   "scripts": {
     "dev": "next dev",
     "build": "next build",

packages/autotool/package.json

@@ -6,7 +6,7 @@
     "url": "git+https://github.com/run-llama/LlamaIndexTS.git",
     "directory": "packages/autotool"
   },
-  "version": "6.0.5",
+  "version": "6.0.9",
   "description": "auto transpile your JS function to LLM Agent compatible",
   "files": [
     "dist",

packages/cloud/CHANGELOG.md

@@ -1,5 +1,27 @@
 # @llamaindex/cloud
 
+## 3.0.8
+
+### Patch Changes
+
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+
+## 3.0.7
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+
+## 3.0.6
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+
 ## 3.0.5
 
 ### Patch Changes

packages/cloud/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/cloud",
-  "version": "3.0.5",
+  "version": "3.0.8",
   "type": "module",
   "license": "MIT",
   "scripts": {

packages/community/CHANGELOG.md

@@ -1,5 +1,28 @@
 # @llamaindex/community
 
+## 0.0.89
+
+### Patch Changes
+
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+
+## 0.0.88
+
+### Patch Changes
+
+- e28c29d: Added Llama 3.3 70B Instruct support
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+
+## 0.0.87
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+
 ## 0.0.86
 
 ### Patch Changes

packages/community/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/community",
   "description": "Community package for LlamaIndexTS",
-  "version": "0.0.86",
+  "version": "0.0.89",
   "type": "module",
   "types": "dist/type/index.d.ts",
   "main": "dist/cjs/index.js",

packages/community/src/llm/bedrock/index.ts

@@ -81,6 +81,7 @@ export const BEDROCK_MODELS = {
   META_LLAMA3_2_3B_INSTRUCT: "meta.llama3-2-3b-instruct-v1:0",
   META_LLAMA3_2_11B_INSTRUCT: "meta.llama3-2-11b-instruct-v1:0",
   META_LLAMA3_2_90B_INSTRUCT: "meta.llama3-2-90b-instruct-v1:0",
+  META_LLAMA3_3_70B_INSTRUCT: "meta.llama3-3-70b-instruct-v1:0",
   MISTRAL_7B_INSTRUCT: "mistral.mistral-7b-instruct-v0:2",
   MISTRAL_MIXTRAL_7B_INSTRUCT: "mistral.mixtral-8x7b-instruct-v0:1",
   MISTRAL_MIXTRAL_LARGE_2402: "mistral.mistral-large-2402-v1:0",
@@ -107,6 +108,7 @@ export const INFERENCE_BEDROCK_MODELS = {
   US_META_LLAMA_3_2_3B_INSTRUCT: "us.meta.llama3-2-3b-instruct-v1:0",
   US_META_LLAMA_3_2_11B_INSTRUCT: "us.meta.llama3-2-11b-instruct-v1:0",
   US_META_LLAMA_3_2_90B_INSTRUCT: "us.meta.llama3-2-90b-instruct-v1:0",
+  US_META_LLAMA_3_3_70B_INSTRUCT: "us.meta.llama3-3-70b-instruct-v1:0",
   US_AMAZON_NOVA_PRO_1: "us.amazon.nova-pro-v1:0",
   US_AMAZON_NOVA_LITE_1: "us.amazon.nova-lite-v1:0",
   US_AMAZON_NOVA_MICRO_1: "us.amazon.nova-micro-v1:0",
@@ -151,6 +153,8 @@ export const INFERENCE_TO_BEDROCK_MAP: Record<
     BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT,
   [INFERENCE_BEDROCK_MODELS.US_META_LLAMA_3_2_90B_INSTRUCT]:
     BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT,
+  [INFERENCE_BEDROCK_MODELS.US_META_LLAMA_3_3_70B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_3_70B_INSTRUCT,
 
   [INFERENCE_BEDROCK_MODELS.US_AMAZON_NOVA_PRO_1]:
     BEDROCK_MODELS.AMAZON_NOVA_PRO_1,
@@ -212,6 +216,7 @@ const CHAT_ONLY_MODELS = {
   [BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT]: 131000,
   [BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT]: 128000,
   [BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT]: 128000,
+  [BEDROCK_MODELS.META_LLAMA3_3_70B_INSTRUCT]: 128000,
   [BEDROCK_MODELS.MISTRAL_7B_INSTRUCT]: 32000,
   [BEDROCK_MODELS.MISTRAL_MIXTRAL_7B_INSTRUCT]: 32000,
   [BEDROCK_MODELS.MISTRAL_MIXTRAL_LARGE_2402]: 32000,
@@ -252,6 +257,7 @@ export const STREAMING_MODELS = new Set([
   BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT,
   BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT,
   BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_3_70B_INSTRUCT,
   BEDROCK_MODELS.MISTRAL_7B_INSTRUCT,
   BEDROCK_MODELS.MISTRAL_MIXTRAL_7B_INSTRUCT,
   BEDROCK_MODELS.MISTRAL_MIXTRAL_LARGE_2402,
@@ -273,6 +279,7 @@ export const TOOL_CALL_MODELS: BEDROCK_MODELS[] = [
   BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT,
   BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT,
   BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_3_70B_INSTRUCT,
   BEDROCK_MODELS.AMAZON_NOVA_PRO_1,
   BEDROCK_MODELS.AMAZON_NOVA_LITE_1,
   BEDROCK_MODELS.AMAZON_NOVA_MICRO_1,
@@ -318,6 +325,7 @@ export const BEDROCK_MODEL_MAX_TOKENS: Partial<Record<BEDROCK_MODELS, number>> =
     [BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT]: 2048,
     [BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT]: 2048,
     [BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_3_70B_INSTRUCT]: 2048,
   };
 
 const DEFAULT_BEDROCK_PARAMS = {

packages/core/CHANGELOG.md

@@ -1,5 +1,25 @@
 # @llamaindex/core
 
+## 0.5.7
+
+### Patch Changes
+
+- 4bac71d: Support binding additional argument to function tool
+
+## 0.5.6
+
+### Patch Changes
+
+- beb922b: Fix edge runtime builds by adding missing packages to env package. Make gpt-tokenizer optional for llamaindex to reduce package size.
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+
+## 0.5.5
+
+### Patch Changes
+
+- 5668970: feat: Support AgentWorkflow
+
 ## 0.5.4
 
 ### Patch Changes

packages/core/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/core",
   "type": "module",
-  "version": "0.5.4",
+  "version": "0.5.7",
   "description": "LlamaIndex Core Module",
   "exports": {
     "./agent": {

packages/core/src/llms/type.ts

@@ -215,13 +215,19 @@ export type ToolMetadata<
    * @link https://json-schema.org/understanding-json-schema
    */
   parameters?: Parameters;
+  /**
+   * Whether the tool requires workflow context to be passed in.
+   */
+  requireContext?: boolean;
 };
 
 /**
  * Simple Tool interface. Likely to change.
  */
-// eslint-disable-next-line @typescript-eslint/no-explicit-any
-export interface BaseTool<Input = any> {
+export interface BaseTool<
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  Input = any,
+> {
   /**
    * This could be undefined if the implementation is not provided,
    *  which might be the case when communicating with a llm.

packages/core/src/tools/function-tool.ts

@@ -4,40 +4,66 @@ import { zodToJsonSchema } from "zod-to-json-schema";
 import type { JSONValue } from "../global";
 import type { BaseTool, ToolMetadata } from "../llms";
 
-export class FunctionTool<T, R extends JSONValue | Promise<JSONValue>>
-  implements BaseTool<T>
+export class FunctionTool<
+  T,
+  R extends JSONValue | Promise<JSONValue>,
+  AdditionalToolArgument extends object = object,
+> implements BaseTool<T>
 {
-  #fn: (input: T) => R;
+  #fn: (input: T, additionalArg?: AdditionalToolArgument) => R;
+  #additionalArg: AdditionalToolArgument | undefined;
   readonly #metadata: ToolMetadata<JSONSchemaType<T>>;
   readonly #zodType: z.ZodType<T> | null = null;
   constructor(
-    fn: (input: T) => R,
+    fn: (input: T, additionalArg?: AdditionalToolArgument) => R,
     metadata: ToolMetadata<JSONSchemaType<T>>,
     zodType?: z.ZodType<T>,
+    additionalArg?: AdditionalToolArgument,
   ) {
     this.#fn = fn;
     this.#metadata = metadata;
     if (zodType) {
       this.#zodType = zodType;
     }
+    this.#additionalArg = additionalArg;
   }
 
-  static from<T>(
-    fn: (input: T) => JSONValue | Promise<JSONValue>,
+  static from<T, AdditionalToolArgument extends object = object>(
+    fn: (
+      input: T,
+      additionalArg?: AdditionalToolArgument,
+    ) => JSONValue | Promise<JSONValue>,
     schema: ToolMetadata<JSONSchemaType<T>>,
-  ): FunctionTool<T, JSONValue | Promise<JSONValue>>;
-  static from<R extends z.ZodType>(
-    fn: (input: z.infer<R>) => JSONValue | Promise<JSONValue>,
+  ): FunctionTool<T, JSONValue | Promise<JSONValue>, AdditionalToolArgument>;
+  static from<
+    R extends z.ZodType,
+    AdditionalToolArgument extends object = object,
+  >(
+    fn: (
+      input: z.infer<R>,
+      additionalArg?: AdditionalToolArgument,
+    ) => JSONValue | Promise<JSONValue>,
     schema: Omit<ToolMetadata, "parameters"> & {
       parameters: R;
     },
-  ): FunctionTool<z.infer<R>, JSONValue | Promise<JSONValue>>;
-  static from<T, R extends z.ZodType<T>>(
-    fn: (input: T) => JSONValue | Promise<JSONValue>,
+  ): FunctionTool<
+    z.infer<R>,
+    JSONValue | Promise<JSONValue>,
+    AdditionalToolArgument
+  >;
+  static from<
+    T,
+    R extends z.ZodType<T>,
+    AdditionalToolArgument extends object = object,
+  >(
+    fn: (
+      input: T,
+      additionalArg?: AdditionalToolArgument,
+    ) => JSONValue | Promise<JSONValue>,
     schema: Omit<ToolMetadata, "parameters"> & {
       parameters: R;
     },
-  ): FunctionTool<T, JSONValue>;
+  ): FunctionTool<T, JSONValue, AdditionalToolArgument>;
   // eslint-disable-next-line @typescript-eslint/no-explicit-any
   static from(fn: any, schema: any): any {
     if (schema.parameters instanceof z.ZodSchema) {
@@ -58,15 +84,41 @@ export class FunctionTool<T, R extends JSONValue | Promise<JSONValue>>
     return this.#metadata as BaseTool<T>["metadata"];
   }
 
+  bind = (additionalArg: AdditionalToolArgument) => {
+    return new FunctionTool(
+      this.#fn,
+      this.#metadata,
+      this.#zodType ?? undefined,
+      additionalArg,
+    );
+  };
+
   call = (input: T) => {
+    if (this.#metadata.requireContext) {
+      const inputWithContext = input as Record<string, unknown>;
+      if (!inputWithContext.context) {
+        throw new Error(
+          "Tool call requires context, but context parameter is missing",
+        );
+      }
+    }
     if (this.#zodType) {
       const result = this.#zodType.safeParse(input);
       if (result.success) {
-        return this.#fn.call(null, result.data);
+        if (this.#metadata.requireContext) {
+          const { context } = input as Record<string, unknown>;
+          return this.#fn.call(
+            null,
+            { context, ...result.data },
+            this.#additionalArg,
+          );
+        } else {
+          return this.#fn.call(null, result.data, this.#additionalArg);
+        }
       } else {
         console.warn(result.error.errors);
       }
     }
-    return this.#fn.call(null, input);
+    return this.#fn.call(null, input, this.#additionalArg);
   };
 }

packages/core/tests/tools.test.ts

@@ -1,5 +1,5 @@
 import { FunctionTool } from "@llamaindex/core/tools";
-import { describe, test } from "vitest";
+import { describe, expect, test, vi } from "vitest";
 import { z } from "zod";
 
 describe("FunctionTool", () => {
@@ -32,4 +32,38 @@ describe("FunctionTool", () => {
       parameters: inputSchema,
     });
   });
+
+  test("bind additional argument", () => {
+    type AdditionalHelloArgument = {
+      question?: string;
+    };
+
+    const hello = vi
+      .fn()
+      .mockImplementation((name: string, arg?: AdditionalHelloArgument) => {
+        return `Hello ${name}. ${arg?.question ?? ""}`;
+      });
+
+    const helloTool = FunctionTool.from<string, AdditionalHelloArgument>(
+      hello,
+      {
+        name: "hello",
+        description: "Says hello",
+      },
+    );
+
+    helloTool.call("Alice");
+    expect(hello).to.toHaveBeenCalledOnce();
+    expect(hello).to.toHaveBeenCalledWith("Alice", undefined);
+
+    hello.mockReset();
+
+    const additionalArg = {
+      question: "How is it going?",
+    };
+    const helloBoundTool = helloTool.bind(additionalArg);
+    helloBoundTool.call("Bob");
+    expect(hello).to.toHaveBeenCalledOnce();
+    expect(hello).to.toHaveBeenCalledWith("Bob", additionalArg);
+  });
 });

packages/env/CHANGELOG.md

@@ -1,5 +1,11 @@
 # @llamaindex/env
 
+## 0.1.29
+
+### Patch Changes
+
+- beb922b: Fix edge runtime builds by adding missing packages to env package. Make gpt-tokenizer optional for llamaindex to reduce package size.
+
 ## 0.1.28
 
 ### Patch Changes

packages/env/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/env",
   "description": "environment wrapper, supports all JS environment including node, deno, bun, edge runtime, and cloudflare worker",
-  "version": "0.1.28",
+  "version": "0.1.29",
   "type": "module",
   "types": "dist/index.d.ts",
   "module": "dist/index.js",
@@ -120,31 +120,22 @@
     "@types/node": "^22.9.0",
     "@types/readable-stream": "^4.0.15",
     "bunchee": "6.3.4",
-    "gpt-tokenizer": "^2.6.2",
-    "pathe": "^1.1.2",
     "vitest": "^2.1.5"
   },
-  "peerDependencies": {
+  "dependencies": {
+    "pathe": "^1.1.2",
     "@aws-crypto/sha256-js": "^5.2.0",
+    "js-tiktoken": "^1.0.12"
+  },
+  "peerDependencies": {
     "@huggingface/transformers": "^3.0.2",
-    "gpt-tokenizer": "^2.5.0",
-    "js-tiktoken": "^1.0.12",
-    "pathe": "^1.1.2"
+    "gpt-tokenizer": "^2.5.0"
   },
   "peerDependenciesMeta": {
-    "@aws-crypto/sha256-js": {
-      "optional": true
-    },
     "@huggingface/transformers": {
       "optional": true
     },
-    "pathe": {
-      "optional": true
-    },
-    "tiktoken": {
-      "optional": true
-    },
-    "js-tiktoken": {
+    "gpt-tokenizer": {
       "optional": true
     }
   }

packages/env/src/internal/tokenizers/node.ts

@@ -1,20 +1,48 @@
+import { getEncoding } from "js-tiktoken";
 import type { Tokenizer } from "./types.js";
 import { Tokenizers } from "./types.js";
 
-import cl100kBase from "gpt-tokenizer";
+function tryLoadGptTokenizer() {
+  try {
+    // eslint-disable-next-line @typescript-eslint/no-require-imports
+    return require("gpt-tokenizer"); // using require for CommonJS compatibility
+  } catch (e) {
+    return null;
+  }
+}
+
+const gptTokenizerModule = tryLoadGptTokenizer();
 
 class TokenizerSingleton {
   #defaultTokenizer: Tokenizer;
 
   constructor() {
-    this.#defaultTokenizer = {
-      encode: (text: string): Uint32Array => {
-        return new Uint32Array(cl100kBase.encode(text));
-      },
-      decode: (tokens: Uint32Array) => {
-        return cl100kBase.decode(tokens);
-      },
-    };
+    // Use gpt-tokenizer if available, otherwise use js-tiktoken
+    if (gptTokenizerModule) {
+      this.#defaultTokenizer = {
+        encode: (text: string): Uint32Array => {
+          return new Uint32Array(gptTokenizerModule.encode(text));
+        },
+        decode: (tokens: Uint32Array): string => {
+          return gptTokenizerModule.decode(Array.from(tokens));
+        },
+      };
+    } else {
+      // Fall back to js-tiktoken which is always available
+      // Note: js-tiktoken it's 60x slower than gpt-tokenizer
+      const encoding = getEncoding("cl100k_base");
+      this.#defaultTokenizer = {
+        encode: (text: string) => {
+          return new Uint32Array(encoding.encode(text));
+        },
+        decode: (tokens: Uint32Array) => {
+          const numberArray = Array.from(tokens);
+          const text = encoding.decode(numberArray);
+          const uint8Array = new TextEncoder().encode(text);
+          return new TextDecoder().decode(uint8Array);
+        },
+      };
+    }
   }
 
   tokenizer(encoding?: Tokenizers): Tokenizer {

packages/experimental/CHANGELOG.md

@@ -1,5 +1,31 @@
 # @llamaindex/experimental
 
+## 0.0.159
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 0.0.158
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.0.157
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+
+## 0.0.156
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
 ## 0.0.155
 
 ### Patch Changes

packages/experimental/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/experimental",
   "description": "Experimental package for LlamaIndexTS",
-  "version": "0.0.155",
+  "version": "0.0.159",
   "type": "module",
   "types": "dist/type/index.d.ts",
   "main": "dist/cjs/index.js",
@@ -55,12 +55,10 @@
     "dev": "concurrently \"pnpm run build:esm --watch\" \"pnpm run build:cjs --watch\" \"pnpm run build:type --watch\""
   },
   "devDependencies": {
-    "@aws-crypto/sha256-js": "^5.2.0",
     "@swc/cli": "^0.5.0",
     "@swc/core": "^1.9.2",
     "@types/jsonpath": "^0.2.4",
-    "concurrently": "^9.1.0",
-    "pathe": "^1.1.2"
+    "concurrently": "^9.1.0"
   },
   "dependencies": {
     "@types/lodash": "^4.17.7",

packages/llamaindex/CHANGELOG.md

@@ -1,5 +1,48 @@
 # llamaindex
 
+## 0.9.9
+
+### Patch Changes
+
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+  - @llamaindex/cloud@3.0.8
+  - @llamaindex/node-parser@1.0.7
+  - @llamaindex/openai@0.1.59
+  - @llamaindex/workflow@0.0.15
+
+## 0.9.8
+
+### Patch Changes
+
+- bbc8c87: fix: prefer using embedding model from vector store
+- Updated dependencies [4b49428]
+  - @llamaindex/workflow@0.0.14
+
+## 0.9.7
+
+### Patch Changes
+
+- beb922b: Fix edge runtime builds by adding missing packages to env package. Make gpt-tokenizer optional for llamaindex to reduce package size.
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+  - @llamaindex/cloud@3.0.7
+  - @llamaindex/node-parser@1.0.6
+  - @llamaindex/openai@0.1.58
+  - @llamaindex/workflow@0.0.13
+
+## 0.9.6
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+  - @llamaindex/workflow@0.0.12
+  - @llamaindex/cloud@3.0.6
+  - @llamaindex/node-parser@1.0.5
+  - @llamaindex/openai@0.1.57
+
 ## 0.9.5
 
 ### Patch Changes

packages/llamaindex/package.json

@@ -1,6 +1,6 @@
 {
   "name": "llamaindex",
-  "version": "0.9.5",
+  "version": "0.9.9",
   "license": "MIT",
   "type": "module",
   "keywords": [
@@ -25,12 +25,12 @@
     "@llamaindex/env": "workspace:*",
     "@llamaindex/node-parser": "workspace:*",
     "@llamaindex/openai": "workspace:*",
+    "@llamaindex/workflow": "workspace:*",
     "@types/lodash": "^4.17.7",
     "@types/node": "^22.9.0",
     "ajv": "^8.17.1",
     "lodash": "^4.17.21",
-    "magic-bytes.js": "^1.10.0",
-    "gpt-tokenizer": "^2.6.2"
+    "magic-bytes.js": "^1.10.0"
   },
   "devDependencies": {
     "@swc/cli": "^0.5.0",

packages/llamaindex/src/embeddings/OpenAIEmbedding.ts

@@ -1 +0,0 @@
-export * from "@llamaindex/openai";

packages/llamaindex/src/embeddings/index.ts

@@ -1,5 +0,0 @@
-export * from "@llamaindex/core/embeddings";
-export { FireworksEmbedding } from "./fireworks.js";
-export * from "./JinaAIEmbedding.js";
-export * from "./OpenAIEmbedding.js";
-export { TogetherEmbedding } from "./together.js";

packages/llamaindex/src/index.edge.ts

@@ -22,6 +22,7 @@ export {
 export * from "@llamaindex/core/agent";
 export * from "@llamaindex/core/chat-engine";
 export * from "@llamaindex/core/data-structs";
+export * from "@llamaindex/core/embeddings";
 export {
   CallbackManager,
   DEFAULT_BASE_URL,
@@ -65,9 +66,10 @@ export * from "@llamaindex/core/storage/doc-store";
 export * from "@llamaindex/core/storage/index-store";
 export * from "@llamaindex/core/storage/kv-store";
 export * from "@llamaindex/core/utils";
+export * from "@llamaindex/openai";
+export * from "@llamaindex/workflow/agent";
 export * from "./agent/index.js";
 export * from "./cloud/index.js";
-export * from "./embeddings/index.js";
 export * from "./engines/chat/index.js";
 export * from "./engines/query/index.js";
 export * from "./evaluation/index.js";
@@ -75,7 +77,6 @@ export * from "./extractors/index.js";
 export * from "./indices/index.js";
 export * from "./ingestion/index.js";
 export { imageToDataUrl } from "./internal/utils.js";
-export * from "./llm/index.js";
 export * from "./node-parser.js";
 export * from "./objects/index.js";
 export * from "./OutputParser.js";

packages/llamaindex/src/index.ts

@@ -1,8 +1,5 @@
 export * from "./index.edge.js";
 
-// TODO: clean up, move to jinaai package
-export { JinaAIEmbedding } from "./embeddings/JinaAIEmbedding.js";
-
 // Don't export file-system stores for non-node.js runtime on top level,
 //  as we cannot guarantee that they will work in other environments
 export * from "./storage/index.js";

packages/llamaindex/src/indices/vectorStore/index.ts

@@ -175,7 +175,7 @@ export class VectorStoreIndex extends BaseIndex<IndexDict> {
     for (const type in nodeMap) {
       const nodes = nodeMap[type as ModalityType];
       const embedModel =
-        this.embedModel ?? this.vectorStores[type as ModalityType]?.embedModel;
+        this.vectorStores[type as ModalityType]?.embedModel ?? this.embedModel;
       if (embedModel && nodes) {
         await embedModel(nodes, {
           logProgress: options?.logProgress,

packages/llamaindex/src/llm/index.ts

@@ -1,4 +0,0 @@
-export { DeepSeekLLM } from "./deepseek.js";
-export { FireworksLLM } from "./fireworks.js";
-export * from "./openai.js";
-export { TogetherLLM } from "./together.js";

packages/llamaindex/src/llm/openai.ts

@@ -1 +0,0 @@
-export * from "@llamaindex/openai";

packages/llamaindex/tests/MetadataExtractors.test.ts

@@ -1,13 +1,11 @@
 import { Document } from "@llamaindex/core/schema";
-import { Settings } from "llamaindex";
-import { OpenAIEmbedding } from "llamaindex/embeddings/index";
+import { OpenAI, OpenAIEmbedding, Settings } from "llamaindex";
 import {
   KeywordExtractor,
   QuestionsAnsweredExtractor,
   SummaryExtractor,
   TitleExtractor,
 } from "llamaindex/extractors/index";
-import { OpenAI } from "llamaindex/llm/openai";
 import { SentenceSplitter } from "llamaindex/node-parser";
 import { afterAll, beforeAll, describe, expect, test, vi } from "vitest";
 import {

packages/llamaindex/tests/Selectors.test.ts

@@ -1,7 +1,7 @@
 import { describe, expect, test } from "vitest";
 // from unittest.mock import patch
 
-import { OpenAI } from "llamaindex/llm/index";
+import { OpenAI } from "llamaindex";
 import { LLMSingleSelector } from "llamaindex/selectors/index";
 import { mocStructuredkLlmGeneration } from "./utility/mockOpenAI.js";
 

packages/llamaindex/tests/indices/SummaryIndex.test.ts

@@ -20,13 +20,13 @@ describe("SummaryIndex", () => {
   let storageContext: StorageContext;
 
   beforeAll(async () => {
-    storageContext = await storageContextFromDefaults({
-      persistDir: testDir,
-    });
-
     const embedModel = new OpenAIEmbedding();
     mockEmbeddingModel(embedModel);
     Settings.embedModel = embedModel;
+
+    storageContext = await storageContextFromDefaults({
+      persistDir: testDir,
+    });
   });
 
   afterAll(() => {

packages/llamaindex/tests/indices/VectorStoreIndex.test.ts

@@ -9,7 +9,7 @@ import { DocStoreStrategy } from "llamaindex/ingestion/strategies/index";
 import { mkdtemp, rm } from "node:fs/promises";
 import { tmpdir } from "node:os";
 import { join } from "node:path";
-import { afterAll, beforeAll, describe, expect, test, vi } from "vitest";
+import { afterAll, beforeAll, describe, expect, it, test, vi } from "vitest";
 
 const testDir = await mkdtemp(join(tmpdir(), "test-"));
 
@@ -24,6 +24,10 @@ describe("VectorStoreIndex", () => {
   ) => Promise<Array<number>>;
 
   beforeAll(async () => {
+    const embedModel = new OpenAIEmbedding();
+    mockEmbeddingModel(embedModel);
+    Settings.embedModel = embedModel;
+
     storageContext = await mockStorageContext(testDir);
     testStrategy = async (
       strategy: DocStoreStrategy,
@@ -41,10 +45,6 @@ describe("VectorStoreIndex", () => {
       }
       return entries;
     };
-
-    const embedModel = new OpenAIEmbedding();
-    mockEmbeddingModel(embedModel);
-    Settings.embedModel = embedModel;
   });
 
   afterAll(() => {
@@ -65,3 +65,28 @@ describe("VectorStoreIndex", () => {
     await rm(testDir, { recursive: true });
   });
 });
+
+describe("[VectorStoreIndex] use embedding model", () => {
+  it("should use embedding model passed in options instead of Settings", async () => {
+    const documents = [new Document({ text: "This needs to be embedded" })];
+
+    // Create mock embedding models
+    const settingsEmbedModel = new OpenAIEmbedding();
+    const customEmbedModel = new OpenAIEmbedding();
+
+    // Mock the embedding models using the utility function
+    mockEmbeddingModel(settingsEmbedModel);
+    mockEmbeddingModel(customEmbedModel);
+
+    // Add spies to track calls
+    const settingsSpy = vi.spyOn(settingsEmbedModel, "getTextEmbeddings");
+    const customSpy = vi.spyOn(customEmbedModel, "getTextEmbeddings");
+
+    Settings.embedModel = settingsEmbedModel;
+
+    const storageContext = await mockStorageContext(testDir, customEmbedModel); // setup custom embedding model
+    await VectorStoreIndex.fromDocuments(documents, { storageContext });
+    expect(customSpy).toHaveBeenCalled();
+    expect(settingsSpy).not.toHaveBeenCalled();
+  });
+});

packages/llamaindex/tests/utility/mockOpenAI.ts

@@ -1,8 +1,6 @@
 import type { CallbackManager } from "@llamaindex/core/global";
-import type { LLMChatParamsBase } from "llamaindex";
-import { Settings } from "llamaindex";
-import type { OpenAIEmbedding } from "llamaindex/embeddings/OpenAIEmbedding";
-import { OpenAI } from "llamaindex/llm/openai";
+import type { LLMChatParamsBase, OpenAIEmbedding } from "llamaindex";
+import { OpenAI, Settings } from "llamaindex";
 import { vi } from "vitest";
 
 export const DEFAULT_LLM_TEXT_OUTPUT = "MOCK_TOKEN_1-MOCK_TOKEN_2";

packages/llamaindex/tests/utility/mockStorageContext.ts

@@ -1,14 +1,27 @@
-import { OpenAIEmbedding, storageContextFromDefaults } from "llamaindex";
+import {
+  BaseEmbedding,
+  OpenAIEmbedding,
+  storageContextFromDefaults,
+} from "llamaindex";
 
 import { mockEmbeddingModel } from "./mockOpenAI.js";
 
-export async function mockStorageContext(testDir: string) {
+export async function mockStorageContext(
+  testDir: string,
+  embeddingModel?: BaseEmbedding,
+) {
   const storageContext = await storageContextFromDefaults({
     persistDir: testDir,
   });
   for (const store of Object.values(storageContext.vectorStores)) {
-    store.embedModel = new OpenAIEmbedding();
-    mockEmbeddingModel(store.embedModel as OpenAIEmbedding);
+    if (embeddingModel) {
+      // use embeddingModel if it is passed in
+      store.embedModel = embeddingModel;
+    } else {
+      // mock an embedding model for testing
+      store.embedModel = new OpenAIEmbedding();
+      mockEmbeddingModel(store.embedModel as OpenAIEmbedding);
+    }
   }
   return storageContext;
 }

packages/node-parser/CHANGELOG.md

@@ -1,5 +1,27 @@
 # @llamaindex/node-parser
 
+## 1.0.7
+
+### Patch Changes
+
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+
+## 1.0.6
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+
+## 1.0.5
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+
 ## 1.0.4
 
 ### Patch Changes

packages/node-parser/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/node-parser",
-  "version": "1.0.4",
+  "version": "1.0.7",
   "description": "Node parser for LlamaIndex",
   "type": "module",
   "exports": {

packages/providers/anthropic/CHANGELOG.md

@@ -1,5 +1,28 @@
 # @llamaindex/anthropic
 
+## 0.2.5
+
+### Patch Changes
+
+- 8bf1ca1: Support chat stream with tools for Anthropic LLM
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+
+## 0.2.4
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+
+## 0.2.3
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+
 ## 0.2.2
 
 ### Patch Changes

packages/providers/anthropic/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/anthropic",
   "description": "Anthropic Adapter for LlamaIndex",
-  "version": "0.2.2",
+  "version": "0.2.5",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/anthropic/src/llm.ts

@@ -13,7 +13,7 @@ import type {
   Tool,
   ToolUseBlock,
 } from "@anthropic-ai/sdk/resources/messages";
-import { wrapLLMEvent } from "@llamaindex/core/decorator";
+import { wrapEventCaller, wrapLLMEvent } from "@llamaindex/core/decorator";
 import type { JSONObject } from "@llamaindex/core/global";
 import type {
   BaseTool,
@@ -22,6 +22,7 @@ import type {
   ChatResponseChunk,
   LLMChatParamsNonStreaming,
   LLMChatParamsStreaming,
+  PartialToolCall,
   ToolCallLLMMessageOptions,
 } from "@llamaindex/core/llms";
 import { ToolCallLLM } from "@llamaindex/core/llms";
@@ -378,6 +379,7 @@ export class Anthropic extends ToolCallLLM<
       AnthropicToolCallLLMMessageOptions
     >,
   ): Promise<ChatResponse<AnthropicToolCallLLMMessageOptions>>;
+  @wrapEventCaller
   @wrapLLMEvent
   async chat(
     params:
@@ -445,19 +447,16 @@ export class Anthropic extends ToolCallLLM<
       ),
     };
 
-    if (stream) {
-      if (tools) {
-        console.error("Tools are not supported in streaming mode");
-      }
-      return this.streamChat(anthropic, apiParams);
-    }
-
     if (tools?.length) {
       Object.assign(apiParams, {
         tools: this.prepareToolsForAPI(tools),
       });
     }
 
+    if (stream) {
+      return this.streamChat(anthropic, apiParams);
+    }
+
     const response = await anthropic.messages.create(apiParams);
 
     const toolUseBlock = response.content.filter(
@@ -494,6 +493,7 @@ export class Anthropic extends ToolCallLLM<
     };
   }
 
+  @wrapEventCaller
   protected async *streamChat(
     anthropic: SDKAnthropic,
     params: MessageCreateParams,
@@ -503,7 +503,9 @@ export class Anthropic extends ToolCallLLM<
       stream: true,
     });
 
-    let idx_counter: number = 0;
+    let currentToolCall: PartialToolCall | null = null;
+    let accumulatedToolInput = "";
+
     for await (const part of stream) {
       const textContent =
         part.type === "content_block_delta" && part.delta.type === "text_delta"
@@ -516,9 +518,48 @@ export class Anthropic extends ToolCallLLM<
           ? part.delta.thinking
           : undefined;
 
+      if (
+        part.type === "content_block_start" &&
+        part.content_block.type === "tool_use"
+      ) {
+        currentToolCall = {
+          id: part.content_block.id,
+          name: part.content_block.name,
+          input: "",
+        };
+        accumulatedToolInput = "";
+        continue;
+      }
+
+      if (
+        part.type === "content_block_delta" &&
+        part.delta.type === "input_json_delta" &&
+        currentToolCall
+      ) {
+        accumulatedToolInput += part.delta.partial_json;
+        continue;
+      }
+
+      if (part.type === "content_block_stop" && currentToolCall) {
+        yield {
+          raw: part,
+          delta: "",
+          options: {
+            toolCall: [
+              {
+                id: currentToolCall.id,
+                name: currentToolCall.name,
+                input: accumulatedToolInput,
+              },
+            ],
+          },
+        };
+        currentToolCall = null;
+        continue;
+      }
+
       if (!textContent && !thinking) continue;
 
-      idx_counter++;
       yield {
         raw: part,
         delta: textContent ?? "",

packages/providers/clip/CHANGELOG.md

@@ -1,5 +1,30 @@
 # @llamaindex/clip
 
+## 0.0.43
+
+### Patch Changes
+
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+  - @llamaindex/openai@0.1.59
+
+## 0.0.42
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+  - @llamaindex/openai@0.1.58
+
+## 0.0.41
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+  - @llamaindex/openai@0.1.57
+
 ## 0.0.40
 
 ### Patch Changes

packages/providers/clip/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/clip",
   "description": "Clip Embedding Adapter for LlamaIndex",
-  "version": "0.0.40",
+  "version": "0.0.43",
   "type": "module",
   "types": "dist/index.d.ts",
   "main": "dist/index.cjs",

packages/providers/cohere/CHANGELOG.md

@@ -1,5 +1,27 @@
 # @llamaindex/cohere
 
+## 0.0.12
+
+### Patch Changes
+
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+
+## 0.0.11
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+
+## 0.0.10
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+
 ## 0.0.9
 
 ### Patch Changes

packages/providers/cohere/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/cohere",
   "description": "Cohere Adapter for LlamaIndex",
-  "version": "0.0.9",
+  "version": "0.0.12",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/deepinfra/CHANGELOG.md

@@ -1,5 +1,30 @@
 # @llamaindex/deepinfra
 
+## 0.0.43
+
+### Patch Changes
+
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+  - @llamaindex/openai@0.1.59
+
+## 0.0.42
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+  - @llamaindex/openai@0.1.58
+
+## 0.0.41
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+  - @llamaindex/openai@0.1.57
+
 ## 0.0.40
 
 ### Patch Changes

packages/providers/deepinfra/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/deepinfra",
   "description": "Deepinfra Adapter for LlamaIndex",
-  "version": "0.0.40",
+  "version": "0.0.43",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/deepseek/CHANGELOG.md

@@ -0,0 +1,13 @@
+# @llamaindex/deepseek
+
+## 0.0.3
+
+### Patch Changes
+
+- @llamaindex/openai@0.1.59
+
+## 0.0.2
+
+### Patch Changes
+
+- bbc8c87: fix: prefer using embedding model from vector store

packages/providers/deepseek/package.json

@@ -0,0 +1,39 @@
+{
+  "name": "@llamaindex/deepseek",
+  "description": "DeepSeek Adapter for LlamaIndex",
+  "version": "0.0.3",
+  "type": "module",
+  "main": "./dist/index.cjs",
+  "module": "./dist/index.js",
+  "exports": {
+    ".": {
+      "require": {
+        "types": "./dist/index.d.cts",
+        "default": "./dist/index.cjs"
+      },
+      "import": {
+        "types": "./dist/index.d.ts",
+        "default": "./dist/index.js"
+      }
+    }
+  },
+  "files": [
+    "dist"
+  ],
+  "repository": {
+    "type": "git",
+    "url": "git+https://github.com/run-llama/LlamaIndexTS.git",
+    "directory": "packages/providers/deepseek"
+  },
+  "scripts": {
+    "build": "bunchee",
+    "dev": "bunchee --watch"
+  },
+  "devDependencies": {
+    "bunchee": "6.3.4"
+  },
+  "dependencies": {
+    "@llamaindex/env": "workspace:*",
+    "@llamaindex/openai": "workspace:*"
+  }
+}

packages/providers/deepseek/src/index.ts

@@ -0,0 +1 @@
+export * from "./llm";

packages/providers/deepseek/tsconfig.json

@@ -0,0 +1,19 @@
+{
+  "extends": "../../../tsconfig.json",
+  "compilerOptions": {
+    "target": "ESNext",
+    "module": "ESNext",
+    "moduleResolution": "bundler",
+    "outDir": "./lib",
+    "tsBuildInfoFile": "./lib/.tsbuildinfo"
+  },
+  "include": ["./src"],
+  "references": [
+    {
+      "path": "../openai/tsconfig.json"
+    },
+    {
+      "path": "../../env/tsconfig.json"
+    }
+  ]
+}

packages/providers/fireworks/CHANGELOG.md

@@ -0,0 +1,13 @@
+# @llamaindex/fireworks
+
+## 0.0.3
+
+### Patch Changes
+
+- @llamaindex/openai@0.1.59
+
+## 0.0.2
+
+### Patch Changes
+
+- bbc8c87: fix: prefer using embedding model from vector store

packages/providers/fireworks/package.json

@@ -0,0 +1,39 @@
+{
+  "name": "@llamaindex/fireworks",
+  "description": "Fireworks Adapter for LlamaIndex",
+  "version": "0.0.3",
+  "type": "module",
+  "main": "./dist/index.cjs",
+  "module": "./dist/index.js",
+  "exports": {
+    ".": {
+      "require": {
+        "types": "./dist/index.d.cts",
+        "default": "./dist/index.cjs"
+      },
+      "import": {
+        "types": "./dist/index.d.ts",
+        "default": "./dist/index.js"
+      }
+    }
+  },
+  "files": [
+    "dist"
+  ],
+  "repository": {
+    "type": "git",
+    "url": "git+https://github.com/run-llama/LlamaIndexTS.git",
+    "directory": "packages/providers/fireworks"
+  },
+  "scripts": {
+    "build": "bunchee",
+    "dev": "bunchee --watch"
+  },
+  "devDependencies": {
+    "bunchee": "6.3.4"
+  },
+  "dependencies": {
+    "@llamaindex/env": "workspace:*",
+    "@llamaindex/openai": "workspace:*"
+  }
+}

packages/providers/fireworks/src/index.ts

@@ -0,0 +1,2 @@
+export * from "./embedding";
+export * from "./llm";

packages/providers/fireworks/tsconfig.json

@@ -0,0 +1,19 @@
+{
+  "extends": "../../../tsconfig.json",
+  "compilerOptions": {
+    "target": "ESNext",
+    "module": "ESNext",
+    "moduleResolution": "bundler",
+    "outDir": "./lib",
+    "tsBuildInfoFile": "./lib/.tsbuildinfo"
+  },
+  "include": ["./src"],
+  "references": [
+    {
+      "path": "../openai/tsconfig.json"
+    },
+    {
+      "path": "../../env/tsconfig.json"
+    }
+  ]
+}

packages/providers/google/CHANGELOG.md

@@ -1,5 +1,37 @@
 # @llamaindex/google
 
+## 0.1.0
+
+### Minor Changes
+
+- 58b3ee5: google vertex ai don't support empty functionDeclarations array. You must pass an empty array to LLMAgent if you don't have tools so Gemini was no able to use it in agent mode. Also Gemini 2.0 flash lite was added to model list.
+
+### Patch Changes
+
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+
+## 0.0.14
+
+### Patch Changes
+
+- 7ee4968: Add Gemini 2.0 Pro Experimental
+
+## 0.0.13
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+
+## 0.0.12
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+
 ## 0.0.11
 
 ### Patch Changes

packages/providers/google/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/google",
   "description": "Google Adapter for LlamaIndex",
-  "version": "0.0.11",
+  "version": "0.1.0",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/google/src/base.ts

@@ -56,7 +56,9 @@ export const GEMINI_MODEL_INFO_MAP: Record<GEMINI_MODEL, GeminiModelInfo> = {
   [GEMINI_MODEL.GEMINI_2_0_FLASH_EXPERIMENTAL]: { contextWindow: 10 ** 6 },
   [GEMINI_MODEL.GEMINI_2_0_FLASH]: { contextWindow: 10 ** 6 },
   [GEMINI_MODEL.GEMINI_2_0_FLASH_LITE_PREVIEW]: { contextWindow: 10 ** 6 },
+  [GEMINI_MODEL.GEMINI_2_0_FLASH_LITE]: { contextWindow: 10 ** 6 },
   [GEMINI_MODEL.GEMINI_2_0_FLASH_THINKING_EXP]: { contextWindow: 32768 },
+  [GEMINI_MODEL.GEMINI_2_0_PRO_EXPERIMENTAL]: { contextWindow: 2 * 10 ** 6 },
 };
 
 const SUPPORT_TOOL_CALL_MODELS: GEMINI_MODEL[] = [
@@ -72,6 +74,7 @@ const SUPPORT_TOOL_CALL_MODELS: GEMINI_MODEL[] = [
   GEMINI_MODEL.GEMINI_PRO_1_5_FLASH_LATEST,
   GEMINI_MODEL.GEMINI_2_0_FLASH_EXPERIMENTAL,
   GEMINI_MODEL.GEMINI_2_0_FLASH,
+  GEMINI_MODEL.GEMINI_2_0_PRO_EXPERIMENTAL,
 ];
 
 const DEFAULT_GEMINI_PARAMS = {
@@ -276,24 +279,26 @@ export class Gemini extends ToolCallLLM<GeminiAdditionalChatOptions> {
   ): GeminiChatStreamResponse {
     const context = getChatContext(params);
     const client = this.session.getGenerativeModel(this.metadata);
-    const chat = client.startChat(
-      params.tools
-        ? {
-            history: context.history,
-            tools: [
-              {
-                functionDeclarations: params.tools.map(
-                  mapBaseToolToGeminiFunctionDeclaration,
-                ),
-              },
-            ],
-            safetySettings: DEFAULT_SAFETY_SETTINGS,
-          }
-        : {
-            history: context.history,
-            safetySettings: DEFAULT_SAFETY_SETTINGS,
+    const tools = params.tools?.length
+      ? [
+          {
+            functionDeclarations: params.tools.map(
+              mapBaseToolToGeminiFunctionDeclaration,
+            ),
           },
-    );
+        ]
+      : [];
+    const startChatParams = params.tools
+      ? {
+          history: context.history,
+          tools,
+          safetySettings: DEFAULT_SAFETY_SETTINGS,
+        }
+      : {
+          history: context.history,
+          safetySettings: DEFAULT_SAFETY_SETTINGS,
+        };
+    const chat = client.startChat(startChatParams);
     const result = await chat.sendMessageStream(context.message);
     yield* this.session.getChatStream(result);
   }