Release 0.8.27 (#1545)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: himself65 <himself65@users.noreply.github.com>

.github/workflows/test.yml

@@ -23,7 +23,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        node-version: [20.x, 22.x, 23.x]
+        node-version: [18.x, 20.x, 22.x, 23.x]
     name: E2E on Node.js ${{ matrix.node-version }}
     runs-on: ubuntu-latest
     steps:
@@ -53,7 +53,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        node-version: [20.x, 22.x, 23.x]
+        node-version: [18.x, 20.x, 22.x, 23.x]
     name: Test on Node.js ${{ matrix.node-version }}
     runs-on: ubuntu-latest
     steps:

apps/docs/CHANGELOG.md

@@ -1,5 +1,15 @@
 # docs
 
+## 0.0.133
+
+### Patch Changes
+
+- c1850ee: feat: Amazon Nova support via Bedrock
+- Updated dependencies [b504303]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+  - @llamaindex/examples@0.0.20
+
 ## 0.0.132
 
 ### Patch Changes

apps/docs/docs/modules/llms/available_llms/bedrock.md

@@ -37,6 +37,9 @@ META_LLAMA3_2_1B_INSTRUCT = "meta.llama3-2-1b-instruct-v1:0"; // only available
 META_LLAMA3_2_3B_INSTRUCT = "meta.llama3-2-3b-instruct-v1:0"; // only available via inference endpoints (see below)
 META_LLAMA3_2_11B_INSTRUCT = "meta.llama3-2-11b-instruct-v1:0"; // only available via inference endpoints (see below), multimodal and function call supported
 META_LLAMA3_2_90B_INSTRUCT = "meta.llama3-2-90b-instruct-v1:0"; // only available via inference endpoints (see below), multimodal and function call supported
+AMAZON_NOVA_PRO_1 = "amazon.nova-pro-v1:0";
+AMAZON_NOVA_LITE_1 = "amazon.nova-lite-v1:0";
+AMAZON_NOVA_MICRO_1 = "amazon.nova-micro-v1:0";
 ```
 
 You can also use Bedrock's Inference endpoints by using the model names:
@@ -53,6 +56,9 @@ US_META_LLAMA_3_2_1B_INSTRUCT = "us.meta.llama3-2-1b-instruct-v1:0";
 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_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";
 
 // EU
 EU_ANTHROPIC_CLAUDE_3_HAIKU = "eu.anthropic.claude-3-haiku-20240307-v1:0";

apps/docs/package.json

@@ -1,6 +1,6 @@
 {
   "name": "docs",
-  "version": "0.0.132",
+  "version": "0.0.133",
   "private": true,
   "scripts": {
     "docusaurus": "docusaurus",

apps/next/CHANGELOG.md

@@ -1,5 +1,20 @@
 # @llamaindex/doc
 
+## 0.0.31
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+  - @llamaindex/core@0.4.18
+  - @llamaindex/cloud@2.0.18
+  - @llamaindex/node-parser@0.0.19
+  - @llamaindex/openai@0.1.43
+  - @llamaindex/readers@1.0.20
+  - @llamaindex/workflow@0.0.8
+
 ## 0.0.30
 
 ### Patch Changes

apps/next/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/doc",
-  "version": "0.0.30",
+  "version": "0.0.31",
   "private": true,
   "scripts": {
     "build": "pnpm run build:docs && next build",

apps/next/src/content/docs/llamaindex/integration/vercel.mdx

@@ -3,7 +3,9 @@ title: Vercel
 description: Integrate LlamaIndex with Vercel's AI SDK
 ---
 
-LlamaIndex provides integration with Vercel's AI SDK, allowing you to create powerful search and retrieval applications. Below are examples of how to use LlamaIndex with `streamText` from the Vercel AI SDK.
+LlamaIndex provides integration with Vercel's AI SDK, allowing you to create powerful search and retrieval applications. You can:
+- Use any of Vercel AI's [model providers](https://sdk.vercel.ai/docs/foundations/providers-and-models) as LLMs in LlamaIndex
+- Use indexes (e.g. VectorStoreIndex, LlamaCloudIndex) from LlamaIndexTS in your Vercel AI applications
 
 ## Setup
 
@@ -13,7 +15,22 @@ First, install the required dependencies:
 npm install @llamaindex/vercel ai
 ```
 
-## Using Local Vector Store
+## Using Vercel AI's Model Providers 
+
+Using the `VercelLLM` adapter, it's easy to use any of Vercel AI's [model providers](https://sdk.vercel.ai/docs/foundations/providers-and-models) as LLMs in LlamaIndex. Here's an example of how to use OpenAI's GPT-4o model:
+
+```typescript
+const llm = new VercelLLM({ model: openai("gpt-4o") });
+const result = await llm.complete({
+  prompt: "What is the capital of France?",
+  stream: false, // Set to true if you want streaming responses
+});
+console.log(result.text);
+```
+
+## Use Indexes
+
+### Using VectorStoreIndex
 
 Here's how to create a simple vector store index and query it using Vercel's AI SDK:
 
@@ -29,22 +46,25 @@ const index = await VectorStoreIndex.fromDocuments([document]);
 
 // Create a query tool
 const queryTool = llamaindex({
+  model: openai("gpt-4"),
   index,
   description: "Search through the documents", // optional
 });
 
 // Use the tool with Vercel's AI SDK
 streamText({
-  tools: { queryTool },
-  prompt: "Your question here",
   model: openai("gpt-4"),
+  prompt: "Your question here",
+  tools: { queryTool },
   onFinish({ response }) {
     console.log("Response:", response.messages); // log the response
   },
 }).toDataStream();
 ```
 
-## Using LlamaCloud
+> Note: the Vercel AI model referenced in the `llamaindex` function is used by the response synthesizer to generate a response for the tool call.
+
+### Using LlamaCloud
 
 For production deployments, you can use LlamaCloud to store and manage your documents:
 
@@ -61,20 +81,21 @@ const index = await LlamaCloudIndex.fromDocuments({
 
 // Use it the same way as VectorStoreIndex
 const queryTool = llamaindex({
+  model: openai("gpt-4"),
   index,
   description: "Search through the documents",
 });
 
 // Use the tool with Vercel's AI SDK
 streamText({
-  tools: { queryTool },
-  prompt: "Your question here",
   model: openai("gpt-4"),
+  prompt: "Your question here",
+  tools: { queryTool },
 }).toDataStream();
 ```
 
 ## Next Steps
 
 1. Explore [LlamaCloud](https://cloud.llamaindex.ai/) for managed document storage and retrieval
-2. Join our [Discord community](https://discord.gg/llamaindex) for support and discussions
+2. Join our [Discord community](https://discord.gg/dGcwcsnxhU) for support and discussions
 

apps/next/src/content/docs/llamaindex/setup/typescript.mdx

@@ -84,7 +84,7 @@ Imaging you put output file into `/dist/openai.js` but you are importing `llamai
 }
 ```
 
-In old module resolution, TypeScript will not be able to find the module because it is not follow the file structure, even you run `node index.js` successfully. (on Node.js >=16)
+In old module resolution, TypeScript will not be able to find the module because it is not following the file structure, even you run `node index.js` successfully. (on Node.js >=16)
 
 See more about [moduleResolution](https://www.typescriptlang.org/docs/handbook/modules/theory.html#module-resolution) or
 [TypeScript 5.0 blog](https://devblogs.microsoft.com/typescript/announcing-typescript-5-0/#--moduleresolution-bundler7).

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

@@ -1,5 +1,13 @@
 # @llamaindex/cloudflare-worker-agent-test
 
+## 0.0.123
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+
 ## 0.0.122
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/cloudflare-worker-agent-test",
-  "version": "0.0.122",
+  "version": "0.0.123",
   "type": "module",
   "private": true,
   "scripts": {

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

@@ -1,5 +1,11 @@
 # @llamaindex/llama-parse-browser-test
 
+## 0.0.38
+
+### Patch Changes
+
+- @llamaindex/cloud@2.0.18
+
 ## 0.0.37
 
 ### Patch Changes

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

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/llama-parse-browser-test",
   "private": true,
-  "version": "0.0.37",
+  "version": "0.0.38",
   "type": "module",
   "scripts": {
     "dev": "vite",

e2e/examples/nextjs-agent/CHANGELOG.md

@@ -1,5 +1,13 @@
 # @llamaindex/next-agent-test
 
+## 0.1.123
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+
 ## 0.1.122
 
 ### Patch Changes

e2e/examples/nextjs-agent/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-agent-test",
-  "version": "0.1.122",
+  "version": "0.1.123",
   "private": true,
   "scripts": {
     "dev": "next dev",

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

@@ -1,5 +1,13 @@
 # test-edge-runtime
 
+## 0.1.122
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+
 ## 0.1.121
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/nextjs-edge-runtime-test",
-  "version": "0.1.121",
+  "version": "0.1.122",
   "private": true,
   "scripts": {
     "dev": "next dev",

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

@@ -1,5 +1,13 @@
 # @llamaindex/next-node-runtime
 
+## 0.0.104
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+
 ## 0.0.103
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-node-runtime-test",
-  "version": "0.0.103",
+  "version": "0.0.104",
   "private": true,
   "scripts": {
     "dev": "next dev",

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

@@ -1,5 +1,13 @@
 # @llamaindex/waku-query-engine-test
 
+## 0.0.123
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+
 ## 0.0.122
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/waku-query-engine-test",
-  "version": "0.0.122",
+  "version": "0.0.123",
   "type": "module",
   "private": true,
   "scripts": {

e2e/node/embedding/clip.e2e.ts

@@ -21,6 +21,11 @@ test.beforeEach(() => {
 });
 
 await test("clip embedding", async (t) => {
+  const major = parseInt(process.versions.node.split(".")[0] ?? "0", 10);
+  if (major < 20) {
+    t.skip("Skip CLIP tests on Node.js < 20");
+    return;
+  }
   await t.test("should trigger load transformer event", async () => {
     const nodes = [
       new ImageNode({

examples/CHANGELOG.md

@@ -1,5 +1,19 @@
 # examples
 
+## 0.0.20
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [086a651]
+- Updated dependencies [e0f6cc3]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+  - @llamaindex/vercel@0.0.5
+  - @llamaindex/core@0.4.18
+  - @llamaindex/readers@1.0.20
+  - @llamaindex/workflow@0.0.8
+
 ## 0.0.19
 
 ### Patch Changes

examples/ingestion/basicIngestion.ts

@@ -1,16 +1,15 @@
-import fs from "node:fs/promises";
-
 import {
   Document,
   IngestionPipeline,
-  MetadataMode,
   OpenAIEmbedding,
   SentenceSplitter,
+  VectorStoreIndex,
 } from "llamaindex";
+import fs from "node:fs/promises";
 
 async function main() {
   // Load essay from abramov.txt in Node
-  const path = "node_modules/llamaindex/examples/abramov.txt";
+  const path = "../node_modules/llamaindex/examples/abramov.txt";
 
   const essay = await fs.readFile(path, "utf-8");
 
@@ -22,14 +21,23 @@ async function main() {
       new OpenAIEmbedding(),
     ],
   });
+  console.time("Pipeline Run Time");
 
-  // run the pipeline
   const nodes = await pipeline.run({ documents: [document] });
 
-  // print out the result of the pipeline run
-  for (const node of nodes) {
-    console.log(node.getContent(MetadataMode.NONE));
-  }
+  console.timeEnd("Pipeline Run Time");
+
+  // initialize the VectorStoreIndex from nodes
+  const index = await VectorStoreIndex.init({ nodes });
+
+  // Query the index
+  const queryEngine = index.asQueryEngine();
+
+  const { message } = await queryEngine.query({
+    query: "summarize the article in three sentence",
+  });
+
+  console.log(message);
 }
 
 main().catch(console.error);

examples/package.json

@@ -1,17 +1,17 @@
 {
   "name": "@llamaindex/examples",
   "private": true,
-  "version": "0.0.19",
+  "version": "0.0.20",
   "dependencies": {
     "@ai-sdk/openai": "^1.0.5",
     "@aws-crypto/sha256-js": "^5.2.0",
     "@azure/cosmos": "^4.1.1",
     "@azure/identity": "^4.4.1",
     "@datastax/astra-db-ts": "^1.4.1",
-    "@llamaindex/core": "^0.4.17",
-    "@llamaindex/readers": "^1.0.19",
-    "@llamaindex/workflow": "^0.0.7",
-    "@llamaindex/vercel": "^0.0.4",
+    "@llamaindex/core": "^0.4.18",
+    "@llamaindex/readers": "^1.0.20",
+    "@llamaindex/workflow": "^0.0.8",
+    "@llamaindex/vercel": "^0.0.5",
     "@notionhq/client": "^2.2.15",
     "@pinecone-database/pinecone": "^4.0.0",
     "@vercel/postgres": "^0.10.0",
@@ -21,7 +21,7 @@
     "commander": "^12.1.0",
     "dotenv": "^16.4.5",
     "js-tiktoken": "^1.0.14",
-    "llamaindex": "^0.8.26",
+    "llamaindex": "^0.8.27",
     "mongodb": "^6.7.0",
     "pathe": "^1.1.2",
     "postgres": "^3.4.4"

examples/vercel/README.md

@@ -14,6 +14,16 @@ npm i
 
 Make sure to run the examples from the parent folder called `examples`. The following examples are available:
 
+### Vercel LLM Example
+
+Run the Vercel LLM example with:
+
+```bash
+npx tsx vercel/llm.ts
+```
+
+This example demonstrates using the `VercelLLM` adapter with Vercel's OpenAI model provider
+
 ### Vector Store Example
 
 Run the local vector store example with:

examples/vercel/llamacloud.ts

@@ -22,6 +22,7 @@ async function main() {
     prompt: "Cost of moving cat from Russia to UK?",
     tools: {
       queryTool: llamaindex({
+        model: openai("gpt-4o"),
         index,
         description:
           "get information from your knowledge base to answer questions.", // optional description

examples/vercel/llm.ts

@@ -0,0 +1,45 @@
+import { openai } from "@ai-sdk/openai";
+import { VercelLLM } from "@llamaindex/vercel";
+import { LLMAgent, WikipediaTool } from "llamaindex";
+
+async function main() {
+  // Create an instance of VercelLLM with the OpenAI model
+  const vercelLLM = new VercelLLM({ model: openai("gpt-4o") });
+
+  console.log("\n=== Test 1: Using complete() for single response ===");
+  const result = await vercelLLM.complete({
+    prompt: "What is the capital of France?",
+    stream: false, // Set to true if you want streaming responses
+  });
+  console.log(result.text);
+
+  console.log("\n=== Test 2: Using chat() for streaming response ===");
+  const stream = await vercelLLM.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);
+  }
+
+  console.log("\n=== Test 3: Using LLMAgent with WikipediaTool ===");
+  const agent = new LLMAgent({
+    llm: vercelLLM,
+    tools: [new WikipediaTool()],
+  });
+
+  const { message } = await agent.chat({
+    message: "What's the history of New York from Wikipedia in 3 sentences?",
+  });
+
+  console.log(message);
+}
+
+main().catch(console.error);

examples/vercel/vector-store.ts

@@ -18,6 +18,7 @@ async function main() {
     prompt: "Cost of moving cat from Russia to UK?",
     tools: {
       queryTool: llamaindex({
+        model: openai("gpt-4o"),
         index,
         description:
           "get information from your knowledge base to answer questions.", // optional description

packages/autotool/CHANGELOG.md

@@ -1,5 +1,13 @@
 # @llamaindex/autotool
 
+## 5.0.27
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+
 ## 5.0.26
 
 ### Patch Changes

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

@@ -1,5 +1,14 @@
 # @llamaindex/autotool-01-node-example
 
+## 0.0.70
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+  - @llamaindex/autotool@5.0.27
+
 ## 0.0.69
 
 ### 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": "0.0.69"
+  "version": "0.0.70"
 }

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

@@ -1,5 +1,14 @@
 # @llamaindex/autotool-02-next-example
 
+## 0.1.114
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+  - @llamaindex/autotool@5.0.27
+
 ## 0.1.113
 
 ### Patch Changes

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

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/autotool-02-next-example",
   "private": true,
-  "version": "0.1.113",
+  "version": "0.1.114",
   "scripts": {
     "dev": "next dev",
     "build": "next build",

packages/autotool/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/autotool",
   "type": "module",
-  "version": "5.0.26",
+  "version": "5.0.27",
   "description": "auto transpile your JS function to LLM Agent compatible",
   "files": [
     "dist",

packages/cloud/CHANGELOG.md

@@ -1,5 +1,14 @@
 # @llamaindex/cloud
 
+## 2.0.18
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+
 ## 2.0.17
 
 ### Patch Changes

packages/cloud/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/cloud",
-  "version": "2.0.17",
+  "version": "2.0.18",
   "type": "module",
   "license": "MIT",
   "scripts": {

packages/community/CHANGELOG.md

@@ -1,5 +1,15 @@
 # @llamaindex/community
 
+## 0.0.76
+
+### Patch Changes
+
+- c1850ee: feat: Amazon Nova support via Bedrock
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+
 ## 0.0.75
 
 ### Patch Changes

packages/community/README.md

@@ -4,6 +4,7 @@
 
 ## Current Features:
 
+- Bedrock support for Amazon Nova models Pro, Lite and Micro
 - Bedrock support for the Anthropic Claude Models [usage](https://ts.llamaindex.ai/modules/llms/available_llms/bedrock) including the latest Sonnet 3.5 v2 and Haiku 3.5
 - Bedrock support for the Meta LLama 2, 3, 3.1 and 3.2 Models [usage](https://ts.llamaindex.ai/modules/llms/available_llms/bedrock)
 - Meta LLama3.1 405b and Llama3.2 tool call support

packages/community/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/community",
   "description": "Community package for LlamaIndexTS",
-  "version": "0.0.75",
+  "version": "0.0.76",
   "type": "module",
   "types": "dist/type/index.d.ts",
   "main": "dist/cjs/index.js",
@@ -46,8 +46,8 @@
     "bunchee": "5.6.1"
   },
   "dependencies": {
-    "@aws-sdk/client-bedrock-agent-runtime": "^3.693.0",
-    "@aws-sdk/client-bedrock-runtime": "^3.693.0",
+    "@aws-sdk/client-bedrock-agent-runtime": "^3.706.0",
+    "@aws-sdk/client-bedrock-runtime": "^3.706.0",
     "@llamaindex/core": "workspace:*",
     "@llamaindex/env": "workspace:*"
   }

packages/community/src/llm/bedrock/amazon/provider.ts

@@ -0,0 +1,133 @@
+import type {
+  ContentBlockDelta,
+  ConverseOutput,
+  ConverseRequest,
+  ConverseResponse,
+  ConverseStreamOutput,
+  InvokeModelCommandInput,
+  InvokeModelWithResponseStreamCommandInput,
+  ResponseStream,
+} from "@aws-sdk/client-bedrock-runtime";
+import type {
+  BaseTool,
+  ChatMessage,
+  LLMMetadata,
+  ToolCall,
+  ToolCallLLMMessageOptions,
+} from "@llamaindex/core/llms";
+import { toUtf8 } from "../utils";
+
+import { Provider, type BedrockChatStreamResponse } from "../provider";
+import {
+  mapBaseToolsToAmazonTools,
+  mapChatMessagesToAmazonMessages,
+} from "./utils";
+
+export class AmazonProvider extends Provider<ConverseStreamOutput> {
+  getResultFromResponse(response: Record<string, any>): ConverseResponse {
+    return JSON.parse(toUtf8(response.body));
+  }
+
+  getToolsFromResponse<ToolContent>(response: ConverseOutput): ToolContent[] {
+    return (
+      response.message?.content
+        ?.filter((item) => item.toolUse)
+        .map(
+          (item) =>
+            ({
+              id: item.toolUse!.toolUseId,
+              name: item.toolUse!.name,
+              input: item.toolUse!.input
+                ? JSON.parse(item.toolUse!.input as string)
+                : "",
+            }) as ToolContent,
+        ) ?? []
+    );
+  }
+
+  getTextFromResponse(response: ConverseResponse): string {
+    const result = this.getResultFromResponse(response);
+    const content = result.output?.message?.content ?? [];
+    return content.map((item) => item.text).join(" ");
+  }
+
+  getTextFromStreamResponse(response: ResponseStream): string {
+    let event: ConverseStreamOutput | undefined =
+      this.getStreamingEventResponse(response);
+    if (!event || !event.contentBlockDelta) return "";
+    const delta: ContentBlockDelta | undefined = event.contentBlockDelta.delta;
+    return delta?.text || "";
+  }
+
+  async *reduceStream(
+    stream: AsyncIterable<ResponseStream>,
+  ): BedrockChatStreamResponse {
+    let toolId: string | undefined = undefined;
+    let toolName: string | undefined = undefined;
+    for await (const response of stream) {
+      const event = this.getStreamingEventResponse(response);
+      const delta = this.getTextFromStreamResponse(response);
+
+      let options: undefined | ToolCallLLMMessageOptions = undefined;
+      if (event?.contentBlockStart && event.contentBlockStart.start?.toolUse) {
+        toolId = event.contentBlockStart.start?.toolUse.toolUseId;
+        toolName = event.contentBlockStart.start?.toolUse.name;
+        continue;
+      }
+      if (
+        toolId &&
+        toolName &&
+        event?.contentBlockDelta?.delta?.toolUse?.input
+      ) {
+        options = {
+          toolCall: [
+            {
+              id: toolId,
+              name: toolName,
+              input: JSON.parse(event?.contentBlockDelta?.delta?.toolUse.input),
+            } as ToolCall,
+          ],
+        };
+        toolId = undefined;
+        toolName = undefined;
+      }
+
+      if (!delta && !options) continue;
+
+      yield {
+        delta: options ? "" : delta,
+        options,
+        raw: response,
+      };
+    }
+  }
+
+  getRequestBody<T extends ChatMessage>(
+    metadata: LLMMetadata,
+    messages: T[],
+    tools: BaseTool[] = [],
+    options: Omit<ConverseRequest, "modelId" | "messages" | "inferenceConfig">,
+  ): InvokeModelCommandInput | InvokeModelWithResponseStreamCommandInput {
+    const request: Omit<ConverseRequest, "modelId"> = {
+      ...options,
+      messages: mapChatMessagesToAmazonMessages(messages),
+      inferenceConfig: {
+        maxTokens: metadata.maxTokens,
+        temperature: metadata.temperature,
+        topP: metadata.topP,
+      },
+    };
+    if (tools.length) {
+      request.toolConfig = {
+        tools: mapBaseToolsToAmazonTools(tools),
+      };
+    }
+
+    return {
+      modelId: metadata.model,
+      contentType: "application/json",
+      accept: "application/json",
+      body: JSON.stringify(request),
+    };
+  }
+}

packages/community/src/llm/bedrock/amazon/types.ts

@@ -0,0 +1,5 @@
+import type { ConverseRequest, Message } from "@aws-sdk/client-bedrock-runtime";
+
+export type AmazonMessages = ConverseRequest["messages"];
+
+export type AmazonMessage = Message;

packages/community/src/llm/bedrock/amazon/utils.ts

@@ -0,0 +1,141 @@
+import type {
+  ImageBlock,
+  ImageFormat,
+  Message,
+  Tool,
+} from "@aws-sdk/client-bedrock-runtime";
+import type {
+  BaseTool,
+  ChatMessage,
+  MessageContentDetail,
+  ToolCallLLMMessageOptions,
+} from "@llamaindex/core/llms";
+import {
+  extractDataUrlComponents,
+  mapMessageContentToMessageContentDetails,
+} from "../utils";
+
+import type { JSONObject } from "@llamaindex/core/global";
+import type { AmazonMessage, AmazonMessages } from "./types";
+
+const ACCEPTED_IMAGE_MIME_TYPES = [
+  "image/jpeg",
+  "image/png",
+  "image/webp",
+  "image/gif",
+] as const;
+
+const ACCEPTED_IMAGE_MIME_TYPE_FORMAT_MAP: Record<
+  (typeof ACCEPTED_IMAGE_MIME_TYPES)[number],
+  ImageFormat
+> = {
+  "image/jpeg": "jpeg",
+  "image/png": "png",
+  "image/webp": "webp",
+  "image/gif": "gif",
+};
+
+export const mapImageContent = (imageUrl: string): ImageBlock => {
+  if (!imageUrl.startsWith("data:"))
+    throw new Error(
+      "For Amazon 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 as keyof typeof ACCEPTED_IMAGE_MIME_TYPE_FORMAT_MAP,
+    )
+  )
+    throw new Error(
+      `Amazon only accepts the following mimeTypes: ${ACCEPTED_IMAGE_MIME_TYPES.join("\n")}`,
+    );
+
+  return {
+    format:
+      ACCEPTED_IMAGE_MIME_TYPE_FORMAT_MAP[
+        mimeType as keyof typeof ACCEPTED_IMAGE_MIME_TYPE_FORMAT_MAP
+      ],
+
+    // @ts-ignore: there's a mistake in the "@aws-sdk/client-bedrock-runtime" compared to the actual api
+    source: { bytes: data },
+  };
+};
+
+export const mapMessageContentDetailToAmazonContent = <
+  T extends MessageContentDetail,
+>(
+  detail: T,
+): Message["content"] => {
+  let content: Message["content"] = [];
+
+  if (detail.type === "text") {
+    content = [{ text: detail.text }];
+  } else if (detail.type === "image_url") {
+    content = [{ image: mapImageContent(detail.image_url.url) }];
+  } else {
+    throw new Error("Unsupported content detail type");
+  }
+  return content;
+};
+
+export const mapChatMessagesToAmazonMessages = <
+  T extends ChatMessage<ToolCallLLMMessageOptions>,
+>(
+  messages: T[],
+): AmazonMessages => {
+  return messages.flatMap((msg: T): AmazonMessage[] => {
+    return mapMessageContentToMessageContentDetails(msg.content).map(
+      (detail: MessageContentDetail): AmazonMessage => {
+        if (msg.options && "toolCall" in msg.options) {
+          return {
+            role: "assistant",
+            content: msg.options.toolCall.map((call) => ({
+              toolUse: {
+                toolUseId: call.id,
+                name: call.name,
+                input: call.input as JSONObject,
+              },
+            })),
+          };
+        }
+        if (msg.options && "toolResult" in msg.options) {
+          return {
+            role: "user",
+            content: [
+              {
+                toolResult: {
+                  toolUseId: msg.options.toolResult.id,
+                  content: [
+                    {
+                      text: msg.options.toolResult.result,
+                    },
+                  ],
+                },
+              },
+            ],
+          };
+        }
+
+        return {
+          role: msg.role === "assistant" ? "assistant" : "user",
+          content: mapMessageContentDetailToAmazonContent(detail),
+        };
+      },
+    );
+  });
+};
+
+export const mapBaseToolsToAmazonTools = (tools?: BaseTool[]): Tool[] => {
+  if (!tools) return [];
+  return tools.map((tool: BaseTool) => {
+    const {
+      metadata: { parameters, ...options },
+    } = tool;
+    return {
+      toolSpec: {
+        ...options,
+        inputSchema: parameters,
+      },
+    } as Tool;
+  });
+};

packages/community/src/llm/bedrock/anthropic/provider.ts

@@ -11,13 +11,10 @@ import type {
   ToolCall,
   ToolCallLLMMessageOptions,
 } from "@llamaindex/core/llms";
-import {
-  type BedrockAdditionalChatOptions,
-  type BedrockChatStreamResponse,
-  Provider,
-} from "../provider";
+import { type BedrockChatStreamResponse, Provider } from "../provider";
 import { toUtf8 } from "../utils";
 import type {
+  AnthropicAdditionalChatOptions,
   AnthropicNoneStreamingResponse,
   AnthropicStreamEvent,
   AnthropicTextContent,
@@ -134,7 +131,7 @@ export class AnthropicProvider extends Provider<AnthropicStreamEvent> {
     metadata: LLMMetadata,
     messages: T[],
     tools?: BaseTool[],
-    options?: BedrockAdditionalChatOptions,
+    options?: AnthropicAdditionalChatOptions,
   ): InvokeModelCommandInput | InvokeModelWithResponseStreamCommandInput {
     const extra: Record<string, unknown> = {};
     if (options?.toolChoice) {

packages/community/src/llm/bedrock/anthropic/types.ts

@@ -1,6 +1,13 @@
 import type { ToolMetadata } from "@llamaindex/core/llms";
 import type { InvocationMetrics } from "../types";
 
+export type ToolChoice =
+  | { type: "any" }
+  | { type: "auto" }
+  | { type: "tool"; name: string };
+
+export type AnthropicAdditionalChatOptions = { toolChoice: ToolChoice };
+
 type Usage = {
   input_tokens: number;
   output_tokens: number;

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

@@ -25,6 +25,7 @@ import {
 import { mapMessageContentToMessageContentDetails } from "./utils";
 
 import { wrapLLMEvent } from "@llamaindex/core/decorator";
+import { AmazonProvider } from "./amazon/provider";
 import { AnthropicProvider } from "./anthropic/provider";
 import { MetaProvider } from "./meta/provider";
 
@@ -32,6 +33,7 @@ import { MetaProvider } from "./meta/provider";
 export const PROVIDERS: { [key: string]: Provider } = {
   anthropic: new AnthropicProvider(),
   meta: new MetaProvider(),
+  amazon: new AmazonProvider(),
 };
 
 export type BedrockChatParamsStreaming = LLMChatParamsStreaming<
@@ -81,7 +83,11 @@ export const BEDROCK_MODELS = {
   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",
+  AMAZON_NOVA_PRO_1: "amazon.nova-pro-v1:0",
+  AMAZON_NOVA_LITE_1: "amazon.nova-lite-v1:0",
+  AMAZON_NOVA_MICRO_1: "amazon.nova-micro-v1:0",
 };
+
 export type BEDROCK_MODELS =
   (typeof BEDROCK_MODELS)[keyof typeof BEDROCK_MODELS];
 
@@ -98,6 +104,9 @@ 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_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",
 
   EU_ANTHROPIC_CLAUDE_3_HAIKU: "eu.anthropic.claude-3-haiku-20240307-v1:0",
   EU_ANTHROPIC_CLAUDE_3_5_HAIKU: "eu.anthropic.claude-3-5-haiku-20240307-v1:0",
@@ -189,6 +198,9 @@ const CHAT_ONLY_MODELS = {
   [BEDROCK_MODELS.MISTRAL_7B_INSTRUCT]: 32000,
   [BEDROCK_MODELS.MISTRAL_MIXTRAL_7B_INSTRUCT]: 32000,
   [BEDROCK_MODELS.MISTRAL_MIXTRAL_LARGE_2402]: 32000,
+  [BEDROCK_MODELS.AMAZON_NOVA_PRO_1]: 300000,
+  [BEDROCK_MODELS.AMAZON_NOVA_LITE_1]: 300000,
+  [BEDROCK_MODELS.AMAZON_NOVA_MICRO_1]: 130000,
 };
 
 const BEDROCK_FOUNDATION_LLMS = { ...COMPLETION_MODELS, ...CHAT_ONLY_MODELS };
@@ -225,6 +237,9 @@ export const STREAMING_MODELS = new Set([
   BEDROCK_MODELS.MISTRAL_7B_INSTRUCT,
   BEDROCK_MODELS.MISTRAL_MIXTRAL_7B_INSTRUCT,
   BEDROCK_MODELS.MISTRAL_MIXTRAL_LARGE_2402,
+  BEDROCK_MODELS.AMAZON_NOVA_PRO_1,
+  BEDROCK_MODELS.AMAZON_NOVA_LITE_1,
+  BEDROCK_MODELS.AMAZON_NOVA_MICRO_1,
 ]);
 
 export const TOOL_CALL_MODELS: BEDROCK_MODELS[] = [
@@ -239,6 +254,9 @@ 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.AMAZON_NOVA_PRO_1,
+  BEDROCK_MODELS.AMAZON_NOVA_LITE_1,
+  BEDROCK_MODELS.AMAZON_NOVA_MICRO_1,
 ];
 
 const getProvider = (model: string): Provider => {
@@ -320,10 +338,6 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
     this.temperature = temperature ?? DEFAULT_BEDROCK_PARAMS.temperature;
     this.topP = topP ?? DEFAULT_BEDROCK_PARAMS.topP;
     this.client = new BedrockRuntimeClient(params);
-
-    if (!this.supportToolCall) {
-      console.warn(`The model "${this.model}" doesn't support ToolCall`);
-    }
   }
 
   get supportToolCall(): boolean {
@@ -345,6 +359,9 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
   protected async nonStreamChat(
     params: BedrockChatParamsNonStreaming,
   ): Promise<BedrockChatNonStreamResponse> {
+    if (!this.supportToolCall && params.tools?.length) {
+      console.warn(`The model "${this.model}" doesn't support ToolCall`);
+    }
     const input = this.provider.getRequestBody(
       this.metadata,
       params.messages,
@@ -378,6 +395,10 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
     if (!STREAMING_MODELS.has(this.model))
       throw new Error(`The model: ${this.model} does not support streaming`);
 
+    if (!this.supportToolCall && params.tools?.length) {
+      console.warn(`The model "${this.model}" doesn't support ToolCall`);
+    }
+
     const input = this.provider.getRequestBody(
       this.metadata,
       params.messages,
@@ -388,7 +409,6 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
     command.input.modelId = this.actualModel;
 
     const response = await this.client.send(command);
-
     if (response.body) yield* this.provider.reduceStream(response.body);
   }
 

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

@@ -11,10 +11,9 @@ import {
   type ToolCallLLMMessageOptions,
 } from "@llamaindex/core/llms";
 import { streamConverter } from "@llamaindex/core/utils";
-import type { ToolChoice } from "./types";
 import { toUtf8 } from "./utils";
 
-export type BedrockAdditionalChatOptions = { toolChoice: ToolChoice };
+export type BedrockAdditionalChatOptions = Record<string, unknown>;
 
 export type BedrockChatStreamResponse = AsyncIterable<
   ChatResponseChunk<ToolCallLLMMessageOptions>

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

@@ -4,8 +4,3 @@ export type InvocationMetrics = {
   invocationLatency: number;
   firstByteLatency: number;
 };
-
-export type ToolChoice =
-  | { type: "any" }
-  | { type: "auto" }
-  | { type: "tool"; name: string };

packages/core/CHANGELOG.md

@@ -1,5 +1,13 @@
 # @llamaindex/core
 
+## 0.4.18
+
+### Patch Changes
+
+- e0f6cc3: The compact and refine response synthesizer (retrieved by using `getResponseSynthesizer('compact')`) has been fixed to return the original source nodes that were provided to it in its response. Previous to this it was returning the compacted text chunk documents.
+- Updated dependencies [b504303]
+  - @llamaindex/env@0.1.25
+
 ## 0.4.17
 
 ### Patch Changes

packages/core/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/core",
   "type": "module",
-  "version": "0.4.17",
+  "version": "0.4.18",
   "description": "LlamaIndex Core Module",
   "exports": {
     "./agent": {

packages/core/src/response-synthesizers/factory.ts

@@ -77,6 +77,16 @@ class Refine extends BaseSynthesizer {
     }
   }
 
+  async getResponse(
+    query: MessageContent,
+    nodes: NodeWithScore[],
+    stream: true,
+  ): Promise<AsyncIterable<EngineResponse>>;
+  async getResponse(
+    query: MessageContent,
+    nodes: NodeWithScore[],
+    stream: false,
+  ): Promise<EngineResponse>;
   async getResponse(
     query: MessageContent,
     nodes: NodeWithScore[],
@@ -197,6 +207,16 @@ class Refine extends BaseSynthesizer {
  * CompactAndRefine is a slight variation of Refine that first compacts the text chunks into the smallest possible number of chunks.
  */
 class CompactAndRefine extends Refine {
+  async getResponse(
+    query: MessageContent,
+    nodes: NodeWithScore[],
+    stream: true,
+  ): Promise<AsyncIterable<EngineResponse>>;
+  async getResponse(
+    query: MessageContent,
+    nodes: NodeWithScore[],
+    stream: false,
+  ): Promise<EngineResponse>;
   async getResponse(
     query: MessageContent,
     nodes: NodeWithScore[],
@@ -216,17 +236,24 @@ class CompactAndRefine extends Refine {
     const newTexts = this.promptHelper.repack(maxPrompt, textChunks);
     const newNodes = newTexts.map((text) => new TextNode({ text }));
     if (stream) {
-      return super.getResponse(
+      const streamResponse = await super.getResponse(
         query,
         newNodes.map((node) => ({ node })),
         true,
       );
+      return streamConverter(streamResponse, (chunk) => {
+        chunk.sourceNodes = nodes;
+        return chunk;
+      });
     }
-    return super.getResponse(
+
+    const originalResponse = await super.getResponse(
       query,
       newNodes.map((node) => ({ node })),
       false,
     );
+    originalResponse.sourceNodes = nodes;
+    return originalResponse;
   }
 }
 

packages/core/tests/response-synthesizers/compact-and-refine.test.ts

@@ -0,0 +1,66 @@
+import { describe, expect, test, vi } from "vitest";
+import type { LLMMetadata } from "../../llms/dist/index.js";
+import { getResponseSynthesizer } from "../../response-synthesizers/dist/index.js";
+import { Document } from "../../schema/dist/index.js";
+
+const mockLllm = () => ({
+  complete: vi.fn().mockImplementation(({ stream }) => {
+    const response = { text: "unimportant" };
+    if (!stream) {
+      return response;
+    }
+
+    function* gen() {
+      // yield a few times to make sure each chunk has the sourceNodes
+      yield response;
+      yield response;
+      yield response;
+    }
+
+    return gen();
+  }),
+  chat: vi.fn(),
+  metadata: {} as unknown as LLMMetadata,
+});
+
+describe("compact and refine response synthesizer", () => {
+  describe("synthesize", () => {
+    test("should return original sourceNodes with response when stream = false", async () => {
+      const synthesizer = getResponseSynthesizer("compact", {
+        llm: mockLllm(),
+      });
+
+      const sourceNode = { node: new Document({}), score: 1 };
+
+      const response = await synthesizer.synthesize(
+        {
+          query: "test",
+          nodes: [sourceNode],
+        },
+        false,
+      );
+
+      expect(response.sourceNodes).toEqual([sourceNode]);
+    });
+
+    test("should return original sourceNodes with response when stream = true", async () => {
+      const synthesizer = getResponseSynthesizer("compact", {
+        llm: mockLllm(),
+      });
+
+      const sourceNode = { node: new Document({}), score: 1 };
+
+      const response = await synthesizer.synthesize(
+        {
+          query: "test",
+          nodes: [sourceNode],
+        },
+        true,
+      );
+
+      for await (const chunk of response) {
+        expect(chunk.sourceNodes).toEqual([sourceNode]);
+      }
+    });
+  });
+});

packages/env/CHANGELOG.md

@@ -1,5 +1,11 @@
 # @llamaindex/env
 
+## 0.1.25
+
+### Patch Changes
+
+- b504303: Allow Node 18 again (throw run-time error if not possible) to make Stackblitz work
+
 ## 0.1.24
 
 ### 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": "0.1.24",
+  "version": "0.1.25",
   "type": "module",
   "types": "dist/index.d.ts",
   "module": "dist/index.js",

packages/env/src/internal/multi-model/node.ts

@@ -7,6 +7,13 @@ export {
 } from "./shared.js";
 
 export async function loadTransformers(onLoad: OnLoad) {
+  const nodeVersions = process.versions.node.split(".");
+  if (nodeVersions[0] && parseInt(nodeVersions[0], 10) < 20) {
+    throw new Error(
+      "@huggingface/transformers is not supported on Node.js versions below 20",
+    );
+  }
+
   if (getTransformers() === null) {
     setTransformers(await import("@huggingface/transformers"));
   } else {

packages/experimental/CHANGELOG.md

@@ -1,5 +1,13 @@
 # @llamaindex/experimental
 
+## 0.0.139
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+
 ## 0.0.138
 
 ### Patch Changes

packages/experimental/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/experimental",
   "description": "Experimental package for LlamaIndexTS",
-  "version": "0.0.138",
+  "version": "0.0.139",
   "type": "module",
   "types": "dist/type/index.d.ts",
   "main": "dist/cjs/index.js",

packages/llamaindex/CHANGELOG.md

@@ -1,5 +1,29 @@
 # llamaindex
 
+## 0.8.27
+
+### Patch Changes
+
+- b504303: Allow Node 18 again (throw run-time error if not possible) to make Stackblitz work
+- a0e6f57: withLlamaIndex now passes through webpack options to the passed in customized NextJS webpack config. Before it was only passing through the config.
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+  - @llamaindex/cloud@2.0.18
+  - @llamaindex/node-parser@0.0.19
+  - @llamaindex/anthropic@0.0.27
+  - @llamaindex/clip@0.0.27
+  - @llamaindex/deepinfra@0.0.27
+  - @llamaindex/groq@0.0.42
+  - @llamaindex/huggingface@0.0.27
+  - @llamaindex/ollama@0.0.34
+  - @llamaindex/openai@0.1.43
+  - @llamaindex/portkey-ai@0.0.27
+  - @llamaindex/replicate@0.0.27
+  - @llamaindex/readers@1.0.20
+  - @llamaindex/vllm@0.0.13
+
 ## 0.8.26
 
 ### Patch Changes

packages/llamaindex/package.json

@@ -1,6 +1,6 @@
 {
   "name": "llamaindex",
-  "version": "0.8.26",
+  "version": "0.8.27",
   "license": "MIT",
   "type": "module",
   "keywords": [
@@ -86,7 +86,6 @@
     }
   },
   "devDependencies": {
-    "@huggingface/transformers": "^3.0.2",
     "@swc/cli": "^0.5.0",
     "@swc/core": "^1.9.2",
     "@vercel/postgres": "^0.10.0",
@@ -98,7 +97,7 @@
     "typescript": "^5.6.3"
   },
   "engines": {
-    "node": ">=20.0.0"
+    "node": ">=18.0.0"
   },
   "types": "./dist/type/index.d.ts",
   "main": "./dist/cjs/index.js",

packages/llamaindex/src/next.ts

@@ -41,7 +41,7 @@ export default function withLlamaIndex(config: any) {
   // eslint-disable-next-line @typescript-eslint/no-explicit-any
   config.webpack = function (webpackConfig: any, options: any) {
     if (userWebpack) {
-      webpackConfig = userWebpack(webpackConfig);
+      webpackConfig = userWebpack(webpackConfig, options);
     }
     webpackConfig.resolve.alias = {
       ...webpackConfig.resolve.alias,

packages/node-parser/CHANGELOG.md

@@ -1,5 +1,14 @@
 # @llamaindex/node-parser
 
+## 0.0.19
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+
 ## 0.0.18
 
 ### Patch Changes

packages/node-parser/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/node-parser",
-  "version": "0.0.18",
+  "version": "0.0.19",
   "description": "Node parser for LlamaIndex",
   "type": "module",
   "exports": {

packages/providers/anthropic/CHANGELOG.md

@@ -1,5 +1,14 @@
 # @llamaindex/anthropic
 
+## 0.0.27
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+
 ## 0.0.26
 
 ### Patch Changes

packages/providers/anthropic/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/anthropic",
   "description": "Anthropic Adapter for LlamaIndex",
-  "version": "0.0.26",
+  "version": "0.0.27",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/clip/CHANGELOG.md

@@ -1,5 +1,15 @@
 # @llamaindex/clip
 
+## 0.0.27
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+  - @llamaindex/openai@0.1.43
+
 ## 0.0.26
 
 ### Patch Changes

packages/providers/clip/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/clip",
   "description": "Clip Embedding Adapter for LlamaIndex",
-  "version": "0.0.26",
+  "version": "0.0.27",
   "type": "module",
   "types": "dist/index.d.ts",
   "main": "dist/index.cjs",

packages/providers/deepinfra/CHANGELOG.md

@@ -1,5 +1,15 @@
 # @llamaindex/deepinfra
 
+## 0.0.27
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+  - @llamaindex/openai@0.1.43
+
 ## 0.0.26
 
 ### Patch Changes

packages/providers/deepinfra/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/deepinfra",
   "description": "Deepinfra Adapter for LlamaIndex",
-  "version": "0.0.26",
+  "version": "0.0.27",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/groq/CHANGELOG.md

@@ -1,5 +1,13 @@
 # @llamaindex/groq
 
+## 0.0.42
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/openai@0.1.43
+
 ## 0.0.41
 
 ### Patch Changes

packages/providers/groq/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/groq",
   "description": "Groq Adapter for LlamaIndex",
-  "version": "0.0.41",
+  "version": "0.0.42",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/huggingface/CHANGELOG.md

@@ -1,5 +1,15 @@
 # @llamaindex/huggingface
 
+## 0.0.27
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+  - @llamaindex/openai@0.1.43
+
 ## 0.0.26
 
 ### Patch Changes

packages/providers/huggingface/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/huggingface",
   "description": "Huggingface Adapter for LlamaIndex",
-  "version": "0.0.26",
+  "version": "0.0.27",
   "type": "module",
   "types": "dist/index.d.ts",
   "main": "dist/index.cjs",

packages/providers/ollama/CHANGELOG.md

@@ -1,5 +1,14 @@
 # @llamaindex/ollama
 
+## 0.0.34
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+
 ## 0.0.33
 
 ### Patch Changes

packages/providers/ollama/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/ollama",
   "description": "Ollama Adapter for LlamaIndex",
-  "version": "0.0.33",
+  "version": "0.0.34",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/openai/CHANGELOG.md

@@ -1,5 +1,14 @@
 # @llamaindex/openai
 
+## 0.1.43
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+
 ## 0.1.42
 
 ### Patch Changes

packages/providers/openai/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/openai",
   "description": "OpenAI Adapter for LlamaIndex",
-  "version": "0.1.42",
+  "version": "0.1.43",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/portkey-ai/CHANGELOG.md

@@ -1,5 +1,14 @@
 # @llamaindex/portkey-ai
 
+## 0.0.27
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+
 ## 0.0.26
 
 ### Patch Changes

packages/providers/portkey-ai/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/portkey-ai",
   "description": "Portkey Adapter for LlamaIndex",
-  "version": "0.0.26",
+  "version": "0.0.27",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/replicate/CHANGELOG.md

@@ -1,5 +1,14 @@
 # @llamaindex/replicate
 
+## 0.0.27
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+
 ## 0.0.26
 
 ### Patch Changes

packages/providers/replicate/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/replicate",
   "description": "Replicate Adapter for LlamaIndex",
-  "version": "0.0.26",
+  "version": "0.0.27",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/vercel/CHANGELOG.md

@@ -1,5 +1,13 @@
 # @llamaindex/vercel
 
+## 0.0.5
+
+### Patch Changes
+
+- 086a651: Add VercelLLM (adapter to use any model provider from Vercel AI in LlamaIndex)
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/core@0.4.18
+
 ## 0.0.4
 
 ### Patch Changes

packages/providers/vercel/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/vercel",
   "description": "Vercel Adapter for LlamaIndex",
-  "version": "0.0.4",
+  "version": "0.0.5",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/providers/vercel/src/index.ts

@@ -1 +1,2 @@
+export { VercelLLM } from "./llm";
 export { llamaindex } from "./tool";

packages/providers/vercel/src/llm.ts

@@ -0,0 +1,183 @@
+import { wrapEventCaller, wrapLLMEvent } from "@llamaindex/core/decorator";
+import {
+  ToolCallLLM,
+  type ChatMessage,
+  type ChatResponse,
+  type ChatResponseChunk,
+  type LLMChatParamsNonStreaming,
+  type LLMChatParamsStreaming,
+  type LLMMetadata,
+  type ToolCallLLMMessageOptions,
+} from "@llamaindex/core/llms";
+import { extractText } from "@llamaindex/core/utils";
+import {
+  generateText,
+  streamText,
+  type CoreAssistantMessage,
+  type CoreMessage,
+  type CoreSystemMessage,
+  type CoreToolMessage,
+  type CoreUserMessage,
+  type ImagePart,
+  type LanguageModelV1,
+  type TextPart,
+} from "ai";
+
+export type VercelAdditionalChatOptions = ToolCallLLMMessageOptions;
+
+export class VercelLLM extends ToolCallLLM<VercelAdditionalChatOptions> {
+  supportToolCall: boolean = true;
+  private model: LanguageModelV1;
+
+  constructor({ model }: { model: LanguageModelV1 }) {
+    super();
+    this.model = model;
+  }
+
+  get metadata(): LLMMetadata {
+    return {
+      model: this.model.modelId,
+      temperature: 1,
+      topP: 1,
+      contextWindow: 128000,
+      tokenizer: undefined,
+    };
+  }
+
+  private toVercelMessages(
+    messages: ChatMessage<ToolCallLLMMessageOptions>[],
+  ): CoreMessage[] {
+    return messages.map((message) => {
+      const options = message.options ?? {};
+
+      if ("toolResult" in options) {
+        return {
+          role: "tool",
+          content: [
+            {
+              type: "tool-result",
+              toolCallId: options.toolResult.id,
+              toolName: "", // XXX: tool result doesn't name
+              isError: options.toolResult.isError,
+              result: options.toolResult.result,
+            },
+          ],
+        } satisfies CoreToolMessage;
+      } else if ("toolCall" in options) {
+        return {
+          role: "assistant",
+          content: options.toolCall.map((toolCall) => ({
+            type: "tool-call",
+            toolName: toolCall.name,
+            toolCallId: toolCall.id,
+            args: toolCall.input,
+          })),
+        } satisfies CoreAssistantMessage;
+      }
+
+      if (message.role === "system" || message.role === "assistant") {
+        return {
+          role: message.role,
+          content: extractText(message.content),
+        } satisfies CoreSystemMessage | CoreAssistantMessage;
+      }
+
+      if (message.role === "user") {
+        return {
+          role: message.role,
+          content:
+            typeof message.content === "string"
+              ? message.content
+              : message.content.map((contentDetail) => {
+                  if (contentDetail.type === "image_url") {
+                    return {
+                      type: "image",
+                      image: new URL(contentDetail.image_url.url),
+                    } satisfies ImagePart;
+                  }
+                  return {
+                    type: "text",
+                    text: contentDetail.text,
+                  } satisfies TextPart;
+                }),
+        } satisfies CoreUserMessage;
+      }
+
+      throw new Error(`Can not convert message ${JSON.stringify(message)}`);
+    });
+  }
+
+  chat(
+    params: LLMChatParamsStreaming<
+      VercelAdditionalChatOptions,
+      ToolCallLLMMessageOptions
+    >,
+  ): Promise<AsyncIterable<ChatResponseChunk<ToolCallLLMMessageOptions>>>;
+  chat(
+    params: LLMChatParamsNonStreaming<
+      VercelAdditionalChatOptions,
+      ToolCallLLMMessageOptions
+    >,
+  ): Promise<ChatResponse<ToolCallLLMMessageOptions>>;
+  @wrapEventCaller
+  @wrapLLMEvent
+  async chat(
+    params:
+      | LLMChatParamsNonStreaming<
+          VercelAdditionalChatOptions,
+          ToolCallLLMMessageOptions
+        >
+      | LLMChatParamsStreaming<
+          VercelAdditionalChatOptions,
+          ToolCallLLMMessageOptions
+        >,
+  ): Promise<
+    | ChatResponse<ToolCallLLMMessageOptions>
+    | AsyncIterable<ChatResponseChunk<ToolCallLLMMessageOptions>>
+  > {
+    const { messages, stream } = params;
+
+    // Streaming
+    if (stream) {
+      const result = streamText({
+        model: this.model,
+        messages: this.toVercelMessages(messages),
+      });
+      return result.fullStream.pipeThrough(
+        new TransformStream({
+          async transform(message, controller): Promise<void> {
+            switch (message.type) {
+              case "text-delta":
+                controller.enqueue({ raw: message, delta: message.textDelta });
+            }
+          },
+        }),
+      );
+    }
+
+    // Non-streaming
+    const result = await generateText({
+      model: this.model,
+      messages: this.toVercelMessages(messages),
+    });
+
+    return {
+      raw: result,
+      message: {
+        content: result.text,
+        role: "assistant",
+        options: result.toolCalls?.length
+          ? {
+              toolCall: result.toolCalls.map(
+                ({ toolCallId, toolName, args }) => ({
+                  id: toolCallId,
+                  name: toolName,
+                  input: args,
+                }),
+              ),
+            }
+          : {},
+      },
+    };
+  }
+}

packages/providers/vercel/src/tool.ts

@@ -1,29 +1,36 @@
+import { Settings } from "@llamaindex/core/global";
 import type { BaseQueryEngine } from "@llamaindex/core/query-engine";
-import { type CoreTool, tool } from "ai";
+import { type CoreTool, type LanguageModelV1, tool } from "ai";
 import { z } from "zod";
+import { VercelLLM } from "./llm";
 
 interface DatasourceIndex {
   asQueryEngine: () => BaseQueryEngine;
 }
 
 export function llamaindex({
+  model,
   index,
   description,
 }: {
+  model: LanguageModelV1;
   index: DatasourceIndex;
   description?: string;
 }): CoreTool {
-  const queryEngine = index.asQueryEngine();
-  return tool({
-    description: description ?? "Get information about your documents.",
-    parameters: z.object({
-      query: z
-        .string()
-        .describe("The query to get information about your documents."),
-    }),
-    execute: async ({ query }) => {
-      const result = await queryEngine?.query({ query });
-      return result?.message.content ?? "No result found in documents.";
-    },
+  const llm = new VercelLLM({ model });
+  return Settings.withLLM<CoreTool>(llm, () => {
+    const queryEngine = index.asQueryEngine();
+    return tool({
+      description: description ?? "Get information about your documents.",
+      parameters: z.object({
+        query: z
+          .string()
+          .describe("The query to get information about your documents."),
+      }),
+      execute: async ({ query }) => {
+        const result = await queryEngine?.query({ query });
+        return result?.message.content ?? "No result found in documents.";
+      },
+    });
   });
 }

packages/providers/vllm/CHANGELOG.md

@@ -1,5 +1,11 @@
 # @llamaindex/vllm
 
+## 0.0.13
+
+### Patch Changes
+
+- @llamaindex/openai@0.1.43
+
 ## 0.0.12
 
 ### Patch Changes

packages/providers/vllm/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/vllm",
   "description": "vLLM Adapter for LlamaIndex",
-  "version": "0.0.12",
+  "version": "0.0.13",
   "type": "module",
   "main": "./dist/index.cjs",
   "module": "./dist/index.js",

packages/readers/CHANGELOG.md

@@ -1,5 +1,14 @@
 # @llamaindex/readers
 
+## 1.0.20
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+  - @llamaindex/env@0.1.25
+  - @llamaindex/core@0.4.18
+
 ## 1.0.19
 
 ### Patch Changes

packages/readers/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/readers",
   "description": "LlamaIndex Readers",
-  "version": "1.0.19",
+  "version": "1.0.20",
   "type": "module",
   "exports": {
     "./node/hook": "./node/dist/hook.js",

packages/workflow/CHANGELOG.md

@@ -1,5 +1,12 @@
 # @llamaindex/workflow
 
+## 0.0.8
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+  - @llamaindex/env@0.1.25
+
 ## 0.0.7
 
 ### Patch Changes

packages/workflow/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/workflow",
   "description": "Workflow API",
-  "version": "0.0.7",
+  "version": "0.0.8",
   "type": "module",
   "types": "dist/index.d.ts",
   "module": "dist/index.js",
@@ -54,7 +54,11 @@
     "build": "bunchee"
   },
   "devDependencies": {
+    "@llamaindex/env": "workspace:*",
     "@types/node": "^22.9.0",
     "bunchee": "5.6.1"
+  },
+  "peerDependencies": {
+    "@llamaindex/env": "workspace:*"
   }
 }

packages/workflow/src/workflow-context.ts

@@ -1,3 +1,4 @@
+import { CustomEvent, randomUUID } from "@llamaindex/env";
 import {
   type AnyWorkflowEventConstructor,
   StartEvent,
@@ -231,7 +232,7 @@ export class WorkflowContext<Start = string, Stop = string, Data = unknown>
   #requireEvent = async <T extends AnyWorkflowEventConstructor>(
     event: T,
   ): Promise<InstanceType<T>> => {
-    const requestId = crypto.randomUUID();
+    const requestId = randomUUID();
     this.#queue.push({
       type: "requestEvent",
       id: requestId,

packages/workflow/tsconfig.json

@@ -7,6 +7,7 @@
     "emitDeclarationOnly": true,
     "module": "ESNext",
     "moduleResolution": "bundler",
+    "skipLibCheck": true,
     "types": ["node"],
     "resolveJsonModule": true
   },

unit/CHANGELOG.md

@@ -1,5 +1,20 @@
 # @llamaindex/unit-test
 
+## 0.0.37
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+  - @llamaindex/core@0.4.18
+  - @llamaindex/cloud@2.0.18
+  - @llamaindex/node-parser@0.0.19
+  - @llamaindex/openai@0.1.43
+  - @llamaindex/readers@1.0.20
+  - @llamaindex/workflow@0.0.8
+
 ## 0.0.36
 
 ### Patch Changes

unit/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/unit-test",
   "private": true,
-  "version": "0.0.36",
+  "version": "0.0.37",
   "type": "module",
   "scripts": {
     "test": "vitest run"