e2e install pack and run the package

Co-authored-by: Alex Yang <himself65@outlook.com>

.changeset/gorgeous-rocks-grow.md

@@ -1,5 +0,0 @@
----
-"llamaindex": patch
----
-
-easier prompt customization for SimpleResponseBuilder

.changeset/smart-eels-design.md

@@ -0,0 +1,5 @@
+---
+"llamaindex": patch
+---
+
+fix: update `VectorIndexRetriever` constructor parameters' type.

.changeset/three-stingrays-build.md

@@ -1,5 +0,0 @@
----
-"llamaindex": patch
----
-
-fix(cyclic): remove cyclic structures from transform hash

.changeset/twenty-carrots-design.md

@@ -1,5 +0,0 @@
----
-"llamaindex": patch
----
-
-chore: improve extractors prompt

.github/workflows/e2e.yml

@@ -49,14 +49,8 @@ jobs:
       - name: Build create-llama
         run: pnpm run build
         working-directory: ./packages/create-llama
-      - name: Pack
-        run: pnpm pack --pack-destination ./output
-        working-directory: ./packages/create-llama
-      - name: Extract Pack
-        run: tar -xvzf ./output/*.tgz -C ./output
-        working-directory: ./packages/create-llama
       - name: Run Playwright tests
-        run: pnpm exec playwright test
+        run: pnpm run e2e
         env:
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
         working-directory: ./packages/create-llama

README.md

@@ -70,7 +70,7 @@ main();
 Then you can run it using
 
 ```bash
-pnpx ts-node example.ts
+pnpm dlx ts-node example.ts
 ```
 
 ## Playground

apps/docs/docs/examples/agent.mdx

@@ -0,0 +1,85 @@
+# Agents
+
+A built-in agent that can take decisions and reasoning based on the tools provided to it.
+
+## OpenAI Agent
+
+```ts
+import { FunctionTool, OpenAIAgent } from "llamaindex";
+
+// Define a function to sum two numbers
+function sumNumbers({ a, b }: { a: number; b: number }): number {
+  return a + b;
+}
+
+// Define a function to divide two numbers
+function divideNumbers({ a, b }: { a: number; b: number }): number {
+  return a / b;
+}
+
+// Define the parameters of the sum function as a JSON schema
+const sumJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The first number",
+    },
+    b: {
+      type: "number",
+      description: "The second number",
+    },
+  },
+  required: ["a", "b"],
+};
+
+// Define the parameters of the divide function as a JSON schema
+const divideJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The dividend to divide",
+    },
+    b: {
+      type: "number",
+      description: "The divisor to divide by",
+    },
+  },
+  required: ["a", "b"],
+};
+
+async function main() {
+  // Create a function tool from the sum function
+  const sumFunctionTool = new FunctionTool(sumNumbers, {
+    name: "sumNumbers",
+    description: "Use this function to sum two numbers",
+    parameters: sumJSON,
+  });
+
+  // Create a function tool from the divide function
+  const divideFunctionTool = new FunctionTool(divideNumbers, {
+    name: "divideNumbers",
+    description: "Use this function to divide two numbers"
+    parameters: divideJSON,
+  });
+
+  // Create an OpenAIAgent with the function tools
+  const agent = new OpenAIAgent({
+    tools: [sumFunctionTool, divideFunctionTool],
+    verbose: true,
+  });
+
+  // Chat with the agent
+  const response = await agent.chat({
+    message: "How much is 5 + 5? then divide by 2",
+  });
+
+  // Print the response
+  console.log(String(response));
+}
+
+main().then(() => {
+  console.log("Done");
+});
+```

apps/docs/docs/getting_started/concepts.md

@@ -35,7 +35,7 @@ LlamaIndex.TS help you prepare the knowledge base with a suite of data connector
 [**Data Loaders**](../modules/data_loader.md):
 A data connector (i.e. `Reader`) ingest data from different data sources and data formats into a simple `Document` representation (text and simple metadata).
 
-[**Documents / Nodes**](../modules/documents_and_nodes.md): A `Document` is a generic container around any data source - for instance, a PDF, an API output, or retrieved data from a database. A `Node` is the atomic unit of data in LlamaIndex and represents a "chunk" of a source `Document`. It's a rich representation that includes metadata and relationships (to other nodes) to enable accurate and expressive retrieval operations.
+[**Documents / Nodes**](../modules/documents_and_nodes/index.md): A `Document` is a generic container around any data source - for instance, a PDF, an API output, or retrieved data from a database. A `Node` is the atomic unit of data in LlamaIndex and represents a "chunk" of a source `Document`. It's a rich representation that includes metadata and relationships (to other nodes) to enable accurate and expressive retrieval operations.
 
 [**Data Indexes**](../modules/data_index.md):
 Once you've ingested your data, LlamaIndex helps you index data into a format that's easy to retrieve.
@@ -69,7 +69,7 @@ A response synthesizer generates a response from an LLM, using a user query and
 
 #### Pipelines
 
-[**Query Engines**](../modules/query_engine.md):
+[**Query Engines**](../modules/query_engines):
 A query engine is an end-to-end pipeline that allow you to ask question over your data.
 It takes in a natural language query, and returns a response, along with reference context retrieved and passed to the LLM.
 

apps/docs/docs/getting_started/installation.mdx

@@ -58,6 +58,6 @@ Our examples use OpenAI by default. You'll need to set up your Open AI key like
 export OPENAI_API_KEY="sk-......" # Replace with your key from https://platform.openai.com/account/api-keys
 ```
 
-If you want to have it automatically loaded every time, add it to your .zshrc/.bashrc.
+If you want to have it automatically loaded every time, add it to your `.zshrc/.bashrc`.
 
 WARNING: do not check in your OpenAI key into version control.

apps/docs/docs/getting_started/starter.md

@@ -36,9 +36,9 @@ async function main() {
 
   // Query the index
   const queryEngine = index.asQueryEngine();
-  const response = await queryEngine.query(
-    "What did the author do in college?",
-  );
+  const response = await queryEngine.query({
+    query: "What did the author do in college?",
+  });
 
   // Output response
   console.log(response.toString());

apps/docs/docs/introduction.md

@@ -37,9 +37,9 @@ For more complex applications, our lower-level APIs allow advanced users to cust
 
 `npm install llamaindex`
 
-Our documentation includes [Installation Instructions](./installation.mdx) and a [Starter Tutorial](./starter.md) to build your first application.
+Our documentation includes [Installation Instructions](./getting_started/installation.mdx) and a [Starter Tutorial](./getting_started/starter.md) to build your first application.
 
-Once you're up and running, [High-Level Concepts](./getting_started/concepts.md) has an overview of LlamaIndex's modular architecture. For more hands-on practical examples, look through our [End-to-End Tutorials](./end_to_end.md).
+Once you're up and running, [High-Level Concepts](./getting_started/concepts.md) has an overview of LlamaIndex's modular architecture. For more hands-on practical examples, look through our Examples section on the sidebar.
 
 ## 🗺️ Ecosystem
 

apps/docs/docs/modules/agent/_category_.yml

@@ -0,0 +1 @@
+label: "Agents"

apps/docs/docs/modules/agent/index.md

@@ -0,0 +1,14 @@
+# Agents
+
+An “agent” is an automated reasoning and decision engine. It takes in a user input/query and can make internal decisions for executing that query in order to return the correct result. The key agent components can include, but are not limited to:
+
+- Breaking down a complex question into smaller ones
+- Choosing an external Tool to use + coming up with parameters for calling the Tool
+- Planning out a set of tasks
+- Storing previously completed tasks in a memory module
+
+## Getting Started
+
+LlamaIndex.TS comes with a few built-in agents, but you can also create your own. The built-in agents include:
+
+- [OpenAI Agent](./openai.mdx)

apps/docs/docs/modules/agent/openai.mdx

@@ -0,0 +1,183 @@
+# OpenAI Agent
+
+OpenAI API that supports function calling, it’s never been easier to build your own agent!
+
+In this notebook tutorial, we showcase how to write your own OpenAI agent
+
+## Setup
+
+First, you need to install the `llamaindex` package. You can do this by running the following command in your terminal:
+
+```bash
+pnpm i llamaindex
+```
+
+Then we can define a function to sum two numbers and another function to divide two numbers.
+
+```ts
+function sumNumbers({ a, b }: { a: number; b: number }): number {
+  return a + b;
+}
+
+// Define a function to divide two numbers
+function divideNumbers({ a, b }: { a: number; b: number }): number {
+  return a / b;
+}
+```
+
+## Create a function tool
+
+Now we can create a function tool from the sum function and another function tool from the divide function.
+
+For the parameters of the sum function, we can define a JSON schema.
+
+### JSON Schema
+
+```ts
+const sumJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The first number",
+    },
+    b: {
+      type: "number",
+      description: "The second number",
+    },
+  },
+  required: ["a", "b"],
+};
+
+const divideJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The dividend a to divide",
+    },
+    b: {
+      type: "number",
+      description: "The divisor b to divide by",
+    },
+  },
+  required: ["a", "b"],
+};
+
+const sumFunctionTool = new FunctionTool(sumNumbers, {
+  name: "sumNumbers",
+  description: "Use this function to sum two numbers",
+  parameters: sumJSON,
+});
+
+const divideFunctionTool = new FunctionTool(divideNumbers, {
+  name: "divideNumbers",
+  description: "Use this function to divide two numbers",
+  parameters: divideJSON,
+});
+```
+
+## Create an OpenAIAgent
+
+Now we can create an OpenAIAgent with the function tools.
+
+```ts
+const worker = new OpenAIAgent({
+  tools: [sumFunctionTool, divideFunctionTool],
+  verbose: true,
+});
+```
+
+## Chat with the agent
+
+Now we can chat with the agent.
+
+```ts
+const response = await worker.chat({
+  message: "How much is 5 + 5? then divide by 2",
+});
+
+console.log(String(response));
+```
+
+## Full code
+
+```ts
+import { FunctionTool, OpenAIAgent } from "llamaindex";
+
+// Define a function to sum two numbers
+function sumNumbers({ a, b }: { a: number; b: number }): number {
+  return a + b;
+}
+
+// Define a function to divide two numbers
+function divideNumbers({ a, b }: { a: number; b: number }): number {
+  return a / b;
+}
+
+// Define the parameters of the sum function as a JSON schema
+const sumJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The first number",
+    },
+    b: {
+      type: "number",
+      description: "The second number",
+    },
+  },
+  required: ["a", "b"],
+};
+
+// Define the parameters of the divide function as a JSON schema
+const divideJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The argument a to divide",
+    },
+    b: {
+      type: "number",
+      description: "The argument b to divide",
+    },
+  },
+  required: ["a", "b"],
+};
+
+async function main() {
+  // Create a function tool from the sum function
+  const sumFunctionTool = new FunctionTool(sumNumbers, {
+    name: "sumNumbers",
+    description: "Use this function to sum two numbers",
+    parameters: sumJSON,
+  });
+
+  // Create a function tool from the divide function
+  const divideFunctionTool = new FunctionTool(divideNumbers, {
+    name: "divideNumbers",
+    description: "Use this function to divide two numbers",
+    parameters: divideJSON,
+  });
+
+  // Create an OpenAIAgent with the function tools
+  const agent = new OpenAIAgent({
+    tools: [sumFunctionTool, divideFunctionTool],
+    verbose: true,
+  });
+
+  // Chat with the agent
+  const response = await agent.chat({
+    message: "How much is 5 + 5? then divide by 2",
+  });
+
+  // Print the response
+  console.log(String(response));
+}
+
+main().then(() => {
+  console.log("Done");
+});
+```

apps/docs/docs/modules/query_engines/index.md

@@ -36,6 +36,6 @@ You can learn more about Tools by taking a look at the LlamaIndex Python documen
 
 ## API Reference
 
-- [RetrieverQueryEngine](../api/classes/RetrieverQueryEngine.md)
-- [SubQuestionQueryEngine](../api/classes/SubQuestionQueryEngine.md)
-- [QueryEngineTool](../api/interfaces//QueryEngineTool.md)
+- [RetrieverQueryEngine](../../api/classes/RetrieverQueryEngine.md)
+- [SubQuestionQueryEngine](../../api/classes/SubQuestionQueryEngine.md)
+- [QueryEngineTool](../../api/interfaces/QueryEngineTool.md)

apps/docs/docs/modules/query_engines/metadata_filtering.md

@@ -0,0 +1,152 @@
+# Metadata Filtering
+
+Metadata filtering is a way to filter the documents that are returned by a query based on the metadata associated with the documents. This is useful when you want to filter the documents based on some metadata that is not part of the document text.
+
+You can also check our multi-tenancy blog post to see how metadata filtering can be used in a multi-tenant environment. [https://blog.llamaindex.ai/building-multi-tenancy-rag-system-with-llamaindex-0d6ab4e0c44b] (the article uses the Python version of LlamaIndex, but the concepts are the same).
+
+## Setup
+
+Firstly if you haven't already, you need to install the `llamaindex` package:
+
+```bash
+pnpm i llamaindex
+```
+
+Then you can import the necessary modules from `llamaindex`:
+
+```ts
+import {
+  ChromaVectorStore,
+  Document,
+  VectorStoreIndex,
+  storageContextFromDefaults,
+} from "llamaindex";
+
+const collectionName = "dog_colors";
+```
+
+## Creating documents with metadata
+
+You can create documents with metadata using the `Document` class:
+
+```ts
+const docs = [
+  new Document({
+    text: "The dog is brown",
+    metadata: {
+      color: "brown",
+      dogId: "1",
+    },
+  }),
+  new Document({
+    text: "The dog is red",
+    metadata: {
+      color: "red",
+      dogId: "2",
+    },
+  }),
+];
+```
+
+## Creating a ChromaDB vector store
+
+You can create a `ChromaVectorStore` to store the documents:
+
+```ts
+const chromaVS = new ChromaVectorStore({ collectionName });
+const serviceContext = await storageContextFromDefaults({
+  vectorStore: chromaVS,
+});
+
+const index = await VectorStoreIndex.fromDocuments(docs, {
+  storageContext: serviceContext,
+});
+```
+
+## Querying the index with metadata filtering
+
+Now you can query the index with metadata filtering using the `preFilters` option:
+
+```ts
+const queryEngine = index.asQueryEngine({
+  preFilters: {
+    filters: [
+      {
+        key: "dogId",
+        value: "2",
+        filterType: "ExactMatch",
+      },
+    ],
+  },
+});
+
+const response = await queryEngine.query({
+  query: "What is the color of the dog?",
+});
+
+console.log(response.toString());
+```
+
+## Full Code
+
+```ts
+import {
+  ChromaVectorStore,
+  Document,
+  VectorStoreIndex,
+  storageContextFromDefaults,
+} from "llamaindex";
+
+const collectionName = "dog_colors";
+
+async function main() {
+  try {
+    const docs = [
+      new Document({
+        text: "The dog is brown",
+        metadata: {
+          color: "brown",
+          dogId: "1",
+        },
+      }),
+      new Document({
+        text: "The dog is red",
+        metadata: {
+          color: "red",
+          dogId: "2",
+        },
+      }),
+    ];
+
+    console.log("Creating ChromaDB vector store");
+    const chromaVS = new ChromaVectorStore({ collectionName });
+    const ctx = await storageContextFromDefaults({ vectorStore: chromaVS });
+
+    console.log("Embedding documents and adding to index");
+    const index = await VectorStoreIndex.fromDocuments(docs, {
+      storageContext: ctx,
+    });
+
+    console.log("Querying index");
+    const queryEngine = index.asQueryEngine({
+      preFilters: {
+        filters: [
+          {
+            key: "dogId",
+            value: "2",
+            filterType: "ExactMatch",
+          },
+        ],
+      },
+    });
+    const response = await queryEngine.query({
+      query: "What is the color of the dog?",
+    });
+    console.log(response.toString());
+  } catch (e) {
+    console.error(e);
+  }
+}
+
+main();
+```

examples/agent/openai.ts

@@ -0,0 +1,76 @@
+import { FunctionTool, OpenAIAgent } from "llamaindex";
+
+// Define a function to sum two numbers
+function sumNumbers({ a, b }: { a: number; b: number }): number {
+  return a + b;
+}
+
+// Define a function to divide two numbers
+function divideNumbers({ a, b }: { a: number; b: number }): number {
+  return a / b;
+}
+
+// Define the parameters of the sum function as a JSON schema
+const sumJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The first number",
+    },
+    b: {
+      type: "number",
+      description: "The second number",
+    },
+  },
+  required: ["a", "b"],
+};
+
+const divideJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The dividend a to divide",
+    },
+    b: {
+      type: "number",
+      description: "The divisor b to divide by",
+    },
+  },
+  required: ["a", "b"],
+};
+
+async function main() {
+  // Create a function tool from the sum function
+  const functionTool = new FunctionTool(sumNumbers, {
+    name: "sumNumbers",
+    description: "Use this function to sum two numbers",
+    parameters: sumJSON,
+  });
+
+  // Create a function tool from the divide function
+  const functionTool2 = new FunctionTool(divideNumbers, {
+    name: "divideNumbers",
+    description: "Use this function to divide two numbers",
+    parameters: divideJSON,
+  });
+
+  // Create an OpenAIAgent with the function tools
+  const agent = new OpenAIAgent({
+    tools: [functionTool, functionTool2],
+    verbose: true,
+  });
+
+  // Chat with the agent
+  const response = await agent.chat({
+    message: "How much is 5 + 5? then divide by 2",
+  });
+
+  // Print the response
+  console.log(String(response));
+}
+
+main().then(() => {
+  console.log("Done");
+});

examples/chromadb/README.md

@@ -6,7 +6,7 @@ Export your OpenAI API Key using `export OPEN_API_KEY=insert your api key here`
 
 If you haven't installed chromadb, run `pip install chromadb`. Start the server using `chroma run`.
 
-Now, open a new terminal window and inside `examples`, run `pnpx ts-node chromadb/test.ts`.
+Now, open a new terminal window and inside `examples`, run `pnpm dlx ts-node chromadb/test.ts`.
 
 Here's the output for the input query `Tell me about Godfrey Cheshire's rating of La Sapienza.`:
 

packages/core/CHANGELOG.md

@@ -1,5 +1,13 @@
 # llamaindex
 
+## 0.1.8
+
+### Patch Changes
+
+- d903da6: easier prompt customization for SimpleResponseBuilder
+- ab9d941: fix(cyclic): remove cyclic structures from transform hash
+- 177b446: chore: improve extractors prompt
+
 ## 0.1.7
 
 ### Patch Changes

packages/core/package.json

@@ -1,7 +1,7 @@
 {
   "name": "llamaindex",
   "private": true,
-  "version": "0.1.7",
+  "version": "0.1.8",
   "license": "MIT",
   "dependencies": {
     "@anthropic-ai/sdk": "^0.12.4",
@@ -200,7 +200,7 @@
   "scripts": {
     "lint": "eslint .",
     "test": "jest",
-    "build": "NODE_OPTIONS=\"--max-old-space-size=8192\" bunchee",
+    "build": "rm -rf ./dist && NODE_OPTIONS=\"--max-old-space-size=8192\" bunchee",
     "postbuild": "pnpm run copy && pnpm run modify-package-json",
     "copy": "cp -r package.json CHANGELOG.md ../../README.md ../../LICENSE examples src dist/",
     "modify-package-json": "node ./scripts/modify-package-json.mjs",

packages/core/src/OutputParser.ts

@@ -74,9 +74,6 @@ export class SubQuestionOutputParser
 {
   parse(output: string): StructuredOutput<SubQuestion[]> {
     const parsed = parseJsonMarkdown(output);
-
-    // TODO add zod validation
-
     return { rawOutput: output, parsedOutput: parsed };
   }
 

packages/core/src/Response.ts

@@ -13,7 +13,7 @@ export class Response {
     this.sourceNodes = sourceNodes || [];
   }
 
-  getFormattedSources() {
+  protected _getFormattedSources() {
     throw new Error("Not implemented yet");
   }
 

packages/core/src/agent/index.ts

@@ -0,0 +1,2 @@
+export * from "./openai/base";
+export * from "./openai/worker";

packages/core/src/agent/openai/base.ts

@@ -0,0 +1,55 @@
+import { CallbackManager } from "../../callbacks/CallbackManager";
+import { ChatMessage, OpenAI } from "../../llm";
+import { ObjectRetriever } from "../../objects/base";
+import { BaseTool } from "../../types";
+import { AgentRunner } from "../runner/base";
+import { OpenAIAgentWorker } from "./worker";
+
+type OpenAIAgentParams = {
+  tools: BaseTool[];
+  llm?: OpenAI;
+  memory?: any;
+  prefixMessages?: ChatMessage[];
+  verbose?: boolean;
+  maxFunctionCalls?: number;
+  defaultToolChoice?: string;
+  callbackManager?: CallbackManager;
+  toolRetriever?: ObjectRetriever<BaseTool>;
+};
+
+/**
+ * An agent that uses OpenAI's API to generate text.
+ *
+ * @category OpenAI
+ */
+export class OpenAIAgent extends AgentRunner {
+  constructor({
+    tools,
+    llm,
+    memory,
+    prefixMessages,
+    verbose,
+    maxFunctionCalls = 5,
+    defaultToolChoice = "auto",
+    callbackManager,
+    toolRetriever,
+  }: OpenAIAgentParams) {
+    const stepEngine = new OpenAIAgentWorker({
+      tools,
+      callbackManager,
+      llm,
+      prefixMessages,
+      maxFunctionCalls,
+      toolRetriever,
+      verbose,
+    });
+
+    super({
+      agentWorker: stepEngine,
+      memory,
+      callbackManager,
+      defaultToolChoice,
+      chatHistory: prefixMessages,
+    });
+  }
+}

packages/core/src/agent/openai/types/chat.ts

@@ -0,0 +1,13 @@
+export type OpenAIToolCall = ChatCompletionMessageToolCall;
+
+export interface Function {
+  arguments: string;
+  name: string;
+  type: "function";
+}
+
+export interface ChatCompletionMessageToolCall {
+  id: string;
+  function: Function;
+  type: "function";
+}

packages/core/src/agent/openai/utils.ts

@@ -0,0 +1,27 @@
+import { ToolMetadata } from "../../types";
+
+export type OpenAIFunction = {
+  type: "function";
+  function: ToolMetadata;
+};
+
+type OpenAiTool = {
+  name: string;
+  description: string;
+  parameters: ToolMetadata["parameters"];
+};
+
+export const toOpenAiTool = ({
+  name,
+  description,
+  parameters,
+}: OpenAiTool): OpenAIFunction => {
+  return {
+    type: "function",
+    function: {
+      name: name,
+      description: description,
+      parameters,
+    },
+  };
+};

packages/core/src/agent/openai/worker.ts

@@ -0,0 +1,405 @@
+// Assuming that the necessary interfaces and classes (like BaseTool, OpenAI, ChatMessage, CallbackManager, etc.) are defined elsewhere
+
+import { CallbackManager } from "../../callbacks/CallbackManager";
+import { AgentChatResponse, ChatResponseMode } from "../../engines/chat";
+import { randomUUID } from "../../env";
+import {
+  ChatMessage,
+  ChatResponse,
+  ChatResponseChunk,
+  OpenAI,
+} from "../../llm";
+import { ChatMemoryBuffer } from "../../memory/ChatMemoryBuffer";
+import { ObjectRetriever } from "../../objects/base";
+import { ToolOutput } from "../../tools/types";
+import { callToolWithErrorHandling } from "../../tools/utils";
+import { BaseTool } from "../../types";
+import { AgentWorker, Task, TaskStep, TaskStepOutput } from "../types";
+import { addUserStepToMemory, getFunctionByName } from "../utils";
+import { OpenAIToolCall } from "./types/chat";
+import { toOpenAiTool } from "./utils";
+
+const DEFAULT_MAX_FUNCTION_CALLS = 5;
+
+/**
+ * Call function.
+ * @param tools: tools
+ * @param toolCall: tool call
+ * @param verbose: verbose
+ * @returns: void
+ */
+async function callFunction(
+  tools: BaseTool[],
+  toolCall: OpenAIToolCall,
+  verbose: boolean = false,
+): Promise<[ChatMessage, ToolOutput]> {
+  const id_ = toolCall.id;
+  const functionCall = toolCall.function;
+  const name = toolCall.function.name;
+  const argumentsStr = toolCall.function.arguments;
+
+  if (verbose) {
+    console.log("=== Calling Function ===");
+    console.log(`Calling function: ${name} with args: ${argumentsStr}`);
+  }
+
+  const tool = getFunctionByName(tools, name);
+  const argumentDict = JSON.parse(argumentsStr);
+
+  // Call tool
+  // Use default error message
+  const output = await callToolWithErrorHandling(tool, argumentDict, null);
+
+  if (verbose) {
+    console.log(`Got output ${output}`);
+    console.log("==========================");
+  }
+
+  return [
+    {
+      content: String(output),
+      role: "tool",
+      additionalKwargs: {
+        name,
+        tool_call_id: id_,
+      },
+    },
+    output,
+  ];
+}
+
+type OpenAIAgentWorkerParams = {
+  tools: BaseTool[];
+  llm?: OpenAI;
+  prefixMessages?: ChatMessage[];
+  verbose?: boolean;
+  maxFunctionCalls?: number;
+  callbackManager?: CallbackManager | undefined;
+  toolRetriever?: ObjectRetriever<BaseTool>;
+};
+
+type CallFunctionOutput = {
+  message: ChatMessage;
+  toolOutput: ToolOutput;
+};
+
+/**
+ * OpenAI agent worker.
+ * This class is responsible for running the agent.
+ */
+export class OpenAIAgentWorker implements AgentWorker {
+  private _llm: OpenAI;
+  private _verbose: boolean;
+  private _maxFunctionCalls: number;
+
+  public prefixMessages: ChatMessage[];
+  public callbackManager: CallbackManager | undefined;
+
+  private _getTools: (input: string) => BaseTool[];
+
+  /**
+   * Initialize.
+   */
+  constructor({
+    tools,
+    llm,
+    prefixMessages,
+    verbose,
+    maxFunctionCalls = DEFAULT_MAX_FUNCTION_CALLS,
+    callbackManager,
+    toolRetriever,
+  }: OpenAIAgentWorkerParams) {
+    this._llm = llm ?? new OpenAI({ model: "gpt-3.5-turbo-0613" });
+    this._verbose = verbose || false;
+    this._maxFunctionCalls = maxFunctionCalls;
+    this.prefixMessages = prefixMessages || [];
+    this.callbackManager = callbackManager || this._llm.callbackManager;
+
+    if (tools.length > 0 && toolRetriever) {
+      throw new Error("Cannot specify both tools and tool_retriever");
+    } else if (tools.length > 0) {
+      this._getTools = () => tools;
+    } else if (toolRetriever) {
+      // @ts-ignore
+      this._getTools = (message: string) => toolRetriever.retrieve(message);
+    } else {
+      this._getTools = () => [];
+    }
+  }
+
+  /**
+   * Get all messages.
+   * @param task: task
+   * @returns: messages
+   */
+  public getAllMessages(task: Task): ChatMessage[] {
+    return [
+      ...this.prefixMessages,
+      ...task.memory.get(),
+      ...task.extraState.newMemory.get(),
+    ];
+  }
+
+  /**
+   * Get latest tool calls.
+   * @param task: task
+   * @returns: tool calls
+   */
+  public getLatestToolCalls(task: Task): OpenAIToolCall[] | null {
+    const chatHistory: ChatMessage[] = task.extraState.newMemory.getAll();
+
+    if (chatHistory.length === 0) {
+      return null;
+    }
+
+    return chatHistory[chatHistory.length - 1].additionalKwargs?.toolCalls;
+  }
+
+  /**
+   *
+   * @param task
+   * @param openaiTools
+   * @param toolChoice
+   * @returns
+   */
+  private _getLlmChatKwargs(
+    task: Task,
+    openaiTools: { [key: string]: any }[],
+    toolChoice: string | { [key: string]: any } = "auto",
+  ): { [key: string]: any } {
+    const llmChatKwargs: { [key: string]: any } = {
+      messages: this.getAllMessages(task),
+    };
+
+    if (openaiTools.length > 0) {
+      llmChatKwargs.tools = openaiTools;
+      llmChatKwargs.toolChoice = toolChoice;
+    }
+
+    return llmChatKwargs;
+  }
+
+  /**
+   * Process message.
+   * @param task: task
+   * @param chatResponse: chat response
+   * @returns: agent chat response
+   */
+  private _processMessage(
+    task: Task,
+    chatResponse: ChatResponse,
+  ): AgentChatResponse | AsyncIterable<ChatResponseChunk> {
+    const aiMessage = chatResponse.message;
+    task.extraState.newMemory.put(aiMessage);
+    return new AgentChatResponse(aiMessage.content, task.extraState.sources);
+  }
+
+  /**
+   * Get agent response.
+   * @param task: task
+   * @param mode: mode
+   * @param llmChatKwargs: llm chat kwargs
+   * @returns: agent chat response
+   */
+  private async _getAgentResponse(
+    task: Task,
+    mode: ChatResponseMode,
+    llmChatKwargs: any,
+  ): Promise<AgentChatResponse> {
+    if (mode === ChatResponseMode.WAIT) {
+      const chatResponse = (await this._llm.chat({
+        stream: false,
+        ...llmChatKwargs,
+      })) as unknown as ChatResponse;
+
+      return this._processMessage(task, chatResponse) as AgentChatResponse;
+    } else {
+      throw new Error("Not implemented");
+    }
+  }
+
+  /**
+   * Call function.
+   * @param tools: tools
+   * @param toolCall: tool call
+   * @param memory: memory
+   * @param sources: sources
+   * @returns: void
+   */
+  async callFunction(
+    tools: BaseTool[],
+    toolCall: OpenAIToolCall,
+  ): Promise<CallFunctionOutput> {
+    const functionCall = toolCall.function;
+
+    if (!functionCall) {
+      throw new Error("Invalid tool_call object");
+    }
+
+    const functionMessage = await callFunction(tools, toolCall, this._verbose);
+
+    const message = functionMessage[0];
+    const toolOutput = functionMessage[1];
+
+    return {
+      message,
+      toolOutput,
+    };
+  }
+
+  /**
+   * Initialize step.
+   * @param task: task
+   * @param kwargs: kwargs
+   * @returns: task step
+   */
+  initializeStep(task: Task, kwargs?: any): TaskStep {
+    const sources: ToolOutput[] = [];
+
+    const newMemory = new ChatMemoryBuffer();
+
+    const taskState = {
+      sources,
+      nFunctionCalls: 0,
+      newMemory,
+    };
+
+    task.extraState = {
+      ...task.extraState,
+      ...taskState,
+    };
+
+    return new TaskStep(task.taskId, randomUUID(), task.input);
+  }
+
+  /**
+   * Should continue.
+   * @param toolCalls: tool calls
+   * @param nFunctionCalls: number of function calls
+   * @returns: boolean
+   */
+  private _shouldContinue(
+    toolCalls: OpenAIToolCall[] | null,
+    nFunctionCalls: number,
+  ): boolean {
+    if (nFunctionCalls > this._maxFunctionCalls) {
+      return false;
+    }
+
+    if (toolCalls?.length === 0) {
+      return false;
+    }
+
+    return true;
+  }
+
+  /**
+   * Get tools.
+   * @param input: input
+   * @returns: tools
+   */
+  getTools(input: string): BaseTool[] {
+    return this._getTools(input);
+  }
+
+  private async _runStep(
+    step: TaskStep,
+    task: Task,
+    mode: ChatResponseMode = ChatResponseMode.WAIT,
+    toolChoice: string | { [key: string]: any } = "auto",
+  ): Promise<TaskStepOutput> {
+    const tools = this.getTools(task.input);
+
+    if (step.input) {
+      addUserStepToMemory(step, task.extraState.newMemory, this._verbose);
+    }
+
+    const openaiTools = tools.map((tool) =>
+      toOpenAiTool({
+        name: tool.metadata.name,
+        description: tool.metadata.description,
+        parameters: tool.metadata.parameters,
+      }),
+    );
+
+    const llmChatKwargs = this._getLlmChatKwargs(task, openaiTools, toolChoice);
+
+    const agentChatResponse = await this._getAgentResponse(
+      task,
+      mode,
+      llmChatKwargs,
+    );
+
+    const latestToolCalls = this.getLatestToolCalls(task) || [];
+
+    let isDone: boolean;
+    let newSteps: TaskStep[] = [];
+
+    if (
+      !this._shouldContinue(latestToolCalls, task.extraState.nFunctionCalls)
+    ) {
+      isDone = true;
+      newSteps = [];
+    } else {
+      isDone = false;
+      for (const toolCall of latestToolCalls) {
+        const { message, toolOutput } = await this.callFunction(
+          tools,
+          toolCall,
+        );
+
+        task.extraState.sources.push(toolOutput);
+        task.extraState.newMemory.put(message);
+
+        task.extraState.nFunctionCalls += 1;
+      }
+
+      newSteps = [step.getNextStep(randomUUID(), undefined)];
+    }
+
+    return new TaskStepOutput(agentChatResponse, step, newSteps, isDone);
+  }
+
+  /**
+   * Run step.
+   * @param step: step
+   * @param task: task
+   * @param kwargs: kwargs
+   * @returns: task step output
+   */
+  async runStep(
+    step: TaskStep,
+    task: Task,
+    kwargs?: any,
+  ): Promise<TaskStepOutput> {
+    const toolChoice = kwargs?.toolChoice || "auto";
+    return this._runStep(step, task, ChatResponseMode.WAIT, toolChoice);
+  }
+
+  /**
+   * Stream step.
+   * @param step: step
+   * @param task: task
+   * @param kwargs: kwargs
+   * @returns: task step output
+   */
+  async streamStep(
+    step: TaskStep,
+    task: Task,
+    kwargs?: any,
+  ): Promise<TaskStepOutput> {
+    const toolChoice = kwargs?.toolChoice || "auto";
+    return this._runStep(step, task, ChatResponseMode.STREAM, toolChoice);
+  }
+
+  /**
+   * Finalize task.
+   * @param task: task
+   * @param kwargs: kwargs
+   * @returns: void
+   */
+  finalizeTask(task: Task, kwargs?: any): void {
+    task.memory.set(task.memory.get().concat(task.extraState.newMemory.get()));
+    task.extraState.newMemory.reset();
+  }
+}

packages/core/src/agent/runner/base.ts

@@ -0,0 +1,343 @@
+import { randomUUID } from "crypto";
+import { CallbackManager } from "../../callbacks/CallbackManager";
+import {
+  AgentChatResponse,
+  ChatEngineAgentParams,
+  ChatResponseMode,
+} from "../../engines/chat";
+import { ChatMessage, LLM } from "../../llm";
+import { ChatMemoryBuffer } from "../../memory/ChatMemoryBuffer";
+import { BaseMemory } from "../../memory/types";
+import { AgentWorker, Task, TaskStep, TaskStepOutput } from "../types";
+import { AgentState, BaseAgentRunner, TaskState } from "./types";
+
+const validateStepFromArgs = (
+  taskId: string,
+  input: string,
+  step?: any,
+  kwargs?: any,
+): TaskStep | undefined => {
+  if (step) {
+    if (input) {
+      throw new Error("Cannot specify both `step` and `input`");
+    }
+    return step;
+  } else {
+    return new TaskStep(taskId, step, input, kwargs);
+  }
+};
+
+type AgentRunnerParams = {
+  agentWorker: AgentWorker;
+  chatHistory?: ChatMessage[];
+  state?: AgentState;
+  memory?: BaseMemory;
+  llm?: LLM;
+  callbackManager?: CallbackManager;
+  initTaskStateKwargs?: Record<string, any>;
+  deleteTaskOnFinish?: boolean;
+  defaultToolChoice?: string;
+};
+
+export class AgentRunner extends BaseAgentRunner {
+  agentWorker: AgentWorker;
+  state: AgentState;
+  memory: BaseMemory;
+  callbackManager: CallbackManager;
+  initTaskStateKwargs: Record<string, any>;
+  deleteTaskOnFinish: boolean;
+  defaultToolChoice: string;
+
+  /**
+   * Creates an AgentRunner.
+   */
+  constructor(params: AgentRunnerParams) {
+    super();
+
+    this.agentWorker = params.agentWorker;
+    this.state = params.state ?? new AgentState();
+    this.memory =
+      params.memory ??
+      new ChatMemoryBuffer({
+        chatHistory: params.chatHistory,
+      });
+    this.callbackManager = params.callbackManager ?? new CallbackManager();
+    this.initTaskStateKwargs = params.initTaskStateKwargs ?? {};
+    this.deleteTaskOnFinish = params.deleteTaskOnFinish ?? false;
+    this.defaultToolChoice = params.defaultToolChoice ?? "auto";
+  }
+
+  /**
+   * Creates a task.
+   * @param input
+   * @param kwargs
+   */
+  createTask(input: string, kwargs?: any): Task {
+    let extraState;
+
+    if (!this.initTaskStateKwargs) {
+      if (kwargs && "extraState" in kwargs) {
+        if (extraState) {
+          delete extraState["extraState"];
+        }
+      }
+    } else {
+      if (kwargs && "extraState" in kwargs) {
+        throw new Error(
+          "Cannot specify both `extraState` and `initTaskStateKwargs`",
+        );
+      } else {
+        extraState = this.initTaskStateKwargs;
+      }
+    }
+
+    const task = new Task({
+      taskId: randomUUID(),
+      input,
+      memory: this.memory,
+      extraState,
+      ...kwargs,
+    });
+
+    const initialStep = this.agentWorker.initializeStep(task);
+
+    const taskState = new TaskState({
+      task,
+      stepQueue: [initialStep],
+    });
+
+    this.state.taskDict[task.taskId] = taskState;
+
+    return task;
+  }
+
+  /**
+   * Deletes the task.
+   * @param taskId
+   */
+  deleteTask(taskId: string): void {
+    delete this.state.taskDict[taskId];
+  }
+
+  /**
+   * Returns the list of tasks.
+   */
+  listTasks(): Task[] {
+    return Object.values(this.state.taskDict).map(
+      (taskState) => taskState.task,
+    );
+  }
+
+  /**
+   * Returns the task.
+   */
+  getTask(taskId: string): Task {
+    return this.state.taskDict[taskId].task;
+  }
+
+  /**
+   * Returns the completed steps in the task.
+   * @param taskId
+   * @param kwargs
+   */
+  getCompletedSteps(taskId: string): TaskStepOutput[] {
+    return this.state.taskDict[taskId].completedSteps;
+  }
+
+  /**
+   * Returns the next steps in the task.
+   * @param taskId
+   * @param kwargs
+   */
+  getUpcomingSteps(taskId: string, kwargs: any): TaskStep[] {
+    return this.state.taskDict[taskId].stepQueue;
+  }
+
+  private async _runStep(
+    taskId: string,
+    step?: TaskStep,
+    mode: ChatResponseMode = ChatResponseMode.WAIT,
+    kwargs?: any,
+  ): Promise<TaskStepOutput> {
+    const task = this.state.getTask(taskId);
+    const curStep = step || this.state.getStepQueue(taskId).shift();
+
+    let curStepOutput;
+
+    if (!curStep) {
+      throw new Error(`No step found for task ${taskId}`);
+    }
+
+    if (mode === ChatResponseMode.WAIT) {
+      curStepOutput = await this.agentWorker.runStep(curStep, task, kwargs);
+    } else if (mode === ChatResponseMode.STREAM) {
+      curStepOutput = await this.agentWorker.streamStep(curStep, task, kwargs);
+    } else {
+      throw new Error(`Invalid mode: ${mode}`);
+    }
+
+    const nextSteps = curStepOutput.nextSteps;
+
+    this.state.addSteps(taskId, nextSteps);
+    this.state.addCompletedStep(taskId, [curStepOutput]);
+
+    return curStepOutput;
+  }
+
+  /**
+   * Runs the next step in the task.
+   * @param taskId
+   * @param kwargs
+   * @param step
+   * @returns
+   */
+  async runStep(
+    taskId: string,
+    input: string,
+    step?: TaskStep,
+    kwargs: any = {},
+  ): Promise<TaskStepOutput> {
+    const curStep = validateStepFromArgs(taskId, input, step, kwargs);
+    return this._runStep(taskId, curStep, ChatResponseMode.WAIT, kwargs);
+  }
+
+  /**
+   * Runs the step and returns the response.
+   * @param taskId
+   * @param input
+   * @param step
+   * @param kwargs
+   */
+  async streamStep(
+    taskId: string,
+    input: string,
+    step?: TaskStep,
+    kwargs?: any,
+  ): Promise<TaskStepOutput> {
+    const curStep = validateStepFromArgs(taskId, input, step, kwargs);
+    return this._runStep(taskId, curStep, ChatResponseMode.STREAM, kwargs);
+  }
+
+  /**
+   * Finalizes the response and returns it.
+   * @param taskId
+   * @param kwargs
+   * @param stepOutput
+   * @returns
+   */
+  async finalizeResponse(
+    taskId: string,
+    stepOutput: TaskStepOutput,
+    kwargs?: any,
+  ): Promise<AgentChatResponse> {
+    if (!stepOutput) {
+      stepOutput =
+        this.getCompletedSteps(taskId)[
+          this.getCompletedSteps(taskId).length - 1
+        ];
+    }
+    if (!stepOutput.isLast) {
+      throw new Error(
+        "finalizeResponse can only be called on the last step output",
+      );
+    }
+
+    if (!(stepOutput.output instanceof AgentChatResponse)) {
+      throw new Error(
+        `When \`isLast\` is True, cur_step_output.output must be AGENT_CHAT_RESPONSE_TYPE: ${stepOutput.output}`,
+      );
+    }
+
+    this.agentWorker.finalizeTask(this.getTask(taskId), kwargs);
+
+    if (this.deleteTaskOnFinish) {
+      this.deleteTask(taskId);
+    }
+
+    return stepOutput.output;
+  }
+
+  protected async _chat({
+    message,
+    toolChoice,
+  }: ChatEngineAgentParams & { mode: ChatResponseMode }) {
+    const task = this.createTask(message as string);
+
+    let resultOutput;
+
+    while (true) {
+      const curStepOutput = await this._runStep(task.taskId);
+
+      if (curStepOutput.isLast) {
+        resultOutput = curStepOutput;
+        break;
+      }
+
+      toolChoice = "auto";
+    }
+
+    return this.finalizeResponse(task.taskId, resultOutput);
+  }
+
+  /**
+   * Sends a message to the LLM and returns the response.
+   * @param message
+   * @param chatHistory
+   * @param toolChoice
+   * @returns
+   */
+  public async chat({
+    message,
+    chatHistory,
+    toolChoice,
+  }: ChatEngineAgentParams): Promise<AgentChatResponse> {
+    if (!toolChoice) {
+      toolChoice = this.defaultToolChoice;
+    }
+
+    const chatResponse = await this._chat({
+      message,
+      chatHistory,
+      toolChoice,
+      mode: ChatResponseMode.WAIT,
+    });
+
+    return chatResponse;
+  }
+
+  protected _getPromptModules(): string[] {
+    return [];
+  }
+
+  protected _getPrompts(): string[] {
+    return [];
+  }
+
+  /**
+   * Resets the agent.
+   */
+  reset(): void {
+    this.state = new AgentState();
+  }
+
+  getCompletedStep(
+    taskId: string,
+    stepId: string,
+    kwargs: any,
+  ): TaskStepOutput {
+    const completedSteps = this.getCompletedSteps(taskId);
+    for (const stepOutput of completedSteps) {
+      if (stepOutput.taskStep.stepId === stepId) {
+        return stepOutput;
+      }
+    }
+
+    throw new Error(`Step ${stepId} not found in task ${taskId}`);
+  }
+
+  /**
+   * Undoes the step.
+   * @param taskId
+   */
+  undoStep(taskId: string): void {}
+}

packages/core/src/agent/runner/types.ts

@@ -0,0 +1,102 @@
+import { AgentChatResponse } from "../../engines/chat";
+import { BaseAgent, Task, TaskStep, TaskStepOutput } from "../types";
+
+export class TaskState {
+  task!: Task;
+  stepQueue!: TaskStep[];
+  completedSteps!: TaskStepOutput[];
+
+  constructor(init?: Partial<TaskState>) {
+    Object.assign(this, init);
+  }
+}
+
+export abstract class BaseAgentRunner extends BaseAgent {
+  constructor(init?: Partial<BaseAgentRunner>) {
+    super();
+  }
+
+  abstract createTask(input: string, kwargs: any): Task;
+  abstract deleteTask(taskId: string): void;
+  abstract getTask(taskId: string, kwargs: any): Task;
+  abstract listTasks(kwargs: any): Task[];
+  abstract getUpcomingSteps(taskId: string, kwargs: any): TaskStep[];
+  abstract getCompletedSteps(taskId: string, kwargs: any): TaskStepOutput[];
+
+  getCompletedStep(
+    taskId: string,
+    stepId: string,
+    kwargs: any,
+  ): TaskStepOutput {
+    const completedSteps = this.getCompletedSteps(taskId, kwargs);
+    for (const stepOutput of completedSteps) {
+      if (stepOutput.taskStep.stepId === stepId) {
+        return stepOutput;
+      }
+    }
+
+    throw new Error(`Step ${stepId} not found in task ${taskId}`);
+  }
+
+  abstract runStep(
+    taskId: string,
+    input: string,
+    step: TaskStep,
+    kwargs: any,
+  ): Promise<TaskStepOutput>;
+
+  abstract streamStep(
+    taskId: string,
+    input: string,
+    step: TaskStep,
+    kwargs?: any,
+  ): Promise<TaskStepOutput>;
+
+  abstract finalizeResponse(
+    taskId: string,
+    stepOutput: TaskStepOutput,
+    kwargs?: any,
+  ): Promise<AgentChatResponse>;
+
+  abstract undoStep(taskId: string): void;
+}
+
+export class AgentState {
+  taskDict!: Record<string, TaskState>;
+
+  constructor(init?: Partial<AgentState>) {
+    Object.assign(this, init);
+
+    if (!this.taskDict) {
+      this.taskDict = {};
+    }
+  }
+
+  getTask(taskId: string): Task {
+    return this.taskDict[taskId].task;
+  }
+
+  getCompletedSteps(taskId: string): TaskStepOutput[] {
+    return this.taskDict[taskId].completedSteps || [];
+  }
+
+  getStepQueue(taskId: string): TaskStep[] {
+    return this.taskDict[taskId].stepQueue || [];
+  }
+
+  addSteps(taskId: string, steps: TaskStep[]): void {
+    if (!this.taskDict[taskId].stepQueue) {
+      this.taskDict[taskId].stepQueue = [];
+    }
+
+    this.taskDict[taskId].stepQueue.push(...steps);
+  }
+
+  addCompletedStep(taskId: string, stepOutputs: TaskStepOutput[]): void {
+    if (!this.taskDict[taskId].completedSteps) {
+      this.taskDict[taskId].completedSteps = [];
+    }
+
+    this.taskDict[taskId].completedSteps.push(...stepOutputs);
+  }
+}

packages/core/src/agent/types.ts

@@ -0,0 +1,181 @@
+import { AgentChatResponse, ChatEngineAgentParams } from "../engines/chat";
+import { QueryEngineParamsNonStreaming } from "../types";
+
+export interface AgentWorker {
+  initializeStep(task: Task, kwargs?: any): TaskStep;
+  runStep(step: TaskStep, task: Task, kwargs?: any): Promise<TaskStepOutput>;
+  streamStep(step: TaskStep, task: Task, kwargs?: any): Promise<TaskStepOutput>;
+  finalizeTask(task: Task, kwargs?: any): void;
+}
+
+interface BaseChatEngine {
+  chat(params: ChatEngineAgentParams): Promise<AgentChatResponse>;
+}
+
+interface BaseQueryEngine {
+  query(params: QueryEngineParamsNonStreaming): Promise<AgentChatResponse>;
+}
+
+/**
+ * BaseAgent is the base class for all agents.
+ */
+export abstract class BaseAgent implements BaseChatEngine, BaseQueryEngine {
+  protected _getPrompts(): string[] {
+    return [];
+  }
+
+  protected _getPromptModules(): string[] {
+    return [];
+  }
+
+  abstract chat(params: ChatEngineAgentParams): Promise<AgentChatResponse>;
+  abstract reset(): void;
+
+  /**
+   * query is the main entrypoint for the agent. It takes a query and returns a response.
+   * @param params
+   * @returns
+   */
+  async query(
+    params: QueryEngineParamsNonStreaming,
+  ): Promise<AgentChatResponse> {
+    // Handle non-streaming query
+    const agentResponse = await this.chat({
+      message: params.query,
+      chatHistory: [],
+    });
+
+    return agentResponse;
+  }
+}
+
+type TaskParams = {
+  taskId: string;
+  input: string;
+  memory: any;
+  extraState: Record<string, any>;
+};
+
+/**
+ * Task is a unit of work for the agent.
+ * @param taskId: taskId
+ */
+export class Task {
+  taskId: string;
+  input: string;
+
+  memory: any;
+  extraState: Record<string, any>;
+
+  constructor({ taskId, input, memory, extraState }: TaskParams) {
+    this.taskId = taskId;
+    this.input = input;
+    this.memory = memory;
+    this.extraState = extraState ?? {};
+  }
+}
+
+interface ITaskStep {
+  taskId: string;
+  stepId: string;
+  input?: string | null;
+  stepState: Record<string, any>;
+  nextSteps: Record<string, TaskStep>;
+  prevSteps: Record<string, TaskStep>;
+  isReady: boolean;
+  getNextStep(
+    stepId: string,
+    input?: string,
+    stepState?: Record<string, any>,
+  ): TaskStep;
+  linkStep(nextStep: TaskStep): void;
+}
+
+/**
+ * TaskStep is a unit of work for the agent.
+ * @param taskId: taskId
+ * @param stepId: stepId
+ * @param input: input
+ * @param stepState: stepState
+ */
+export class TaskStep implements ITaskStep {
+  taskId: string;
+  stepId: string;
+  input?: string | null;
+  stepState: Record<string, any> = {};
+  nextSteps: Record<string, TaskStep> = {};
+  prevSteps: Record<string, TaskStep> = {};
+  isReady: boolean = true;
+
+  constructor(
+    taskId: string,
+    stepId: string,
+    input?: string | null,
+    stepState?: Record<string, any> | null,
+  ) {
+    this.taskId = taskId;
+    this.stepId = stepId;
+    this.input = input;
+    this.stepState = stepState ?? this.stepState;
+  }
+
+  /*
+   * getNextStep is a function that returns the next step.
+   * @param stepId: stepId
+   * @param input: input
+   * @param stepState: stepState
+   * @returns: TaskStep
+   */
+  getNextStep(
+    stepId: string,
+    input?: string,
+    stepState?: Record<string, unknown>,
+  ): TaskStep {
+    return new TaskStep(
+      this.taskId,
+      stepId,
+      input,
+      stepState ?? this.stepState,
+    );
+  }
+
+  /*
+   * linkStep is a function that links the next step.
+   * @param nextStep: nextStep
+   * @returns: void
+   */
+  linkStep(nextStep: TaskStep): void {
+    this.nextSteps[nextStep.stepId] = nextStep;
+    nextStep.prevSteps[this.stepId] = this;
+  }
+}
+
+/**
+ * TaskStepOutput is a unit of work for the agent.
+ * @param output: output
+ * @param taskStep: taskStep
+ * @param nextSteps: nextSteps
+ * @param isLast: isLast
+ */
+export class TaskStepOutput {
+  output: unknown;
+  taskStep: TaskStep;
+  nextSteps: TaskStep[];
+  isLast: boolean;
+
+  constructor(
+    output: unknown,
+    taskStep: TaskStep,
+    nextSteps: TaskStep[],
+    isLast: boolean = false,
+  ) {
+    this.output = output;
+    this.taskStep = taskStep;
+    this.nextSteps = nextSteps;
+    this.isLast = isLast;
+  }
+
+  toString(): string {
+    return String(this.output);
+  }
+}

packages/core/src/agent/utils.ts

@@ -0,0 +1,51 @@
+import { ChatMessage } from "../llm";
+import { ChatMemoryBuffer } from "../memory/ChatMemoryBuffer";
+import { BaseTool } from "../types";
+import { TaskStep } from "./types";
+
+/**
+ * Adds the user's input to the memory.
+ *
+ * @param step - The step to add to the memory.
+ * @param memory - The memory to add the step to.
+ * @param verbose - Whether to print debug messages.
+ */
+export function addUserStepToMemory(
+  step: TaskStep,
+  memory: ChatMemoryBuffer,
+  verbose: boolean = false,
+): void {
+  if (!step.input) {
+    return;
+  }
+
+  const userMessage: ChatMessage = {
+    content: step.input,
+    role: "user",
+  };
+
+  memory.put(userMessage);
+
+  if (verbose) {
+    console.log(`Added user message to memory!: ${userMessage.content}`);
+  }
+}
+
+/**
+ * Get function by name.
+ * @param tools: tools
+ * @param name: name
+ * @returns: tool
+ */
+export function getFunctionByName(tools: BaseTool[], name: string): BaseTool {
+  const nameToTool: { [key: string]: BaseTool } = {};
+  tools.forEach((tool) => {
+    nameToTool[tool.metadata.name] = tool;
+  });
+
+  if (!(name in nameToTool)) {
+    throw new Error(`Tool with name ${name} not found`);
+  }
+
+  return nameToTool[name];
+}

packages/core/src/engines/chat/types.ts

@@ -1,9 +1,10 @@
 import { ChatHistory } from "../../ChatHistory";
-import { NodeWithScore } from "../../Node";
+import { BaseNode, NodeWithScore } from "../../Node";
 import { Response } from "../../Response";
 import { Event } from "../../callbacks/CallbackManager";
 import { ChatMessage } from "../../llm";
 import { MessageContent } from "../../llm/types";
+import { ToolOutput } from "../../tools/types";
 
 /**
  * Represents the base parameters for ChatEngine.
@@ -24,6 +25,10 @@ export interface ChatEngineParamsNonStreaming extends ChatEngineParamsBase {
   stream?: false | null;
 }
 
+export interface ChatEngineAgentParams extends ChatEngineParamsBase {
+  toolChoice?: string | Record<string, any>;
+}
+
 /**
  * A ChatEngine is used to handle back and forth chats between the application and the LLM.
  */
@@ -52,3 +57,32 @@ export interface Context {
 export interface ContextGenerator {
   generate(message: string, parentEvent?: Event): Promise<Context>;
 }
+
+export enum ChatResponseMode {
+  WAIT = "wait",
+  STREAM = "stream",
+}
+
+export class AgentChatResponse {
+  response: string;
+  sources: ToolOutput[];
+  sourceNodes?: BaseNode[];
+
+  constructor(
+    response: string,
+    sources?: ToolOutput[],
+    sourceNodes?: BaseNode[],
+  ) {
+    this.response = response;
+    this.sources = sources || [];
+    this.sourceNodes = sourceNodes || [];
+  }
+
+  protected _getFormattedSources() {
+    throw new Error("Not implemented yet");
+  }
+
+  toString() {
+    return this.response ?? "";
+  }
+}

packages/core/src/index.ts

@@ -9,6 +9,7 @@ export * from "./Response";
 export * from "./Retriever";
 export * from "./ServiceContext";
 export * from "./TextSplitter";
+export * from "./agent";
 export * from "./callbacks/CallbackManager";
 export * from "./constants";
 export * from "./embeddings";
@@ -33,4 +34,4 @@ export * from "./readers/base";
 export * from "./selectors";
 export * from "./storage";
 export * from "./synthesizers";
-export type * from "./types";
+export * from "./tools";

packages/core/src/indices/vectorStore/VectorIndexRetriever.ts

@@ -17,6 +17,12 @@ import { VectorStoreIndex } from "./VectorStoreIndex";
  * VectorIndexRetriever retrieves nodes from a VectorIndex.
  */
 
+export type VectorIndexRetrieverOptions = {
+  index: VectorStoreIndex;
+  similarityTopK?: number;
+  imageSimilarityTopK?: number;
+};
+
 export class VectorIndexRetriever implements BaseRetriever {
   index: VectorStoreIndex;
   similarityTopK: number;
@@ -27,11 +33,7 @@ export class VectorIndexRetriever implements BaseRetriever {
     index,
     similarityTopK,
     imageSimilarityTopK,
-  }: {
-    index: VectorStoreIndex;
-    similarityTopK?: number;
-    imageSimilarityTopK?: number;
-  }) {
+  }: VectorIndexRetrieverOptions) {
     this.index = index;
     this.serviceContext = this.index.serviceContext;
     this.similarityTopK = similarityTopK ?? DEFAULT_SIMILARITY_TOP_K;

packages/core/src/indices/vectorStore/VectorStoreIndex.ts

@@ -34,7 +34,10 @@ import {
   IndexDict,
   IndexStructType,
 } from "../BaseIndex";
-import { VectorIndexRetriever } from "./VectorIndexRetriever";
+import {
+  VectorIndexRetriever,
+  VectorIndexRetrieverOptions,
+} from "./VectorIndexRetriever";
 
 interface IndexStructOptions {
   indexStruct?: IndexDict;
@@ -260,7 +263,9 @@ export class VectorStoreIndex extends BaseIndex<IndexDict> {
     return index;
   }
 
-  asRetriever(options?: any): VectorIndexRetriever {
+  asRetriever(
+    options?: Omit<VectorIndexRetrieverOptions, "index">,
+  ): VectorIndexRetriever {
     return new VectorIndexRetriever({ index: this, ...options });
   }
 

packages/core/src/llm/LLM.ts

@@ -77,7 +77,14 @@ export class OpenAI extends BaseLLM {
   maxTokens?: number;
   additionalChatOptions?: Omit<
     Partial<OpenAILLM.Chat.ChatCompletionCreateParams>,
-    "max_tokens" | "messages" | "model" | "temperature" | "top_p" | "stream"
+    | "max_tokens"
+    | "messages"
+    | "model"
+    | "temperature"
+    | "top_p"
+    | "stream"
+    | "tools"
+    | "toolChoice"
   >;
 
   // OpenAI session params
@@ -179,7 +186,7 @@ export class OpenAI extends BaseLLM {
 
   mapMessageType(
     messageType: MessageType,
-  ): "user" | "assistant" | "system" | "function" {
+  ): "user" | "assistant" | "system" | "function" | "tool" {
     switch (messageType) {
       case "user":
         return "user";
@@ -189,11 +196,30 @@ export class OpenAI extends BaseLLM {
         return "system";
       case "function":
         return "function";
+      case "tool":
+        return "tool";
       default:
         return "user";
     }
   }
 
+  toOpenAIMessage(messages: ChatMessage[]) {
+    return messages.map((message) => {
+      const additionalKwargs = message.additionalKwargs ?? {};
+
+      if (message.additionalKwargs?.toolCalls) {
+        additionalKwargs.tool_calls = message.additionalKwargs.toolCalls;
+        delete additionalKwargs.toolCalls;
+      }
+
+      return {
+        role: this.mapMessageType(message.role),
+        content: message.content,
+        ...additionalKwargs,
+      };
+    });
+  }
+
   chat(
     params: LLMChatParamsStreaming,
   ): Promise<AsyncIterable<ChatResponseChunk>>;
@@ -201,18 +227,15 @@ export class OpenAI extends BaseLLM {
   async chat(
     params: LLMChatParamsNonStreaming | LLMChatParamsStreaming,
   ): Promise<ChatResponse | AsyncIterable<ChatResponseChunk>> {
-    const { messages, parentEvent, stream } = params;
-    const baseRequestParams: OpenAILLM.Chat.ChatCompletionCreateParams = {
+    const { messages, parentEvent, stream, tools, toolChoice } = params;
+
+    let baseRequestParams: OpenAILLM.Chat.ChatCompletionCreateParams = {
       model: this.model,
       temperature: this.temperature,
       max_tokens: this.maxTokens,
-      messages: messages.map(
-        (message) =>
-          ({
-            role: this.mapMessageType(message.role),
-            content: message.content,
-          }) as ChatCompletionMessageParam,
-      ),
+      tools: tools,
+      tool_choice: toolChoice,
+      messages: this.toOpenAIMessage(messages) as ChatCompletionMessageParam[],
       top_p: this.topP,
       ...this.additionalChatOptions,
     };
@@ -221,6 +244,7 @@ export class OpenAI extends BaseLLM {
     if (stream) {
       return this.streamChat(params);
     }
+
     // Non-streaming
     const response = await this.session.openai.chat.completions.create({
       ...baseRequestParams,
@@ -228,8 +252,19 @@ export class OpenAI extends BaseLLM {
     });
 
     const content = response.choices[0].message?.content ?? "";
+
+    const kwargsOutput: Record<string, any> = {};
+
+    if (response.choices[0].message?.tool_calls) {
+      kwargsOutput.toolCalls = response.choices[0].message.tool_calls;
+    }
+
     return {
-      message: { content, role: response.choices[0].message.role },
+      message: {
+        content,
+        role: response.choices[0].message.role,
+        additionalKwargs: kwargsOutput,
+      },
     };
   }
 

packages/core/src/llm/types.ts

@@ -39,17 +39,20 @@ export type MessageType =
   | "system"
   | "generic"
   | "function"
-  | "memory";
+  | "memory"
+  | "tool";
 
 export interface ChatMessage {
   // TODO: use MessageContent
   content: any;
   role: MessageType;
+  additionalKwargs?: Record<string, any>;
 }
 
 export interface ChatResponse {
   message: ChatMessage;
   raw?: Record<string, any>;
+  additionalKwargs?: Record<string, any>;
 }
 
 export interface ChatResponseChunk {
@@ -74,6 +77,9 @@ export interface LLMChatParamsBase {
   messages: ChatMessage[];
   parentEvent?: Event;
   extraParams?: Record<string, any>;
+  tools?: any;
+  toolChoice?: any;
+  additionalKwargs?: Record<string, any>;
 }
 
 export interface LLMChatParamsStreaming extends LLMChatParamsBase {

packages/core/src/memory/ChatMemoryBuffer.ts

@@ -0,0 +1,119 @@
+import { ChatMessage } from "../llm";
+import { SimpleChatStore } from "../storage/chatStore/SimpleChatStore";
+import { BaseChatStore } from "../storage/chatStore/types";
+import { BaseMemory } from "./types";
+
+type ChatMemoryBufferParams = {
+  tokenLimit?: number;
+  chatStore?: BaseChatStore;
+  chatStoreKey?: string;
+  chatHistory?: ChatMessage[];
+};
+
+/**
+ * Chat memory buffer.
+ */
+export class ChatMemoryBuffer implements BaseMemory {
+  tokenLimit: number;
+
+  chatStore: BaseChatStore;
+  chatStoreKey: string;
+
+  /**
+   * Initialize.
+   */
+  constructor(init?: Partial<ChatMemoryBufferParams>) {
+    this.tokenLimit = init?.tokenLimit ?? 3000;
+    this.chatStore = init?.chatStore ?? new SimpleChatStore();
+    this.chatStoreKey = init?.chatStoreKey ?? "chat_history";
+
+    if (init?.chatHistory) {
+      this.chatStore.setMessages(this.chatStoreKey, init.chatHistory);
+    }
+  }
+
+  /**
+    Get chat history.
+    @param initialTokenCount: number of tokens to start with
+  */
+  get(initialTokenCount: number = 0): ChatMessage[] {
+    const chatHistory = this.getAll();
+
+    if (initialTokenCount > this.tokenLimit) {
+      throw new Error("Initial token count exceeds token limit");
+    }
+
+    let messageCount = chatHistory.length;
+    let tokenCount =
+      this._tokenCountForMessageCount(messageCount) + initialTokenCount;
+
+    while (tokenCount > this.tokenLimit && messageCount > 1) {
+      messageCount -= 1;
+      if (chatHistory[-messageCount].role === "assistant") {
+        // we cannot have an assistant message at the start of the chat history
+        // if after removal of the first, we have an assistant message,
+        // we need to remove the assistant message too
+        messageCount -= 1;
+      }
+
+      tokenCount =
+        this._tokenCountForMessageCount(messageCount) + initialTokenCount;
+    }
+
+    // catch one message longer than token limit
+    if (tokenCount > this.tokenLimit || messageCount <= 0) {
+      return [];
+    }
+
+    return chatHistory.slice(-messageCount);
+  }
+
+  /**
+   * Get all chat history.
+   * @returns {ChatMessage[]} chat history
+   */
+  getAll(): ChatMessage[] {
+    return this.chatStore.getMessages(this.chatStoreKey);
+  }
+
+  /**
+   * Put chat history.
+   * @param message
+   */
+  put(message: ChatMessage): void {
+    this.chatStore.addMessage(this.chatStoreKey, message);
+  }
+
+  /**
+   * Set chat history.
+   * @param messages
+   */
+  set(messages: ChatMessage[]): void {
+    this.chatStore.setMessages(this.chatStoreKey, messages);
+  }
+
+  /**
+   * Reset chat history.
+   */
+  reset(): void {
+    this.chatStore.deleteMessages(this.chatStoreKey);
+  }
+
+  /**
+   * Get token count for message count.
+   * @param messageCount
+   * @returns {number} token count
+   */
+  private _tokenCountForMessageCount(messageCount: number): number {
+    if (messageCount <= 0) {
+      return 0;
+    }
+
+    const chatHistory = this.getAll();
+    const msgStr = chatHistory
+      .slice(-messageCount)
+      .map((m) => m.content)
+      .join(" ");
+    return msgStr.split(" ").length;
+  }
+}

packages/core/src/memory/types.ts

@@ -0,0 +1,24 @@
+import { ChatMessage } from "../llm";
+
+export interface BaseMemory {
+  /* 
+   Get chat history.
+  */
+  get(...args: any): ChatMessage[];
+  /*
+    Get all chat history.
+  */
+  getAll(): ChatMessage[];
+  /*
+    Put chat history.
+  */
+  put(message: ChatMessage): void;
+  /*
+    Set chat history.
+  */
+  set(messages: ChatMessage[]): void;
+  /*
+    Reset chat history.
+  */
+  reset(): void;
+}

packages/core/src/objects/base.ts

@@ -0,0 +1,80 @@
+import { BaseNode, TextNode } from "../Node";
+import { BaseRetriever } from "../Retriever";
+
+// Assuming that necessary interfaces and classes (like OT, TextNode, BaseNode, etc.) are defined elsewhere
+// Import statements (e.g., for TextNode, BaseNode) should be added based on your project's structure
+
+export abstract class BaseObjectNodeMapping<OT> {
+  // TypeScript doesn't support Python's classmethod directly, but we can use static methods as an alternative
+  abstract fromObjects<OT>(
+    objs: OT[],
+    ...args: any[]
+  ): BaseObjectNodeMapping<OT>;
+
+  // Abstract methods in TypeScript
+  abstract objNodeMapping(): Record<any, any>;
+  abstract toNode(obj: OT): TextNode;
+
+  // Concrete methods can be defined as usual
+  validateObject(obj: OT): void {}
+
+  // Implementing the add object logic
+  addObj(obj: OT): void {
+    this.validateObject(obj);
+    this._addObj(obj);
+  }
+
+  // Abstract method for internal add object logic
+  protected abstract _addObj(obj: OT): void;
+
+  // Implementing toNodes method
+  toNodes(objs: OT[]): TextNode[] {
+    return objs.map((obj) => this.toNode(obj));
+  }
+
+  // Abstract method for internal from node logic
+  protected abstract _fromNode(node: BaseNode): OT;
+
+  // Implementing fromNode method
+  fromNode(node: BaseNode): OT {
+    const obj = this._fromNode(node);
+    this.validateObject(obj);
+    return obj;
+  }
+
+  // Abstract methods for persistence
+  abstract persist(persistDir: string, objNodeMappingFilename: string): void;
+}
+
+// You will need to implement specific subclasses of BaseObjectNodeMapping as per your project requirements.
+
+type QueryType = string;
+
+export class ObjectRetriever<OT> {
+  private _retriever: BaseRetriever;
+  private _objectNodeMapping: BaseObjectNodeMapping<OT>;
+
+  constructor(
+    retriever: BaseRetriever,
+    objectNodeMapping: BaseObjectNodeMapping<OT>,
+  ) {
+    this._retriever = retriever;
+    this._objectNodeMapping = objectNodeMapping;
+  }
+
+  // In TypeScript, getters are defined like this.
+  get retriever(): BaseRetriever {
+    return this._retriever;
+  }
+
+  // Translating the retrieve method
+  async retrieve(strOrQueryBundle: QueryType): Promise<OT[]> {
+    const nodes = await this._retriever.retrieve(strOrQueryBundle);
+    return nodes.map((node) => this._objectNodeMapping.fromNode(node.node));
+  }
+
+  // // Translating the _asQueryComponent method
+  // public asQueryComponent(kwargs: any): any {
+  //     return new ObjectRetrieverComponent(this);
+  // }
+}

packages/core/src/storage/chatStore/SimpleChatStore.ts

@@ -0,0 +1,92 @@
+import { ChatMessage } from "../../llm";
+import { BaseChatStore } from "./types";
+
+/**
+ * Simple chat store.
+ */
+export class SimpleChatStore implements BaseChatStore {
+  store: { [key: string]: ChatMessage[] } = {};
+
+  /**
+   * Set messages.
+   * @param key: key
+   * @param messages: messages
+   * @returns: void
+   */
+  public setMessages(key: string, messages: ChatMessage[]): void {
+    this.store[key] = messages;
+  }
+
+  /**
+   * Get messages.
+   * @param key: key
+   * @returns: messages
+   */
+  public getMessages(key: string): ChatMessage[] {
+    return this.store[key] || [];
+  }
+
+  /**
+   * Add message.
+   * @param key: key
+   * @param message: message
+   * @returns: void
+   */
+  public addMessage(key: string, message: ChatMessage): void {
+    this.store[key] = this.store[key] || [];
+    this.store[key].push(message);
+  }
+
+  /**
+   * Delete messages.
+   * @param key: key
+   * @returns: messages
+   */
+  public deleteMessages(key: string): ChatMessage[] | null {
+    if (!(key in this.store)) {
+      return null;
+    }
+    const messages = this.store[key];
+    delete this.store[key];
+    return messages;
+  }
+
+  /**
+   * Delete message.
+   * @param key: key
+   * @param idx: idx
+   * @returns: message
+   */
+  public deleteMessage(key: string, idx: number): ChatMessage | null {
+    if (!(key in this.store)) {
+      return null;
+    }
+    if (idx >= this.store[key].length) {
+      return null;
+    }
+    return this.store[key].splice(idx, 1)[0];
+  }
+
+  /**
+   * Delete last message.
+   * @param key: key
+   * @returns: message
+   */
+  public deleteLastMessage(key: string): ChatMessage | null {
+    if (!(key in this.store)) {
+      return null;
+    }
+
+    const lastMessage = this.store[key].pop();
+
+    return lastMessage || null;
+  }
+
+  /**
+   * Get keys.
+   * @returns: keys
+   */
+  public getKeys(): string[] {
+    return Object.keys(this.store);
+  }
+}

packages/core/src/storage/chatStore/types.ts

@@ -0,0 +1,11 @@
+import { ChatMessage } from "../../llm";
+
+export interface BaseChatStore {
+  setMessages(key: string, messages: ChatMessage[]): void;
+  getMessages(key: string): ChatMessage[];
+  addMessage(key: string, message: ChatMessage): void;
+  deleteMessages(key: string): ChatMessage[] | null;
+  deleteMessage(key: string, idx: number): ChatMessage | null;
+  deleteLastMessage(key: string): ChatMessage | null;
+  getKeys(): string[];
+}

packages/core/src/storage/index.ts

@@ -1,5 +1,7 @@
 export * from "./FileSystem";
 export * from "./StorageContext";
+export { SimpleChatStore } from "./chatStore/SimpleChatStore";
+export * from "./chatStore/types";
 export * from "./constants";
 export { SimpleDocumentStore } from "./docStore/SimpleDocumentStore";
 export * from "./docStore/types";

packages/core/src/storage/vectorStore/PineconeVectorStore.ts

@@ -142,8 +142,8 @@ export class PineconeVectorStore implements VectorStore {
     var options: any = {
       vector: query.queryEmbedding,
       topK: query.similarityTopK,
-      include_values: true,
-      include_metadara: true,
+      includeValues: true,
+      includeMetadata: true,
       filter: filter,
     };
 

packages/core/src/tests/MetadataExtractors.test.ts

@@ -50,6 +50,7 @@ describe("[MetadataExtractor]: Extractors should populate the metadata", () => {
     mockLlmGeneration({ languageModel, callbackManager });
 
     const embedModel = new OpenAIEmbedding();
+
     mockEmbeddingModel(embedModel);
 
     serviceContext = serviceContextFromDefaults({

packages/core/src/tests/agent/OpenAIAgent.test.ts

@@ -0,0 +1,69 @@
+import { OpenAIAgent } from "../../agent";
+import { CallbackManager } from "../../callbacks/CallbackManager";
+import { OpenAI } from "../../llm";
+import { FunctionTool } from "../../tools";
+import { mockLlmToolCallGeneration } from "../utility/mockOpenAI";
+
+// Define a function to sum two numbers
+function sumNumbers({ a, b }: { a: number; b: number }): number {
+  return a + b;
+}
+
+const sumJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The first number",
+    },
+    b: {
+      type: "number",
+      description: "The second number",
+    },
+  },
+  required: ["a", "b"],
+};
+
+jest.mock("../../llm/open_ai", () => {
+  return {
+    getOpenAISession: jest.fn().mockImplementation(() => null),
+  };
+});
+
+describe("OpenAIAgent", () => {
+  let openaiAgent: OpenAIAgent;
+
+  beforeEach(() => {
+    const callbackManager = new CallbackManager({});
+
+    const languageModel = new OpenAI({
+      model: "gpt-3.5-turbo",
+      callbackManager,
+    });
+
+    mockLlmToolCallGeneration({
+      languageModel,
+      callbackManager,
+    });
+
+    const sumFunctionTool = new FunctionTool(sumNumbers, {
+      name: "sumNumbers",
+      description: "Use this function to sum two numbers",
+      parameters: sumJSON,
+    });
+
+    openaiAgent = new OpenAIAgent({
+      tools: [sumFunctionTool],
+      llm: languageModel,
+      verbose: false,
+    });
+  });
+
+  it("should be able to chat with agent", async () => {
+    const response = await openaiAgent.chat({
+      message: "how much is 1 + 1?",
+    });
+
+    expect(String(response)).toEqual("The sum is 2");
+  });
+});

packages/core/src/tests/agent/runner/AgentRunner.test.ts

@@ -0,0 +1,99 @@
+import { OpenAIAgentWorker } from "../../../agent";
+import { AgentRunner } from "../../../agent/runner/base";
+import { CallbackManager } from "../../../callbacks/CallbackManager";
+import { OpenAI } from "../../../llm/LLM";
+
+import {
+  DEFAULT_LLM_TEXT_OUTPUT,
+  mockLlmGeneration,
+} from "../../utility/mockOpenAI";
+
+jest.mock("../../../llm/open_ai", () => {
+  return {
+    getOpenAISession: jest.fn().mockImplementation(() => null),
+  };
+});
+
+describe("Agent Runner", () => {
+  let agentRunner: AgentRunner;
+
+  beforeEach(() => {
+    const callbackManager = new CallbackManager({});
+
+    const languageModel = new OpenAI({
+      model: "gpt-3.5-turbo",
+      callbackManager,
+    });
+
+    mockLlmGeneration({
+      languageModel,
+      callbackManager,
+    });
+
+    agentRunner = new AgentRunner({
+      llm: languageModel,
+      agentWorker: new OpenAIAgentWorker({
+        llm: languageModel,
+        tools: [],
+        verbose: false,
+      }),
+    });
+  });
+
+  it("should be able to initialize a task", () => {
+    const task = agentRunner.createTask("hello world");
+
+    expect(task.input).toEqual("hello world");
+    expect(task.taskId in agentRunner.state.taskDict).toEqual(true);
+
+    expect(agentRunner.listTasks().length).toEqual(1);
+  });
+
+  it("should be able to run a step", async () => {
+    const task = agentRunner.createTask("hello world");
+
+    expect(agentRunner.getCompletedSteps(task.taskId)).toBeUndefined();
+
+    const stepOutput = await agentRunner.runStep(task.taskId, task.input);
+
+    const completedSteps = agentRunner.getCompletedSteps(task.taskId);
+
+    expect(completedSteps.length).toEqual(1);
+
+    expect(stepOutput.isLast).toEqual(true);
+  });
+
+  it("should be able to finalize a task", async () => {
+    const task = agentRunner.createTask("hello world");
+
+    expect(agentRunner.getCompletedSteps(task.taskId)).toBeUndefined();
+
+    const stepOutput1 = await agentRunner.runStep(task.taskId, task.input);
+
+    expect(stepOutput1.isLast).toEqual(true);
+  });
+
+  it("should be able to delete a task", () => {
+    const task = agentRunner.createTask("hello world");
+
+    expect(agentRunner.listTasks().length).toEqual(1);
+
+    agentRunner.deleteTask(task.taskId);
+
+    expect(agentRunner.listTasks().length).toEqual(0);
+  });
+
+  it("should be able to run a chat", async () => {
+    const response = await agentRunner.chat({
+      message: "hello world",
+    });
+
+    expect(agentRunner.listTasks().length).toEqual(1);
+
+    expect(response).toEqual({
+      response: DEFAULT_LLM_TEXT_OUTPUT,
+      sourceNodes: [],
+      sources: [],
+    });
+  });
+});

packages/core/src/tests/tools/Tools.test.ts

@@ -0,0 +1,45 @@
+import { FunctionTool, ToolOutput } from "../../tools";
+import { callToolWithErrorHandling } from "../../tools/utils";
+
+function sumNumbers({ a, b }: { a: number; b: number }): number {
+  return a + b;
+}
+
+const sumJSON = {
+  type: "object",
+  properties: {
+    a: {
+      type: "number",
+      description: "The first number",
+    },
+    b: {
+      type: "number",
+      description: "The second number",
+    },
+  },
+  required: ["a", "b"],
+};
+
+describe("Tools", () => {
+  it("should be able to call a tool with a common JSON", async () => {
+    const tool = new FunctionTool(sumNumbers, {
+      name: "sumNumbers",
+      description: "Use this function to sum two numbers",
+      parameters: sumJSON,
+    });
+
+    const response = await callToolWithErrorHandling(tool, {
+      a: 1,
+      b: 2,
+    });
+
+    expect(response).toEqual(
+      new ToolOutput(
+        response.content,
+        tool.metadata.name,
+        { a: 1, b: 2 },
+        response.content,
+      ),
+    );
+  });
+});

packages/core/src/tests/utility/mockOpenAI.ts

@@ -64,6 +64,26 @@ export function mockLlmGeneration({
     );
 }
 
+export function mockLlmToolCallGeneration({
+  languageModel,
+  callbackManager,
+}: {
+  languageModel: OpenAI;
+  callbackManager: CallbackManager;
+}) {
+  jest.spyOn(languageModel, "chat").mockImplementation(
+    () =>
+      new Promise((resolve) =>
+        resolve({
+          message: {
+            content: "The sum is 2",
+            role: "assistant",
+          },
+        }),
+      ),
+  );
+}
+
 export function mockEmbeddingModel(embedModel: OpenAIEmbedding) {
   jest.spyOn(embedModel, "getTextEmbedding").mockImplementation(async (x) => {
     return new Promise((resolve) => {

packages/core/src/tools/functionTool.ts

@@ -0,0 +1,32 @@
+import { BaseTool, ToolMetadata } from "../types";
+
+type Metadata = {
+  name: string;
+  description: string;
+  parameters: ToolMetadata["parameters"];
+};
+
+export class FunctionTool<T = any> implements BaseTool {
+  private _fn: (...args: any[]) => any;
+  private _metadata: ToolMetadata;
+
+  constructor(fn: (...args: any[]) => any, metadata: Metadata) {
+    this._fn = fn;
+    this._metadata = metadata as ToolMetadata;
+  }
+
+  static fromDefaults<T = any>(
+    fn: (...args: any[]) => any,
+    metadata?: Metadata,
+  ): FunctionTool<T> {
+    return new FunctionTool(fn, metadata!);
+  }
+
+  get metadata(): ToolMetadata {
+    return this._metadata;
+  }
+
+  async call(...args: any[]): Promise<any> {
+    return this._fn(...args);
+  }
+}

packages/core/src/tools/index.ts

@@ -0,0 +1,2 @@
+export * from "./functionTool";
+export * from "./types";

packages/core/src/tools/types.ts

@@ -0,0 +1,22 @@
+export class ToolOutput {
+  content: string;
+  toolName: string;
+  rawInput: any;
+  rawOutput: any;
+
+  constructor(
+    content: string,
+    toolName: string,
+    rawInput: any,
+    rawOutput: any,
+  ) {
+    this.content = content;
+    this.toolName = toolName;
+    this.rawInput = rawInput;
+    this.rawOutput = rawOutput;
+  }
+
+  toString(): string {
+    return this.content;
+  }
+}

packages/core/src/tools/utils.ts

@@ -0,0 +1,33 @@
+import { BaseTool } from "../types";
+import { ToolOutput } from "./types";
+
+/**
+ * Call tool with error handling.
+ * @param tool: tool
+ * @param inputDict: input dict
+ * @param errorMessage: error message
+ * @param raiseError: raise error
+ * @returns: tool output
+ */
+export async function callToolWithErrorHandling(
+  tool: BaseTool,
+  inputDict: { [key: string]: any },
+  errorMessage: string | null = null,
+  raiseError: boolean = false,
+): Promise<ToolOutput> {
+  try {
+    const value = await tool.call?.(inputDict);
+    return new ToolOutput(value, tool.metadata.name, inputDict, value);
+  } catch (e) {
+    if (raiseError) {
+      throw e;
+    }
+    errorMessage = errorMessage || `Error: ${e}`;
+    return new ToolOutput(
+      errorMessage,
+      tool.metadata.name,
+      { kwargs: inputDict },
+      e,
+    );
+  }
+}

packages/core/src/types.ts

@@ -1,7 +1,6 @@
 /**
  * Top level types to avoid circular dependencies
  */
-
 import { Event } from "./callbacks/CallbackManager";
 import { Response } from "./Response";
 
@@ -37,6 +36,7 @@ export interface BaseQueryEngine {
  * Simple Tool interface. Likely to change.
  */
 export interface BaseTool {
+  call?: (...args: any[]) => any;
   metadata: ToolMetadata;
 }
 
@@ -64,9 +64,17 @@ export interface StructuredOutput<T> {
   parsedOutput: T;
 }
 
+export type ToolParameters = {
+  type: string | "object";
+  properties: Record<string, { type: string; description?: string }>;
+  required?: string[];
+};
+
 export interface ToolMetadata {
   description: string;
   name: string;
+  parameters?: ToolParameters;
+  argsKwargs?: Record<string, any>;
 }
 
 export type ToolMetadataOnlyDescription = Pick<ToolMetadata, "description">;

packages/create-llama/CHANGELOG.md

@@ -1,5 +1,11 @@
 # create-llama
 
+## 0.0.24
+
+### Patch Changes
+
+- ba95ca3: Use condense plus context chat engine for FastAPI as default
+
 ## 0.0.23
 
 ### Patch Changes

packages/create-llama/e2e/utils.ts

@@ -74,15 +74,6 @@ export async function runCreateLlama(
   externalPort: number,
   postInstallAction: TemplatePostInstallAction,
 ): Promise<CreateLlamaResult> {
-  const createLlama = path.join(
-    __dirname,
-    "..",
-    "output",
-    "package",
-    "dist",
-    "index.js",
-  );
-
   const name = [
     templateType,
     templateFramework,
@@ -91,8 +82,8 @@ export async function runCreateLlama(
     appType,
   ].join("-");
   const command = [
-    "node",
-    createLlama,
+    "npx",
+    "create-llama",
     name,
     "--template",
     templateType,

packages/create-llama/package.json

@@ -1,6 +1,6 @@
 {
   "name": "create-llama",
-  "version": "0.0.23",
+  "version": "0.0.24",
   "keywords": [
     "rag",
     "llamaindex",
@@ -24,7 +24,7 @@
     "dev": "ncc build ./index.ts -w -o dist/",
     "build": "npm run clean && ncc build ./index.ts -o ./dist/ --minify --no-cache --no-source-map-register",
     "lint": "eslint . --ignore-pattern dist",
-    "e2e": "playwright test",
+    "e2e": "pnpm pack --pack-destination ./output && npm i -g ./output/create-llama-*.tgz && playwright test",
     "prepublishOnly": "cd ../../ && pnpm run build:release"
   },
   "devDependencies": {
@@ -36,7 +36,7 @@
     "@types/prompts": "2.0.1",
     "@types/tar": "6.1.5",
     "@types/validate-npm-package-name": "3.0.0",
-    "@vercel/ncc": "0.34.0",
+    "@vercel/ncc": "0.38.1",
     "async-retry": "1.3.1",
     "async-sema": "3.0.1",
     "ci-info": "github:watson/ci-info#f43f6a1cefff47fb361c88cf4b943fdbcaafe540",

packages/create-llama/questions.ts

@@ -7,6 +7,7 @@ import prompts from "prompts";
 import { InstallAppArgs } from "./create-app";
 import { TemplateDataSourceType, TemplateFramework } from "./helpers";
 import { COMMUNITY_OWNER, COMMUNITY_REPO } from "./helpers/constant";
+import { templatesDir } from "./helpers/dir";
 import { getAvailableLlamapackOptions } from "./helpers/llama-pack";
 import { getRepoRootFolders } from "./helpers/repo";
 
@@ -89,7 +90,7 @@ const getVectorDbChoices = (framework: TemplateFramework) => {
   ];
 
   const vectordbLang = framework === "fastapi" ? "python" : "typescript";
-  const compPath = path.join(__dirname, "..", "templates", "components");
+  const compPath = path.join(templatesDir, "components");
   const vectordbPath = path.join(compPath, "vectordbs", vectordbLang);
 
   const availableChoices = fs

packages/create-llama/templates/components/vectordbs/python/mongo/index.py

@@ -20,4 +20,4 @@ def get_chat_engine():
     )
     index = VectorStoreIndex.from_vector_store(store, service_context)
     logger.info("Finished connecting to index from MongoDB.")
-    return index.as_chat_engine(similarity_top_k=5)
+    return index.as_chat_engine(similarity_top_k=5, chat_mode="condense_plus_context")

packages/create-llama/templates/components/vectordbs/python/none/index.py

@@ -22,4 +22,4 @@ def get_chat_engine():
     storage_context = StorageContext.from_defaults(persist_dir=STORAGE_DIR)
     index = load_index_from_storage(storage_context, service_context=service_context)
     logger.info(f"Finished loading index from {STORAGE_DIR}")
-    return index.as_chat_engine()
+    return index.as_chat_engine(similarity_top_k=5, chat_mode="condense_plus_context")

packages/create-llama/templates/components/vectordbs/python/pg/index.py

@@ -13,4 +13,4 @@ def get_chat_engine():
     store = init_pg_vector_store_from_env()
     index = VectorStoreIndex.from_vector_store(store, service_context)
     logger.info("Finished connecting to index from PGVector.")
-    return index.as_chat_engine(similarity_top_k=5)
+    return index.as_chat_engine(similarity_top_k=5, chat_mode="condense_plus_context")

pnpm-lock.yaml

@@ -17,7 +17,7 @@ importers:
         version: 2.27.1
       '@turbo/gen':
         specifier: ^1.11.3
-        version: 1.11.3(@types/node@20.11.7)(typescript@5.3.3)
+        version: 1.11.3(@types/node@20.11.16)(typescript@5.3.3)
       '@types/jest':
         specifier: ^29.5.11
         version: 29.5.11
@@ -32,7 +32,7 @@ importers:
         version: 9.0.6
       jest:
         specifier: ^29.7.0
-        version: 29.7.0(@types/node@20.11.7)
+        version: 29.7.0(@types/node@20.11.16)
       lint-staged:
         specifier: ^15.2.0
         version: 15.2.0
@@ -62,7 +62,7 @@ importers:
         version: 3.1.1
       '@mdx-js/react':
         specifier: ^3.0.0
-        version: 3.0.0(@types/react@18.2.48)(react@18.2.0)
+        version: 3.0.0(@types/react@18.2.51)(react@18.2.0)
       clsx:
         specifier: ^2.1.0
         version: 2.1.0
@@ -74,7 +74,7 @@ importers:
         version: 2.3.1(react@18.2.0)
       raw-loader:
         specifier: ^4.0.2
-        version: 4.0.2(webpack@5.90.0)
+        version: 4.0.2(webpack@5.90.1)
       react:
         specifier: ^18.2.0
         version: 18.2.0
@@ -87,10 +87,10 @@ importers:
         version: 3.1.0(react-dom@18.2.0)(react@18.2.0)
       '@docusaurus/preset-classic':
         specifier: ^3.1.1
-        version: 3.1.1(@algolia/client-search@4.22.1)(@types/react@18.2.48)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3)
+        version: 3.1.1(@algolia/client-search@4.22.1)(@types/react@18.2.51)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3)
       '@docusaurus/theme-classic':
         specifier: ^3.1.1
-        version: 3.1.1(@types/react@18.2.48)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
+        version: 3.1.1(@types/react@18.2.51)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
       '@docusaurus/types':
         specifier: ^3.1.1
         version: 3.1.1(react-dom@18.2.0)(react@18.2.0)
@@ -295,8 +295,8 @@ importers:
         specifier: 3.0.0
         version: 3.0.0
       '@vercel/ncc':
-        specifier: 0.34.0
-        version: 0.34.0
+        specifier: 0.38.1
+        version: 0.38.1
       async-retry:
         specifier: 1.3.1
         version: 1.3.1
@@ -599,7 +599,7 @@ packages:
     resolution: {integrity: sha512-qrSfCYxYQB5owCmGLbl8XRpX1ytXlpueOb0N0UmQwA073KZxejgQTzAmJezxvpwQD9uGtK2shHdi55QT+MbjIw==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
       '@jridgewell/gen-mapping': 0.3.3
       '@jridgewell/trace-mapping': 0.3.22
       jsesc: 2.5.2
@@ -608,13 +608,13 @@ packages:
     resolution: {integrity: sha512-LvBTxu8bQSQkcyKOU+a1btnNFQ1dMAd0R6PyW3arXes06F6QLWLIrd681bxRPIXlrMGR3XYnW9JyML7dP3qgxg==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
 
   /@babel/helper-builder-binary-assignment-operator-visitor@7.22.15:
     resolution: {integrity: sha512-QkBXwGgaoC2GtGZRoma6kv7Szfv06khvhFav67ZExau2RaXzy8MpHSMO2PNoP2XtmQphJQRHFfg77Bq731Yizw==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
 
   /@babel/helper-compilation-targets@7.23.6:
     resolution: {integrity: sha512-9JB548GZoQVmzrFgp8o7KxdgkTGm6xs9DW0o/Pim72UDjzr5ObUQ6ZzYPqA+g9OTS2bBQoctLJrky0RDCAWRgQ==}
@@ -677,25 +677,25 @@ packages:
     engines: {node: '>=6.9.0'}
     dependencies:
       '@babel/template': 7.23.9
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
 
   /@babel/helper-hoist-variables@7.22.5:
     resolution: {integrity: sha512-wGjk9QZVzvknA6yKIUURb8zY3grXCcOZt+/7Wcy8O2uctxhplmUPkOdlgoNhmdVee2c92JXbf1xpMtVNbfoxRw==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
 
   /@babel/helper-member-expression-to-functions@7.23.0:
     resolution: {integrity: sha512-6gfrPwh7OuT6gZyJZvd6WbTfrqAo7vm4xCzAXOusKqq/vWdKXphTpj5klHKNmRUU6/QRGlBsyU9mAIPaWHlqJA==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
 
   /@babel/helper-module-imports@7.22.15:
     resolution: {integrity: sha512-0pYVBnDKZO2fnSPCrgM/6WMc7eS20Fbok+0r88fp+YtWVLZrp4CkafFGIp+W0VKw4a22sgebPT99y+FDNMdP4w==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
 
   /@babel/helper-module-transforms@7.23.3(@babel/core@7.23.9):
     resolution: {integrity: sha512-7bBs4ED9OmswdfDzpz4MpWgSrV7FXlc3zIagvLFjS5H+Mk7Snr21vQ6QwrsoCGMfNC4e4LQPdoULEt4ykz0SRQ==}
@@ -714,7 +714,7 @@ packages:
     resolution: {integrity: sha512-HBwaojN0xFRx4yIvpwGqxiV2tUfl7401jlok564NgB9EHS1y6QT17FmKWm4ztqjeVdXLuC4fSvHc5ePpQjoTbw==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
 
   /@babel/helper-plugin-utils@7.22.5:
     resolution: {integrity: sha512-uLls06UVKgFG9QD4OeFYLEGteMIAa5kpTPcFL28yuCIIzsf6ZyKZMllKVOCZFhiZ5ptnwX4mtKdWCBE/uT4amg==}
@@ -752,13 +752,13 @@ packages:
     resolution: {integrity: sha512-tK14r66JZKiC43p8Ki33yLBVJKlQDFoA8GYN67lWCDCqoL6EMMSuM9b+Iff2jHaM/RRFYl7K+iiru7hbRqNx8Q==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
 
   /@babel/helper-split-export-declaration@7.22.6:
     resolution: {integrity: sha512-AsUnxuLhRYsisFiaJwvp1QF+I3KjD5FOxut14q/GzovUe6orHLesW2C7d754kRm53h5gqrz6sFl6sxc4BVtE/g==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
 
   /@babel/helper-string-parser@7.23.4:
     resolution: {integrity: sha512-803gmbQdqwdf4olxrX4AJyFBV/RTr3rSmOj0rKwesmzlfhYNDEs+/iOcznzpNWlJlIlTJC2QfPFcHB6DlzdVLQ==}
@@ -778,7 +778,7 @@ packages:
     dependencies:
       '@babel/helper-function-name': 7.23.0
       '@babel/template': 7.23.9
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
 
   /@babel/helpers@7.23.9:
     resolution: {integrity: sha512-87ICKgU5t5SzOT7sBMfCOZQ2rHjRU+Pcb9BoILMYz600W6DkVRLFBPwQ18gwUVvggqXivaUakpnxWQGbpywbBQ==}
@@ -1447,7 +1447,7 @@ packages:
       '@babel/helper-module-imports': 7.22.15
       '@babel/helper-plugin-utils': 7.22.5
       '@babel/plugin-syntax-jsx': 7.23.3(@babel/core@7.23.9)
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
 
   /@babel/plugin-transform-react-pure-annotations@7.23.3(@babel/core@7.23.9):
     resolution: {integrity: sha512-qMFdSS+TUhB7Q/3HVPnEdYJDQIk57jkntAwSuz9xfSE4n+3I+vHYCli3HoHawN1Z3RfCz/y1zXA/JXjG6cVImQ==}
@@ -1688,7 +1688,7 @@ packages:
     dependencies:
       '@babel/core': 7.23.9
       '@babel/helper-plugin-utils': 7.22.5
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
       esutils: 2.0.3
 
   /@babel/preset-react@7.23.3(@babel/core@7.23.9):
@@ -1753,7 +1753,7 @@ packages:
       '@babel/helper-hoist-variables': 7.22.5
       '@babel/helper-split-export-declaration': 7.22.6
       '@babel/parser': 7.23.9
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
       debug: 4.3.4
       globals: 11.12.0
     transitivePeerDependencies:
@@ -1766,7 +1766,6 @@ packages:
       '@babel/helper-string-parser': 7.23.4
       '@babel/helper-validator-identifier': 7.22.20
       to-fast-properties: 2.0.0
-    dev: true
 
   /@babel/types@7.23.9:
     resolution: {integrity: sha512-dQjSq/7HaSjRM43FFGnv5keM2HsxpmyV1PfaSVm0nzzjwwTmjOe6J4bC8e3+pTEIgHaHj+1ZlLThRJ2auc/w1Q==}
@@ -2018,7 +2017,7 @@ packages:
     resolution: {integrity: sha512-SPiDHaWKQZpwR2siD0KQUwlStvIAnEyK6tAE2h2Wuoq8ue9skzhlyVQ1ddzOxX6khULnAALDiR/isSF3bnuciA==}
     dev: true
 
-  /@docsearch/react@3.5.2(@algolia/client-search@4.22.1)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0):
+  /@docsearch/react@3.5.2(@algolia/client-search@4.22.1)(@types/react@18.2.51)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0):
     resolution: {integrity: sha512-9Ahcrs5z2jq/DcAvYtvlqEBHImbm4YJI8M9y0x6Tqg598P40HTEkX7hsMcIuThI+hTFxRGZ9hll0Wygm2yEjng==}
     peerDependencies:
       '@types/react': '>= 16.8.0 < 19.0.0'
@@ -2038,7 +2037,7 @@ packages:
       '@algolia/autocomplete-core': 1.9.3(@algolia/client-search@4.22.1)(algoliasearch@4.22.1)(search-insights@2.13.0)
       '@algolia/autocomplete-preset-algolia': 1.9.3(@algolia/client-search@4.22.1)(algoliasearch@4.22.1)
       '@docsearch/css': 3.5.2
-      '@types/react': 18.2.48
+      '@types/react': 18.2.51
       algoliasearch: 4.22.1
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
@@ -2544,7 +2543,7 @@ packages:
       - webpack-cli
     dev: true
 
-  /@docusaurus/preset-classic@3.1.1(@algolia/client-search@4.22.1)(@types/react@18.2.48)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3):
+  /@docusaurus/preset-classic@3.1.1(@algolia/client-search@4.22.1)(@types/react@18.2.51)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3):
     resolution: {integrity: sha512-jG4ys/hWYf69iaN/xOmF+3kjs4Nnz1Ay3CjFLDtYa8KdxbmUhArA9HmP26ru5N0wbVWhY+6kmpYhTJpez5wTyg==}
     engines: {node: '>=18.0'}
     peerDependencies:
@@ -2560,9 +2559,9 @@ packages:
       '@docusaurus/plugin-google-gtag': 3.1.1(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
       '@docusaurus/plugin-google-tag-manager': 3.1.1(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
       '@docusaurus/plugin-sitemap': 3.1.1(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
-      '@docusaurus/theme-classic': 3.1.1(@types/react@18.2.48)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
+      '@docusaurus/theme-classic': 3.1.1(@types/react@18.2.51)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
       '@docusaurus/theme-common': 3.1.1(@docusaurus/types@3.1.1)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
-      '@docusaurus/theme-search-algolia': 3.1.1(@algolia/client-search@4.22.1)(@docusaurus/types@3.1.1)(@types/react@18.2.48)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3)
+      '@docusaurus/theme-search-algolia': 3.1.1(@algolia/client-search@4.22.1)(@docusaurus/types@3.1.1)(@types/react@18.2.51)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3)
       '@docusaurus/types': 3.1.1(react-dom@18.2.0)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
@@ -2610,7 +2609,7 @@ packages:
       - supports-color
     dev: false
 
-  /@docusaurus/theme-classic@3.1.1(@types/react@18.2.48)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3):
+  /@docusaurus/theme-classic@3.1.1(@types/react@18.2.51)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3):
     resolution: {integrity: sha512-GiPE/jbWM8Qv1A14lk6s9fhc0LhPEQ00eIczRO4QL2nAQJZXkjPG6zaVx+1cZxPFWbAsqSjKe2lqkwF3fGkQ7Q==}
     engines: {node: '>=18.0'}
     peerDependencies:
@@ -2629,7 +2628,7 @@ packages:
       '@docusaurus/utils': 3.1.1(@docusaurus/types@3.1.1)
       '@docusaurus/utils-common': 3.1.1(@docusaurus/types@3.1.1)
       '@docusaurus/utils-validation': 3.1.1(@docusaurus/types@3.1.1)
-      '@mdx-js/react': 3.0.0(@types/react@18.2.48)(react@18.2.0)
+      '@mdx-js/react': 3.0.0(@types/react@18.2.51)(react@18.2.0)
       clsx: 2.1.0
       copy-text-to-clipboard: 3.2.0
       infima: 0.2.0-alpha.43
@@ -2708,14 +2707,14 @@ packages:
       - webpack-cli
     dev: true
 
-  /@docusaurus/theme-search-algolia@3.1.1(@algolia/client-search@4.22.1)(@docusaurus/types@3.1.1)(@types/react@18.2.48)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3):
+  /@docusaurus/theme-search-algolia@3.1.1(@algolia/client-search@4.22.1)(@docusaurus/types@3.1.1)(@types/react@18.2.51)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)(typescript@5.3.3):
     resolution: {integrity: sha512-tBH9VY5EpRctVdaAhT+b1BY8y5dyHVZGFXyCHgTrvcXQy5CV4q7serEX7U3SveNT9zksmchPyct6i1sFDC4Z5g==}
     engines: {node: '>=18.0'}
     peerDependencies:
       react: ^18.0.0
       react-dom: ^18.0.0
     dependencies:
-      '@docsearch/react': 3.5.2(@algolia/client-search@4.22.1)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)
+      '@docsearch/react': 3.5.2(@algolia/client-search@4.22.1)(@types/react@18.2.51)(react-dom@18.2.0)(react@18.2.0)(search-insights@2.13.0)
       '@docusaurus/core': 3.1.1(@docusaurus/types@3.1.1)(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
       '@docusaurus/logger': 3.1.1
       '@docusaurus/plugin-content-docs': 3.1.1(eslint@8.56.0)(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
@@ -2931,11 +2930,11 @@ packages:
     engines: {node: '>=18'}
     dev: false
 
-  /@humanwhocodes/config-array@0.11.14:
-    resolution: {integrity: sha512-3T8LkOmg45BV5FICb15QQMsyUSWrQ8AygVfC7ZG32zOalnqrilm018ZVCw0eapXux8FtA33q8PSRSstjee3jSg==}
+  /@humanwhocodes/config-array@0.11.13:
+    resolution: {integrity: sha512-JSBDMiDKSzQVngfRjOdFXgFfklaXI4K9nLF49Auh21lmBWRLIK3+xTErTWD4KU54pb6coM6ESE7Awz/FNU3zgQ==}
     engines: {node: '>=10.10.0'}
     dependencies:
-      '@humanwhocodes/object-schema': 2.0.2
+      '@humanwhocodes/object-schema': 2.0.1
       debug: 4.3.4
       minimatch: 3.1.2
     transitivePeerDependencies:
@@ -2945,8 +2944,8 @@ packages:
     resolution: {integrity: sha512-bxveV4V8v5Yb4ncFTT3rPSgZBOpCkjfK0y4oVVVJwIuDVBRMDXrPyXRL988i5ap9m9bnyEEjWfm5WkBmtffLfA==}
     engines: {node: '>=12.22'}
 
-  /@humanwhocodes/object-schema@2.0.2:
-    resolution: {integrity: sha512-6EwiSjwWYP7pTckG6I5eyFANjPhmPjUX9JRLUSfNPC7FX7zK9gyZAfUEaECL6ALTpGX5AjnBq3C9XmVWPitNpw==}
+  /@humanwhocodes/object-schema@2.0.1:
+    resolution: {integrity: sha512-dvuCeX5fC9dXgJn9t+X5atfmgQAzUOWqS1254Gh0m6i8wKd10ebXkfNKiRK+1GWi/yTvvLDHpoxLr0xxxeslWw==}
 
   /@isaacs/cliui@8.0.2:
     resolution: {integrity: sha512-O8jcjabXaleOG9DQ0+ARXWZBTfnP4WNAqzuiJK7ll44AmxGKv/J2M4TPjxjY3znBCfvBXFzucm1twdyFybFqEA==}
@@ -3278,14 +3277,14 @@ packages:
     transitivePeerDependencies:
       - supports-color
 
-  /@mdx-js/react@3.0.0(@types/react@18.2.48)(react@18.2.0):
+  /@mdx-js/react@3.0.0(@types/react@18.2.51)(react@18.2.0):
     resolution: {integrity: sha512-nDctevR9KyYFyV+m+/+S4cpzCWHqj+iHDHq3QrsWezcC+B17uZdIWgCguESUkwFhM3n/56KxWVE3V6EokrmONQ==}
     peerDependencies:
       '@types/react': '>=16'
       react: '>=16'
     dependencies:
       '@types/mdx': 2.0.10
-      '@types/react': 18.2.48
+      '@types/react': 18.2.51
       react: 18.2.0
 
   /@mistralai/mistralai@0.0.10:
@@ -3774,8 +3773,8 @@ packages:
     resolution: {integrity: sha512-TV7t8GKYaJWsn00tFDqBw8+Uqmr8A0fRU1tvTQhyZzGv0sJCGRQL3JGMI3ucuKo3XIZdUP+Lx7/gh2t3lewy7g==}
     engines: {node: '>=14.16'}
 
-  /@sinonjs/commons@3.0.1:
-    resolution: {integrity: sha512-K3mCHKQ9sVh8o1C9cxkwxaOmXoAMlDxC1mYyHrjqOWEcBjYr76t96zL2zlj5dUGZ3HSw240X1qgH3Mjf1yJWpQ==}
+  /@sinonjs/commons@3.0.0:
+    resolution: {integrity: sha512-jXBtWAF4vmdNmZgD5FoKsVLv3rPgDnLgPbU84LIJ3otV44vJlDRokVng5v8NFJdCf/da9legHcKaRuZs4L7faA==}
     dependencies:
       type-detect: 4.0.8
     dev: true
@@ -3783,7 +3782,7 @@ packages:
   /@sinonjs/fake-timers@10.3.0:
     resolution: {integrity: sha512-V4BG07kuYSUkTCSBHG8G8TNhM+F19jXFWnQtzj+we8DrkpSBCee9Z3Ms8yiGer/dlmhe35/Xdgyo3/0rQKg7YA==}
     dependencies:
-      '@sinonjs/commons': 3.0.1
+      '@sinonjs/commons': 3.0.0
     dev: true
 
   /@slorber/remark-comment@1.0.0:
@@ -3927,7 +3926,7 @@ packages:
     resolution: {integrity: sha512-1hnUxxjd83EAxbL4a0JDJoD3Dao3hmjvyvyEV8PzWmLK3B9m9NPlW7GKjFyoWE8nM7HnXzPcmmSyOW8yOddSXw==}
     engines: {node: '>=10'}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
       entities: 4.5.0
 
   /@svgr/plugin-jsx@6.5.1(@svgr/core@6.5.1):
@@ -4151,7 +4150,7 @@ packages:
     resolution: {integrity: sha512-vxhUy4J8lyeyinH7Azl1pdd43GJhZH/tP2weN8TntQblOY+A0XbT8DJk1/oCPuOOyg/Ja757rG0CgHcWC8OfMA==}
     dev: true
 
-  /@turbo/gen@1.11.3(@types/node@20.11.7)(typescript@5.3.3):
+  /@turbo/gen@1.11.3(@types/node@20.11.16)(typescript@5.3.3):
     resolution: {integrity: sha512-cHGRj7Jn7Hw1cA7NuwWYfYdhEliQX4LuSfEB9L1m8ifGkHalU3bbYXcehzLThmckpGpUQGnXYx0UtVudbQ42HA==}
     hasBin: true
     dependencies:
@@ -4163,7 +4162,7 @@ packages:
       minimatch: 9.0.3
       node-plop: 0.26.3
       proxy-agent: 6.3.1
-      ts-node: 10.9.2(@types/node@20.11.7)(typescript@5.3.3)
+      ts-node: 10.9.2(@types/node@20.11.16)(typescript@5.3.3)
       update-check: 1.5.4
       validate-npm-package-name: 5.0.0
     transitivePeerDependencies:
@@ -4181,7 +4180,7 @@ packages:
       chalk: 2.4.2
       commander: 10.0.1
       execa: 5.1.1
-      fast-glob: 3.3.2
+      fast-glob: 3.3.1
       fs-extra: 10.1.0
       gradient-string: 2.0.2
       inquirer: 8.2.6
@@ -4207,7 +4206,7 @@ packages:
     resolution: {integrity: sha512-qoQprZvz5wQFJwMDqeseRXWv3rqMvhgpbXFfVyWhbx9X47POIA6i/+dXefEmZKoAgOaTdaIgNSMqMIU61yRyzA==}
     dependencies:
       '@babel/parser': 7.23.9
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
       '@types/babel__generator': 7.6.8
       '@types/babel__template': 7.4.4
       '@types/babel__traverse': 7.20.5
@@ -4216,20 +4215,20 @@ packages:
   /@types/babel__generator@7.6.8:
     resolution: {integrity: sha512-ASsj+tpEDsEiFr1arWrlN6V3mdfjRMZt6LtK/Vp/kreFLnr5QH5+DhvD5nINYZXzwJvXeGq+05iUXcAzVrqWtw==}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
     dev: true
 
   /@types/babel__template@7.4.4:
     resolution: {integrity: sha512-h/NUaSyG5EyxBIp8YRxo4RMe2/qQgvyowRwVMzhYhBCONbW8PUsg4lkFMrhgZhUe5z3L3MiLDuvyJ/CaPa2A8A==}
     dependencies:
       '@babel/parser': 7.23.9
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
     dev: true
 
   /@types/babel__traverse@7.20.5:
     resolution: {integrity: sha512-WXCyOcRtH37HAUkpXhUduaxdm82b4GSlyTqajXviN4EfiuPgNYR109xMCKvpl6zPIpua0DGlMEDCq+g8EdoheQ==}
     dependencies:
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
     dev: true
 
   /@types/body-parser@1.19.5:
@@ -4465,6 +4464,12 @@ packages:
     dependencies:
       undici-types: 5.26.5
 
+  /@types/node@20.11.16:
+    resolution: {integrity: sha512-gKb0enTmRCzXSSUJDq6/sPcqrfCv2mkkG6Jt/clpn5eiCbKTY+SgZUxo+p8ZKMof5dCp9vHQUAB7wOUTod22wQ==}
+    dependencies:
+      undici-types: 5.26.5
+    dev: true
+
   /@types/node@20.11.7:
     resolution: {integrity: sha512-GPmeN1C3XAyV5uybAf4cMLWT9fDWcmQhZVtMFu7OR32WjrqGG+Wnk2V1d0bmtUyE/Zy1QJ9BxyiTih9z8Oks8A==}
     dependencies:
@@ -4498,6 +4503,9 @@ packages:
     resolution: {integrity: sha512-AhtMcmETelF8wFDV1ucbChKhLgsc+ytXZXkNz/nnTAMSDeqsjALknEFxi7ZtLgS/G8bV2rp90LhDW5SGACimIQ==}
     dev: true
 
+  /@types/prop-types@15.7.11:
+    resolution: {integrity: sha512-ga8y9v9uyeiLdpKddhxYQkxNDrfvuPrlFb0N1qnZZByvcElJaXthF1UhvCh9TLWJBEHeNtdnbysW7Y6Uq8CVng==}
+
   /@types/prop-types@15.7.8:
     resolution: {integrity: sha512-kMpQpfZKSCBqltAJwskgePRaYRFukDkm1oItcAbC3gNELR20XIBcN9VRgg4+m8DKsTfkWeA4m4Imp4DDuWy7FQ==}
 
@@ -4545,6 +4553,13 @@ packages:
       '@types/scheduler': 0.16.4
       csstype: 3.1.2
 
+  /@types/react@18.2.51:
+    resolution: {integrity: sha512-XeoMaU4CzyjdRr3c4IQQtiH7Rpo18V07rYZUucEZQwOUEtGgTXv7e6igQiQ+xnV6MbMe1qjEmKdgMNnfppnXfg==}
+    dependencies:
+      '@types/prop-types': 15.7.11
+      '@types/scheduler': 0.16.8
+      csstype: 3.1.3
+
   /@types/resolve@1.20.2:
     resolution: {integrity: sha512-60BCwRFOZCQhDncwQdxxeOEEkbc5dIMccYLwbxsS4TUNeVECQ/pBJ0j09mrHOl/JJvpRPGwO9SvE4nR2Nb/a4Q==}
     dev: true
@@ -4571,6 +4586,9 @@ packages:
   /@types/scheduler@0.16.4:
     resolution: {integrity: sha512-2L9ifAGl7wmXwP4v3pN4p2FLhD0O1qsJpvKmNin5VA8+UvNVb447UDaAEV6UdrkA+m/Xs58U1RFps44x6TFsVQ==}
 
+  /@types/scheduler@0.16.8:
+    resolution: {integrity: sha512-WZLiwShhwLRmeV6zH+GkbOFT6Z6VklCItrDioxUnv+u4Ll+8vKeFySoFyK/0ctcRpOmwAicELfmys1sDc/Rw+A==}
+
   /@types/semver@7.5.6:
     resolution: {integrity: sha512-dn1l8LaMea/IjDoHNd9J52uBbInB796CDffS6VdIxvqYCPSG0V0DzHp76GpaWnlhg88uYyPbXCDIowa86ybd5A==}
     dev: true
@@ -4795,8 +4813,8 @@ packages:
   /@ungap/structured-clone@1.2.0:
     resolution: {integrity: sha512-zuVdFrMJiuCDQUMCzQaD6KL28MjnqqN8XnAqiEq9PNm/hCPTSGfrXCOfwj1ow4LFb/tNymJPwsNbVePc1xFqrQ==}
 
-  /@vercel/ncc@0.34.0:
-    resolution: {integrity: sha512-G9h5ZLBJ/V57Ou9vz5hI8pda/YQX5HQszCs3AmIus3XzsmRn/0Ptic5otD3xVST8QLKk7AMk7AqpsyQGN7MZ9A==}
+  /@vercel/ncc@0.38.1:
+    resolution: {integrity: sha512-IBBb+iI2NLu4VQn3Vwldyi2QwaXt5+hTyh58ggAMoCGE6DJmPvwL3KPBWcJl1m9LYPChBLE980Jw+CS4Wokqxw==}
     hasBin: true
     dev: true
 
@@ -5421,7 +5439,7 @@ packages:
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
     dependencies:
       '@babel/template': 7.23.9
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
       '@types/babel__core': 7.20.5
       '@types/babel__traverse': 7.20.5
     dev: true
@@ -6052,7 +6070,7 @@ packages:
     engines: {node: '>=18'}
     dependencies:
       slice-ansi: 5.0.0
-      string-width: 7.1.0
+      string-width: 7.0.0
     dev: true
 
   /cli-width@3.0.0:
@@ -6112,7 +6130,7 @@ packages:
     resolution: {integrity: sha512-jsayHP4Z1gKjXB+NsFhEKrM2dAN4XCpbHbhwzzYfFrVL/DYPw9D/ACob6EjbIiV47PSe3OcxJqX/b1V/T7XK3A==}
     engines: {node: '>=14.18.0'}
     dependencies:
-      rfdc: 1.3.1
+      rfdc: 1.3.0
     dev: false
 
   /collapse-white-space@2.1.0:
@@ -6198,10 +6216,10 @@ packages:
 
   /commander@2.20.0:
     resolution: {integrity: sha512-7j2y+40w61zy6YC2iRNpUe/NwhNyoXrYpHMrSunaMG64nRnaf96zO/KMQR4OyN/UnE5KLyEBnKHd4aG3rskjpQ==}
-    dev: true
 
   /commander@2.20.3:
     resolution: {integrity: sha512-GpVkmM8vF2vQUkj2LvZmD35JxeJOLCwJ9cUkugyk2nuhbv3+mJvpLYYt+0+USMxE+oj+ey/lJEnhZw75x/OMcQ==}
+    dev: true
 
   /commander@5.1.0:
     resolution: {integrity: sha512-P0CysNDQ7rtVw4QIQtm+MRxV66vKFSvlsQvGYXZWR3qFU0jlMKHZZZgw8e+8DSah4UDKMqnknRDQz+xuQXQ/Zg==}
@@ -6390,7 +6408,7 @@ packages:
       path-type: 4.0.0
       typescript: 5.3.3
 
-  /create-jest@29.7.0(@types/node@20.11.7):
+  /create-jest@29.7.0(@types/node@20.11.16):
     resolution: {integrity: sha512-Adz2bdH0Vq3F53KEMJOoftQFutWCukm6J24wbPWRO4k1kMY7gS7ds/uoJkNuV8wDCtWWnuwGcJwpWcih+zEW1Q==}
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
     hasBin: true
@@ -6399,7 +6417,7 @@ packages:
       chalk: 4.1.2
       exit: 0.1.2
       graceful-fs: 4.2.11
-      jest-config: 29.7.0(@types/node@20.11.7)
+      jest-config: 29.7.0(@types/node@20.11.16)
       jest-util: 29.7.0
       prompts: 2.4.2
     transitivePeerDependencies:
@@ -6619,6 +6637,9 @@ packages:
   /csstype@3.1.2:
     resolution: {integrity: sha512-I7K1Uu0MBPzaFKg4nI5Q7Vs2t+3gWWW648spaF+Rg7pI9ds18Ugn+lvg4SHczUdKlHI5LWBXyqfS8+DufyBsgQ==}
 
+  /csstype@3.1.3:
+    resolution: {integrity: sha512-M1uQkMl8rQK/szD0LNhtqxIPLpimGm8sOBwU7lLnCpSbTyY3yeU1Vc7l4KT5zT4s/yOxHH5O7tIuuLOCnLADRw==}
+
   /csv-generate@3.4.3:
     resolution: {integrity: sha512-w/T+rqR0vwvHqWs/1ZyMDWtHHSJaN06klRqJXBEpDJaM/+dZkso0OKh1VcuuYvK3XM53KysVNq8Ko/epCK8wOw==}
     dev: true
@@ -7377,8 +7398,8 @@ packages:
       object-keys: 1.1.1
       object.assign: 4.1.5
       regexp.prototype.flags: 1.5.1
-      safe-array-concat: 1.1.0
-      safe-regex-test: 1.0.2
+      safe-array-concat: 1.0.1
+      safe-regex-test: 1.0.0
       string.prototype.trim: 1.2.8
       string.prototype.trimend: 1.0.7
       string.prototype.trimstart: 1.0.7
@@ -7405,7 +7426,7 @@ packages:
       has-symbols: 1.0.3
       internal-slot: 1.0.6
       iterator.prototype: 1.1.2
-      safe-array-concat: 1.1.0
+      safe-array-concat: 1.0.1
     dev: false
 
   /es-module-lexer@1.4.1:
@@ -7751,7 +7772,7 @@ packages:
       '@eslint-community/regexpp': 4.10.0
       '@eslint/eslintrc': 2.1.4
       '@eslint/js': 8.56.0
-      '@humanwhocodes/config-array': 0.11.14
+      '@humanwhocodes/config-array': 0.11.13
       '@humanwhocodes/module-importer': 1.0.1
       '@nodelib/fs.walk': 1.2.8
       '@ungap/structured-clone': 1.2.0
@@ -8659,7 +8680,7 @@ packages:
       '@types/glob': 7.2.0
       array-union: 2.1.0
       dir-glob: 3.0.1
-      fast-glob: 3.3.2
+      fast-glob: 3.3.1
       glob: 7.2.3
       ignore: 5.3.0
       merge2: 1.4.1
@@ -9870,7 +9891,7 @@ packages:
       - supports-color
     dev: true
 
-  /jest-cli@29.7.0(@types/node@20.11.7):
+  /jest-cli@29.7.0(@types/node@20.11.16):
     resolution: {integrity: sha512-OVVobw2IubN/GSYsxETi+gOe7Ka59EFMR/twOU3Jb2GnKKeMGJB5SGUUrEz3SFVmJASUdZUzy83sLNNQ2gZslg==}
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
     hasBin: true
@@ -9884,10 +9905,10 @@ packages:
       '@jest/test-result': 29.7.0
       '@jest/types': 29.6.3
       chalk: 4.1.2
-      create-jest: 29.7.0(@types/node@20.11.7)
+      create-jest: 29.7.0(@types/node@20.11.16)
       exit: 0.1.2
       import-local: 3.1.0
-      jest-config: 29.7.0(@types/node@20.11.7)
+      jest-config: 29.7.0(@types/node@20.11.16)
       jest-util: 29.7.0
       jest-validate: 29.7.0
       yargs: 17.7.2
@@ -9898,6 +9919,46 @@ packages:
       - ts-node
     dev: true
 
+  /jest-config@29.7.0(@types/node@20.11.16):
+    resolution: {integrity: sha512-uXbpfeQ7R6TZBqI3/TxCU4q4ttk3u0PJeC+E0zbfSoSjq6bJ7buBPxzQPL0ifrkY4DNu4JUdk0ImlBUYi840eQ==}
+    engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
+    peerDependencies:
+      '@types/node': '*'
+      ts-node: '>=9.0.0'
+    peerDependenciesMeta:
+      '@types/node':
+        optional: true
+      ts-node:
+        optional: true
+    dependencies:
+      '@babel/core': 7.23.9
+      '@jest/test-sequencer': 29.7.0
+      '@jest/types': 29.6.3
+      '@types/node': 20.11.16
+      babel-jest: 29.7.0(@babel/core@7.23.9)
+      chalk: 4.1.2
+      ci-info: 3.9.0
+      deepmerge: 4.3.1
+      glob: 7.2.3
+      graceful-fs: 4.2.11
+      jest-circus: 29.7.0
+      jest-environment-node: 29.7.0
+      jest-get-type: 29.6.3
+      jest-regex-util: 29.6.3
+      jest-resolve: 29.7.0
+      jest-runner: 29.7.0
+      jest-util: 29.7.0
+      jest-validate: 29.7.0
+      micromatch: 4.0.5
+      parse-json: 5.2.0
+      pretty-format: 29.7.0
+      slash: 3.0.0
+      strip-json-comments: 3.1.1
+    transitivePeerDependencies:
+      - babel-plugin-macros
+      - supports-color
+    dev: true
+
   /jest-config@29.7.0(@types/node@20.11.7):
     resolution: {integrity: sha512-uXbpfeQ7R6TZBqI3/TxCU4q4ttk3u0PJeC+E0zbfSoSjq6bJ7buBPxzQPL0ifrkY4DNu4JUdk0ImlBUYi840eQ==}
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
@@ -10153,7 +10214,7 @@ packages:
       '@babel/generator': 7.23.6
       '@babel/plugin-syntax-jsx': 7.23.3(@babel/core@7.23.9)
       '@babel/plugin-syntax-typescript': 7.23.3(@babel/core@7.23.9)
-      '@babel/types': 7.23.9
+      '@babel/types': 7.23.6
       '@jest/expect-utils': 29.7.0
       '@jest/transform': 29.7.0
       '@jest/types': 29.6.3
@@ -10227,7 +10288,7 @@ packages:
       merge-stream: 2.0.0
       supports-color: 8.1.1
 
-  /jest@29.7.0(@types/node@20.11.7):
+  /jest@29.7.0(@types/node@20.11.16):
     resolution: {integrity: sha512-NIy3oAFp9shda19hy4HK0HRTWKtPJmGdnvywu01nOqNC2vZg+Z+fvJDxpMQA88eb2I9EcafcdjYgsDthnYTvGw==}
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
     hasBin: true
@@ -10240,7 +10301,7 @@ packages:
       '@jest/core': 29.7.0
       '@jest/types': 29.6.3
       import-local: 3.1.0
-      jest-cli: 29.7.0(@types/node@20.11.7)
+      jest-cli: 29.7.0(@types/node@20.11.16)
     transitivePeerDependencies:
       - '@types/node'
       - babel-plugin-macros
@@ -10473,7 +10534,7 @@ packages:
       colorette: 2.0.20
       eventemitter3: 5.0.1
       log-update: 6.0.0
-      rfdc: 1.3.1
+      rfdc: 1.3.0
       wrap-ansi: 9.0.0
     dev: true
 
@@ -11554,7 +11615,7 @@ packages:
     engines: {node: '>=10.13.0'}
     hasBin: true
     dependencies:
-      commander: 2.20.3
+      commander: 2.20.0
       debug: 4.3.4
       glob: 7.2.3
       requirejs: 2.3.6
@@ -13387,7 +13448,7 @@ packages:
       iconv-lite: 0.4.24
       unpipe: 1.0.0
 
-  /raw-loader@4.0.2(webpack@5.90.0):
+  /raw-loader@4.0.2(webpack@5.90.1):
     resolution: {integrity: sha512-ZnScIV3ag9A4wPX/ZayxL/jZH+euYb6FcUinPcgiQW0+UBtEv0O6Q3lGd3cqJ+GHH+rksEv3Pj99oxJ3u3VIKA==}
     engines: {node: '>= 10.13.0'}
     peerDependencies:
@@ -13395,7 +13456,7 @@ packages:
     dependencies:
       loader-utils: 2.0.4
       schema-utils: 3.3.0
-      webpack: 5.90.0
+      webpack: 5.90.1
     dev: false
 
   /rc@1.2.8:
@@ -13988,8 +14049,8 @@ packages:
     resolution: {integrity: sha512-U9nH88a3fc/ekCF1l0/UP1IosiuIjyTh7hBvXVMHYgVcfGvt897Xguj2UOLDeI5BG2m7/uwyaLVT6fbtCwTyzw==}
     engines: {iojs: '>=1.0.0', node: '>=0.10.0'}
 
-  /rfdc@1.3.1:
-    resolution: {integrity: sha512-r5a3l5HzYlIC68TpmYKlxWjmOP6wiPJ1vWv2HeLhNsRZMrCkxeqxiHlQ21oXmQ4F3SiryXBHhAD7JZqvOJjFmg==}
+  /rfdc@1.3.0:
+    resolution: {integrity: sha512-V2hovdzFbOi77/WajaSMXk2OLm+xNIeQdMMuB7icj7bk6zi2F8GGAxigcnDFpJHbNyNcgyJDiP+8nOrY5cZGrA==}
 
   /rimraf@3.0.2:
     resolution: {integrity: sha512-JZkJMZkAGFFPP2YqXZXPbMlMBgsxzE8ILs4lMIX/2o0L9UBw9O/Y3o6wFw/i9YLapcUJWwqbi3kdxIPdC62TIA==}
@@ -14103,8 +14164,8 @@ packages:
       tslib: 2.6.2
     dev: true
 
-  /safe-array-concat@1.1.0:
-    resolution: {integrity: sha512-ZdQ0Jeb9Ofti4hbt5lX3T2JcAamT9hfzYU1MNB+z/jaEbB6wfFfPIR/zEORmZqobkCCJhSjodobH6WHNmJ97dg==}
+  /safe-array-concat@1.0.1:
+    resolution: {integrity: sha512-6XbUAseYE2KtOuGueyeobCySj9L4+66Tn6KQMOPQJrAJEowYKW/YR/MGJZl7FdydUdaFu4LYyDZjxf4/Nmo23Q==}
     engines: {node: '>=0.4'}
     dependencies:
       call-bind: 1.0.5
@@ -14120,15 +14181,6 @@ packages:
 
   /safe-regex-test@1.0.0:
     resolution: {integrity: sha512-JBUUzyOgEwXQY1NuPtvcj/qcBDbDmEvWufhlnXZIm75DEHp+afM1r1ujJpJsV/gSM4t59tpDyPi1sd6ZaPFfsA==}
-    dependencies:
-      call-bind: 1.0.2
-      get-intrinsic: 1.2.0
-      is-regex: 1.1.4
-    dev: false
-
-  /safe-regex-test@1.0.2:
-    resolution: {integrity: sha512-83S9w6eFq12BBIJYvjMux6/dkirb8+4zJRA9cxNBVb7Wq5fJBW+Xze48WqR8pxua7bDuAaaAxtVVd4Idjp1dBQ==}
-    engines: {node: '>= 0.4'}
     dependencies:
       call-bind: 1.0.5
       get-intrinsic: 1.2.2
@@ -14147,7 +14199,7 @@ packages:
     engines: {node: '>=6.0.0'}
     hasBin: true
     dependencies:
-      commander: 2.20.3
+      commander: 2.20.0
     dev: true
 
   /sax@1.3.0:
@@ -14599,14 +14651,14 @@ packages:
       spdx-license-ids: 3.0.16
     dev: true
 
-  /spdx-exceptions@2.4.0:
-    resolution: {integrity: sha512-hcjppoJ68fhxA/cjbN4T8N6uCUejN8yFw69ttpqtBeCbF3u13n7mb31NB9jKwGTTWWnt9IbRA/mf1FprYS8wfw==}
+  /spdx-exceptions@2.3.0:
+    resolution: {integrity: sha512-/tTrYOC7PPI1nUAgx34hUpqXuyJG+DTHJTnIULG4rDygi4xu/tfgmq1e1cIRwRzwZgo4NLySi+ricLkZkw4i5A==}
     dev: true
 
   /spdx-expression-parse@3.0.1:
     resolution: {integrity: sha512-cbqHunsQWnJNE6KhVSMsMeH5H/L9EpymbzqTQ3uLwNCLZ1Q481oWaofqH7nO6V07xlXwY6PhQdQ2IedWx/ZK4Q==}
     dependencies:
-      spdx-exceptions: 2.4.0
+      spdx-exceptions: 2.3.0
       spdx-license-ids: 3.0.16
     dev: true
 
@@ -14694,8 +14746,8 @@ packages:
     engines: {node: '>=10.0.0'}
     dev: true
 
-  /streamx@2.15.6:
-    resolution: {integrity: sha512-q+vQL4AAz+FdfT137VF69Cc/APqUbxy+MDOImRrMvchJpigHj9GksgDU2LYbO9rx7RX6osWgxJB2WxhYv4SZAw==}
+  /streamx@2.15.5:
+    resolution: {integrity: sha512-9thPGMkKC2GctCzyCUjME3yR03x2xNo0GPKGkRw2UMYN+gqWa9uqpyNWhmsNCutU5zHmkUum0LsCRQTXUgUCAg==}
     dependencies:
       fast-fifo: 1.3.2
       queue-tick: 1.0.1
@@ -14716,7 +14768,7 @@ packages:
     engines: {node: '>=14.18.0'}
     dependencies:
       codsen-utils: 1.6.3
-      rfdc: 1.3.1
+      rfdc: 1.3.0
     dev: false
 
   /string-length@4.0.2:
@@ -14761,8 +14813,8 @@ packages:
       emoji-regex: 9.2.2
       strip-ansi: 7.1.0
 
-  /string-width@7.1.0:
-    resolution: {integrity: sha512-SEIJCWiX7Kg4c129n48aDRwLbFb2LJmXXFrWBG4NGaRtMQ3myKPKbwrD1BKqQn74oCoNMBVrfDEr5M9YxCsrkw==}
+  /string-width@7.0.0:
+    resolution: {integrity: sha512-GPQHj7row82Hjo9hKZieKcHIhaAIKOJvFSIZXuCU9OASVZrMNUaZuz++SPVrBjnLsnk4k+z9f2EIypgxf2vNFw==}
     engines: {node: '>=18'}
     dependencies:
       emoji-regex: 10.3.0
@@ -14968,7 +15020,7 @@ packages:
     engines: {node: '>=6.0.0'}
     hasBin: true
     dependencies:
-      commander: 2.20.3
+      commander: 2.20.0
       debug: 4.3.4
     transitivePeerDependencies:
       - supports-color
@@ -15068,7 +15120,7 @@ packages:
     dependencies:
       b4a: 1.6.4
       fast-fifo: 1.3.2
-      streamx: 2.15.6
+      streamx: 2.15.5
     dev: false
 
   /tar@6.1.15:
@@ -15119,6 +15171,30 @@ packages:
       terser: 5.27.0
       webpack: 5.90.0
 
+  /terser-webpack-plugin@5.3.10(webpack@5.90.1):
+    resolution: {integrity: sha512-BKFPWlPDndPs+NGGCr1U59t0XScL5317Y0UReNrHaw9/FwhPENlq6bfgs+4yPfyP51vqC1bQ4rp1EfXW5ZSH9w==}
+    engines: {node: '>= 10.13.0'}
+    peerDependencies:
+      '@swc/core': '*'
+      esbuild: '*'
+      uglify-js: '*'
+      webpack: ^5.1.0
+    peerDependenciesMeta:
+      '@swc/core':
+        optional: true
+      esbuild:
+        optional: true
+      uglify-js:
+        optional: true
+    dependencies:
+      '@jridgewell/trace-mapping': 0.3.22
+      jest-worker: 27.5.1
+      schema-utils: 3.3.0
+      serialize-javascript: 6.0.2
+      terser: 5.27.0
+      webpack: 5.90.1
+    dev: false
+
   /terser@5.27.0:
     resolution: {integrity: sha512-bi1HRwVRskAjheeYl291n3JC4GgO/Ty4z1nVs5AAsmonJulGxpSektecnNedrwK9C7vpvVtcX3cw00VSLt7U2A==}
     engines: {node: '>=10'}
@@ -15126,7 +15202,7 @@ packages:
     dependencies:
       '@jridgewell/source-map': 0.3.5
       acorn: 8.11.3
-      commander: 2.20.3
+      commander: 2.20.0
       source-map-support: 0.5.21
 
   /test-exclude@6.0.0:
@@ -15296,7 +15372,7 @@ packages:
       '@babel/core': 7.23.9
       bs-logger: 0.2.6
       fast-json-stable-stringify: 2.1.0
-      jest: 29.7.0(@types/node@20.11.7)
+      jest: 29.7.0(@types/node@20.11.16)
       jest-util: 29.7.0
       json5: 2.2.3
       lodash.memoize: 4.1.2
@@ -15337,7 +15413,7 @@ packages:
       yn: 3.1.1
     dev: true
 
-  /ts-node@10.9.2(@types/node@20.11.7)(typescript@5.3.3):
+  /ts-node@10.9.2(@types/node@20.11.16)(typescript@5.3.3):
     resolution: {integrity: sha512-f0FFpIdcHgn8zcPSbf1dRevwt047YMnaiJM3u2w2RewrB+fob/zePZcrOyQoLMMO7aBIddLcQIEK5dYjkLnGrQ==}
     hasBin: true
     peerDependencies:
@@ -15356,7 +15432,7 @@ packages:
       '@tsconfig/node12': 1.0.11
       '@tsconfig/node14': 1.0.3
       '@tsconfig/node16': 1.0.4
-      '@types/node': 20.11.7
+      '@types/node': 20.11.16
       acorn: 8.11.3
       acorn-walk: 8.3.2
       arg: 4.1.3
@@ -15643,7 +15719,7 @@ packages:
   /unbox-primitive@1.0.2:
     resolution: {integrity: sha512-61pPlCD9h51VoreyJ0BReideM3MDKMKnh6+V9L08331ipq6Q8OFXZYiqP6n/tbHx4s5I9uRhcye6BrbkizkBDw==}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.2
       has-bigints: 1.0.2
       has-symbols: 1.0.3
       which-boxed-primitive: 1.0.2
@@ -16113,6 +16189,46 @@ packages:
       - esbuild
       - uglify-js
 
+  /webpack@5.90.1:
+    resolution: {integrity: sha512-SstPdlAC5IvgFnhiRok8hqJo/+ArAbNv7rhU4fnWGHNVfN59HSQFaxZDSAL3IFG2YmqxuRs+IU33milSxbPlog==}
+    engines: {node: '>=10.13.0'}
+    hasBin: true
+    peerDependencies:
+      webpack-cli: '*'
+    peerDependenciesMeta:
+      webpack-cli:
+        optional: true
+    dependencies:
+      '@types/eslint-scope': 3.7.7
+      '@types/estree': 1.0.5
+      '@webassemblyjs/ast': 1.11.6
+      '@webassemblyjs/wasm-edit': 1.11.6
+      '@webassemblyjs/wasm-parser': 1.11.6
+      acorn: 8.11.3
+      acorn-import-assertions: 1.9.0(acorn@8.11.3)
+      browserslist: 4.22.3
+      chrome-trace-event: 1.0.3
+      enhanced-resolve: 5.15.0
+      es-module-lexer: 1.4.1
+      eslint-scope: 5.1.1
+      events: 3.3.0
+      glob-to-regexp: 0.4.1
+      graceful-fs: 4.2.11
+      json-parse-even-better-errors: 2.3.1
+      loader-runner: 4.3.0
+      mime-types: 2.1.35
+      neo-async: 2.6.2
+      schema-utils: 3.3.0
+      tapable: 2.2.1
+      terser-webpack-plugin: 5.3.10(webpack@5.90.1)
+      watchpack: 2.4.0
+      webpack-sources: 3.2.3
+    transitivePeerDependencies:
+      - '@swc/core'
+      - esbuild
+      - uglify-js
+    dev: false
+
   /webpackbar@5.0.2(webpack@5.90.0):
     resolution: {integrity: sha512-BmFJo7veBDgQzfWXl/wwYXr/VFus0614qZ8i9znqcl9fnEdiVkdbi0TedLQ6xAK92HZHDJ0QmyQ0fmuZPAgCYQ==}
     engines: {node: '>=12'}
@@ -16311,7 +16427,7 @@ packages:
     engines: {node: '>=18'}
     dependencies:
       ansi-styles: 6.2.1
-      string-width: 7.1.0
+      string-width: 7.0.0
       strip-ansi: 7.1.0
     dev: true