Avoid using window deployment name on localhost, as that is conventional to default ot public. Optionally read deployment name from env vars as well

add changeset
feat: default to _public agent data
2026-07-15 06:52:45 -04:00 · 2025-07-21 11:28:15 -04:00 · 2025-07-18 19:37:40 -04:00 · 2025-07-18 19:30:14 -04:00
152 changed files with 228 additions and 2150 deletions
@@ -0,0 +1,5 @@
+---
+"@llamaindex/cloud": patch
+---
+
+Default to \_public agent url id
@@ -1,40 +1,5 @@
 # @llamaindex/doc

-## 0.2.44
-
-### Patch Changes
-
- 38da40b: feat: VectoryMemoryBlock
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-  - @llamaindex/cloud@4.0.26
-  - llamaindex@0.11.21
-  - @llamaindex/node-parser@2.0.17
-  - @llamaindex/openai@0.4.12
-  - @llamaindex/readers@3.1.16
-  - @llamaindex/workflow@1.1.17
-
-## 0.2.43
-
-### Patch Changes
-
- ea15e75: Minor updates in deployment docs
-
-## 0.2.42
-
-### Patch Changes
-
- a8ec08c: fix: ensure correct message content in agent workflow
- Updated dependencies [a8ec08c]
- Updated dependencies [2967d57]
-  - @llamaindex/core@0.6.16
-  - @llamaindex/workflow@1.1.16
-  - @llamaindex/cloud@4.0.25
-  - llamaindex@0.11.20
-  - @llamaindex/node-parser@2.0.16
-  - @llamaindex/openai@0.4.11
-  - @llamaindex/readers@3.1.15
-
 ## 0.2.41

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/doc",
-  "version": "0.2.44",
+  "version": "0.2.41",
  "private": true,
  "scripts": {
    "postinstall": "fumadocs-mdx",
@@ -1,6 +1,6 @@
 import { AIProvider } from "@/actions";
 import { TooltipProvider } from "@/components/ui/tooltip";
-import { GoogleAnalytics, GoogleTagManager } from "@next/third-parties/google";
+import { GoogleAnalytics } from "@next/third-parties/google";
 import { RootProvider } from "fumadocs-ui/provider";
 import { Inter } from "next/font/google";
 import type { ReactNode } from "react";
@@ -36,7 +36,6 @@ export default function Layout({ children }: { children: ReactNode }) {
          LlamaIndex.TS - Build LLM-powered document agents and workflows
        </title>
      </head>
-      <GoogleTagManager gtmId="GTM-WWRFB36R" />
      <body className="flex min-h-screen flex-col">
        <TooltipProvider>
          <AIProvider>
@@ -77,7 +77,7 @@ export async function POST(request: NextRequest) {
    const agent = await initializeAgent();
    const result = await agent.run(message);
    
-    return NextResponse.json({ response: result.data });
+    return NextResponse.json({ response: result.result });
  } catch (error) {
    console.error("Chat error:", error);
    return NextResponse.json(
@@ -132,7 +132,7 @@ export default async function handler(
    const agent = await initializeAgent();
    const result = await agent.run(message);
    
-    res.json({ response: result.data });
+    res.json({ response: result.result });
  } catch (error) {
    console.error("Chat error:", error);
    res.status(500).json({ error: "Internal server error" });
@@ -220,7 +220,7 @@ export async function POST(request: NextRequest) {
    });

    const result = await myAgent.run(message);
-    return NextResponse.json({ response: result.data });
+    return NextResponse.json({ response: result.result });
  } catch (error) {
    return NextResponse.json({ error: error.message }, { status: 500 });
  }
@@ -233,40 +233,11 @@ Implement streaming for better user experience:

 ```typescript
 // app/api/chat-stream/route.ts
-import { agent } from "@llamaindex/workflow";
-import { tool } from "llamaindex";
-import { openai } from "@llamaindex/openai";
 import { agentStreamEvent } from "@llamaindex/workflow";
 import { NextRequest } from "next/server";
-import { z } from "zod";

-// Initialize agent once (consider using a singleton pattern)
-let myAgent: any = null;
-
-async function initializeAgent() {
-  if (myAgent) return myAgent;
-  
-  try {
-    const greetTool = tool({
-      name: "greet",
-      description: "Greets a user with their name",
-      parameters: z.object({
-        name: z.string(),
-      }),
-      execute: ({ name }) => `Hello, ${name}! How can I help you today?`,
-    });
-
-    myAgent = agent({
-      tools: [greetTool],
-      llm: openai({ model: "gpt-4o-mini" }),
-    });
-    
-    return myAgent;
-  } catch (error) {
-    console.error("Failed to initialize agent:", error);
-    throw error;
-  }
-}
+// Assume myAgent is initialized elsewhere
+declare const myAgent: any;

 export async function POST(request: NextRequest) {
  const { message } = await request.json();
@@ -274,10 +245,9 @@ export async function POST(request: NextRequest) {
  const stream = new ReadableStream({
    async start(controller) {
      try {
-        const agent = await initializeAgent();
-        const events = agent.runStream(message);
+        const context = myAgent.runStream(message);
        
-        for await (const event of events) {
+        for await (const event of context) {
          if (agentStreamEvent.include(event)) {
            controller.enqueue(new TextEncoder().encode(event.data.delta));
          }
@@ -63,7 +63,7 @@ app.post('/api/chat', async (req, res) => {
  try {
    const { message } = req.body;
    const result = await myAgent.run(message);
-    res.json({ response: result.data });
+    res.json({ response: result.result });
  } catch (error) {
    res.status(500).json({ error: 'Chat failed' });
  }
@@ -110,7 +110,7 @@ fastify.post('/api/chat', async (request, reply) => {
  try {
    const { message } = request.body as { message: string };
    const result = await myAgent.run(message);
-    return { response: result.data };
+    return { response: result.result };
  } catch (error) {
    reply.status(500).send({ error: 'Chat failed' });
  }
@@ -162,7 +162,7 @@ app.post("/api/chat", async (c) => {
  
  try {
    const result = await myAgent.run(message);
-    return c.json({ response: result.data });
+    return c.json({ response: result.result });
  } catch (error) {
    return c.json({ error: error.message }, 500);
  }
@@ -187,9 +187,9 @@ app.post('/api/chat-stream', async (req, res) => {
  });
  
  try {
-    const events = myAgent.runStream(message);
+    const context = myAgent.runStream(message);
    
-    for await (const event of events) {
+    for await (const event of context) {
      if (agentStreamEvent.include(event)) {
        res.write(event.data.delta);
      }
@@ -34,7 +34,7 @@ export default {
      const { message } = await request.json();
      const result = await myAgent.run(message);
      
-      return new Response(JSON.stringify({ response: result.data }), {
+      return new Response(JSON.stringify({ response: result.result }), {
        headers: { "Content-Type": "application/json" },
      });
    } catch (error) {
@@ -83,7 +83,7 @@ export default async function handler(req, res) {
  
  try {
    const result = await myAgent.run(message);
-    res.json({ response: result.data });
+    res.json({ response: result.result });
  } catch (error) {
    res.status(500).json({ error: error.message });
  }
@@ -124,7 +124,7 @@ export async function POST(request: NextRequest) {
    });

    const result = await myAgent.run(message);
-    return NextResponse.json({ response: result.data });
+    return NextResponse.json({ response: result.result });
  } catch (error) {
    return NextResponse.json({ error: error.message }, { status: 500 });
  }
@@ -173,7 +173,7 @@ export const handler: APIGatewayProxyHandler = async (event, context) => {
        "Content-Type": "application/json",
        "Access-Control-Allow-Origin": "*",
      },
-      body: JSON.stringify({ response: result.data }),
+      body: JSON.stringify({ response: result.result }),
    };
  } catch (error) {
    return {
@@ -222,7 +222,7 @@ export const handler: Handler = async (event, context) => {
    
    return {
      statusCode: 200,
-      body: JSON.stringify({ response: result.data }),
+      body: JSON.stringify({ response: result.result }),
    };
  } catch (error) {
    return {
@@ -34,7 +34,6 @@ const jokeAgent = agent({
 // Run the workflow
 const result = await jokeAgent.run("Tell me something funny");
 console.log(result.data.result); // Baby Llama is called cria
-console.log(result.data.message); // { role: 'assistant', content: 'Baby Llama is called cria' }
 ```

 ### Event Streaming
@@ -106,40 +106,34 @@ const memory = createMemory({

 Long-term memory is represented as `Memory Block` objects. These objects contain information that are from previous user sessions or from the beginning of the current conversation. When memory is retrieved (by calling `getLLM`), the short-term and long-term memories are merged together within the given `tokenLimit`. 

-Currently, there are three predefined memory blocks:
+Currently, there are two predefined memory blocks:

 - `staticBlock`: A memory block that stores a static piece of information.
 - `factExtractionBlock`: A memory block that extracts facts from the chat history.
- `vectorBlock`: A memory block that stores and retrieves chat messages from a vector database using semantic similarity search. Messages are stored individually and retrieved based on their relevance to recent conversation context. Here we've passed in the `vectorStore` to use to store and retrieve the chat messages.

 This sounds a bit complicated, but it's actually quite simple. Let's look at an example:

 ```ts
-import { createMemory, factExtractionBlock, staticBlock, vectorBlock } from "llamaindex";
-import { QdrantVectorStore } from "@llamaindex/qdrant";
-import { OpenAIEmbedding } from "@llamaindex/openai";
+import { createMemory, factExtractionBlock, staticBlock } from "llamaindex";

 const memoryBlocks= [
  staticBlock({
+    id: "core_info",
    content: "My name is Logan, and I live in Saskatoon. I work at LlamaIndex.",
  }),
  factExtractionBlock({
+    id: "user-extracted_info",
    priority: 1,
    llm: llm,
    maxFacts: 50,
  }),
-  vectorBlock({
-    vectorStore: new QdrantVectorStore({ url: "http://localhost:6333" }),
-    priority: 2,
-  }),
 ];
 ```

-Here, we've setup three memory blocks:
+Here, we've setup two memory blocks:

- `staticBlock`: A static memory block that stores some core information about the user. This information will always be inserted into the memory. The type used is `MessageContent` to support multi-modal content.
- `factExtractionBlock`: An extracted memory block that will extract information from the chat history. Here we've passed in the `llm` to use to extract facts from the chat history, and set the `maxFacts` to 50. If the number of extracted facts exceeds this limit, the `maxFacts` will be automatically summarized and reduced to leave room for new information.
- `vectorBlock`: A vector memory block that will store in a vector database and retrieve them from there. Messages are stored individually and retrieved based on their relevance to recent conversation context. Here we've passed in the `vectorStore` to use to store and retrieve the chat messages.
+- `core_info`: A static memory block that stores some core information about the user. This information will always be inserted into the memory. The type used is `MessageContent` to support multi-modal content.
+- `extracted_info`: An extracted memory block that will extract information from the chat history. Here we've passed in the `llm` to use to extract facts from the chat history, and set the `maxFacts` to 50. If the number of extracted facts exceeds this limit, the `maxFacts` will be automatically summarized and reduced to leave room for new information.

 You'll also notice that we've set the `priority` for the `factExtractionBlock` block. This is used to determine the handling when the memory blocks content (i.e. long-term memory) + short-term memory exceeds the token limit on the `Memory` object.

@@ -164,46 +158,6 @@ When memory is retrieved (using `getLLM`), the short-term and long-term memories

 The amount of short-term memory included is specified by the `shortTermTokenLimitRatio`. If it's set to `0.7`, 70% of the `tokenLimit` is used for short-term memory (not including the static memory block).

-
-#### VectorBlock Configuration Options
-
-The `vectorBlock` offers several configuration options to customize its behavior:
-
-```ts
-vectorBlock({
-  vectorStore: new QdrantVectorStore({ url: "http://localhost:6333" }),
-  priority: 2,
-  retrievalContextWindow: 5, // Number of recent messages to use for context when retrieving
-  formatTemplate: new PromptTemplate({ template: "Context: {{ context }}" }), // Custom formatting template
-  nodePostprocessors: [/* custom postprocessors */], // Apply processing to retrieved nodes
-  queryOptions: {
-    similarityTopK: 3, // Number of top similar results to return (default: 2)
-    mode: VectorStoreQueryMode.DEFAULT, // Query mode for the vector store
-    sessionFilterKey: "session_id", // Metadata key for session filtering (default: "session_id")
-    // Custom filters can be added here - session filter is automatically included
-    filters: {
-      filters: [
-        { key: "custom_field", value: "custom_value", operator: "==" }
-      ],
-      condition: "and"
-    }
-  }
-})
-```
-
-**Key Configuration Options:**
-
- **`retrievalContextWindow`**: Number of recent messages to consider when creating the retrieval query (default: 5). A larger window provides more context but may be less precise.
- **`formatTemplate`**: Template for formatting retrieved information before adding to memory. Defaults to a simple context template.
- **`nodePostprocessors`**: Array of postprocessors to apply to retrieved nodes, useful for filtering or transforming results.
- **`queryOptions.similarityTopK`**: Number of most similar messages to retrieve from the vector store (default: 2).
- **`queryOptions.sessionFilterKey`**: Metadata key used to isolate memory between different sessions (default: "session_id").
- **`queryOptions.filters`**: Additional metadata filters for retrieval. The session filter is automatically added to ensure memory isolation.
-
-**Session Isolation:**
-
-The vectorBlock automatically adds a session filter using the block's ID to ensure that memories from different sessions don't interfere with each other. This filter uses the `sessionFilterKey` (default: "session_id") and can be customized if needed.
-
 ## Persistence with Snapshots

 Save and restore memory state:
@@ -1,17 +1,5 @@
 # @llamaindex/cloudflare-worker-agent-test

-## 0.0.182
-
-### Patch Changes
-
- llamaindex@0.11.21
-
-## 0.0.181
-
-### Patch Changes
-
- llamaindex@0.11.20
-
 ## 0.0.180

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/cloudflare-worker-agent-test",
-  "version": "0.0.182",
+  "version": "0.0.180",
  "type": "module",
  "private": true,
  "scripts": {
@@ -1,18 +1,5 @@
 # @llamaindex/llama-parse-browser-test

-## 0.0.81
-
-### Patch Changes
-
- @llamaindex/cloud@4.0.26
-
-## 0.0.80
-
-### Patch Changes
-
- Updated dependencies [2967d57]
-  - @llamaindex/cloud@4.0.25
-
 ## 0.0.79

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/llama-parse-browser-test",
  "private": true,
-  "version": "0.0.81",
+  "version": "0.0.79",
  "type": "module",
  "scripts": {
    "dev": "vite",
@@ -1,17 +1,5 @@
 # @llamaindex/next-agent-test

-## 0.1.182
-
-### Patch Changes
-
- llamaindex@0.11.21
-
-## 0.1.181
-
-### Patch Changes
-
- llamaindex@0.11.20
-
 ## 0.1.180

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/next-agent-test",
-  "version": "0.1.182",
+  "version": "0.1.180",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -1,17 +1,5 @@
 # test-edge-runtime

-## 0.1.181
-
-### Patch Changes
-
- llamaindex@0.11.21
-
-## 0.1.180
-
-### Patch Changes
-
- llamaindex@0.11.20
-
 ## 0.1.179

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/nextjs-edge-runtime-test",
-  "version": "0.1.181",
+  "version": "0.1.179",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -1,21 +1,5 @@
 # @llamaindex/next-node-runtime

-## 0.1.51
-
-### Patch Changes
-
- llamaindex@0.11.21
- @llamaindex/huggingface@0.1.22
- @llamaindex/readers@3.1.16
-
-## 0.1.50
-
-### Patch Changes
-
- llamaindex@0.11.20
- @llamaindex/huggingface@0.1.21
- @llamaindex/readers@3.1.15
-
 ## 0.1.49

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/next-node-runtime-test",
-  "version": "0.1.51",
+  "version": "0.1.49",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -1,17 +1,5 @@
 # vite-import-llamaindex

-## 0.0.48
-
-### Patch Changes
-
- llamaindex@0.11.21
-
-## 0.0.47
-
-### Patch Changes
-
- llamaindex@0.11.20
-
 ## 0.0.46

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "vite-import-llamaindex",
  "private": true,
-  "version": "0.0.48",
+  "version": "0.0.46",
  "type": "module",
  "scripts": {
    "build": "vite build",
@@ -1,17 +1,5 @@
 # @llamaindex/waku-query-engine-test

-## 0.0.182
-
-### Patch Changes
-
- llamaindex@0.11.21
-
-## 0.0.181
-
-### Patch Changes
-
- llamaindex@0.11.20
-
 ## 0.0.180

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/waku-query-engine-test",
-  "version": "0.0.182",
+  "version": "0.0.180",
  "type": "module",
  "private": true,
  "scripts": {
@@ -23,7 +23,7 @@ await test("pinecone", async (t) => {
  });

  const vectorStore = new PineconeVectorStore({
-    embedModel: openaiEmbedding,
+    embeddingModel: openaiEmbedding,
  });

  t.after(async () => {
@@ -1,111 +1,5 @@
 # examples

-## 0.3.33
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-  - @llamaindex/cloud@4.0.26
-  - llamaindex@0.11.21
-  - @llamaindex/node-parser@2.0.17
-  - @llamaindex/anthropic@0.3.19
-  - @llamaindex/assemblyai@0.1.16
-  - @llamaindex/clip@0.0.68
-  - @llamaindex/cohere@0.0.31
-  - @llamaindex/deepinfra@0.0.68
-  - @llamaindex/discord@0.1.16
-  - @llamaindex/google@0.3.16
-  - @llamaindex/huggingface@0.1.22
-  - @llamaindex/jinaai@0.0.28
-  - @llamaindex/mistral@0.1.17
-  - @llamaindex/mixedbread@0.0.31
-  - @llamaindex/notion@0.1.16
-  - @llamaindex/ollama@0.1.17
-  - @llamaindex/openai@0.4.12
-  - @llamaindex/perplexity@0.0.25
-  - @llamaindex/portkey-ai@0.0.59
-  - @llamaindex/replicate@0.0.59
-  - @llamaindex/bm25-retriever@0.0.6
-  - @llamaindex/astra@0.0.31
-  - @llamaindex/azure@0.1.29
-  - @llamaindex/chroma@0.0.31
-  - @llamaindex/elastic-search@0.1.17
-  - @llamaindex/firestore@1.0.24
-  - @llamaindex/milvus@0.1.26
-  - @llamaindex/mongodb@0.0.32
-  - @llamaindex/pinecone@0.1.17
-  - @llamaindex/postgres@0.0.60
-  - @llamaindex/qdrant@0.1.27
-  - @llamaindex/supabase@0.1.18
-  - @llamaindex/upstash@0.0.31
-  - @llamaindex/weaviate@0.0.32
-  - @llamaindex/vercel@0.1.17
-  - @llamaindex/voyage-ai@1.0.23
-  - @llamaindex/readers@3.1.16
-  - @llamaindex/tools@0.1.7
-  - @llamaindex/workflow@1.1.17
-  - @llamaindex/deepseek@0.0.29
-  - @llamaindex/fireworks@0.0.28
-  - @llamaindex/groq@0.0.84
-  - @llamaindex/together@0.0.28
-  - @llamaindex/vllm@0.0.54
-  - @llamaindex/xai@0.0.15
-
-## 0.3.32
-
-### Patch Changes
-
- Updated dependencies [650eeb1]
- Updated dependencies [a8ec08c]
- Updated dependencies [2967d57]
-  - @llamaindex/google@0.3.15
-  - @llamaindex/core@0.6.16
-  - @llamaindex/workflow@1.1.16
-  - @llamaindex/cloud@4.0.25
-  - llamaindex@0.11.20
-  - @llamaindex/node-parser@2.0.16
-  - @llamaindex/anthropic@0.3.18
-  - @llamaindex/assemblyai@0.1.15
-  - @llamaindex/clip@0.0.67
-  - @llamaindex/cohere@0.0.30
-  - @llamaindex/deepinfra@0.0.67
-  - @llamaindex/discord@0.1.15
-  - @llamaindex/huggingface@0.1.21
-  - @llamaindex/jinaai@0.0.27
-  - @llamaindex/mistral@0.1.16
-  - @llamaindex/mixedbread@0.0.30
-  - @llamaindex/notion@0.1.15
-  - @llamaindex/ollama@0.1.16
-  - @llamaindex/openai@0.4.11
-  - @llamaindex/perplexity@0.0.24
-  - @llamaindex/portkey-ai@0.0.58
-  - @llamaindex/replicate@0.0.58
-  - @llamaindex/bm25-retriever@0.0.5
-  - @llamaindex/astra@0.0.30
-  - @llamaindex/azure@0.1.28
-  - @llamaindex/chroma@0.0.30
-  - @llamaindex/elastic-search@0.1.16
-  - @llamaindex/firestore@1.0.23
-  - @llamaindex/milvus@0.1.25
-  - @llamaindex/mongodb@0.0.31
-  - @llamaindex/pinecone@0.1.16
-  - @llamaindex/postgres@0.0.59
-  - @llamaindex/qdrant@0.1.26
-  - @llamaindex/supabase@0.1.17
-  - @llamaindex/upstash@0.0.30
-  - @llamaindex/weaviate@0.0.31
-  - @llamaindex/vercel@0.1.16
-  - @llamaindex/voyage-ai@1.0.22
-  - @llamaindex/readers@3.1.15
-  - @llamaindex/tools@0.1.6
-  - @llamaindex/deepseek@0.0.28
-  - @llamaindex/fireworks@0.0.27
-  - @llamaindex/groq@0.0.83
-  - @llamaindex/together@0.0.27
-  - @llamaindex/vllm@0.0.53
-  - @llamaindex/xai@0.0.14
-
 ## 0.3.31

 ### Patch Changes
@@ -24,7 +24,6 @@ async function main() {
    state: result.data.state,
  });
  console.log(`${JSON.stringify(caResult, null, 2)}`);
-  console.log("assistant message:", result.data.message);
 }

 main().catch((error) => {
@@ -1,150 +0,0 @@
-/**
- * Example: Vector Memory Block
- *
- * This example demonstrates how to use the VectorMemoryBlock to store and retrieve
- * conversation history using vector similarity search. The vector memory block
- * stores messages in a vector store and can retrieve relevant context based on
- * semantic similarity to recent messages.
- */
-
-import { OpenAI, OpenAIEmbedding } from "@llamaindex/openai";
-import { QdrantVectorStore } from "@llamaindex/qdrant";
-import { createMemory, vectorBlock } from "llamaindex";
-
-// Set up the LLM and embedding model
-const llm = new OpenAI({ model: "gpt-4.1-mini" });
-const embedModel = new OpenAIEmbedding({ model: "text-embedding-3-small" });
-
-// Simulate a conversation with some context
-// This conversation has 8 messages, which is more than the token limit of 100 tokens (set below)
-// The last 4 messages are kept in to short term memory block (as their tokens are in the limit)
-// Whereas the first 5 messages are added to long term memory block (in here we will use the vector memory block with Qdrant)
-const CONVERSATION_TURNS = [
-  //// This is the first 5 messages that are added to long term memory block (vector memory block)
-  {
-    role: "user",
-    content: "Hi, I'm Sarah and I work as a data scientist at Google.",
-  },
-  {
-    role: "assistant",
-    content:
-      "Hello Sarah! It's great to meet you. Data science at Google must be exciting!",
-  },
-  {
-    role: "user",
-    content:
-      "Yes, I specialize in machine learning and natural language processing.",
-  },
-  {
-    role: "assistant",
-    content: "That's impressive! ML and NLP are fascinating fields.",
-  },
-  {
-    role: "user",
-    content:
-      "I have a PhD in Computer Science from Stanford, and I love hiking on weekends.",
-  },
-
-  //// This is the last 4 messages that are added to short term memory block
-  {
-    role: "assistant",
-    content:
-      "Wow, Stanford PhD! And hiking is a great way to unwind from tech work.",
-  },
-  {
-    role: "user",
-    content: "I also have two cats named Whiskers and Mittens.",
-  },
-  {
-    role: "assistant",
-    content:
-      "Cats make wonderful companions! Whiskers and Mittens are cute names.",
-  },
-  {
-    role: "user",
-    content: "Summary information about Sarah and her cats",
-  },
-];
-
-async function main() {
-  console.log("=== Vector Memory Block Example ===\n");
-
-  /**
-   * Create a vector store. You can quickly get a local instance of Qdrant running with Docker:
-   * ```bash
-   * docker pull qdrant/qdrant
-   * docker run -p 6333:6333 qdrant/qdrant
-   * ```
-   *
-   * Go to http://localhost:6333/dashboard#/collections to see your data
-   */
-  const vectorStore = new QdrantVectorStore({
-    url: "http://localhost:6333",
-    embedModel,
-  });
-
-  // Create a vector memory block using the factory function
-  const vectorMemoryBlock = vectorBlock({
-    vectorStore,
-    priority: 5,
-  });
-
-  // Create a memory store with the vector memory block
-  const memory = createMemory([], {
-    llm,
-    memoryBlocks: [vectorMemoryBlock],
-    tokenLimit: 100,
-    shortTermTokenLimitRatio: 0.7,
-  });
-
-  // Store the conversation history in the vector memory
-  console.log(`Adding ${CONVERSATION_TURNS.length} messages to the memory...`);
-  for (const message of CONVERSATION_TURNS) {
-    await memory.add(message);
-  }
-
-  // Retrieve relevant context for the current user request
-  console.log("Retrieving relevant context...");
-  const chatHistory = await memory.getLLM();
-
-  // You will see there's 1 generated context message from vector memory block, and 4 messages from short term memory block
-  console.log("Chat memory:", chatHistory);
-
-  // Now simulate the assistant responding with context
-  console.log("\nAssistant response with context:");
-  const response = await llm.chat({
-    messages: chatHistory,
-  });
-  console.log(response.message.content);
-
-  // Try adding more messages to the memory
-  const newMessages = [
-    {
-      role: "user",
-      content: "Write a long paragraph about weather in Tokyo",
-    },
-    {
-      role: "assistant",
-      content:
-        "The weather in Tokyo is sunny and warm. The temperature is around 20 degrees Celsius. The weather is very nice and the people are friendly.",
-    },
-    {
-      role: "user",
-      content: "What is the weather in Tokyo?",
-    },
-  ];
-  // Add the new messages to the memory
-  for (const message of newMessages) {
-    await memory.add(message);
-  }
-
-  // Try retrieving the new messages
-  const newChatHistory = await memory.getLLM();
-  // You can see now that new chat history will contain the nodes (separated by `\n`) in the
-  // context message that is generated by the vector memory block
-  // The number of retrieved nodes is set by `similarityTopK` in `queryOptions` of `vectorBlock`
-  // (default `similarityTopK` is 2)
-  console.log("New chat history:", newChatHistory);
-}
-
-main().catch(console.error);
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/examples",
-  "version": "0.3.33",
+  "version": "0.3.31",
  "private": true,
  "scripts": {
    "lint": "eslint .",
@@ -11,52 +11,52 @@
    "@azure/cosmos": "^4.1.1",
    "@azure/identity": "^4.4.1",
    "@azure/search-documents": "^12.1.0",
-    "@llamaindex/anthropic": "^0.3.19",
-    "@llamaindex/assemblyai": "^0.1.16",
-    "@llamaindex/astra": "^0.0.31",
-    "@llamaindex/azure": "^0.1.29",
-    "@llamaindex/bm25-retriever": "^0.0.6",
-    "@llamaindex/chroma": "^0.0.31",
-    "@llamaindex/clip": "^0.0.68",
-    "@llamaindex/cloud": "^4.0.26",
-    "@llamaindex/cohere": "^0.0.31",
-    "@llamaindex/core": "^0.6.17",
-    "@llamaindex/deepinfra": "^0.0.68",
-    "@llamaindex/deepseek": "^0.0.29",
-    "@llamaindex/discord": "^0.1.16",
-    "@llamaindex/elastic-search": "^0.1.17",
+    "@llamaindex/anthropic": "^0.3.17",
+    "@llamaindex/assemblyai": "^0.1.14",
+    "@llamaindex/astra": "^0.0.29",
+    "@llamaindex/azure": "^0.1.27",
+    "@llamaindex/bm25-retriever": "^0.0.4",
+    "@llamaindex/chroma": "^0.0.29",
+    "@llamaindex/clip": "^0.0.66",
+    "@llamaindex/cloud": "^4.0.24",
+    "@llamaindex/cohere": "^0.0.29",
+    "@llamaindex/core": "^0.6.15",
+    "@llamaindex/deepinfra": "^0.0.66",
+    "@llamaindex/deepseek": "^0.0.27",
+    "@llamaindex/discord": "^0.1.14",
+    "@llamaindex/elastic-search": "^0.1.15",
    "@llamaindex/env": "^0.1.30",
-    "@llamaindex/firestore": "^1.0.24",
-    "@llamaindex/fireworks": "^0.0.28",
-    "@llamaindex/google": "^0.3.16",
-    "@llamaindex/groq": "^0.0.84",
-    "@llamaindex/huggingface": "^0.1.22",
-    "@llamaindex/jinaai": "^0.0.28",
-    "@llamaindex/milvus": "^0.1.26",
-    "@llamaindex/mistral": "^0.1.17",
-    "@llamaindex/mixedbread": "^0.0.31",
-    "@llamaindex/mongodb": "^0.0.32",
-    "@llamaindex/node-parser": "^2.0.17",
-    "@llamaindex/notion": "^0.1.16",
-    "@llamaindex/ollama": "^0.1.17",
-    "@llamaindex/openai": "^0.4.12",
-    "@llamaindex/perplexity": "^0.0.25",
-    "@llamaindex/pinecone": "^0.1.17",
-    "@llamaindex/portkey-ai": "^0.0.59",
-    "@llamaindex/postgres": "^0.0.60",
-    "@llamaindex/qdrant": "^0.1.27",
-    "@llamaindex/readers": "^3.1.16",
-    "@llamaindex/replicate": "^0.0.59",
-    "@llamaindex/supabase": "^0.1.18",
-    "@llamaindex/together": "^0.0.28",
-    "@llamaindex/tools": "^0.1.7",
-    "@llamaindex/upstash": "^0.0.31",
-    "@llamaindex/vercel": "^0.1.17",
-    "@llamaindex/vllm": "^0.0.54",
-    "@llamaindex/voyage-ai": "^1.0.23",
-    "@llamaindex/weaviate": "^0.0.32",
-    "@llamaindex/workflow": "^1.1.17",
-    "@llamaindex/xai": "^0.0.15",
+    "@llamaindex/firestore": "^1.0.22",
+    "@llamaindex/fireworks": "^0.0.26",
+    "@llamaindex/google": "^0.3.14",
+    "@llamaindex/groq": "^0.0.82",
+    "@llamaindex/huggingface": "^0.1.20",
+    "@llamaindex/jinaai": "^0.0.26",
+    "@llamaindex/milvus": "^0.1.24",
+    "@llamaindex/mistral": "^0.1.15",
+    "@llamaindex/mixedbread": "^0.0.29",
+    "@llamaindex/mongodb": "^0.0.30",
+    "@llamaindex/node-parser": "^2.0.15",
+    "@llamaindex/notion": "^0.1.14",
+    "@llamaindex/ollama": "^0.1.15",
+    "@llamaindex/openai": "^0.4.10",
+    "@llamaindex/perplexity": "^0.0.23",
+    "@llamaindex/pinecone": "^0.1.15",
+    "@llamaindex/portkey-ai": "^0.0.57",
+    "@llamaindex/postgres": "^0.0.58",
+    "@llamaindex/qdrant": "^0.1.25",
+    "@llamaindex/readers": "^3.1.14",
+    "@llamaindex/replicate": "^0.0.57",
+    "@llamaindex/supabase": "^0.1.16",
+    "@llamaindex/together": "^0.0.26",
+    "@llamaindex/tools": "^0.1.5",
+    "@llamaindex/upstash": "^0.0.29",
+    "@llamaindex/vercel": "^0.1.15",
+    "@llamaindex/vllm": "^0.0.52",
+    "@llamaindex/voyage-ai": "^1.0.21",
+    "@llamaindex/weaviate": "^0.0.30",
+    "@llamaindex/workflow": "^1.1.15",
+    "@llamaindex/xai": "^0.0.13",
    "@notionhq/client": "^4.0.0",
    "@pinecone-database/pinecone": "^4.0.0",
    "@vercel/postgres": "^0.10.0",
@@ -65,7 +65,7 @@
    "commander": "^12.1.0",
    "dotenv": "^17.2.0",
    "js-tiktoken": "^1.0.14",
-    "llamaindex": "^0.11.21",
+    "llamaindex": "^0.11.19",
    "mongodb": "6.7.0",
    "postgres": "^3.4.4",
    "wikipedia": "^2.1.2",
@@ -15,7 +15,7 @@ async function main() {
  const vectorStore = new QdrantVectorStore({
    url: process.env.QDRANT_URL,
    apiKey: process.env.QDRANT_API_KEY,
-    embedModel: embedding,
+    embeddingModel: embedding,
    collectionName: "gemini_test",
  });
  const storageContext = await storageContextFromDefaults({ vectorStore });
@@ -16,7 +16,7 @@ async function main() {
  const vectorStore = new QdrantVectorStore({
    url: process.env.QDRANT_URL,
    apiKey: process.env.QDRANT_API_KEY,
-    embedModel: embedding,
+    embeddingModel: embedding,
    collectionName: "jina_test",
  });
  const storageContext = await storageContextFromDefaults({ vectorStore });
@@ -1,17 +1,5 @@
 # @llamaindex/autotool

-## 8.0.21
-
-### Patch Changes
-
- llamaindex@0.11.21
-
-## 8.0.20
-
-### Patch Changes
-
- llamaindex@0.11.20
-
 ## 8.0.19

 ### Patch Changes
@@ -1,19 +1,5 @@
 # @llamaindex/autotool-01-node-example

-## 0.0.129
-
-### Patch Changes
-
- llamaindex@0.11.21
- @llamaindex/autotool@8.0.21
-
-## 0.0.128
-
-### Patch Changes
-
- llamaindex@0.11.20
- @llamaindex/autotool@8.0.20
-
 ## 0.0.127

 ### Patch Changes
@@ -13,5 +13,5 @@
  "scripts": {
    "start": "node --import tsx --import @llamaindex/autotool/node ./src/index.ts"
  },
-  "version": "0.0.129"
+  "version": "0.0.127"
 }
@@ -6,7 +6,7 @@
    "url": "git+https://github.com/run-llama/LlamaIndexTS.git",
    "directory": "packages/autotool"
  },
-  "version": "8.0.21",
+  "version": "8.0.19",
  "description": "auto transpile your JS function to LLM Agent compatible",
  "files": [
    "dist",
@@ -1,20 +1,5 @@
 # @llamaindex/cloud

-## 4.0.26
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 4.0.25
-
-### Patch Changes
-
- 2967d57: Default to \_public agent url id
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 4.0.24

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/cloud",
-  "version": "4.0.26",
+  "version": "4.0.24",
  "type": "module",
  "license": "MIT",
  "scripts": {
@@ -1,17 +1,5 @@
 # @llamaindex/core

-## 0.6.17
-
-### Patch Changes
-
- 38da40b: feat: VectoryMemoryBlock
-
-## 0.6.16
-
-### Patch Changes
-
- a8ec08c: fix: ensure correct message content in agent workflow
-
 ## 0.6.15

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/core",
  "type": "module",
-  "version": "0.6.17",
+  "version": "0.6.15",
  "description": "LlamaIndex Core Module",
  "exports": {
    "./agent": {
@@ -39,9 +39,7 @@ export abstract class BaseMemoryBlock<
   *
   * @returns The memory block content as an array of ChatMessage.
   */
-  abstract get(
-    messages?: MemoryMessage<TAdditionalMessageOptions>[],
-  ): Promise<MemoryMessage<TAdditionalMessageOptions>[]>;
+  abstract get(): Promise<MemoryMessage<TAdditionalMessageOptions>[]>;

  /**
   * Store the messages in the memory block.
@@ -1,4 +1,3 @@
 export { BaseMemoryBlock } from "./base";
 export { FactExtractionMemoryBlock } from "./fact";
 export { StaticMemoryBlock } from "./static";
-export { VectorMemoryBlock } from "./vector";
@@ -1,250 +0,0 @@
-import type { BaseEmbedding } from "../../embeddings";
-import type { BaseNodePostprocessor } from "../../postprocessor";
-import { BasePromptTemplate, defaultContextSystemPrompt } from "../../prompts";
-import type { NodeWithScore } from "../../schema";
-import { MetadataMode, TextNode } from "../../schema";
-import { extractText } from "../../utils/llms";
-import type {
-  BaseVectorStore,
-  MetadataFilter,
-  VectorStoreQuery,
-} from "../../vector-store";
-import { VectorStoreQueryMode } from "../../vector-store";
-import type { MemoryMessage } from "../types";
-import { BaseMemoryBlock, type MemoryBlockOptions } from "./base";
-
-/**
- * The options for the vector memory block.
- */
-export type VectorMemoryBlockOptions = {
-  /**
-   * The vector store to use for retrieval.
-   */
-  vectorStore: BaseVectorStore;
-
-  /**
-   * Maximum number of messages to include for context when retrieving.
-   * @default 5
-   */
-  retrievalContextWindow?: number;
-
-  /**
-   * Template for formatting the retrieved information.
-   * @default new PromptTemplate({ template: "{{ text }}" })
-   */
-  formatTemplate?: BasePromptTemplate;
-
-  /**
-   * List of node postprocessors to apply to the retrieved nodes containing messages.
-   *
-   * @default []
-   */
-  nodePostprocessors?: BaseNodePostprocessor[];
-
-  /**
-   * Configuration options for vector store queries when retrieving memory.
-   *
-   * @default
-   * ```typescript
-   * {
-   *   similarityTopK: 2,                    // Number of top similar results to return
-   *   mode: VectorStoreQueryMode.DEFAULT,   // Query mode for the vector store
-   *   sessionFilterKey: "session_id",       // Metadata key for session filtering
-   *   filters: {
-   *     filters: [
-   *       { key: "session_id", value: "<current block id>", operator: "==" }
-   *     ],
-   *     condition: "and"
-   *   }
-   * }
-   * ```
-   *
-   * Note: A session filter is automatically added to ensure memory isolation between blocks.
-   * If custom filters are provided, the session filter will be merged with them.
-   */
-  queryOptions?: Partial<VectorMemoryBlockQueryOptions>;
-} & MemoryBlockOptions;
-
-export type VectorMemoryBlockQueryOptions = Omit<
-  VectorStoreQuery,
-  "queryEmbedding" | "queryStr"
-> & {
-  sessionFilterKey: string;
-};
-
-/**
- * A memory block that retrieves relevant information from a vector store.
- *
- * This block stores conversation history in a vector store and retrieves
- * relevant information based on the most recent messages.
- */
-export class VectorMemoryBlock<
-  TAdditionalMessageOptions extends object = object,
-> extends BaseMemoryBlock<TAdditionalMessageOptions> {
-  private readonly vectorStore: BaseVectorStore;
-  private readonly retrievalContextWindow: number;
-  private readonly formatTemplate: BasePromptTemplate;
-  private readonly nodePostprocessors: BaseNodePostprocessor[];
-  private readonly queryOptions: VectorMemoryBlockQueryOptions;
-
-  constructor(options: VectorMemoryBlockOptions) {
-    super(options);
-
-    // Validate vector store
-    if (!options.vectorStore.storesText) {
-      throw new Error(
-        "vectorStore must store text to be used as a retrieval memory block",
-      );
-    }
-
-    this.vectorStore = options.vectorStore;
-    this.retrievalContextWindow = options.retrievalContextWindow ?? 5;
-    this.queryOptions = this.buildDefaultQueryOptions(options.queryOptions);
-    this.formatTemplate = options.formatTemplate ?? defaultContextSystemPrompt;
-    this.nodePostprocessors = options.nodePostprocessors ?? [];
-  }
-
-  get embedModel(): BaseEmbedding {
-    return this.vectorStore.embedModel;
-  }
-
-  async get(
-    messages: MemoryMessage<TAdditionalMessageOptions>[] = [],
-  ): Promise<MemoryMessage<TAdditionalMessageOptions>[]> {
-    if (messages?.length === 0) return [];
-
-    // Use the last message or a context window of messages for the query
-    let context: MemoryMessage<TAdditionalMessageOptions>[];
-    if (
-      this.retrievalContextWindow > 1 &&
-      messages.length >= this.retrievalContextWindow
-    ) {
-      context = messages.slice(-this.retrievalContextWindow);
-    } else {
-      context = messages;
-    }
-    const queryText = context
-      .map((message) => extractText(message.content))
-      .join("\n\n");
-    if (!queryText) return [];
-
-    // Create and execute the query
-    const queryEmbedding = await this.embedModel.getTextEmbedding(queryText);
-    const query: VectorStoreQuery = {
-      queryStr: queryText,
-      queryEmbedding,
-      ...this.queryOptions,
-    };
-    const results = await this.vectorStore.query(query);
-    if (!results.nodes?.length) return [];
-
-    // Create nodes with scores
-    const nodesWithScores: NodeWithScore[] = results.nodes.map(
-      (node, index) => ({
-        node,
-        score: results.similarities?.[index] ?? undefined,
-      }),
-    );
-
-    // Apply postprocessors
-    let processedNodes = nodesWithScores;
-    for (const postprocessor of this.nodePostprocessors) {
-      processedNodes = await postprocessor.postprocessNodes(
-        processedNodes,
-        queryText,
-      );
-    }
-
-    // Format the results
-    const retrievedText = processedNodes
-      .map(({ node }) => node.getContent(MetadataMode.NONE))
-      .join("\n\n");
-
-    const formattedText = this.formatTemplate.format({
-      context: retrievedText,
-    });
-
-    // Return as memory message
-    return [
-      {
-        id: this.id,
-        role: "memory",
-        content: formattedText,
-      } as MemoryMessage<TAdditionalMessageOptions>,
-    ];
-  }
-
-  async put(
-    messages: MemoryMessage<TAdditionalMessageOptions>[],
-  ): Promise<void> {
-    if (messages.length === 0) return;
-
-    // Format messages with role, text content, and additional info
-    const texts: string[] = [];
-
-    for (const message of messages) {
-      const text = extractText(message.content);
-      if (!text) continue;
-
-      let messageText = text;
-
-      // Add additional info if present
-      const additionalInfo = (message.options ?? {}) as Record<string, unknown>;
-      if (Object.keys(additionalInfo).length > 0) {
-        messageText += `\nAdditional Info: (${JSON.stringify(additionalInfo)})`;
-      }
-
-      texts.push(`<message role='${message.role}'>${messageText}</message>`);
-    }
-
-    if (texts.length === 0) return;
-
-    // Create text node with session metadata
-    const textNode = new TextNode({
-      text: texts.join("\n"),
-      metadata: { [this.queryOptions.sessionFilterKey]: this.id },
-    });
-
-    // Get embedding for the text
-    textNode.embedding = await this.embedModel.getTextEmbedding(textNode.text);
-
-    // Add to vector store
-    await this.vectorStore.add([textNode]);
-  }
-
-  private buildDefaultQueryOptions(
-    options: Partial<VectorMemoryBlockQueryOptions> | undefined,
-  ): VectorMemoryBlockQueryOptions {
-    const {
-      similarityTopK = 2,
-      mode = VectorStoreQueryMode.DEFAULT,
-      sessionFilterKey = "session_id",
-    } = options ?? {};
-
-    let filters = options?.filters;
-
-    const sessionFilter: MetadataFilter = {
-      key: sessionFilterKey,
-      value: this.id,
-      operator: "==",
-    };
-
-    if (filters) {
-      // Only add session_id filter if it doesn't exist in the filters list
-      const sessionIdFilterExists = filters.filters.some(
-        (filter) => filter.key === sessionFilterKey,
-      );
-      if (!sessionIdFilterExists) {
-        filters.filters.push(sessionFilter);
-      }
-    } else {
-      // If no filters are provided, add the session_id filter
-      filters = {
-        filters: [sessionFilter],
-        condition: "and",
-      };
-    }
-
-    return { ...options, similarityTopK, mode, sessionFilterKey, filters };
-  }
-}
@@ -8,10 +8,6 @@ import {
  StaticMemoryBlock,
  type StaticMemoryBlockOptions,
 } from "./block/static";
-import {
-  VectorMemoryBlock,
-  type VectorMemoryBlockOptions,
-} from "./block/vector";
 import { DEFAULT_TOKEN_LIMIT, Memory, type MemoryOptions } from "./memory";
 import type { MemoryMessage } from "./types";

@@ -119,17 +115,6 @@ export function factExtractionBlock<TMessageOptions extends object = object>(
  return new FactExtractionMemoryBlock<TMessageOptions>(options);
 }

-/**
- * create a VectorMemoryBlock
- * @param options - Configuration options for the vector memory block
- * @returns A new VectorMemoryBlock instance
- */
-export function vectorBlock<TMessageOptions extends object = object>(
-  options: VectorMemoryBlockOptions,
-): VectorMemoryBlock<TMessageOptions> {
-  return new VectorMemoryBlock<TMessageOptions>(options);
-}
-
 /**
 * Creates a new Memory instance from a snapshot
 * @param snapshot The snapshot to load from
@@ -31,13 +31,6 @@ export type MemoryOptions<TMessageOptions extends object = object> = {
   * Used internally for memory restoration from snapshots.
   */
  memoryCursor?: number;
-
-  /**
-   * The default LLM to use for memory retrieval.
-   * If not provided, the default `Settings.llm` will be used.
-   * This default LLM can be overridden by the LLM passed in the `getLLM` method.
-   */
-  llm?: LLM | undefined;
 };

 export class Memory<
@@ -72,10 +65,6 @@ export class Memory<
   * The cursor for the messages that have been processed into long-term memory.
   */
  private memoryCursor: number = 0;
-  /**
-   * The default LLM to use for memory retrieval.
-   */
-  private llm: LLM | undefined;

  constructor(
    messages: MemoryMessage<TMessageOptions>[] = [],
@@ -87,7 +76,6 @@ export class Memory<
      options.shortTermTokenLimitRatio ?? DEFAULT_SHORT_TERM_TOKEN_LIMIT_RATIO;
    this.memoryBlocks = options.memoryBlocks ?? [];
    this.memoryCursor = options.memoryCursor ?? 0;
-    this.initLLM(options.llm);

    this.adapters = {
      ...options.customAdapters,
@@ -96,15 +84,6 @@ export class Memory<
    } as TAdapters & BuiltinAdapters<TMessageOptions>;
  }

-  private initLLM(llm: LLM | undefined) {
-    // safe initialize LLM without throwing error if Settings.llm hasn't been set yet
-    try {
-      this.llm = llm ?? Settings.llm;
-    } catch (error) {
-      this.llm = undefined;
-    }
-  }
-
  /**
   * Add a message to the memory
   * @param message - The message to add to the memory
@@ -181,13 +160,12 @@ export class Memory<
  /**
   * Get the messages from the memory, optionally including transient messages.
   * only return messages that are within context window of the LLM
-   * @param llm - To fit the result messages to the context window of the LLM  (fallback to default llm if not provided).
-   * If llm is not specified in both the constructor and the method, the default token limit will be used.
+   * @param llm - To fit the result messages to the context window of the LLM. If not provided, the default token limit will be used.
   * @param transientMessages - Optional transient messages to include.
   * @returns The messages from the memory, optionally including transient messages.
   */
  async getLLM(
-    llm: LLM | undefined = this.llm,
+    llm?: LLM,
    transientMessages?: ChatMessage<TMessageOptions>[],
  ): Promise<ChatMessage[]> {
    // Priority of result messages:
@@ -198,20 +176,11 @@ export class Memory<
      ? Math.ceil(contextWindow * DEFAULT_TOKEN_LIMIT_RATIO)
      : this.tokenLimit;

-    let blockInputMessages = this.messages;
-    if (transientMessages && transientMessages.length > 0) {
-      blockInputMessages = [
-        ...this.messages,
-        ...transientMessages.map((m) => this.adapters.llamaindex.toMemory(m)),
-      ];
-    }
-
    // Start with fixed block messages (priority=0)
    // as it must always be included in the retrieval result
    const messages = await this.getMemoryBlockMessages(
      this.memoryBlocks.filter((block) => block.priority === 0),
      tokenLimit,
-      blockInputMessages,
    );
    // remaining token limit for short-term and memory blocks content
    const remainingTokenLimit =
@@ -238,7 +207,6 @@ export class Memory<
    const longTermBlockMessages = await this.getMemoryBlockMessages(
      longTermBlocks,
      memoryBlocksTokenLimit,
-      blockInputMessages,
    );
    messages.push(...longTermBlockMessages);

@@ -284,7 +252,6 @@ export class Memory<
  private async getMemoryBlockMessages(
    blocks: BaseMemoryBlock<TMessageOptions>[],
    tokenLimit?: number,
-    messages?: MemoryMessage<TMessageOptions>[],
  ): Promise<ChatMessage<TMessageOptions>[]> {
    if (blocks.length === 0) {
      return [];
@@ -298,7 +265,7 @@ export class Memory<
    let addedTokenCount = 0;
    for (const block of sortedBlocks) {
      try {
-        const content = await block.get(messages);
+        const content = await block.get();
        for (const message of content) {
          const chatMessage = this.adapters.llamaindex.fromMemory(message);
          const messageTokenCount = this.countMessagesToken([chatMessage]);
@@ -56,45 +56,10 @@ export function prettifyError(error: unknown): string {
  }
 }

-/**
- * Returns a stringfied JSON with double quotes removed.
- *
- * @param value - The JSON value to stringify
- * @returns The stringified JSON with no double quotes
- */
 export function stringifyJSONToMessageContent(value: JSONValue): string {
  return JSON.stringify(value, null, 2).replace(/"([^"]*)"/g, "$1");
 }

-export function assertIsJSONValue(value: unknown): asserts value is JSONValue {
-  if (
-    typeof value === "string" ||
-    typeof value === "number" ||
-    typeof value === "boolean"
-  ) {
-    return;
-  }
-
-  if (Array.isArray(value)) {
-    for (const item of value) {
-      assertIsJSONValue(item);
-    }
-    return;
-  }
-
-  if (typeof value === "object" && value !== null) {
-    for (const [key, val] of Object.entries(value)) {
-      if (typeof key !== "string") {
-        throw new Error(`Invalid object key: ${key}`);
-      }
-      assertIsJSONValue(val);
-    }
-    return;
-  }
-
-  throw new Error(`Value is not a valid JSONValue: ${String(value)}`);
-}
-
 export {
  extractDataUrlComponents,
  extractImage,
@@ -101,9 +101,7 @@ export type VectorStoreByType = {
 };

 export type VectorStoreBaseParams = {
-  // @deprecated: use embedModel instead
  embeddingModel?: BaseEmbedding | undefined;
-  embedModel?: BaseEmbedding | undefined;
 };

 export abstract class BaseVectorStore<Client = unknown, T = unknown> {
@@ -119,8 +117,7 @@ export abstract class BaseVectorStore<Client = unknown, T = unknown> {
  ): Promise<VectorStoreQueryResult>;

  protected constructor(params?: VectorStoreBaseParams) {
-    this.embedModel =
-      params?.embedModel ?? params?.embeddingModel ?? Settings.embedModel;
+    this.embedModel = params?.embeddingModel ?? Settings.embedModel;
  }
 }

@@ -1,17 +1,5 @@
 # @llamaindex/experimental

-## 0.0.198
-
-### Patch Changes
-
- llamaindex@0.11.21
-
-## 0.0.197
-
-### Patch Changes
-
- llamaindex@0.11.20
-
 ## 0.0.196

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/experimental",
  "description": "Experimental package for LlamaIndexTS",
-  "version": "0.0.198",
+  "version": "0.0.196",
  "type": "module",
  "types": "dist/type/index.d.ts",
  "main": "dist/cjs/index.js",
@@ -1,26 +1,5 @@
 # llamaindex

-## 0.11.21
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-  - @llamaindex/cloud@4.0.26
-  - @llamaindex/node-parser@2.0.17
-  - @llamaindex/workflow@1.1.17
-
-## 0.11.20
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
- Updated dependencies [2967d57]
-  - @llamaindex/core@0.6.16
-  - @llamaindex/workflow@1.1.16
-  - @llamaindex/cloud@4.0.25
-  - @llamaindex/node-parser@2.0.16
-
 ## 0.11.19

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "llamaindex",
-  "version": "0.11.21",
+  "version": "0.11.19",
  "license": "MIT",
  "type": "module",
  "keywords": [
@@ -272,7 +272,7 @@ export class SimpleVectorStore extends BaseVectorStore {

  static async fromPersistPath(
    persistPath: string,
-    embedModel?: BaseEmbedding,
+    embeddingModel?: BaseEmbedding,
  ): Promise<SimpleVectorStore> {
    const dirPath = path.dirname(persistPath);
    if (!(await exists(dirPath))) {
@@ -300,20 +300,20 @@ export class SimpleVectorStore extends BaseVectorStore {
    data.textIdToRefDocId = dataDict.textIdToRefDocId ?? {};
    // @ts-expect-error TS2322
    data.metadataDict = dataDict.metadataDict ?? {};
-    const store = new SimpleVectorStore({ data, embedModel });
+    const store = new SimpleVectorStore({ data, embeddingModel });
    store.persistPath = persistPath;
    return store;
  }

  static fromDict(
    saveDict: SimpleVectorStoreData,
-    embedModel?: BaseEmbedding,
+    embeddingModel?: BaseEmbedding,
  ): SimpleVectorStore {
    const data = new SimpleVectorStoreData();
    data.embeddingDict = saveDict.embeddingDict;
    data.textIdToRefDocId = saveDict.textIdToRefDocId;
    data.metadataDict = saveDict.metadataDict;
-    return new SimpleVectorStore({ data, embedModel });
+    return new SimpleVectorStore({ data, embeddingModel });
  }

  toDict(): SimpleVectorStoreData {
@@ -1,17 +1,5 @@
 # @llamaindex/core-test

-## 0.1.13
-
-### Patch Changes
-
- @llamaindex/openai@0.4.12
-
-## 0.1.12
-
-### Patch Changes
-
- @llamaindex/openai@0.4.11
-
 ## 0.1.11

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/llamaindex-test",
  "private": true,
-  "version": "0.1.13",
+  "version": "0.1.11",
  "type": "module",
  "scripts": {
    "test": "vitest run"
@@ -59,7 +59,7 @@ describe("SimpleVectorStore", () => {
      }),
    ];
    store = new SimpleVectorStore({
-      embedModel: {} as BaseEmbedding, // Mocking the embedModel
+      embeddingModel: {} as BaseEmbedding, // Mocking the embedModel
      data: {
        embeddingDict: {},
        textIdToRefDocId: {},
@@ -1,19 +1,5 @@
 # @llamaindex/node-parser

-## 2.0.17
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 2.0.16
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 2.0.15

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/node-parser",
-  "version": "2.0.17",
+  "version": "2.0.15",
  "description": "Node parser for LlamaIndex",
  "type": "module",
  "exports": {
@@ -1,19 +1,5 @@
 # @llamaindex/anthropic

-## 0.3.19
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.3.18
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.3.17

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/anthropic",
  "description": "Anthropic Adapter for LlamaIndex",
-  "version": "0.3.19",
+  "version": "0.3.17",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,19 +1,5 @@
 # @llamaindex/assemblyai

-## 0.1.16
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.1.15
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.1.14

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/assemblyai",
  "description": "AssemblyAI Reader for LlamaIndex",
-  "version": "0.1.16",
+  "version": "0.1.14",
  "type": "module",
  "types": "dist/index.d.ts",
  "main": "dist/index.cjs",
@@ -1,20 +1,5 @@
 # @llamaindex/community

-## 0.0.112
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.0.111
-
-### Patch Changes
-
- 678b327: feat: added apac bedrock models
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.0.110

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/aws",
  "description": "AWS package for LlamaIndexTS",
-  "version": "0.0.112",
+  "version": "0.0.110",
  "type": "module",
  "types": "dist/type/index.d.ts",
  "main": "dist/cjs/index.js",
@@ -134,19 +134,6 @@ export const INFERENCE_BEDROCK_MODELS = {
  EU_AMAZON_NOVA_PRO_1: "eu.amazon.nova-pro-v1:0",
  EU_AMAZON_NOVA_LITE_1: "eu.amazon.nova-lite-v1:0",
  EU_AMAZON_NOVA_MICRO_1: "eu.amazon.nova-micro-v1:0",
-
-  APAC_ANTHROPIC_CLAUDE_3_5_SONNET:
-    "apac.anthropic.claude-3-5-sonnet-20240620-v1:0",
-  APAC_ANTHROPIC_CLAUDE_3_5_SONNET_V2:
-    "apac.anthropic.claude-3-5-sonnet-20241022-v2:0",
-  APAC_ANTHROPIC_CLAUDE_3_7_SONNET:
-    "apac.anthropic.claude-3-7-sonnet-20250219-v1:0",
-  APAC_ANTHROPIC_CLAUDE_3_HAIKU: "apac.anthropic.claude-3-haiku-20240307-v1:0",
-  APAC_ANTHROPIC_CLAUDE_3_SONNET:
-    "apac.anthropic.claude-3-sonnet-20240229-v1:0",
-  APAC_AMAZON_NOVA_PRO_1: "apac.amazon.nova-pro-v1:0",
-  APAC_AMAZON_NOVA_LITE_1: "apac.amazon.nova-lite-v1:0",
-  APAC_AMAZON_NOVA_MICRO_1: "apac.amazon.nova-micro-v1:0",
 };

 export type INFERENCE_BEDROCK_MODELS =
@@ -219,24 +206,6 @@ export const INFERENCE_TO_BEDROCK_MAP: Record<
    BEDROCK_MODELS.AMAZON_NOVA_LITE_1,
  [INFERENCE_BEDROCK_MODELS.EU_AMAZON_NOVA_MICRO_1]:
    BEDROCK_MODELS.AMAZON_NOVA_MICRO_1,
-
-  [INFERENCE_BEDROCK_MODELS.APAC_ANTHROPIC_CLAUDE_3_5_SONNET]:
-    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET,
-  [INFERENCE_BEDROCK_MODELS.APAC_ANTHROPIC_CLAUDE_3_5_SONNET_V2]:
-    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET_V2,
-  [INFERENCE_BEDROCK_MODELS.APAC_ANTHROPIC_CLAUDE_3_7_SONNET]:
-    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_7_SONNET,
-  [INFERENCE_BEDROCK_MODELS.APAC_ANTHROPIC_CLAUDE_3_HAIKU]:
-    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU,
-  [INFERENCE_BEDROCK_MODELS.APAC_ANTHROPIC_CLAUDE_3_SONNET]:
-    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_SONNET,
-
-  [INFERENCE_BEDROCK_MODELS.APAC_AMAZON_NOVA_PRO_1]:
-    BEDROCK_MODELS.AMAZON_NOVA_PRO_1,
-  [INFERENCE_BEDROCK_MODELS.APAC_AMAZON_NOVA_LITE_1]:
-    BEDROCK_MODELS.AMAZON_NOVA_LITE_1,
-  [INFERENCE_BEDROCK_MODELS.APAC_AMAZON_NOVA_MICRO_1]:
-    BEDROCK_MODELS.AMAZON_NOVA_MICRO_1,
 };

 /*
@@ -1,21 +1,5 @@
 # @llamaindex/clip

-## 0.0.68
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-  - @llamaindex/openai@0.4.12
-
-## 0.0.67
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-  - @llamaindex/openai@0.4.11
-
 ## 0.0.66

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/clip",
  "description": "Clip Embedding Adapter for LlamaIndex",
-  "version": "0.0.68",
+  "version": "0.0.66",
  "type": "module",
  "types": "dist/index.d.ts",
  "main": "dist/index.cjs",
@@ -1,19 +1,5 @@
 # @llamaindex/cohere

-## 0.0.31
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.0.30
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.0.29

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/cohere",
  "description": "Cohere Adapter for LlamaIndex",
-  "version": "0.0.31",
+  "version": "0.0.29",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,21 +1,5 @@
 # @llamaindex/deepinfra

-## 0.0.68
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-  - @llamaindex/openai@0.4.12
-
-## 0.0.67
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-  - @llamaindex/openai@0.4.11
-
 ## 0.0.66

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/deepinfra",
  "description": "Deepinfra Adapter for LlamaIndex",
-  "version": "0.0.68",
+  "version": "0.0.66",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,17 +1,5 @@
 # @llamaindex/deepseek

-## 0.0.29
-
-### Patch Changes
-
- @llamaindex/openai@0.4.12
-
-## 0.0.28
-
-### Patch Changes
-
- @llamaindex/openai@0.4.11
-
 ## 0.0.27

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/deepseek",
  "description": "DeepSeek Adapter for LlamaIndex",
-  "version": "0.0.29",
+  "version": "0.0.27",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,19 +1,5 @@
 # @llamaindex/discord

-## 0.1.16
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.1.15
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.1.14

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/discord",
  "description": "Discord Reader for LlamaIndex",
-  "version": "0.1.16",
+  "version": "0.1.14",
  "type": "module",
  "types": "dist/index.d.ts",
  "main": "dist/index.cjs",
@@ -1,19 +1,5 @@
 # @llamaindex/excel

-## 0.1.17
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.1.16
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.1.15

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/excel",
  "description": "Excel Reader for LlamaIndex",
-  "version": "0.1.17",
+  "version": "0.1.15",
  "type": "module",
  "types": "dist/index.d.ts",
  "main": "dist/index.cjs",
@@ -1,17 +1,5 @@
 # @llamaindex/fireworks

-## 0.0.28
-
-### Patch Changes
-
- @llamaindex/openai@0.4.12
-
-## 0.0.27
-
-### Patch Changes
-
- @llamaindex/openai@0.4.11
-
 ## 0.0.26

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/fireworks",
  "description": "Fireworks Adapter for LlamaIndex",
-  "version": "0.0.28",
+  "version": "0.0.26",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,20 +1,5 @@
 # @llamaindex/google

-## 0.3.16
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.3.15
-
-### Patch Changes
-
- 650eeb1: fix: GeminiEmbedding should send batches of max 100
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.3.14

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/google",
  "description": "Google Adapter for LlamaIndex",
-  "version": "0.3.16",
+  "version": "0.3.14",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,248 +0,0 @@
-import { beforeEach, describe, expect, test, vi } from "vitest";
-import {
-  DEFAULT_EMBED_BATCH_SIZE,
-  GEMINI_EMBEDDING_MODEL,
-  GeminiEmbedding,
-} from "./GeminiEmbedding";
-
-// Mock the Google GenAI module
-const mockEmbedContent = vi.fn();
-vi.mock("@google/genai", () => ({
-  GoogleGenAI: vi.fn().mockImplementation(() => ({
-    models: {
-      embedContent: mockEmbedContent,
-    },
-  })),
-}));
-
-describe("GeminiEmbedding", () => {
-  let geminiEmbedding: GeminiEmbedding;
-  // Move capturedBatches to outer scope so all tests can access it
-  // eslint-disable-next-line @typescript-eslint/no-explicit-any
-  let capturedBatches: any[];
-
-  beforeEach(() => {
-    vi.clearAllMocks();
-    geminiEmbedding = new GeminiEmbedding({
-      model: GEMINI_EMBEDDING_MODEL.EMBEDDING_001,
-      apiKey: "test-api-key",
-    });
-    // Default mock for other tests
-    mockEmbedContent.mockResolvedValue({
-      embeddings: [
-        { values: [0.1, 0.2, 0.3] },
-        { values: [0.4, 0.5, 0.6] },
-        { values: [0.7, 0.8, 0.9] },
-      ],
-    });
-  });
-
-  describe("getTextEmbeddingsBatch", () => {
-    beforeEach(() => {
-      // Reset and set up capturedBatches and the mock implementation for all tests in this suite
-      capturedBatches = [];
-      mockEmbedContent.mockImplementation((args) => {
-        capturedBatches.push({
-          ...args,
-          contents: Array.isArray(args.contents)
-            ? [...args.contents]
-            : args.contents,
-        });
-        return Promise.resolve({
-          embeddings: Array.from(
-            { length: Array.isArray(args.contents) ? args.contents.length : 1 },
-            (_, i) => ({
-              values: [i * 0.1, i * 0.2, i * 0.3],
-            }),
-          ),
-        });
-      });
-    });
-
-    test("should respect batch size limit of 10 for texts longer than 10", async () => {
-      // Create a list of 2.5x the batch size texts, to exceed the batch size
-      const texts = Array.from(
-        { length: DEFAULT_EMBED_BATCH_SIZE * 2.5 },
-        (_, i) => `text ${i + 1}`,
-      );
-
-      await geminiEmbedding.getTextEmbeddingsBatch(texts);
-
-      // Verify that embedContent was called exactly 3 times (ceil(250/100) = 3)
-      expect(mockEmbedContent).toHaveBeenCalledTimes(3);
-      // Verify that each call had no more than 100 texts
-      const calls = mockEmbedContent.mock.calls;
-
-      // First batch should have DEFAULT_EMBED_BATCH_SIZE texts
-      expect(capturedBatches[0].contents).toHaveLength(
-        DEFAULT_EMBED_BATCH_SIZE,
-      );
-      expect(capturedBatches[0].contents).toEqual(
-        texts.slice(0 * DEFAULT_EMBED_BATCH_SIZE, 1 * DEFAULT_EMBED_BATCH_SIZE),
-      );
-
-      // Second batch should have DEFAULT_EMBED_BATCH_SIZE texts
-      expect(capturedBatches[1].contents).toHaveLength(
-        DEFAULT_EMBED_BATCH_SIZE,
-      );
-      expect(capturedBatches[1].contents).toEqual(
-        texts.slice(1 * DEFAULT_EMBED_BATCH_SIZE, 2 * DEFAULT_EMBED_BATCH_SIZE),
-      );
-
-      // Third batch should have 0.5 * DEFAULT_EMBED_BATCH_SIZE texts (remaining)
-      expect(capturedBatches[2].contents).toHaveLength(
-        DEFAULT_EMBED_BATCH_SIZE * 0.5,
-      );
-      expect(capturedBatches[2].contents).toEqual(
-        texts.slice(
-          2 * DEFAULT_EMBED_BATCH_SIZE,
-          2.5 * DEFAULT_EMBED_BATCH_SIZE,
-        ),
-      );
-    });
-
-    test("should handle exactly DEFAULT_EMBED_BATCH_SIZE texts in a single batch", async () => {
-      const texts = Array.from(
-        { length: DEFAULT_EMBED_BATCH_SIZE },
-        (_, i) => `text ${i + 1}`,
-      );
-
-      await geminiEmbedding.getTextEmbeddingsBatch(texts);
-
-      // Should be called exactly once
-      expect(mockEmbedContent).toHaveBeenCalledTimes(1);
-      // // Should contain all 100 texts
-      expect(capturedBatches[0]?.contents).toHaveLength(
-        DEFAULT_EMBED_BATCH_SIZE,
-      );
-      expect(capturedBatches[0]?.contents).toEqual(texts);
-    });
-
-    test("should handle texts shorter than batch size", async () => {
-      const short_batch_length = 5; // Less than DEFAULT_EMBED_BATCH_SIZE
-      const texts = Array.from(
-        { length: short_batch_length },
-        (_, i) => `text ${i + 1}`,
-      );
-
-      await geminiEmbedding.getTextEmbeddingsBatch(texts);
-
-      // Should be called exactly once
-      expect(mockEmbedContent).toHaveBeenCalledTimes(1);
-
-      // Should contain all 5 texts
-      expect(capturedBatches[0].contents).toHaveLength(short_batch_length);
-      expect(capturedBatches[0].contents).toEqual(texts);
-    });
-
-    test("should handle large batches correctly (100 texts)", async () => {
-      const n_batches = 10;
-      const texts = Array.from(
-        { length: DEFAULT_EMBED_BATCH_SIZE * n_batches },
-        (_, i) => `text ${i + 1}`,
-      );
-
-      await geminiEmbedding.getTextEmbeddingsBatch(texts);
-
-      // Should be called exactly 10 times
-      expect(mockEmbedContent).toHaveBeenCalledTimes(n_batches);
-
-      // Verify each batch has exactly DEFAULT_EMBED_BATCH_SIZE texts
-      for (let i = 0; i < n_batches; i++) {
-        expect(capturedBatches[i].contents).toHaveLength(
-          DEFAULT_EMBED_BATCH_SIZE,
-        );
-        expect(capturedBatches[i].contents).toEqual(
-          texts.slice(
-            i * DEFAULT_EMBED_BATCH_SIZE,
-            (i + 1) * DEFAULT_EMBED_BATCH_SIZE,
-          ),
-        );
-      }
-    });
-
-    test("should return correct embeddings for all texts", async () => {
-      const texts = ["text1", "text2", "text3"];
-
-      mockEmbedContent.mockResolvedValueOnce({
-        embeddings: [
-          { values: [0.1, 0.2, 0.3] },
-          { values: [0.4, 0.5, 0.6] },
-          { values: [0.7, 0.8, 0.9] },
-        ],
-      });
-
-      const result = await geminiEmbedding.getTextEmbeddingsBatch(texts);
-
-      expect(result).toEqual([
-        [0.1, 0.2, 0.3],
-        [0.4, 0.5, 0.6],
-        [0.7, 0.8, 0.9],
-      ]);
-    });
-
-    test("should handle empty embeddings gracefully", async () => {
-      const texts = ["text1", "text2"];
-
-      mockEmbedContent.mockResolvedValueOnce({
-        embeddings: [{ values: undefined }, { values: [0.1, 0.2, 0.3] }],
-      });
-
-      const result = await geminiEmbedding.getTextEmbeddingsBatch(texts);
-
-      expect(result).toEqual([[], [0.1, 0.2, 0.3]]);
-    });
-
-    test("should handle missing embeddings array", async () => {
-      const texts = ["text1"];
-
-      mockEmbedContent.mockResolvedValueOnce({
-        embeddings: undefined,
-      });
-
-      const result = await geminiEmbedding.getTextEmbeddingsBatch(texts);
-
-      expect(result).toEqual([]);
-    });
-  });
-
-  describe("getTextEmbedding", () => {
-    test("should call embedContent with single text", async () => {
-      const text = "single text";
-
-      mockEmbedContent.mockResolvedValueOnce({
-        embeddings: [{ values: [0.1, 0.2, 0.3] }],
-      });
-
-      const result = await geminiEmbedding.getTextEmbedding(text);
-
-      expect(mockEmbedContent).toHaveBeenCalledTimes(1);
-      expect(mockEmbedContent).toHaveBeenCalledWith({
-        model: GEMINI_EMBEDDING_MODEL.EMBEDDING_001,
-        contents: text,
-      });
-      expect(result).toEqual([0.1, 0.2, 0.3]);
-    });
-  });
-
-  describe("constructor", () => {
-    test("should set default model and batch size", () => {
-      const embedding = new GeminiEmbedding({ apiKey: "test-key" });
-
-      expect(embedding.model).toBe(GEMINI_EMBEDDING_MODEL.EMBEDDING_001);
-      expect(embedding.embedBatchSize).toBe(DEFAULT_EMBED_BATCH_SIZE);
-    });
-
-    test("should use provided model", () => {
-      const new_batch_size = 50;
-      const embedding = new GeminiEmbedding({
-        model: GEMINI_EMBEDDING_MODEL.TEXT_EMBEDDING_004,
-        apiKey: "test-key",
-        embedBatchSize: new_batch_size,
-      });
-
-      expect(embedding.model).toBe(GEMINI_EMBEDDING_MODEL.TEXT_EMBEDDING_004);
-      expect(embedding.embedBatchSize).toBe(new_batch_size);
-    });
-  });
-});
@@ -1,9 +1,5 @@
 import { GoogleGenAI, type GoogleGenAIOptions } from "@google/genai";
-import {
-  BaseEmbedding,
-  batchEmbeddings,
-  type BaseEmbeddingOptions,
-} from "@llamaindex/core/embeddings";
+import { BaseEmbedding } from "@llamaindex/core/embeddings";
 import { getEnv } from "@llamaindex/env";

 export enum GEMINI_EMBEDDING_MODEL {
@@ -11,15 +7,11 @@ export enum GEMINI_EMBEDDING_MODEL {
  TEXT_EMBEDDING_004 = "text-embedding-004",
 }

-// 100 is max batch size, see https://github.com/run-llama/LlamaIndexTS/pull/2099
-export const DEFAULT_EMBED_BATCH_SIZE = 100;
-
 /**
 * Configuration options for GeminiEmbedding.
 */
 export type GeminiEmbeddingOptions = {
  model?: GEMINI_EMBEDDING_MODEL;
-  embedBatchSize?: number;
 } & GoogleGenAIOptions;

 /**
@@ -28,7 +20,6 @@ export type GeminiEmbeddingOptions = {
 export class GeminiEmbedding extends BaseEmbedding {
  model: GEMINI_EMBEDDING_MODEL;
  ai: GoogleGenAI;
-  embedBatchSize: number = DEFAULT_EMBED_BATCH_SIZE;

  constructor(opts?: GeminiEmbeddingOptions) {
    super();
@@ -40,27 +31,15 @@ export class GeminiEmbedding extends BaseEmbedding {

    this.ai = new GoogleGenAI({ ...opts, apiKey });
    this.model = opts?.model ?? GEMINI_EMBEDDING_MODEL.EMBEDDING_001;
-    this.embedBatchSize = opts?.embedBatchSize ?? DEFAULT_EMBED_BATCH_SIZE;
  }

-  getTextEmbeddings = async (texts: string[]) => {
+  async getTextEmbeddingsBatch(texts: string[]): Promise<number[][]> {
    const result = await this.ai.models.embedContent({
      model: this.model,
      contents: texts,
    });
-    return result.embeddings?.map((embedding) => embedding.values ?? []) ?? [];
-  };

-  async getTextEmbeddingsBatch(
-    texts: string[],
-    options?: BaseEmbeddingOptions,
-  ): Promise<Array<number[]>> {
-    return await batchEmbeddings(
-      texts,
-      this.getTextEmbeddings.bind(this),
-      this.embedBatchSize,
-      options,
-    );
+    return result.embeddings?.map((embedding) => embedding.values ?? []) ?? [];
  }

  async getTextEmbedding(text: string): Promise<number[]> {
@@ -1,17 +1,5 @@
 # @llamaindex/groq

-## 0.0.84
-
-### Patch Changes
-
- @llamaindex/openai@0.4.12
-
-## 0.0.83
-
-### Patch Changes
-
- @llamaindex/openai@0.4.11
-
 ## 0.0.82

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/groq",
  "description": "Groq Adapter for LlamaIndex",
-  "version": "0.0.84",
+  "version": "0.0.82",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,21 +1,5 @@
 # @llamaindex/huggingface

-## 0.1.22
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-  - @llamaindex/openai@0.4.12
-
-## 0.1.21
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-  - @llamaindex/openai@0.4.11
-
 ## 0.1.20

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/huggingface",
  "description": "Huggingface Adapter for LlamaIndex",
-  "version": "0.1.22",
+  "version": "0.1.20",
  "type": "module",
  "types": "dist/index.d.ts",
  "main": "dist/index.cjs",
@@ -1,21 +1,5 @@
 # @llamaindex/jinaai

-## 0.0.28
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-  - @llamaindex/openai@0.4.12
-
-## 0.0.27
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-  - @llamaindex/openai@0.4.11
-
 ## 0.0.26

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/jinaai",
  "description": "JinaAI Adapter for LlamaIndex",
-  "version": "0.0.28",
+  "version": "0.0.26",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,19 +1,5 @@
 # @llamaindex/mistral

-## 0.1.17
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.1.16
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.1.15

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/mistral",
  "description": "Mistral Adapter for LlamaIndex",
-  "version": "0.1.17",
+  "version": "0.1.15",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,19 +1,5 @@
 # @llamaindex/mixedbread

-## 0.0.31
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.0.30
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.0.29

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/mixedbread",
  "description": "Mixedbread Adapter for LlamaIndex",
-  "version": "0.0.31",
+  "version": "0.0.29",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,19 +1,5 @@
 # @llamaindex/notion

-## 0.1.16
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.1.15
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.1.14

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/notion",
  "description": "Notion Reader for LlamaIndex",
-  "version": "0.1.16",
+  "version": "0.1.14",
  "type": "module",
  "types": "dist/index.d.ts",
  "main": "dist/index.cjs",
@@ -1,19 +1,5 @@
 # @llamaindex/ollama

-## 0.1.17
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.1.16
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.1.15

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/ollama",
  "description": "Ollama Adapter for LlamaIndex",
-  "version": "0.1.17",
+  "version": "0.1.15",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -1,19 +1,5 @@
 # @llamaindex/openai

-## 0.4.12
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-
-## 0.4.11
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-
 ## 0.4.10

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/openai",
  "description": "OpenAI Adapter for LlamaIndex",
-  "version": "0.4.12",
+  "version": "0.4.10",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
@@ -383,8 +383,8 @@ export class OpenAI extends ToolCallLLM<OpenAIAdditionalChatOptions> {
      // skip parts that don't have any content
      if (
        !(
-          choice.delta?.content ||
-          choice.delta?.tool_calls ||
+          choice.delta.content ||
+          choice.delta.tool_calls ||
          choice.finish_reason
        )
      )
@@ -1,9 +1,5 @@
-import {
-  ChatMessage,
-  ChatResponseChunk,
-  ToolCallLLMMessageOptions,
-} from "@llamaindex/core/llms";
-import { describe, expect, it, vi } from "vitest";
+import { ChatMessage, ToolCallLLMMessageOptions } from "@llamaindex/core/llms";
+import { describe, expect, it } from "vitest";
 import { z } from "zod";
 import { OpenAI } from "../src/llm";

@@ -235,52 +231,3 @@ describe("OpenAI Static Methods", () => {
    });
  });
 });
-
-describe("OpenAI streamChat", () => {
-  it("should handle choice with empty delta and finish_reason stop", async () => {
-    // Create a mock OpenAI instance
-    const mockStream = async function* () {
-      yield {
-        choices: [
-          {
-            delta: {},
-            finish_reason: "stop",
-            index: 0,
-            logprobs: null,
-          },
-        ],
-      };
-    };
-
-    // Mock the OpenAI session and chat completions
-    const mockSession = {
-      chat: {
-        completions: {
-          create: vi.fn().mockResolvedValue(mockStream()),
-        },
-      },
-    };
-
-    const openai = new OpenAI({
-      model: "gpt-4o-mini",
-      apiKey: "test-key",
-      // @ts-expect-error: mockSession is a mock object for testing purposes
-      session: mockSession,
-    });
-
-    // @ts-expect-error accessing protected method
-    const stream = openai.streamChat({
-      messages: [{ role: "user" as const, content: "Hello" }],
-      stream: true,
-    });
-
-    const chunks: ChatResponseChunk[] = [];
-    for await (const chunk of stream) {
-      chunks.push(chunk);
-    }
-
-    expect(chunks).toHaveLength(1);
-    expect(chunks[0].options).toEqual({});
-    expect(chunks[0].delta).toBe("");
-  });
-});
@@ -1,21 +1,5 @@
 # @llamaindex/perplexity

-## 0.0.25
-
-### Patch Changes
-
- Updated dependencies [38da40b]
-  - @llamaindex/core@0.6.17
-  - @llamaindex/openai@0.4.12
-
-## 0.0.24
-
-### Patch Changes
-
- Updated dependencies [a8ec08c]
-  - @llamaindex/core@0.6.16
-  - @llamaindex/openai@0.4.11
-
 ## 0.0.23

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/perplexity",
  "description": "Perplexity Adapter for LlamaIndex",
-  "version": "0.0.25",
+  "version": "0.0.23",
  "type": "module",
  "main": "./dist/index.cjs",
  "module": "./dist/index.js",
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Adrian Lyjak	78d6800b6b	Avoid using window deployment name on localhost, as that is conventional to default ot public. Optionally read deployment name from env vars as well	2025-07-21 11:28:15 -04:00
Adrian Lyjak	8b51db3bd8	add changeset	2025-07-18 19:37:40 -04:00
Adrian Lyjak	749e0f10cd	feat: default to _public agent data	2025-07-18 19:30:14 -04:00