Release 0.6.13 (#1288)

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

apps/docs/CHANGELOG.md

@@ -1,5 +1,20 @@
 # docs
 
+## 0.0.82
+
+### Patch Changes
+
+- llamaindex@0.6.13
+
+## 0.0.81
+
+### Patch Changes
+
+- Updated dependencies [f7b4e94]
+- Updated dependencies [78037a6]
+- Updated dependencies [1d9e3b1]
+  - llamaindex@0.6.12
+
 ## 0.0.80
 
 ### Patch Changes

apps/docs/docs/modules/data_loaders/llama_parse/index.mdx

@@ -13,7 +13,7 @@ Official documentation for LlamaParse can be found [here](https://docs.cloud.lla
 ## Usage
 
 You can then use the `LlamaParseReader` class to load local files and convert them into a parsed document that can be used by LlamaIndex.
-See [LlamaParseReader.ts](https://github.com/run-llama/LlamaIndexTS/blob/main/packages/llamaindex/src/readers/LlamaParseReader.ts) for a list of supported file types:
+See [reader.ts](https://github.com/run-llama/LlamaIndexTS/blob/main/packages/cloud/src/reader.ts) for a list of supported file types:
 
 <CodeBlock language="ts">{CodeSource}</CodeBlock>
 

apps/docs/package.json

@@ -1,6 +1,6 @@
 {
   "name": "docs",
-  "version": "0.0.80",
+  "version": "0.0.82",
   "private": true,
   "scripts": {
     "docusaurus": "docusaurus",

packages/autotool/CHANGELOG.md

@@ -1,5 +1,20 @@
 # @llamaindex/autotool
 
+## 3.0.13
+
+### Patch Changes
+
+- llamaindex@0.6.13
+
+## 3.0.12
+
+### Patch Changes
+
+- Updated dependencies [f7b4e94]
+- Updated dependencies [78037a6]
+- Updated dependencies [1d9e3b1]
+  - llamaindex@0.6.12
+
 ## 3.0.11
 
 ### Patch Changes

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

@@ -1,5 +1,22 @@
 # @llamaindex/autotool-01-node-example
 
+## 0.0.22
+
+### Patch Changes
+
+- llamaindex@0.6.13
+- @llamaindex/autotool@3.0.13
+
+## 0.0.21
+
+### Patch Changes
+
+- Updated dependencies [f7b4e94]
+- Updated dependencies [78037a6]
+- Updated dependencies [1d9e3b1]
+  - llamaindex@0.6.12
+  - @llamaindex/autotool@3.0.12
+
 ## 0.0.20
 
 ### 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": "0.0.20"
+  "version": "0.0.22"
 }

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

@@ -1,5 +1,22 @@
 # @llamaindex/autotool-02-next-example
 
+## 0.1.66
+
+### Patch Changes
+
+- llamaindex@0.6.13
+- @llamaindex/autotool@3.0.13
+
+## 0.1.65
+
+### Patch Changes
+
+- Updated dependencies [f7b4e94]
+- Updated dependencies [78037a6]
+- Updated dependencies [1d9e3b1]
+  - llamaindex@0.6.12
+  - @llamaindex/autotool@3.0.12
+
 ## 0.1.64
 
 ### Patch Changes

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

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/autotool-02-next-example",
   "private": true,
-  "version": "0.1.64",
+  "version": "0.1.66",
   "scripts": {
     "dev": "next dev",
     "build": "next build",

packages/autotool/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/autotool",
   "type": "module",
-  "version": "3.0.11",
+  "version": "3.0.13",
   "description": "auto transpile your JS function to LLM Agent compatible",
   "files": [
     "dist",

packages/cloud/CHANGELOG.md

@@ -1,5 +1,11 @@
 # @llamaindex/cloud
 
+## 0.2.10
+
+### Patch Changes
+
+- 981811e: fix(cloud): llama parse reader save image incorrectly
+
 ## 0.2.9
 
 ### Patch Changes

packages/cloud/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/cloud",
-  "version": "0.2.9",
+  "version": "0.2.10",
   "type": "module",
   "license": "MIT",
   "scripts": {

packages/cloud/src/reader.ts

@@ -1,11 +1,11 @@
-import { createClient, createConfig, type Client } from "@hey-api/client-fetch";
+import { type Client, createClient, createConfig } from "@hey-api/client-fetch";
 import { Document, FileReader } from "@llamaindex/core/schema";
-import { fs, getEnv } from "@llamaindex/env";
+import { fs, getEnv, path } from "@llamaindex/env";
 import { filetypeinfo } from "magic-bytes.js";
 import {
-  ParsingService,
   type Body_upload_file_api_v1_parsing_upload_post,
   type ParserLanguages,
+  ParsingService,
 } from "./api";
 import { sleep } from "./utils";
 
@@ -510,14 +510,7 @@ export class LlamaParseReader extends FileReader {
     jobId: string,
     imageName: string,
   ): Promise<string> {
-    // Get the full path
-    let imagePath = `${downloadPath}/${jobId}-${imageName}`;
-    // Get a valid image path
-    if (!imagePath.endsWith(".png") && !imagePath.endsWith(".jpg")) {
-      imagePath += ".png";
-    }
-
-    return imagePath;
+    return path.join(downloadPath, `${jobId}-${imageName}`);
   }
 
   private async fetchAndSaveImage(
@@ -538,10 +531,9 @@ export class LlamaParseReader extends FileReader {
     if (response.error) {
       throw new Error(`Failed to download image: ${response.error.detail}`);
     }
-    const arrayBuffer = (await response.data) as ArrayBuffer;
-    const buffer = new Uint8Array(arrayBuffer);
+    const blob = (await response.data) as Blob;
     // Write the image buffer to the specified imagePath
-    await fs.writeFile(imagePath, buffer);
+    await fs.writeFile(imagePath, new Uint8Array(await blob.arrayBuffer()));
   }
 
   // Filters out invalid values (null, undefined, empty string) of specific params.

packages/community/CHANGELOG.md

@@ -1,5 +1,11 @@
 # @llamaindex/community
 
+## 0.0.43
+
+### Patch Changes
+
+- 2774e80: feat: added meta3.2 support via Bedrock including vision, tool call and inference region support
+
 ## 0.0.42
 
 ### Patch Changes

packages/community/README.md

@@ -5,9 +5,11 @@
 ## Current Features:
 
 - Bedrock support for the Anthropic Claude Models [usage](https://ts.llamaindex.ai/modules/llms/available_llms/bedrock)
-- Bedrock support for the Meta LLama 2, 3 and 3.1 Models [usage](https://ts.llamaindex.ai/modules/llms/available_llms/bedrock)
-- Meta LLama3.1 405b tool call support
+- 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
+- Meta 3.2 11B and 90B vision support
 - Bedrock support for querying Knowledge Base
+- Bedrock: [Supported Regions and models for cross-region inference](https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference-support.html)
 
 ## LICENSE
 

packages/community/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/community",
   "description": "Community package for LlamaIndexTS",
-  "version": "0.0.42",
+  "version": "0.0.43",
   "type": "module",
   "types": "dist/type/index.d.ts",
   "main": "dist/cjs/index.js",

packages/community/src/index.ts

@@ -2,5 +2,7 @@ export {
   BEDROCK_MODELS,
   BEDROCK_MODEL_MAX_TOKENS,
   Bedrock,
+  INFERENCE_BEDROCK_MODELS,
+  INFERENCE_TO_BEDROCK_MAP,
 } from "./llm/bedrock/index.js";
 export { AmazonKnowledgeBaseRetriever } from "./retrievers/bedrock.js";

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

@@ -6,7 +6,10 @@ import type {
   MessageContentDetail,
   ToolCallLLMMessageOptions,
 } from "@llamaindex/core/llms";
-import { mapMessageContentToMessageContentDetails } from "../utils";
+import {
+  extractDataUrlComponents,
+  mapMessageContentToMessageContentDetails,
+} from "../utils";
 import type {
   AnthropicContent,
   AnthropicImageContent,
@@ -143,27 +146,6 @@ export const mapTextContent = (text: string): AnthropicTextContent => {
   return { type: "text", text };
 };
 
-export const extractDataUrlComponents = (
-  dataUrl: string,
-): {
-  mimeType: string;
-  base64: string;
-} => {
-  const parts = dataUrl.split(";base64,");
-
-  if (parts.length !== 2 || !parts[0]!.startsWith("data:")) {
-    throw new Error("Invalid data URL");
-  }
-
-  const mimeType = parts[0]!.slice(5);
-  const base64 = parts[1]!;
-
-  return {
-    mimeType,
-    base64,
-  };
-};
-
 export const mapImageContent = (imageUrl: string): AnthropicImageContent => {
   if (!imageUrl.startsWith("data:"))
     throw new Error(

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

@@ -47,35 +47,96 @@ export type BedrockChatParamsNonStreaming = LLMChatParamsNonStreaming<
 export type BedrockChatNonStreamResponse =
   ChatResponse<ToolCallLLMMessageOptions>;
 
-export enum BEDROCK_MODELS {
-  AMAZON_TITAN_TG1_LARGE = "amazon.titan-tg1-large",
-  AMAZON_TITAN_TEXT_EXPRESS_V1 = "amazon.titan-text-express-v1",
-  AI21_J2_GRANDE_INSTRUCT = "ai21.j2-grande-instruct",
-  AI21_J2_JUMBO_INSTRUCT = "ai21.j2-jumbo-instruct",
-  AI21_J2_MID = "ai21.j2-mid",
-  AI21_J2_MID_V1 = "ai21.j2-mid-v1",
-  AI21_J2_ULTRA = "ai21.j2-ultra",
-  AI21_J2_ULTRA_V1 = "ai21.j2-ultra-v1",
-  COHERE_COMMAND_TEXT_V14 = "cohere.command-text-v14",
-  ANTHROPIC_CLAUDE_INSTANT_1 = "anthropic.claude-instant-v1",
-  ANTHROPIC_CLAUDE_1 = "anthropic.claude-v1", // EOF: No longer supported
-  ANTHROPIC_CLAUDE_2 = "anthropic.claude-v2",
-  ANTHROPIC_CLAUDE_2_1 = "anthropic.claude-v2:1",
-  ANTHROPIC_CLAUDE_3_SONNET = "anthropic.claude-3-sonnet-20240229-v1:0",
-  ANTHROPIC_CLAUDE_3_HAIKU = "anthropic.claude-3-haiku-20240307-v1:0",
-  ANTHROPIC_CLAUDE_3_OPUS = "anthropic.claude-3-opus-20240229-v1:0",
-  ANTHROPIC_CLAUDE_3_5_SONNET = "anthropic.claude-3-5-sonnet-20240620-v1:0",
-  META_LLAMA2_13B_CHAT = "meta.llama2-13b-chat-v1",
-  META_LLAMA2_70B_CHAT = "meta.llama2-70b-chat-v1",
-  META_LLAMA3_8B_INSTRUCT = "meta.llama3-8b-instruct-v1:0",
-  META_LLAMA3_70B_INSTRUCT = "meta.llama3-70b-instruct-v1:0",
-  META_LLAMA3_1_8B_INSTRUCT = "meta.llama3-1-8b-instruct-v1:0",
-  META_LLAMA3_1_70B_INSTRUCT = "meta.llama3-1-70b-instruct-v1:0",
-  META_LLAMA3_1_405B_INSTRUCT = "meta.llama3-1-405b-instruct-v1:0",
-  MISTRAL_7B_INSTRUCT = "mistral.mistral-7b-instruct-v0:2",
-  MISTRAL_MIXTRAL_7B_INSTRUCT = "mistral.mixtral-8x7b-instruct-v0:1",
-  MISTRAL_MIXTRAL_LARGE_2402 = "mistral.mistral-large-2402-v1:0",
-}
+export const BEDROCK_MODELS = {
+  AMAZON_TITAN_TG1_LARGE: "amazon.titan-tg1-large",
+  AMAZON_TITAN_TEXT_EXPRESS_V1: "amazon.titan-text-express-v1",
+  AI21_J2_GRANDE_INSTRUCT: "ai21.j2-grande-instruct",
+  AI21_J2_JUMBO_INSTRUCT: "ai21.j2-jumbo-instruct",
+  AI21_J2_MID: "ai21.j2-mid",
+  AI21_J2_MID_V1: "ai21.j2-mid-v1",
+  AI21_J2_ULTRA: "ai21.j2-ultra",
+  AI21_J2_ULTRA_V1: "ai21.j2-ultra-v1",
+  COHERE_COMMAND_TEXT_V14: "cohere.command-text-v14",
+  ANTHROPIC_CLAUDE_INSTANT_1: "anthropic.claude-instant-v1",
+  ANTHROPIC_CLAUDE_1: "anthropic.claude-v1", // EOF: No longer supported
+  ANTHROPIC_CLAUDE_2: "anthropic.claude-v2",
+  ANTHROPIC_CLAUDE_2_1: "anthropic.claude-v2:1",
+  ANTHROPIC_CLAUDE_3_SONNET: "anthropic.claude-3-sonnet-20240229-v1:0",
+  ANTHROPIC_CLAUDE_3_HAIKU: "anthropic.claude-3-haiku-20240307-v1:0",
+  ANTHROPIC_CLAUDE_3_OPUS: "anthropic.claude-3-opus-20240229-v1:0",
+  ANTHROPIC_CLAUDE_3_5_SONNET: "anthropic.claude-3-5-sonnet-20240620-v1:0",
+  META_LLAMA2_13B_CHAT: "meta.llama2-13b-chat-v1",
+  META_LLAMA2_70B_CHAT: "meta.llama2-70b-chat-v1",
+  META_LLAMA3_8B_INSTRUCT: "meta.llama3-8b-instruct-v1:0",
+  META_LLAMA3_70B_INSTRUCT: "meta.llama3-70b-instruct-v1:0",
+  META_LLAMA3_1_8B_INSTRUCT: "meta.llama3-1-8b-instruct-v1:0",
+  META_LLAMA3_1_70B_INSTRUCT: "meta.llama3-1-70b-instruct-v1:0",
+  META_LLAMA3_1_405B_INSTRUCT: "meta.llama3-1-405b-instruct-v1:0",
+  META_LLAMA3_2_1B_INSTRUCT: "meta.llama3-2-1b-instruct-v1:0",
+  META_LLAMA3_2_3B_INSTRUCT: "meta.llama3-2-3b-instruct-v1:0",
+  META_LLAMA3_2_11B_INSTRUCT: "meta.llama3-2-11b-instruct-v1:0",
+  META_LLAMA3_2_90B_INSTRUCT: "meta.llama3-2-90b-instruct-v1:0",
+  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",
+};
+export type BEDROCK_MODELS =
+  (typeof BEDROCK_MODELS)[keyof typeof BEDROCK_MODELS];
+
+export const INFERENCE_BEDROCK_MODELS = {
+  US_ANTHROPIC_CLAUDE_3_HAIKU: "us.anthropic.claude-3-haiku-20240307-v1:0",
+  US_ANTHROPIC_CLAUDE_3_OPUS: "us.anthropic.claude-3-opus-20240229-v1:0",
+  US_ANTHROPIC_CLAUDE_3_SONNET: "us.anthropic.claude-3-sonnet-20240229-v1:0",
+  US_ANTHROPIC_CLAUDE_3_5_SONNET:
+    "us.anthropic.claude-3-5-sonnet-20240620-v1:0",
+  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",
+
+  EU_ANTHROPIC_CLAUDE_3_HAIKU: "eu.anthropic.claude-3-haiku-20240307-v1:0",
+  EU_ANTHROPIC_CLAUDE_3_SONNET: "eu.anthropic.claude-3-sonnet-20240229-v1:0",
+  EU_ANTHROPIC_CLAUDE_3_5_SONNET:
+    "eu.anthropic.claude-3-5-sonnet-20240620-v1:0",
+  EU_META_LLAMA_3_2_1B_INSTRUCT: "eu.meta.llama3-2-1b-instruct-v1:0",
+  EU_META_LLAMA_3_2_3B_INSTRUCT: "eu.meta.llama3-2-3b-instruct-v1:0",
+};
+
+export type INFERENCE_BEDROCK_MODELS =
+  (typeof INFERENCE_BEDROCK_MODELS)[keyof typeof INFERENCE_BEDROCK_MODELS];
+
+export const INFERENCE_TO_BEDROCK_MAP: Record<
+  INFERENCE_BEDROCK_MODELS,
+  BEDROCK_MODELS
+> = {
+  [INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_HAIKU]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU,
+  [INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_OPUS]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_OPUS,
+  [INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_SONNET]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_SONNET,
+  [INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_5_SONNET]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET,
+  [INFERENCE_BEDROCK_MODELS.US_META_LLAMA_3_2_1B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_2_1B_INSTRUCT,
+  [INFERENCE_BEDROCK_MODELS.US_META_LLAMA_3_2_3B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT,
+  [INFERENCE_BEDROCK_MODELS.US_META_LLAMA_3_2_11B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT,
+  [INFERENCE_BEDROCK_MODELS.US_META_LLAMA_3_2_90B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT,
+
+  [INFERENCE_BEDROCK_MODELS.EU_ANTHROPIC_CLAUDE_3_HAIKU]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU,
+  [INFERENCE_BEDROCK_MODELS.EU_ANTHROPIC_CLAUDE_3_SONNET]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_SONNET,
+  [INFERENCE_BEDROCK_MODELS.EU_ANTHROPIC_CLAUDE_3_5_SONNET]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET,
+  [INFERENCE_BEDROCK_MODELS.EU_META_LLAMA_3_2_1B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_2_1B_INSTRUCT,
+  [INFERENCE_BEDROCK_MODELS.EU_META_LLAMA_3_2_3B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT,
+};
 
 /*
  * Values taken from https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters.html#model-parameters-claude
@@ -109,6 +170,10 @@ const CHAT_ONLY_MODELS = {
   [BEDROCK_MODELS.META_LLAMA3_1_8B_INSTRUCT]: 128000,
   [BEDROCK_MODELS.META_LLAMA3_1_70B_INSTRUCT]: 128000,
   [BEDROCK_MODELS.META_LLAMA3_1_405B_INSTRUCT]: 128000,
+  [BEDROCK_MODELS.META_LLAMA3_2_1B_INSTRUCT]: 131000,
+  [BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT]: 131000,
+  [BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT]: 128000,
+  [BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT]: 128000,
   [BEDROCK_MODELS.MISTRAL_7B_INSTRUCT]: 32000,
   [BEDROCK_MODELS.MISTRAL_MIXTRAL_7B_INSTRUCT]: 32000,
   [BEDROCK_MODELS.MISTRAL_MIXTRAL_LARGE_2402]: 32000,
@@ -139,17 +204,25 @@ export const STREAMING_MODELS = new Set([
   BEDROCK_MODELS.META_LLAMA3_1_8B_INSTRUCT,
   BEDROCK_MODELS.META_LLAMA3_1_70B_INSTRUCT,
   BEDROCK_MODELS.META_LLAMA3_1_405B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_2_1B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT,
   BEDROCK_MODELS.MISTRAL_7B_INSTRUCT,
   BEDROCK_MODELS.MISTRAL_MIXTRAL_7B_INSTRUCT,
   BEDROCK_MODELS.MISTRAL_MIXTRAL_LARGE_2402,
 ]);
 
-export const TOOL_CALL_MODELS = [
+export const TOOL_CALL_MODELS: BEDROCK_MODELS[] = [
   BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_SONNET,
   BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU,
   BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_OPUS,
   BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET,
   BEDROCK_MODELS.META_LLAMA3_1_405B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_2_1B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT,
 ];
 
 const getProvider = (model: string): Provider => {
@@ -166,7 +239,7 @@ const getProvider = (model: string): Provider => {
 };
 
 export type BedrockModelParams = {
-  model: keyof typeof BEDROCK_FOUNDATION_LLMS;
+  model: BEDROCK_MODELS | INFERENCE_BEDROCK_MODELS;
   temperature?: number;
   topP?: number;
   maxTokens?: number;
@@ -185,6 +258,10 @@ export const BEDROCK_MODEL_MAX_TOKENS: Partial<Record<BEDROCK_MODELS, number>> =
     [BEDROCK_MODELS.META_LLAMA3_1_8B_INSTRUCT]: 2048,
     [BEDROCK_MODELS.META_LLAMA3_1_70B_INSTRUCT]: 2048,
     [BEDROCK_MODELS.META_LLAMA3_1_405B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_2_1B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT]: 2048,
   };
 
 const DEFAULT_BEDROCK_PARAMS = {
@@ -193,14 +270,15 @@ const DEFAULT_BEDROCK_PARAMS = {
   maxTokens: 1024, // required by anthropic
 };
 
-export type BedrockParams = BedrockModelParams & BedrockRuntimeClientConfig;
+export type BedrockParams = BedrockRuntimeClientConfig & BedrockModelParams;
 
 /**
  * ToolCallLLM for Bedrock
  */
 export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
   private client: BedrockRuntimeClient;
-  model: keyof typeof BEDROCK_FOUNDATION_LLMS;
+  protected actualModel: BEDROCK_MODELS | INFERENCE_BEDROCK_MODELS;
+  model: BEDROCK_MODELS;
   temperature: number;
   topP: number;
   maxTokens?: number;
@@ -217,8 +295,8 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
     ...params
   }: BedrockParams) {
     super();
-
-    this.model = model;
+    this.actualModel = model;
+    this.model = INFERENCE_TO_BEDROCK_MAP[model] ?? model;
     this.provider = getProvider(this.model);
     this.maxTokens = maxTokens ?? DEFAULT_BEDROCK_PARAMS.maxTokens;
     this.temperature = temperature ?? DEFAULT_BEDROCK_PARAMS.temperature;
@@ -241,7 +319,7 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
       temperature: this.temperature,
       topP: this.topP,
       maxTokens: this.maxTokens,
-      contextWindow: BEDROCK_FOUNDATION_LLMS[this.model],
+      contextWindow: BEDROCK_FOUNDATION_LLMS[this.model] ?? 128000,
       tokenizer: undefined,
     };
   }
@@ -256,6 +334,8 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
       params.additionalChatOptions,
     );
     const command = new InvokeModelCommand(input);
+    command.input.modelId = this.actualModel;
+
     const response = await this.client.send(command);
     let options: ToolCallLLMMessageOptions = {};
     if (this.supportToolCall) {
@@ -287,6 +367,8 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
       params.additionalChatOptions,
     );
     const command = new InvokeModelWithResponseStreamCommand(input);
+    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/meta/provider.ts

@@ -67,21 +67,26 @@ export class MetaProvider extends Provider<MetaStreamEvent> {
     for await (const response of stream) {
       const event = this.getStreamingEventResponse(response);
       const delta = this.getTextFromStreamResponse(response);
+
       // odd quirk of llama3.1, start token is \n\n
       if (
+        !toolId &&
         !event?.generation.trim() &&
         event?.generation_token_count === 1 &&
-        event.prompt_token_count !== null
+        event?.prompt_token_count !== null
       )
         continue;
 
-      if (delta === TOKENS.TOOL_CALL) {
+      if (delta.startsWith(TOKENS.TOOL_CALL)) {
         toolId = randomUUID();
+        const parts = delta.split(TOKENS.TOOL_CALL).filter((part) => part);
+        collecting.push(...parts);
         continue;
       }
 
       let options: undefined | ToolCallLLMMessageOptions = undefined;
       if (toolId && event?.stop_reason === "stop") {
+        if (delta) collecting.push(delta);
         const tool = JSON.parse(collecting.join(""));
         options = {
           toolCall: [
@@ -110,11 +115,18 @@ export class MetaProvider extends Provider<MetaStreamEvent> {
   getRequestBody<T extends ChatMessage>(
     metadata: LLMMetadata,
     messages: T[],
-    tools?: BaseTool[],
+    tools: BaseTool[] = [],
   ): InvokeModelCommandInput | InvokeModelWithResponseStreamCommandInput {
     let prompt: string = "";
+    let images: string[] = [];
     if (metadata.model.startsWith("meta.llama3")) {
-      prompt = mapChatMessagesToMetaLlama3Messages(messages, tools);
+      const mapped = mapChatMessagesToMetaLlama3Messages({
+        messages,
+        tools,
+        model: metadata.model,
+      });
+      prompt = mapped.prompt;
+      images = mapped.images;
     } else if (metadata.model.startsWith("meta.llama2")) {
       prompt = mapChatMessagesToMetaLlama2Messages(messages);
     } else {
@@ -127,6 +139,7 @@ export class MetaProvider extends Provider<MetaStreamEvent> {
       accept: "application/json",
       body: JSON.stringify({
         prompt,
+        images: images.length ? images : undefined,
         max_gen_len: metadata.maxTokens,
         temperature: metadata.temperature,
         top_p: metadata.topP,

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

@@ -1,9 +1,12 @@
 import type {
   BaseTool,
   ChatMessage,
+  LLMMetadata,
   MessageContentTextDetail,
   ToolCallLLMMessageOptions,
 } from "@llamaindex/core/llms";
+import { extractDataUrlComponents } from "../utils";
+import { TOKENS } from "./constants";
 import type { MetaMessage } from "./types";
 
 const getToolCallInstructionString = (tool: BaseTool): string => {
@@ -24,7 +27,7 @@ const getToolCallParametersString = (tool: BaseTool): string => {
 
 // ported from https://github.com/meta-llama/llama-agentic-system/blob/main/llama_agentic_system/system_prompt.py
 // NOTE: using json instead of the above xml style tool calling works more reliability
-export const getToolsPrompt = (tools?: BaseTool[]) => {
+export const getToolsPrompt_3_1 = (tools?: BaseTool[]) => {
   if (!tools?.length) return "";
 
   const customToolParams = tools.map((tool) => {
@@ -77,6 +80,46 @@ Reminder:
   `;
 };
 
+export const getToolsPrompt_3_2 = (tools?: BaseTool[]) => {
+  if (!tools?.length) return "";
+  return `
+You are an expert in composing functions. You are given a question and a set of possible functions.
+Based on the question, you will need to make one or more function/tool calls to achieve the purpose.
+If none of the function can be used, point it out. If the given question lacks the parameters required by the function,
+also point it out. You should only return the function call in tools call sections.
+
+If you decide to invoke any of the function(s), you MUST put it in the format of and start with the token: ${TOKENS.TOOL_CALL}:
+{
+  "name": function_name,
+  "parameters": parameters,
+}
+where
+
+{
+  "name": function_name,
+  "parameters": parameters, => a JSON dict with the function argument name as key and function argument value as value.
+}
+
+Here is an example,
+
+{
+  "name": "example_function_name",
+  "parameters": {"example_name": "example_value"}
+}
+
+Reminder:
+- Function calls MUST follow the specified format
+- Required parameters MUST be specified
+- Only call one function at a time
+- You SHOULD NOT include any other text in the response
+- Put the entire function call reply on one line
+
+Here is a list of functions in JSON format that you can invoke.
+
+${JSON.stringify(tools)}
+`;
+};
+
 export const mapChatRoleToMetaRole = (
   role: ChatMessage["role"],
 ): MetaMessage["role"] => {
@@ -125,16 +168,46 @@ export const mapChatMessagesToMetaMessages = <
 /**
  * Documentation at https://llama.meta.com/docs/model-cards-and-prompt-formats/meta-llama-3
  */
-export const mapChatMessagesToMetaLlama3Messages = <T extends ChatMessage>(
-  messages: T[],
-  tools?: BaseTool[],
-): string => {
+export const mapChatMessagesToMetaLlama3Messages = <T extends ChatMessage>({
+  messages,
+  model,
+  tools,
+}: {
+  messages: T[];
+  model: LLMMetadata["model"];
+  tools?: BaseTool[];
+}): { prompt: string; images: string[] } => {
+  const images: string[] = [];
+  const textMessages: T[] = [];
+
+  messages.forEach((message) => {
+    if (Array.isArray(message.content)) {
+      message.content.forEach((content) => {
+        if (content.type === "image_url") {
+          const { base64 } = extractDataUrlComponents(content.image_url.url);
+          images.push(base64);
+        } else {
+          textMessages.push(message);
+        }
+      });
+    } else {
+      textMessages.push(message);
+    }
+  });
+
   const parts: string[] = [];
-  if (tools?.length) {
+
+  let toolsPrompt = "";
+  if (model.startsWith("meta.llama3-2")) {
+    toolsPrompt = getToolsPrompt_3_2(tools);
+  } else if (model.startsWith("meta.llama3-1")) {
+    toolsPrompt = getToolsPrompt_3_1(tools);
+  }
+  if (toolsPrompt) {
     parts.push(
       "<|begin_of_text|>",
       "<|start_header_id|>system<|end_header_id|>",
-      getToolsPrompt(tools),
+      toolsPrompt,
       "<|eot_id|>",
     );
   }
@@ -154,7 +227,9 @@ export const mapChatMessagesToMetaLlama3Messages = <T extends ChatMessage>(
     ...mapped,
     "<|start_header_id|>assistant<|end_header_id|>",
   );
-  return parts.join("\n");
+
+  const prompt = parts.join("\n");
+  return { prompt, images };
 };
 
 /**

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

@@ -11,3 +11,24 @@ export const mapMessageContentToMessageContentDetails = (
 
 export const toUtf8 = (input: Uint8Array): string =>
   new TextDecoder("utf-8").decode(input);
+
+export const extractDataUrlComponents = (
+  dataUrl: string,
+): {
+  mimeType: string;
+  base64: string;
+} => {
+  const parts = dataUrl.split(";base64,");
+
+  if (parts.length !== 2 || !parts[0]!.startsWith("data:")) {
+    throw new Error("Invalid data URL");
+  }
+
+  const mimeType = parts[0]!.slice(5);
+  const base64 = parts[1]!;
+
+  return {
+    mimeType,
+    base64,
+  };
+};

packages/core/tests/workflow.test.ts

@@ -166,4 +166,68 @@ describe("Workflow", () => {
       greeting: "Hello Alice, you are 30 years old!",
     });
   });
+
+  test("workflow with two concurrent steps", async () => {
+    const concurrentFlow = new Workflow({ verbose: true });
+
+    const step1 = vi.fn(async (_context, _ev: StartEvent) => {
+      await new Promise((resolve) => setTimeout(resolve, 200));
+      return new StopEvent({ result: "Step 1 completed" });
+    });
+
+    const step2 = vi.fn(async (_context, _ev: StartEvent) => {
+      await new Promise((resolve) => setTimeout(resolve, 100));
+      return new StopEvent({ result: "Step 2 completed" });
+    });
+
+    concurrentFlow.addStep(StartEvent, step1);
+    concurrentFlow.addStep(StartEvent, step2);
+
+    const startTime = new Date();
+    const result = await concurrentFlow.run("start");
+    const endTime = new Date();
+    const duration = endTime.getTime() - startTime.getTime();
+
+    expect(step1).toHaveBeenCalledTimes(1);
+    expect(step2).toHaveBeenCalledTimes(1);
+    expect(duration).toBeLessThan(200);
+    expect(result.data.result).toBe("Step 2 completed");
+  });
+
+  test("workflow with two concurrent cyclic steps", async () => {
+    const concurrentCyclicFlow = new Workflow({ verbose: true });
+
+    class Step1Event extends WorkflowEvent {}
+    class Step2Event extends WorkflowEvent {}
+
+    let step2Count = 0;
+
+    const step1 = vi.fn(async (_context, ev: StartEvent | Step1Event) => {
+      await new Promise((resolve) => setTimeout(resolve, 1000));
+      return new Step1Event({ result: "Step 1 completed" });
+    });
+
+    const step2 = vi.fn(async (_context, ev: StartEvent | Step2Event) => {
+      await new Promise((resolve) => setTimeout(resolve, 100));
+      step2Count++;
+      if (step2Count >= 5) {
+        return new StopEvent({ result: "Step 2 completed 5 times" });
+      }
+      return new Step2Event({ result: "Step 2 completed" });
+    });
+
+    concurrentCyclicFlow.addStep([StartEvent, Step1Event], step1);
+    concurrentCyclicFlow.addStep([StartEvent, Step2Event], step2);
+
+    const startTime = new Date();
+    const result = await concurrentCyclicFlow.run("start");
+    const endTime = new Date();
+    const duration = endTime.getTime() - startTime.getTime();
+
+    expect(step1).toHaveBeenCalledTimes(1);
+    expect(step2).toHaveBeenCalledTimes(5);
+    expect(duration).toBeGreaterThan(500); // At least 5 * 100ms for step2
+    expect(duration).toBeLessThan(1000); // Less than 1 second
+    expect(result.data.result).toBe("Step 2 completed 5 times");
+  });
 });

packages/experimental/CHANGELOG.md

@@ -1,5 +1,20 @@
 # @llamaindex/experimental
 
+## 0.0.91
+
+### Patch Changes
+
+- llamaindex@0.6.13
+
+## 0.0.90
+
+### Patch Changes
+
+- Updated dependencies [f7b4e94]
+- Updated dependencies [78037a6]
+- Updated dependencies [1d9e3b1]
+  - llamaindex@0.6.12
+
 ## 0.0.89
 
 ### Patch Changes

packages/experimental/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/experimental",
   "description": "Experimental package for LlamaIndexTS",
-  "version": "0.0.89",
+  "version": "0.0.91",
   "type": "module",
   "types": "dist/type/index.d.ts",
   "main": "dist/cjs/index.js",

packages/llamaindex/CHANGELOG.md

@@ -1,5 +1,20 @@
 # llamaindex
 
+## 0.6.13
+
+### Patch Changes
+
+- Updated dependencies [981811e]
+  - @llamaindex/cloud@0.2.10
+
+## 0.6.12
+
+### Patch Changes
+
+- f7b4e94: feat: add filters for pinecone
+- 78037a6: fix: bypass service context embed model
+- 1d9e3b1: fix: export llama reader in non-nodejs runtime
+
 ## 0.6.11
 
 ### Patch Changes

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

@@ -1,5 +1,20 @@
 # @llamaindex/cloudflare-worker-agent-test
 
+## 0.0.75
+
+### Patch Changes
+
+- llamaindex@0.6.13
+
+## 0.0.74
+
+### Patch Changes
+
+- Updated dependencies [f7b4e94]
+- Updated dependencies [78037a6]
+- Updated dependencies [1d9e3b1]
+  - llamaindex@0.6.12
+
 ## 0.0.73
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/cloudflare-worker-agent-test",
-  "version": "0.0.73",
+  "version": "0.0.75",
   "type": "module",
   "private": true,
   "scripts": {

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

@@ -1,5 +1,12 @@
 # @llamaindex/llama-parse-browser-test
 
+## 0.0.6
+
+### Patch Changes
+
+- Updated dependencies [981811e]
+  - @llamaindex/cloud@0.2.10
+
 ## 0.0.5
 
 ### Patch Changes

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

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/llama-parse-browser-test",
   "private": true,
-  "version": "0.0.5",
+  "version": "0.0.6",
   "type": "module",
   "scripts": {
     "dev": "vite",

packages/llamaindex/e2e/examples/nextjs-agent/CHANGELOG.md

@@ -1,5 +1,20 @@
 # @llamaindex/next-agent-test
 
+## 0.1.75
+
+### Patch Changes
+
+- llamaindex@0.6.13
+
+## 0.1.74
+
+### Patch Changes
+
+- Updated dependencies [f7b4e94]
+- Updated dependencies [78037a6]
+- Updated dependencies [1d9e3b1]
+  - llamaindex@0.6.12
+
 ## 0.1.73
 
 ### Patch Changes

packages/llamaindex/e2e/examples/nextjs-agent/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-agent-test",
-  "version": "0.1.73",
+  "version": "0.1.75",
   "private": true,
   "scripts": {
     "dev": "next dev",

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

@@ -1,5 +1,20 @@
 # test-edge-runtime
 
+## 0.1.74
+
+### Patch Changes
+
+- llamaindex@0.6.13
+
+## 0.1.73
+
+### Patch Changes
+
+- Updated dependencies [f7b4e94]
+- Updated dependencies [78037a6]
+- Updated dependencies [1d9e3b1]
+  - llamaindex@0.6.12
+
 ## 0.1.72
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/nextjs-edge-runtime-test",
-  "version": "0.1.72",
+  "version": "0.1.74",
   "private": true,
   "scripts": {
     "dev": "next dev",

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

@@ -1,5 +1,20 @@
 # @llamaindex/next-node-runtime
 
+## 0.0.56
+
+### Patch Changes
+
+- llamaindex@0.6.13
+
+## 0.0.55
+
+### Patch Changes
+
+- Updated dependencies [f7b4e94]
+- Updated dependencies [78037a6]
+- Updated dependencies [1d9e3b1]
+  - llamaindex@0.6.12
+
 ## 0.0.54
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-node-runtime-test",
-  "version": "0.0.54",
+  "version": "0.0.56",
   "private": true,
   "scripts": {
     "dev": "next dev",

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

@@ -1,5 +1,20 @@
 # @llamaindex/waku-query-engine-test
 
+## 0.0.75
+
+### Patch Changes
+
+- llamaindex@0.6.13
+
+## 0.0.74
+
+### Patch Changes
+
+- Updated dependencies [f7b4e94]
+- Updated dependencies [78037a6]
+- Updated dependencies [1d9e3b1]
+  - llamaindex@0.6.12
+
 ## 0.0.73
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/waku-query-engine-test",
-  "version": "0.0.73",
+  "version": "0.0.75",
   "type": "module",
   "private": true,
   "scripts": {

packages/llamaindex/package.json

@@ -1,6 +1,6 @@
 {
   "name": "llamaindex",
-  "version": "0.6.11",
+  "version": "0.6.13",
   "license": "MIT",
   "type": "module",
   "keywords": [

packages/llamaindex/src/index.edge.ts

@@ -1,3 +1,8 @@
+export {
+  LlamaParseReader,
+  type Language,
+  type ResultType,
+} from "@llamaindex/cloud/reader";
 export * from "@llamaindex/core/agent";
 export * from "@llamaindex/core/chat-engine";
 export {

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

@@ -203,7 +203,10 @@ export class VectorStoreIndex extends BaseIndex<IndexDict> {
     } = {},
   ): Promise<VectorStoreIndex> {
     args.storageContext =
-      args.storageContext ?? (await storageContextFromDefaults({}));
+      args.storageContext ??
+      (await storageContextFromDefaults({
+        serviceContext: args.serviceContext,
+      }));
     args.vectorStores = args.vectorStores ?? args.storageContext.vectorStores;
     args.docStoreStrategy =
       args.docStoreStrategy ??

packages/llamaindex/src/storage/StorageContext.ts

@@ -5,6 +5,7 @@ import {
 import { ModalityType, ObjectType } from "@llamaindex/core/schema";
 import { path } from "@llamaindex/env";
 import { getImageEmbedModel } from "../internal/settings/image-embed-model.js";
+import type { ServiceContext } from "../ServiceContext.js";
 import { SimpleVectorStore } from "../vector-store/SimpleVectorStore.js";
 import type { VectorStore, VectorStoreByType } from "../vector-store/types.js";
 import { SimpleDocumentStore } from "./docStore/SimpleDocumentStore.js";
@@ -25,6 +26,10 @@ type BuilderParams = {
   vectorStores: VectorStoreByType;
   storeImages: boolean;
   persistDir: string;
+  /**
+   * @deprecated Please use `Settings` instead
+   */
+  serviceContext?: ServiceContext | undefined;
 };
 
 export async function storageContextFromDefaults({
@@ -34,6 +39,7 @@ export async function storageContextFromDefaults({
   vectorStores,
   storeImages,
   persistDir,
+  serviceContext,
 }: Partial<BuilderParams>): Promise<StorageContext> {
   vectorStores = vectorStores ?? {};
   if (!persistDir) {
@@ -48,6 +54,7 @@ export async function storageContextFromDefaults({
       });
     }
   } else {
+    const embedModel = serviceContext?.embedModel;
     docStore =
       docStore ||
       (await SimpleDocumentStore.fromPersistDir(persistDir, DEFAULT_NAMESPACE));
@@ -55,7 +62,8 @@ export async function storageContextFromDefaults({
       indexStore || (await SimpleIndexStore.fromPersistDir(persistDir));
     if (!(ObjectType.TEXT in vectorStores)) {
       vectorStores[ModalityType.TEXT] =
-        vectorStore ?? (await SimpleVectorStore.fromPersistDir(persistDir));
+        vectorStore ??
+        (await SimpleVectorStore.fromPersistDir(persistDir, embedModel));
     }
     if (storeImages && !(ObjectType.IMAGE in vectorStores)) {
       vectorStores[ModalityType.IMAGE] = await SimpleVectorStore.fromPersistDir(

packages/llamaindex/src/vector-store/PineconeVectorStore.ts

@@ -1,4 +1,6 @@
 import {
+  FilterCondition,
+  FilterOperator,
   VectorStoreBase,
   type IEmbedModel,
   type MetadataFilter,
@@ -198,14 +200,60 @@ export class PineconeVectorStore
   }
 
   toPineconeFilter(stdFilters?: MetadataFilters) {
-    return stdFilters?.filters?.reduce((carry: any, item: MetadataFilter) => {
-      // Use MetadataFilter with EQ operator to replace ExactMatchFilter
-      // TODO: support filter with other operators
-      if (item.operator === "==") {
-        carry[item.key] = item.value;
+    if (!stdFilters) return undefined;
+
+    const transformCondition = (
+      condition: `${FilterCondition}` = "and",
+    ): string => {
+      if (condition === "and") return "$and";
+      if (condition === "or") return "$or";
+      throw new Error(`Filter condition ${condition} not supported`);
+    };
+
+    const transformOperator = (operator: `${FilterOperator}`): string => {
+      switch (operator) {
+        case "!=":
+          return "$ne";
+        case "==":
+          return "$eq";
+        case ">":
+          return "$gt";
+        case "<":
+          return "$lt";
+        case ">=":
+          return "$gte";
+        case "<=":
+          return "$lte";
+        case "in":
+          return "$in";
+        case "nin":
+          return "$nin";
+        default:
+          throw new Error(`Filter operator ${operator} not supported`);
       }
-      return carry;
-    }, {});
+    };
+
+    const convertFilterItem = (filter: MetadataFilter) => {
+      return {
+        [filter.key]: {
+          [transformOperator(filter.operator)]: filter.value,
+        },
+      };
+    };
+
+    const convertFilter = (filter: MetadataFilters) => {
+      const filtersList = filter.filters
+        .map((f) => convertFilterItem(f))
+        .filter((f) => Object.keys(f).length > 0);
+
+      if (filtersList.length === 0) return undefined;
+      if (filtersList.length === 1) return filtersList[0];
+
+      const condition = transformCondition(filter.condition);
+      return { [condition]: filtersList };
+    };
+
+    return convertFilter(stdFilters);
   }
 
   textFromResultRow(row: ScoredPineconeRecord<Metadata>): string {