Draft : Add agent astronomy shop and astronomy shop MCP server

.env

@@ -192,3 +192,21 @@ JAEGER_GRPC_PORT=4317
 PROMETHEUS_PORT=9090
 PROMETHEUS_HOST=prometheus
 PROMETHEUS_ADDR=${PROMETHEUS_HOST}:${PROMETHEUS_PORT}
+
+# Agent
+GRAPH_RECURSION_LIMIT=25
+MCP_ENDPOINT=mcp
+MCP_PORT=8011
+MCP_ENABLED=False
+AGENT_ENDPOINT=agent
+AGENT_PORT=8010
+CHATBOT_PORT=7860
+LLM_BASE_URL=
+LLM_MODEL=Azure/gpt-4o
+USE_VCR=True
+AGENT_DOCKERFILE=src/agent/Dockerfile
+MCP_DOCKERFILE=src/mcp/Dockerfile
+CHATBOT_DOCKERFILE=src/chatbot/Dockerfile
+AGENT_ADDR=${AGENT_ENDPOINT}:${AGENT_PORT}
+APPLICATION_ENDPOINT=frontend:8080
+OTEL_EXPORTER_OTLP_INSECURE=true

.gitignore

@@ -55,3 +55,5 @@ test/tracetesting/tracetesting-vars.yaml
 !src/currency/build
 src/cart/src/Program.cs.bak
 src/flagd/demo.flagd.json.bak
+
+src/agent/fixtures/*

docker-compose.yml

@@ -603,7 +603,7 @@ services:
     deploy:
       resources:
         limits:
-          memory: 500M               # This is high to enable supporting the recommendationCache feature flag use case
+          memory: 500M  # This is high to enable supporting the recommendationCache feature flag use case
     restart: unless-stopped
     ports:
       - "${RECOMMENDATION_PORT}"
@@ -674,18 +674,13 @@ services:
       - GOMEMLIMIT=60MiB
       - OTEL_RESOURCE_ATTRIBUTES=${OTEL_RESOURCE_ATTRIBUTES},service.criticality=low
       - OTEL_SERVICE_NAME=flagd
-    command: [
-      "start",
-      "--uri",
-      "file:./etc/flagd/demo.flagd.json"
-    ]
+    command: ["start", "--uri", "file:./etc/flagd/demo.flagd.json"]
     ports:
       - "${FLAGD_PORT}"
       - "${FLAGD_OFREP_PORT}"
     volumes:
       - ./src/flagd:/etc/flagd
-    logging:
-      *logging
+    logging: *logging
 
   # Flagd UI for configuring the feature flag service
   flagd-ui:
@@ -778,6 +773,105 @@ services:
         condition: service_started
     logging: *logging
 
+  # Agent
+  agent:
+    image: ${IMAGE_NAME}:${DEMO_VERSION}-agent
+    container_name: agent
+    build:
+      context: ./
+      dockerfile: ${AGENT_DOCKERFILE}
+      cache_from:
+        - ${IMAGE_NAME}:${IMAGE_VERSION}-agent
+    deploy:
+      resources:
+        limits:
+          memory: 500M
+    restart: unless-stopped
+    ports:
+      - "${AGENT_PORT}"
+    environment:
+      - OTEL_EXPORTER_OTLP_ENDPOINT=${OTEL_COLLECTOR_HOST}:${OTEL_COLLECTOR_PORT_GRPC}
+      - GRAPH_RECURSION_LIMIT
+      - MCP_ENDPOINT
+      - MCP_PORT
+      - MCP_ENABLED
+      - AGENT_ENDPOINT
+      - AGENT_PORT
+      - LLM_BASE_URL
+      - LLM_MODEL
+      - USE_VCR=True
+      - OPENAI_API_KEY
+      - APPLICATION_ENDPOINT=frontend:8080
+      - OTEL_EXPORTER_OTLP_INSECURE=true
+    depends_on:
+      jaeger:
+        condition: service_started
+      otel-collector:
+        condition: service_started
+      product-catalog:
+        condition: service_started
+    logging: *logging
+
+  # MCP
+  mcp:
+    image: ${IMAGE_NAME}:${DEMO_VERSION}-mcp
+    container_name: mcp
+    build:
+      context: ./
+      dockerfile: ${MCP_DOCKERFILE}
+      cache_from:
+        - ${IMAGE_NAME}:${IMAGE_VERSION}-mcp
+    deploy:
+      resources:
+        limits:
+          memory: 500M
+    restart: unless-stopped
+    ports:
+      - "${MCP_PORT}"
+    environment:
+      - OTEL_EXPORTER_OTLP_ENDPOINT=${OTEL_COLLECTOR_HOST}:${OTEL_COLLECTOR_PORT_GRPC}
+      - MCP_ENDPOINT
+      - MCP_PORT
+      - OTEL_EXPORTER_OTLP_INSECURE=true
+      - APPLICATION_ENDPOINT=frontend:8080
+    depends_on:
+      jaeger:
+        condition: service_started
+      otel-collector:
+        condition: service_started
+      product-catalog:
+        condition: service_started
+    logging: *logging
+
+  # ChatBot
+  chatbot:
+    image: ${IMAGE_NAME}:${DEMO_VERSION}-chatbot
+    container_name: chatbot
+    build:
+      context: ./
+      dockerfile: ${CHATBOT_DOCKERFILE}
+      cache_from:
+        - ${IMAGE_NAME}:${IMAGE_VERSION}-chatbot
+    deploy:
+      resources:
+        limits:
+          memory: 500M
+    restart: unless-stopped
+    ports:
+      - "${CHATBOT_PORT}"
+    environment:
+      - AGENT_PORT
+      - AGENT_ENDPOINT
+      - CHATBOT_PORT
+    depends_on:
+      jaeger:
+        condition: service_started
+      otel-collector:
+        condition: service_started
+      product-catalog:
+        condition: service_started
+    logging: *logging
+
   # Postgresql used by Accounting service
   postgresql:
     image: ${POSTGRES_IMAGE}
@@ -811,7 +905,6 @@ services:
       - "${VALKEY_PORT}"
     logging: *logging
 
-
   # ********************
   # Telemetry Components
   # ********************
@@ -867,7 +960,11 @@ services:
         limits:
           memory: 200M
     restart: unless-stopped
-    command: [ "--config=/etc/otelcol-config.yml", "--config=/etc/otelcol-config-extras.yml" ]
+    command:
+      [
+        "--config=/etc/otelcol-config.yml",
+        "--config=/etc/otelcol-config-extras.yml",
+      ]
     user: 0:0
     volumes:
       - ${HOST_FILESYSTEM}:/hostfs:ro

src/agent/Dockerfile

@@ -0,0 +1,23 @@
+# Copyright The OpenTelemetry Authors
+# SPDX-License-Identifier: Apache-2.0
+
+FROM python:3.11-slim
+
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    build-essential \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY src/agent/requirements.txt .
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY src/agent/src src
+COPY src/agent/run.py .
+
+EXPOSE ${AGENT_PORT}
+
+CMD ["python", "run.py"]

src/agent/requirements.txt

@@ -0,0 +1,19 @@
+requests==2.32.5
+traceloop-sdk==0.47.5
+dotenv==0.9.9
+httpx==0.28.1
+langchain_openai==1.0.1
+langchain==1.0.5
+langgraph-prebuilt==1.0.5
+mcp==1.22.0
+fastmcp>=2.13.1
+langchain_mcp_adapters==0.1.14
+langchain_community==0.4.1
+fastapi==0.120.4
+opentelemetry-api==1.38.0
+opentelemetry-sdk==1.38.0
+opentelemetry-semantic-conventions==0.59b0
+opentelemetry-instrumentation-langchain<0.53.0
+fastmcp==2.13.1
+gradio==6.0.1
+vcrpy==7.0.0

src/agent/run.py

@@ -0,0 +1,37 @@
+#!/usr/bin/python
+
+# Copyright The OpenTelemetry Authors
+# SPDX-License-Identifier: Apache-2.0
+
+
+import asyncio
+import logging
+import os
+
+from dotenv import load_dotenv
+from src.agents.agents import Agent
+from traceloop.sdk import Traceloop
+
+logging.basicConfig(level=logging.INFO)
+
+load_dotenv()
+
+Traceloop.init(
+    app_name="AstronomyShopAgent",
+    api_endpoint=os.getenv("OTEL_EXPORTER_OTLP_ENDPOINT", "localhost:4317"),
+)
+
+
+async def start_servers():
+    """Run both the LangGraph Agent and the MCP server concurrently."""
+    tasks = []
+    agent = Agent()
+    tasks.append(agent.launch())
+    await asyncio.gather(*tasks)
+
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(start_servers())
+    except KeyboardInterrupt:
+        logging.info("Shutting down servers...")

src/agent/src/agents/agents.py

@@ -0,0 +1,109 @@
+#!/usr/bin/python
+
+# Copyright The OpenTelemetry Authors
+# SPDX-License-Identifier: Apache-2.0
+
+import logging
+import os
+from contextlib import asynccontextmanager
+from typing import Dict, List
+
+import uvicorn
+from fastapi import FastAPI, HTTPException
+from langchain.agents import create_agent
+from langchain.tools import tool
+from langchain_mcp_adapters.tools import load_mcp_tools
+from pydantic import BaseModel
+from src.agents.llm import ChatLLM
+from src.agents.mcp_client import MCPClient
+from src.agents.tools import (
+    add_to_cart,
+    checkout,
+    convert_currency,
+    empty_cart,
+    get_ads,
+    get_cart,
+    get_product,
+    get_recommendations,
+    get_shipping_quote,
+    get_supported_currencies,
+    list_products,
+)
+from traceloop.sdk.decorators import workflow
+
+
+class ChatRequest(BaseModel):
+    message: str
+    history: List[Dict] = []
+
+
+class Agent:
+    def __init__(self):
+        self.app = FastAPI(lifespan=self.lifespan)
+        self.app.post("/prompt")(self.handle_prompt)
+        self.agentRecursionLimit = int(os.getenv("GRAPH_RECURSION_LIMIT", "25"))
+        self.mcp_server_url = f"http://{os.getenv('MCP_ENDPOINT', '127.0.0.1')}:{os.getenv('MCP_PORT', '8011')}/mcp"
+
+        self.mcp_server = None
+
+    @asynccontextmanager
+    async def lifespan(self, app: FastAPI):
+        mcp_enabled = os.getenv("MCP_ENABLED", "False") == "True"
+        if mcp_enabled:
+            logging.info("MCP tools enabled")
+            self.mcp_server = MCPClient()
+        yield
+        if self.mcp_server:
+            await self.mcp_server.cleanup()
+
+    async def handle_prompt(self, request: ChatRequest):
+        return await self.run_agent(request.message)
+
+    async def get_tool_list(self):
+        mcp_enabled = os.getenv("MCP_ENABLED", "False") == "True"
+        if mcp_enabled and self.mcp_server is not None:
+            await self.mcp_server.connect_to_mcp_server(self.mcp_server_url)
+            return await load_mcp_tools(self.mcp_server.session)
+        else:
+            tool_list = [
+                add_to_cart,
+                checkout,
+                convert_currency,
+                empty_cart,
+                get_ads,
+                get_cart,
+                get_product,
+                get_recommendations,
+                get_shipping_quote,
+                get_supported_currencies,
+                list_products,
+            ]
+            return [tool(t) for t in tool_list]
+
+    @workflow(name="astronomy_shop_agent_workflow")
+    async def run_agent(self, input_prompt):
+        model = ChatLLM()
+        tools = await self.get_tool_list()
+        agent = create_agent(
+            model,
+            tools=tools,
+            system_prompt="You are a helpful assistant. Be concise and accurate.",
+        )
+        try:
+            result = await agent.ainvoke(
+                {"messages": [{"role": "user", "content": input_prompt}]}
+            )
+            return {"response": result}
+        except Exception as e:
+            raise HTTPException(status_code=500, detail=str(e))
+
+    async def launch(self):
+        agent_port = int(os.getenv("AGENT_PORT", "8010"))
+        agent_config = uvicorn.Config(
+            app=self.app,
+            host="0.0.0.0",
+            port=agent_port,
+            log_level="info",
+        )
+        agent_server = uvicorn.Server(agent_config)
+        await agent_server.serve()