Merge branch 'main' of https://github.com/awslabs/multi-agent-orchest…

…rator

docs/src/content/docs/deployment/demo-web-app.md

@@ -16,7 +16,7 @@ In the screen recording below, we demonstrate an extended version of the demo ap
 - **Health Agent**: A Bedrock LLM Agent focused on addressing health-related queries
 
 Watch as the system seamlessly switches context between diverse topics, from booking flights to checking weather, solving math problems, and providing health information.
-Notice how the appropriate agent is selected for each query, maintaining coherence even with brief follow-up inputs. 
+Notice how the appropriate agent is selected for each query, maintaining coherence even with brief follow-up inputs.
 
 The demo highlights the system's ability to handle complex, multi-turn conversations while preserving context and leveraging specialized agents across various domains.
 
@@ -38,7 +38,7 @@ Follow these steps to deploy the demo chat web application:
 
 1. **Clone the Repository** (if you haven't already):
    ```
-   git clone https://github.com/your-repo/multi-agent-orchestrator.git
+   git clone https://github.com/awslabs/multi-agent-orchestrator.git
    cd multi-agent-orchestrator
    ```
 
@@ -80,7 +80,7 @@ Follow these steps to deploy the demo chat web application:
    CDK will show you a summary of the changes and ask for confirmation. Type 'y' and press Enter to proceed.
 
 8. **Note the Outputs**:
-   After deployment, CDK will display outputs including the URL of your deployed web app and the user pool ID. 
+   After deployment, CDK will display outputs including the URL of your deployed web app and the user pool ID.
    Save the URL and the user pool Id.
 
 9. **Create a user in Amazon Cognito user pool**:

examples/python-demo/main.py

@@ -5,6 +5,8 @@
 import json
 import sys
 
+from tools import weather_tool
+
 from multi_agent_orchestrator.orchestrator import MultiAgentOrchestrator, OrchestratorConfig
 from multi_agent_orchestrator.agents import (BedrockLLMAgent,
                         BedrockLLMAgentOptions,
@@ -74,6 +76,20 @@ def custom_output_payload_decoder(response: Dict[str, Any]) -> Any:
     ))
     orchestrator.add_agent(tech_agent)
 
+    # Add some agents
+    weather_agent = BedrockLLMAgent(BedrockLLMAgentOptions(
+        name="Weather Agent",
+        streaming=False,
+        description="Specialized agent for giving weather condition from a city.",
+        tool_config={
+            'tool':weather_tool.weather_tool_description,
+            'toolMaxRecursions': 5,
+            'useToolHandler': weather_tool.weather_tool_handler
+        }
+    ))
+    weather_agent.set_system_prompt(weather_tool.weather_tool_prompt)
+    orchestrator.add_agent(weather_agent)
+
     USER_ID = "user123"
     SESSION_ID = str(uuid.uuid4())
 

examples/python-demo/tools/weather_tool.py

@@ -0,0 +1,105 @@
+import requests
+from requests.exceptions import RequestException
+from typing import List, Dict, Any
+from multi_agent_orchestrator.types import ConversationMessage, ParticipantRole
+
+
+weather_tool_description = [{
+    "toolSpec": {
+        "name": "Weather_Tool",
+        "description": "Get the current weather for a given location, based on its WGS84 coordinates.",
+        "inputSchema": {
+            "json": {
+                "type": "object",
+                "properties": {
+                    "latitude": {
+                        "type": "string",
+                        "description": "Geographical WGS84 latitude of the location.",
+                    },
+                    "longitude": {
+                        "type": "string",
+                        "description": "Geographical WGS84 longitude of the location.",
+                    },
+                },
+                "required": ["latitude", "longitude"],
+            }
+        },
+    }
+}]
+
+weather_tool_prompt = """
+You are a weather assistant that provides current weather data for user-specified locations using only
+the Weather_Tool, which expects latitude and longitude. Infer the coordinates from the location yourself.
+If the user provides coordinates, infer the approximate location and refer to it in your response.
+To use the tool, you strictly apply the provided tool specification.
+
+- Explain your step-by-step process, and give brief updates before each step.
+- Only use the Weather_Tool for data. Never guess or make up information.
+- Repeat the tool use for subsequent requests if necessary.
+- If the tool errors, apologize, explain weather is unavailable, and suggest other options.
+- Report temperatures in °C (°F) and wind in km/h (mph). Keep weather reports concise. Sparingly use
+  emojis where appropriate.
+- Only respond to weather queries. Remind off-topic users of your purpose.
+- Never claim to search online, access external data, or use tools besides Weather_Tool.
+- Complete the entire process until you have all required data before sending the complete response.
+"""
+
+
+async def weather_tool_handler(response: ConversationMessage, conversation: List[Dict[str, Any]]):
+    response_content_blocks = response.content
+
+    # Initialize an empty list of tool results
+    tool_results = []
+
+    if not response_content_blocks:
+        raise ValueError("No content blocks in response")
+
+    for content_block in response_content_blocks:
+        if "text" in content_block:
+            # Handle text content if needed
+            pass
+
+        if "toolUse" in content_block:
+            tool_use_block = content_block["toolUse"]
+            tool_use_name = tool_use_block.get("name")
+
+            if tool_use_name == "Weather_Tool":
+                response = await fetch_weather_data(tool_use_block["input"])
+                tool_results.append({
+                    "toolResult": {
+                        "toolUseId": tool_use_block["toolUseId"],
+                        "content": [{"json": {"result": response}}],
+                    }
+                })
+                print(response)
+
+    # Embed the tool results in a new user message
+    message = ConversationMessage(
+            role=ParticipantRole.USER.value,
+            content=tool_results)
+
+    # Append the new message to the ongoing conversation
+    conversation.append(message)
+
+async def fetch_weather_data(input_data):
+    """
+    Fetches weather data for the given latitude and longitude using the Open-Meteo API.
+    Returns the weather data or an error message if the request fails.
+
+    :param input_data: The input data containing the latitude and longitude.
+    :return: The weather data or an error message.
+    """
+    endpoint = "https://api.open-meteo.com/v1/forecast"
+    latitude = input_data.get("latitude")
+    longitude = input_data.get("longitude", "")
+    params = {"latitude": latitude, "longitude": longitude, "current_weather": True}
+
+    try:
+        response = requests.get(endpoint, params=params)
+        weather_data = {"weather_data": response.json()}
+        response.raise_for_status()
+        return weather_data
+    except RequestException as e:
+        return e.response.json()
+    except Exception as e:
+        return {"error": type(e), "message": str(e)}

python/setup.cfg

@@ -1,6 +1,6 @@
 [metadata]
 name = multi_agent_orchestrator
-version = 0.0.10
+version = 0.0.11
 author = Anthony Bernabeu, Corneliu Croitoru
 author_email = [email protected], [email protected]
 description = Multi-agent orchestrator framework

python/src/multi_agent_orchestrator/agents/bedrock_llm_agent.py

@@ -81,8 +81,8 @@ async def process_request(
         chat_history: List[ConversationMessage],
         additional_params: Optional[Dict[str, str]] = None
     ) -> Union[ConversationMessage, AsyncIterable[Any]]:
-        
-        user_message =ConversationMessage(
+
+        user_message = ConversationMessage(
             role=ParticipantRole.USER.value,
             content=[{'text': input_text}]
         )
@@ -114,7 +114,7 @@ async def process_request(
             converse_cmd["guardrailConfig"] = self.guardrail_config
 
         if self.tool_config:
-            converse_cmd["toolConfig"] = self.tool_config["tool"]
+            converse_cmd["toolConfig"] = {'tools': self.tool_config["tool"]}
 
         if self.tool_config:
             continue_with_tools = True
@@ -132,7 +132,7 @@ async def process_request(
                     final_message = bedrock_response
 
                 max_recursions -= 1
-                converse_cmd['messages'] = conversation
+                converse_cmd['messages'] = conversation_to_dict(conversation)
 
             return final_message