From e3a14a85833c4658137fe21b64e5848b4e837c5c Mon Sep 17 00:00:00 2001 From: Markus Date: Fri, 20 Dec 2024 22:26:26 -0800 Subject: [PATCH 01/13] Update README.md deploy links --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index a49d24c8..5486a2ee 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # Multi-Agent -Custom Automation Engine Solution Accelerator -MENU: [**USER STORY**](#user-story) \| [**SIMPLE DEPLOY**](#simple-deploy) \| [**SUPPORTING DOCUMENTATION**](#supporting-documentation) \| +MENU: [**USER STORY**](#user-story) \| [**SIMPLE DEPLOY**](#quick-deploy) \| [**SUPPORTING DOCUMENTATION**](#supporting-documentation) \|


@@ -71,7 +71,7 @@ This guide provides step-by-step instructions for deploying your application usi There are several ways to deploy the solution. You can deploy to run in Azure in one click, or manually, or you can deploy locally. -## One Click Azure Deployment +## Quick Deploy

From 36e8be3b4386294b79e25e225a558ed029829afc Mon Sep 17 00:00:00 2001 From: Markus Date: Sun, 16 Feb 2025 14:20:42 -0800 Subject: [PATCH 02/13] Update of customize solution doc and images --- documentation/CustomizeSolution.md | 466 ++++++------------ .../images/customize_solution/logic_flow.svg | 4 + .../images/customize_solution/redoc_ui.png | Bin 0 -> 142299 bytes 3 files changed, 154 insertions(+), 316 deletions(-) create mode 100644 documentation/images/customize_solution/logic_flow.svg create mode 100644 documentation/images/customize_solution/redoc_ui.png diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index a867892c..7f681b59 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -1,4 +1,4 @@ -# Accelerating your own Multi-Agent -Custom Automation Engine MVP +# Accelerating your own Multi-Agent - Custom Automation Engine MVP As the name suggests, this project is designed to accelerate development of Multi-Agent solutions in your environment. The example solution presented shows how such a solution would be implemented and provides example agent definitions along with stubs for possible tools those agents could use to accomplish tasks. You will want to implement real functions in your own environment, to be used by agents customized around your own use cases. Users can choose the LLM that is optimized for responsible use. The default LLM is GPT-4o which inherits the existing responsible AI mechanisms and filters from the LLM provider. We encourage developers to review [OpenAI’s Usage policies](https://openai.com/policies/usage-policies/) and [Azure OpenAI’s Code of Conduct](https://learn.microsoft.com/en-us/legal/cognitive-services/openai/code-of-conduct) when using GPT-4o. This document is designed to provide the in-depth technical information to allow you to add these customizations. Once the agents and tools have been developed, you will likely want to implement your own real world front end solution to replace the example in this accelerator. @@ -8,7 +8,7 @@ This application is an AI-driven orchestration system that manages a group of AI - Receive input tasks from users. - Generate a detailed plan to accomplish the task using a Planner agent. -- Execute the plan by delegating steps to specialized agents (e.g., HR, Legal, Marketing). +- Execute the plan by delegating steps to specialized agents (e.g., HR, Procurement, Marketing). - Incorporate human feedback into the workflow. - Maintain state across sessions with persistent storage. @@ -17,319 +17,151 @@ This code has not been tested as an end-to-end, reliable production application- Below, we'll dive into the details of each component, focusing on the endpoints, data types, and the flow of information through the system. # Table of Contents -- [Accelerating your own Multi-Agent - Custom Automation Engine MVP](#accelerating-your-own-multi-agent---custom-automation-engine-mvp) - - [Technical Overview](#technical-overview) - [Table of Contents](#table-of-contents) - - [Endpoints](#endpoints) - - [/input\_task](#input_task) - - [/human\_feedback](#human_feedback) - - [/get\_latest\_plan\_by\_session/{session\_id}](#get_latest_plan_by_session-session_id) - - [/steps/{plan\_id}](#stepsplan_id) - - [/agent\_messages/{session\_id}](#agent_messagessession_id) - - [/messages](#messages) - - [/delete\_all\_messages](#delete_all_messages) - - [/api/agent-tools](#apiagent-tools) - - [Data Types and Models](#data-types-and-models) - - [Messages](#messages) - - [BaseDataModel](#basedatamodel) - - [AgentMessage](#agentmessage) - - [Session](#session) - - [Plan](#plan) - - [Step](#step) - - [PlanWithSteps](#planwithsteps) - - [InputTask](#inputtask) - - [ApprovalRequest](#approvalrequest) - - [HumanFeedback](#humanfeedback) - - [HumanClarification](#humanclarification) - - [ActionRequest](#actionrequest) - - [ActionResponse](#actionresponse) - - [PlanStateUpdate](#planstateupdate) - - [GroupChatMessage](#groupchatmessage) - - [RequestToSpeak](#requesttospeak) - - [Enums](#enums) - - [DataType](#datatype) - - [BAgentType](#bagenttype) - - [StepStatus](#stepstatus) - - [PlanStatus](#planstatus) - - [HumanFeedbackStatus](#humanfeedbackstatus) - - [Application Flow](#application-flow) - - [Initialization](#initialization) - - [Agents Overview](#agents-overview) - - [GroupChatManager](#groupchatmanager) - - [PlannerAgent](#planneragent) - - [HumanAgent](#humanagent) - - [Specialized Agents](#specialized-agents) - - [Persistent Storage with Cosmos DB](#persistent-storage-with-cosmos-db) - - [Utilities](#utilities) - - [`initialize_runtime_and_context` Function](#initialize_runtime_and_context-function) - - [Summary](#summary) - - -## Endpoints - -### /input_task - -**Method:** POST -**Description:** Receives the initial input task from the user. - -**Request Headers:** - -- `user_principal_id`: User ID (`user_id`) extracted from the authentication header. - -**Request Body:** `InputTask` -- `session_id`: Optional string. If not provided, a new UUID will be generated. -- `description`: The description of the task the user wants to accomplish. - - -**Response:** -- `status`: Confirmation message. -- `session_id`: The session ID associated with the task. -- `plan_id`: The ID of the plan generated. -- `description`: The task description. - - -**Flow:** -1. Validates header and extracts `user_principal_id` as `user_id`. -2. Generates a `session_id` if not provided. -3. Initializes agents and context for the session. -4. Sends the `InputTask` message to the `GroupChatManager`. -5. Returns the `status`, `session_id`, `plan_id`, `description`, and `user_id`. - - -### /human_feedback - -**Method:** POST -**Description:** Receives human feedback on a step (e.g., approval, rejection, or modification). - -**Request Headers:** -- `user_principal_id`: User ID (`user_id`) extracted from the authentication header. - -**Request Body:** `HumanFeedback` -- `step_id`: The ID of the step to provide feedback for. -- `plan_id`: The ID of the plan. -- `session_id`: The session ID. -- `approved`: Boolean indicating if the step is approved. -- `human_feedback`: Optional string containing any comments. -- `updated_action`: Optional string if the action was modified. - -**Response:** -- `status`: Confirmation message. -- `session_id`: The session ID. -- `step_id`: The step ID associated with the feedback. - -**Flow:** -1. Validates header and extracts `user_principal_id` as `user_id`. -2. Initializes runtime and context for the session. -3. Sends the `HumanFeedback` message to the `HumanAgent`. -4. Returns the `status`, `session_id`, and `step_id`. - - -### /human_clarification_on_plan - -**Method:** POST -**Description:** Receives human clarification on a plan. - -**Request Headers:** -- `user_principal_id`: User ID (`user_id`) extracted from the authentication header. - -**Request Body:** `HumanClarification` -- `plan_id`: The ID of the plan requiring clarification. -- `session_id`: The session ID associated with the plan. -- `human_clarification`: Clarification details provided by the user. - -**Response:** -- `status`: Confirmation message. -- `session_id`: The session ID associated with the plan. - -**Flow:** -1. Validates header and extracts `user_principal_id` as `user_id`. -2. Initializes runtime and context for the session. -3. Sends the `HumanClarification` message to the `PlannerAgent`. -4. Returns the `status` and `session_id`. - -### /approve_step_or_steps - -**Method:** POST -**Description:** Approves a step or multiple steps in a plan. - -**Request Headers:** - -- `user_principal_id`: User ID (`user_id`) extracted from the authentication header. - -**Request Body:** `HumanFeedback` -- `step_id`: Optional step ID to approve. If not provided, all steps are approved. -- `plan_id`: The ID of the plan. -- `session_id`: The session ID associated with the plan. -- `approved`: Boolean indicating whether the step(s) are approved. -- `human_feedback`: Optional string containing any comments. -- `updated_action`: Optional string if the action was modified. - -**Response:** -- `status`: A confirmation message indicating the approval result. - -**Flow:** -1. Validates header and extracts `user_principal_id` as `user_id`. -2. Initializes runtime and context for the session. -3. Sends the `HumanFeedback` approval message to the `GroupChatManager`. -4. If `step_id` is provided, approves the specific step; otherwise, approves all steps. -5. Returns the `status` message indicating the result of the approval. - -### /plans - -**Method:** GET -**Description:** Retrieves all plans for the current user or the plan for a specific session. - -**Request Headers:** - -- `user_principal_id`: User ID (`user_id`) extracted from the authentication header. - -**Query Parameters:** -- `session_id` (optional): Retrieve the plan for this specific session ID. If not provided, all plans for the user are retrieved. - -**Response:** -- A list of plans with their details: - - `id`: Unique ID of the plan. - - `session_id`: The session ID associated with the plan. - - `initial_goal`: The initial goal derived from the user's input. - - `overall_status`: The status of the plan (e.g., in_progress, completed, failed). - - `steps`: A list of steps associated with the plan, each including: - - `id`: Unique ID of the step. - - `plan_id`: ID of the plan the step belongs to. - - `action`: The action to be performed. - - `agent`: The agent responsible for the step. - - `status`: The status of the step (e.g., planned, approved, completed). - - `agent_reply`: Optional response from the agent after execution. - - `human_feedback`: Optional feedback provided by the user. - - `updated_action`: Optional modified action based on feedback. - -**Flow:** -1. Validates header and extracts `user_principal_id` as `user_id`. -2. If `session_id` is provided: - - Retrieves the plan for the specified session ID. - - Fetches the steps for the plan. -3. If `session_id` is not provided: - - Retrieves all plans for the user. - - Fetches the steps for each plan concurrently. -4. Returns the plan(s) along with their steps. - -### /steps/{plan_id} - -**Method:** GET -**Description:** Retrieves all steps associated with a specific plan. - -**Request Headers:** - -- `user_principal_id`: User ID (`user_id`) extracted from the authentication header. - -**Path Parameters:** -- `plan_id`: The ID of the plan to retrieve steps for. - -**Response:** -- A list of steps with their details: - - `id`: Unique ID of the step. - - `plan_id`: The ID of the plan the step belongs to. - - `action`: The action to be performed. - - `agent`: The agent responsible for the step. - - `status`: The status of the step (e.g., planned, approved, completed). - - `agent_reply`: Optional response from the agent after execution. - - `human_feedback`: Optional feedback provided by the user. - - `updated_action`: Optional modified action based on feedback. - -**Flow:** -1. Validates header and extracts `user_principal_id` as `user_id`. -2. Retrieves the steps for the specified `plan_id`. -3. Returns the list of steps with their details. - -### /agent_messages/{session_id} - -**Method:** GET -**Description:** Retrieves all agent messages for a specific session. - -**Request Headers:** -- `user_principal_id`: User ID (`user_id`) extracted from the authentication header. - -**Path Parameters:** -- `session_id`: The ID of the session to retrieve agent messages for. - -**Response:** -- A list of agent messages with their details: - - `id`: Unique ID of the agent message. - - `session_id`: The session ID associated with the message. - - `plan_id`: The ID of the plan related to the agent message. - - `content`: The content of the message. - - `source`: The source of the message (e.g., agent type). - - `ts`: The timestamp of the message. - - `step_id`: Optional step ID associated with the message. - -**Flow:** -1. Validates header and extracts `user_principal_id` as `user_id`. -2. Retrieves the agent messages for the specified `session_id`. -3. Returns the list of agent messages with their details. - -### /messages - -**Method:** DELETE -**Description:** Deletes all messages across sessions. - -**Request Headers:** - -- `user_principal_id`: User ID (`user_id`) extracted from the authentication header. - -**Response:** -- A confirmation message: - - `status`: A status message indicating all messages were deleted. - -**Flow:** -1. Validates header and extracts `user_principal_id` as `user_id`. -2. Deletes all messages across sessions, including: - - Plans - - Sessions - - Steps - - Agent messages -3. Returns a confirmation `status` message. - -### /messages - -**Method:** GET -**Description:** Retrieves all messages across sessions. - -**Request Headers:** - -- `user_principal_id`: User ID (`user_id`) extracted from the authentication header. - -**Response:** -- A list of all messages with their details: - - `id`: Unique ID of the message. - - `data_type`: The type of the message (e.g., session, step, plan, agent_message). - - `session_id`: The session ID associated with the message. - - `content`: The content of the message. - - `ts`: The timestamp of the message. - -**Flow:** -1. Validates header and extracts `user_principal_id` as `user_id`. -2. Retrieves all messages across sessions. -3. Returns the list of messages with their details. - -### /api/agent-tools - -**Method:** GET -**Description:** Retrieves all available agent tools and their descriptions. - -**Response:** -- A list of agent tools with their details: - - `agent`: The name of the agent associated with the tool. - - `function`: The name of the tool function. - - `description`: A detailed description of what the tool does. - - `arguments`: The arguments required by the tool function. - -**Flow:** -1. Retrieves all agent tools and their metadata. -2. Returns the list of agent tools with their details. - - -## Models and Datatypes -### Models -#### **`BaseDataModel`** + - [Accelerating your own Multi-Agent - Custom Automation Engine MVP](#accelerating-your-own-multi-agent---custom-automation-engine-mvp) + - [Technical Overview](#technical-overview) + - [Adding a New Agent to the Multi-Agent System](#adding-a-new-agent-to-the-multi-agent-system) + - [API Reference](#api-reference) + - [Models and Datatypes](#models-and-datatypes) + - [Application Flow](#application-flow) + - [Agents Overview](#agents-overview) + - [Persistent Storage with Cosmos DB](#persistent-storage-with-cosmos-db) + - [Utilities](#utilities) + - [Summary](#summary) + + +## Adding a New Agent to the Multi-Agent System + +This guide details the steps required to add a new agent to the Multi-Agent Custom Automation Engine. The process includes registering the agent, defining its capabilities through tools, and ensuring the PlannerAgent includes the new agent when generating activity plans. + +### **Step 1: Define the New Agent's Tools** +Every agent is equipped with a set of tools (functions) that it can call to perform specific tasks. These tools need to be defined first. + +1. **Create New Tools**: In a new or existing file, define the tools your agent will use. + + Example (for a `BakerAgent`): + ```python + from autogen_core.components.tools import FunctionTool + + async def bake_cookies(cookie_type: str, quantity: int) -> str: + return f"Baked {quantity} {cookie_type} cookies." + + async def prepare_dough(dough_type: str) -> str: + return f"Prepared {dough_type} dough." + + def get_baker_tools() -> List[Tool]: + return [ + FunctionTool(bake_cookies, description="Bake cookies of a specific type.", name="bake_cookies"), + FunctionTool(prepare_dough, description="Prepare dough of a specific type.", name="prepare_dough"), + ] + ``` + +2. **Add the Tools to the System**: Register the tools with a ToolAgent. + + Example: + ```python + await ToolAgent.register( + runtime, + "baker_tool_agent", + lambda: ToolAgent("Baker tool execution agent", get_baker_tools()), + ) + ``` + +### **Step 2: Implement the Agent Class** +Create a new agent class that inherits from `BaseAgent`. + +Example (for `BakerAgent`): +```python +from agents.base_agent import BaseAgent + +class BakerAgent(BaseAgent): + def __init__(self, model_client, session_id, user_id, memory, tools, agent_id): + super().__init__( + "BakerAgent", + model_client, + session_id, + user_id, + memory, + tools, + agent_id, + system_message="You are an AI Agent specialized in baking tasks.", + ) +``` + +### **Step 3: Register the Agent in the Initialization Process** +Update the `initialize_runtime_and_context` function in `utils.py` to include the new agent. + +1. **Generate Agent IDs**: + ```python + baker_agent_id = AgentId("baker_agent", session_id) + baker_tool_agent_id = AgentId("baker_tool_agent", session_id) + ``` + +2. **Register the Agent and ToolAgent**: + ```python + await BakerAgent.register( + runtime, + baker_agent_id.type, + lambda: BakerAgent( + model_client, + session_id, + user_id, + cosmos_memory, + get_baker_tools(), + baker_tool_agent_id, + ), + ) + ``` + +### **Step 4: Update the Planner Agent** +Modify `PlannerAgent` to recognize and include the new agent when generating plans. + +1. **Update Available Agents**: + ```python + available_agents = [ + hr_agent_id, + marketing_agent_id, + procurement_agent_id, + product_agent_id, + generic_agent_id, + tech_support_agent_id, + baker_agent_id, + ] + ``` + +2. **Update Tool List**: + Ensure the tool list passed to the PlannerAgent includes the new agent's tools. + ```python + tool_list = retrieve_all_agent_tools() + get_baker_tools() + ``` + +### **Step 5: Validate the Integration** +Deploy the updated system and ensure the new agent is properly included in the planning process. For example, if the user requests to bake cookies, the `PlannerAgent` should: + +- Identify the `BakerAgent` as the responsible agent. +- Call `bake_cookies` or `prepare_dough` from the agent's toolset. + +### **Step 6: Update Documentation** +Ensure that the system documentation reflects the addition of the new agent and its capabilities. Update the `README.md` and any related technical documentation to include information about the `BakerAgent`. + +### **Step 7: Testing** +Thoroughly test the agent in both automated and manual scenarios. Verify that: + +- The agent responds correctly to tasks. +- The PlannerAgent includes the new agent in relevant plans. +- The agent's tools are executed as expected. + +Following these steps will successfully integrate a new agent into the Multi-Agent Custom Automation Engine. + +### API Reference +To view the API reference, go to the API endpoint in a browser and add "/docs". This will bring up a full Swagger environment and reference documentation for the REST API included with this accelerator. For example, ```https://macae-backend.eastus2.azurecontainerapps.io/docs```. +If you prefer ReDoc, this is available by appending "/redoc". + +![docs interface](./images/customize_solution/redoc_ui.png) + +### Models and Datatypes +#### Models +##### **`BaseDataModel`** The `BaseDataModel` is a foundational class for creating structured data models using Pydantic. It provides the following attributes: - **`id`**: A unique identifier for the data, generated using `uuid`. @@ -625,7 +457,7 @@ The human can provide feedback on a step via the `/human_feedback` endpoint: If a step is approved: -1. The `GroupChatManager` sends an `ActionRequest` to the appropriate specialized agent (e.g., `HrAgent`, `LegalAgent`). +1. The `GroupChatManager` sends an `ActionRequest` to the appropriate specialized agent (e.g., `HrAgent`, `ProcurementAgent`). 2. The specialized agent executes the action using tools and LLMs. 3. The agent sends an `ActionResponse` back to the `GroupChatManager`. 4. The `GroupChatManager` updates the step status and proceeds to the next step. @@ -692,7 +524,9 @@ If a step is approved: **Common Implementation:** All specialized agents inherit from `BaseAgent`, which handles common functionality. -**Code Reference:** `base_agent.py`, `hr.py`, `legal.py`, etc. +**Code Reference:** `base_agent.py`, `hr.py`, etc. + +![agent flow](./images/customize_solution/logic_flow.svg) ## Persistent Storage with Cosmos DB diff --git a/documentation/images/customize_solution/logic_flow.svg b/documentation/images/customize_solution/logic_flow.svg new file mode 100644 index 00000000..9914ae8a --- /dev/null +++ b/documentation/images/customize_solution/logic_flow.svg @@ -0,0 +1,4 @@ + + + +
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zTOadXi6<-sO_Ho6>>A^Xsm#O(YyHlB8$;08L^FF7cKf@~Xq|c9^!_G!4xGqN@)m6e zA1-Z%_8FBtLrZB-)^C!z1RLI|jeIC&E@fezd%(B7`Gg|f@lisT_u!Gqalr-TXKYzU zIVPb)bn1LtsQ94H!pRdK>965u$U#QEQ|{9jPG7omW>bIs_sQXO)+gF(=(Ey|9cuG{ zg0GlsOk05`?A0D+CK z*cv#v?(6!NkQq`xmy3F?Ejg-aH>gTC=rmiM>PoTxIO~}L&$0^W05Zn?(ZHu&UHB@s zd~+nHPSC6~`&1}3^8T{g{mduXr}WN&2zMcUS!WzMCvlF-Q_R3A7Y^=2(Q4cMr2ahG zpTU|fqQ-x?sd}8P<6D9#PluT}vRJSTxg5(|u6^=F8N?FKv+_XzoqPPodV8UflJkpb zSI^4skSwVo@$B!ngsgFFPj6zJ$ExD5t` Date: Thu, 20 Feb 2025 19:57:59 -0500 Subject: [PATCH 03/13] Update CustomizeSolution.md --- documentation/CustomizeSolution.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index 7f681b59..bc670b2f 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -41,7 +41,7 @@ Every agent is equipped with a set of tools (functions) that it can call to perf Example (for a `BakerAgent`): ```python - from autogen_core.components.tools import FunctionTool + from autogen_core.components.tools import FunctionTool, Tool async def bake_cookies(cookie_type: str, quantity: int) -> str: return f"Baked {quantity} {cookie_type} cookies." From 05c77883c225603555ee2d1a9c334baabe14534e Mon Sep 17 00:00:00 2001 From: Francia Riesco Date: Thu, 20 Feb 2025 20:37:24 -0500 Subject: [PATCH 04/13] Update CustomizeSolution.md --- documentation/CustomizeSolution.md | 70 ++++++++++++++++++++++-------- 1 file changed, 51 insertions(+), 19 deletions(-) diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index bc670b2f..140c45e6 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -56,18 +56,8 @@ Every agent is equipped with a set of tools (functions) that it can call to perf ] ``` -2. **Add the Tools to the System**: Register the tools with a ToolAgent. - Example: - ```python - await ToolAgent.register( - runtime, - "baker_tool_agent", - lambda: ToolAgent("Baker tool execution agent", get_baker_tools()), - ) - ``` - -### **Step 2: Implement the Agent Class** +2. **Implement the Agent Class** Create a new agent class that inherits from `BaseAgent`. Example (for `BakerAgent`): @@ -87,17 +77,42 @@ class BakerAgent(BaseAgent): system_message="You are an AI Agent specialized in baking tasks.", ) ``` +### **Step 2: Register the new Agent in the messages** +Update `messages.py` to include the new agent. + + ```python + baker_agent = "BakerAgent" + ``` ### **Step 3: Register the Agent in the Initialization Process** Update the `initialize_runtime_and_context` function in `utils.py` to include the new agent. -1. **Generate Agent IDs**: +1. **Import new agent**: + ```python + from agents.baker_agent import BakerAgent, get_baker_tools + ``` + +2. **Add the bakers tools**: + ```python + baker_tools = get_baker_tools() + ``` + +3. **Generate Agent IDs**: ```python baker_agent_id = AgentId("baker_agent", session_id) baker_tool_agent_id = AgentId("baker_tool_agent", session_id) ``` -2. **Register the Agent and ToolAgent**: +4. **Register to ToolAgent**: + ```python + await ToolAgent.register( + runtime, + "baker_tool_agent", + lambda: ToolAgent("Baker tool execution agent", baker_tools), + ) + ``` + +5. **Register the Agent and ToolAgent**: ```python await BakerAgent.register( runtime, @@ -112,6 +127,29 @@ Update the `initialize_runtime_and_context` function in `utils.py` to include th ), ) ``` +6. **Add to HumanAgent**: + ```python + await HumanAgent.register( + BAgentType.baker_agent: baker_agent_id, + ``` +7. **Add to GroupChatManager**: + ```python + await GroupChatManager.register( + baker_tools: List[Tool] = get_baker_tools() + ``` +8. **Append to baker_tools to functions**: + ```python + for tool in baker_tools: + functions.append( + { + "agent": "BakerAgent", + "function": tool.name, + "description": tool.description, + "arguments": str(tool.schema["parameters"]["properties"]), + } + ) + ``` + ### **Step 4: Update the Planner Agent** Modify `PlannerAgent` to recognize and include the new agent when generating plans. @@ -129,12 +167,6 @@ Modify `PlannerAgent` to recognize and include the new agent when generating pla ] ``` -2. **Update Tool List**: - Ensure the tool list passed to the PlannerAgent includes the new agent's tools. - ```python - tool_list = retrieve_all_agent_tools() + get_baker_tools() - ``` - ### **Step 5: Validate the Integration** Deploy the updated system and ensure the new agent is properly included in the planning process. For example, if the user requests to bake cookies, the `PlannerAgent` should: From 72c2dc93c03ad8121191ab81afc8e0cb4221edcf Mon Sep 17 00:00:00 2001 From: Francia Riesco Date: Thu, 20 Feb 2025 20:38:30 -0500 Subject: [PATCH 05/13] Update CustomizeSolution.md --- documentation/CustomizeSolution.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index 140c45e6..d9083d92 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -137,7 +137,7 @@ Update the `initialize_runtime_and_context` function in `utils.py` to include th await GroupChatManager.register( baker_tools: List[Tool] = get_baker_tools() ``` -8. **Append to baker_tools to functions**: +8. **Append baker_tools to functions**: ```python for tool in baker_tools: functions.append( From 6210dedeba65b0c883700bbe4bc678f30c2140e1 Mon Sep 17 00:00:00 2001 From: Francia Riesco Date: Tue, 25 Feb 2025 08:47:36 -0500 Subject: [PATCH 06/13] Update CustomizeSolution.md --- documentation/CustomizeSolution.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index d9083d92..b14e1442 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -80,9 +80,9 @@ class BakerAgent(BaseAgent): ### **Step 2: Register the new Agent in the messages** Update `messages.py` to include the new agent. - ```python + ```python baker_agent = "BakerAgent" - ``` +``` ### **Step 3: Register the Agent in the Initialization Process** Update the `initialize_runtime_and_context` function in `utils.py` to include the new agent. From 8513efc93904ada693fab754687c6d482cd1ad2a Mon Sep 17 00:00:00 2001 From: Francia Riesco Date: Tue, 25 Feb 2025 08:48:44 -0500 Subject: [PATCH 07/13] Update CustomizeSolution.md --- documentation/CustomizeSolution.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index b14e1442..67d04b17 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -118,7 +118,7 @@ Update the `initialize_runtime_and_context` function in `utils.py` to include th runtime, baker_agent_id.type, lambda: BakerAgent( - model_client, + aoi_model_client, session_id, user_id, cosmos_memory, From 7cc3e8ea521e8e266aa3164791f19d08e6b846eb Mon Sep 17 00:00:00 2001 From: Francia Riesco Date: Tue, 25 Feb 2025 08:51:58 -0500 Subject: [PATCH 08/13] Update CustomizeSolution.md --- documentation/CustomizeSolution.md | 23 +++-------------------- 1 file changed, 3 insertions(+), 20 deletions(-) diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index 67d04b17..297b7c17 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -150,33 +150,16 @@ Update the `initialize_runtime_and_context` function in `utils.py` to include th ) ``` - -### **Step 4: Update the Planner Agent** -Modify `PlannerAgent` to recognize and include the new agent when generating plans. - -1. **Update Available Agents**: - ```python - available_agents = [ - hr_agent_id, - marketing_agent_id, - procurement_agent_id, - product_agent_id, - generic_agent_id, - tech_support_agent_id, - baker_agent_id, - ] - ``` - -### **Step 5: Validate the Integration** +### **Step 4: Validate the Integration** Deploy the updated system and ensure the new agent is properly included in the planning process. For example, if the user requests to bake cookies, the `PlannerAgent` should: - Identify the `BakerAgent` as the responsible agent. - Call `bake_cookies` or `prepare_dough` from the agent's toolset. -### **Step 6: Update Documentation** +### **Step 5: Update Documentation** Ensure that the system documentation reflects the addition of the new agent and its capabilities. Update the `README.md` and any related technical documentation to include information about the `BakerAgent`. -### **Step 7: Testing** +### **Step 6: Testing** Thoroughly test the agent in both automated and manual scenarios. Verify that: - The agent responds correctly to tasks. From 3073b60ade16a227410e2eecb929844118ec9e8b Mon Sep 17 00:00:00 2001 From: Francia Riesco Date: Tue, 25 Feb 2025 08:53:28 -0500 Subject: [PATCH 09/13] Update CustomizeSolution.md --- documentation/CustomizeSolution.md | 1 + 1 file changed, 1 insertion(+) diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index 297b7c17..ee34fad5 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -81,6 +81,7 @@ class BakerAgent(BaseAgent): Update `messages.py` to include the new agent. ```python + class BAgentType(str, Enum): baker_agent = "BakerAgent" ``` From b34643051168c3e28c865d47f4c5c7867dd21a40 Mon Sep 17 00:00:00 2001 From: Francia Riesco Date: Tue, 25 Feb 2025 08:54:10 -0500 Subject: [PATCH 10/13] Update CustomizeSolution.md --- documentation/CustomizeSolution.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index ee34fad5..ec87a235 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -82,7 +82,7 @@ Update `messages.py` to include the new agent. ```python class BAgentType(str, Enum): - baker_agent = "BakerAgent" + baker_agent = "BakerAgent" ``` ### **Step 3: Register the Agent in the Initialization Process** From df69976d00cae57801e49cf2d6fa931b9e07728e Mon Sep 17 00:00:00 2001 From: Francia Riesco Date: Tue, 25 Feb 2025 12:33:01 -0500 Subject: [PATCH 11/13] Update CustomizeSolution.md --- documentation/CustomizeSolution.md | 31 ++++++++++++++++++++++++++---- 1 file changed, 27 insertions(+), 4 deletions(-) diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index ec87a235..86e1d527 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -150,17 +150,40 @@ Update the `initialize_runtime_and_context` function in `utils.py` to include th } ) ``` - -### **Step 4: Validate the Integration** +### **Step 4: Update home page** +Update `src/frontend/wwwroot/home/home.html` adding new html block + +1. **Add a new UI element was added to allow users to request baking tasks from the BakerAgent** +```html +

+
+
+
+ Bake Cookies +

Please bake 12 chocolate chip cookies for tomorrow's event.

+
+
+
+``` +### **Step 5: Update tasks** +Update `src/frontend/wwwroot/task/task.js` + +1. **Add `BakerAgent` as a recognized agent type in the frontend JavaScript file** +```js + case "BakerAgent": + agentIcon = "manager"; + break; +``` +### **Step 6: Validate the Integration** Deploy the updated system and ensure the new agent is properly included in the planning process. For example, if the user requests to bake cookies, the `PlannerAgent` should: - Identify the `BakerAgent` as the responsible agent. - Call `bake_cookies` or `prepare_dough` from the agent's toolset. -### **Step 5: Update Documentation** +### **Step 7: Update Documentation** Ensure that the system documentation reflects the addition of the new agent and its capabilities. Update the `README.md` and any related technical documentation to include information about the `BakerAgent`. -### **Step 6: Testing** +### **Step 8: Testing** Thoroughly test the agent in both automated and manual scenarios. Verify that: - The agent responds correctly to tasks. From df624b6c45933a72a9c302a5317f26cf17f2ddab Mon Sep 17 00:00:00 2001 From: Roopan-Microsoft <168007406+Roopan-Microsoft@users.noreply.github.com> Date: Thu, 27 Feb 2025 11:12:20 +0530 Subject: [PATCH 12/13] Update CustomizeSolution.md --- documentation/CustomizeSolution.md | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index 86e1d527..8962af79 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -42,6 +42,7 @@ Every agent is equipped with a set of tools (functions) that it can call to perf Example (for a `BakerAgent`): ```python from autogen_core.components.tools import FunctionTool, Tool + from typing import List async def bake_cookies(cookie_type: str, quantity: int) -> str: return f"Baked {quantity} {cookie_type} cookies." @@ -119,7 +120,7 @@ Update the `initialize_runtime_and_context` function in `utils.py` to include th runtime, baker_agent_id.type, lambda: BakerAgent( - aoi_model_client, + aoai_model_client, session_id, user_id, cosmos_memory, @@ -614,4 +615,4 @@ This application orchestrates a group of AI agents to accomplish user-defined ta Understanding the flow of data through the endpoints, agents, and persistent storage is key to grasping the logic of the application. Each component plays a specific role in ensuring tasks are planned, executed, and adjusted based on feedback, providing a robust and interactive system. -For instructions to setup a local development environment for the solution, please see [local deployment guide](./LocalDeployment.md). \ No newline at end of file +For instructions to setup a local development environment for the solution, please see [local deployment guide](./LocalDeployment.md). From f7ec2c869f46e78717d882b9a5b55c1452f5c4e2 Mon Sep 17 00:00:00 2001 From: Francia Riesco Date: Thu, 27 Feb 2025 11:31:37 -0500 Subject: [PATCH 13/13] Update CustomizeSolution.md --- documentation/CustomizeSolution.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/documentation/CustomizeSolution.md b/documentation/CustomizeSolution.md index 8962af79..d07e02d8 100644 --- a/documentation/CustomizeSolution.md +++ b/documentation/CustomizeSolution.md @@ -129,14 +129,14 @@ Update the `initialize_runtime_and_context` function in `utils.py` to include th ), ) ``` -6. **Add to HumanAgent**: +6. **Add to agent_ids**: ```python - await HumanAgent.register( + agent_ids = { BAgentType.baker_agent: baker_agent_id, ``` -7. **Add to GroupChatManager**: +7. **Add to retrieve_all_agent_tools**: ```python - await GroupChatManager.register( + def retrieve_all_agent_tools() -> List[Dict[str, Any]]: baker_tools: List[Tool] = get_baker_tools() ``` 8. **Append baker_tools to functions**: