use pydantic

web/agent/.dockerignore

@@ -1,14 +0,0 @@
-Dockerfile
-.dockerignore
-.git
-.gitignore
-.env
-.env.*
-.venv/
-venv/
-__pycache__/
-*.pyc
-*.pyo
-.langgraph_api/
-.vercel/
-*.md

web/agent/.gitignore

@@ -1,9 +0,0 @@
-venv/
-__pycache__/
-*.pyc
-.env
-.vercel
-
-# python
-.venv/
-.langgraph_api/

web/agent/.python-version

@@ -0,0 +1 @@
+3.12

web/agent/Dockerfile

@@ -1,21 +0,0 @@
-# syntax=docker/dockerfile:1
-
-FROM python:3.13-slim
-
-WORKDIR /app
-
-# Install uv
-COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
-
-# Copy dependency files
-COPY pyproject.toml uv.lock ./
-
-# Install dependencies
-RUN uv sync --frozen --no-dev --no-install-project
-
-# Copy application code
-COPY main.py server.py ./
-
-EXPOSE 8000
-
-CMD ["uv", "run", "python", "server.py"]

web/agent/main.py

@@ -1,26 +0,0 @@
-"""
-PydanticAI agent with MCP tools from Cavepedia server.
-"""
-
-from pydantic_ai import Agent
-from pydantic_ai.models.google import GoogleModel
-from pydantic_ai.mcp import MCPServerStreamableHTTP
-
-
-# Create MCP server connection to Cavepedia
-mcp_server = MCPServerStreamableHTTP(
-    url="https://mcp.caving.dev/mcp",
-    timeout=30.0,
-)
-
-# Create the agent with Google Gemini model
-agent = Agent(
-    model=GoogleModel("gemini-2.5-pro"),
-    toolsets=[mcp_server],
-    instructions="""You are a helpful assistant with access to cave-related information through the Cavepedia MCP server. You can help users find information about caves, caving techniques, and related topics.
-
-IMPORTANT RULES:
-1. Always cite your sources at the end of each response. List the specific sources/documents you used.
-2. If you cannot find information on a topic, say so clearly. Do NOT make up information or hallucinate facts.
-3. If the MCP tools return no results, acknowledge that you couldn't find the information rather than guessing.""",
-)

web/agent/pyproject.toml

@@ -1,11 +1,12 @@
 [project]
-name = "vpi-1000"
-version = "1.0.0"
-description = "VPI-1000"
-requires-python = ">=3.13,<3.14"
+name = "agent"
+version = "0.1.0"
+description = "Cavepedia AI Agent with MCP tools"
+readme = "README.md"
+requires-python = ">=3.12"
 dependencies = [
-    "pydantic-ai>=0.1.0",
-    "fastapi>=0.115.5,<1.0.0",
-    "uvicorn>=0.29.0,<1.0.0",
-    "python-dotenv>=1.0.0,<2.0.0",
+    "uvicorn",
+    "pydantic-ai[google,mcp,ag-ui]",
+    "python-dotenv",
+    "logfire>=4.10.0",
 ]

web/agent/server.py

@@ -1,20 +0,0 @@
-"""
-Self-hosted PydanticAI agent server using AG-UI protocol.
-"""
-
-import os
-import uvicorn
-from dotenv import load_dotenv
-
-from pydantic_ai.ui.ag_ui.app import AGUIApp
-from main import agent
-
-load_dotenv()
-
-# Convert PydanticAI agent to ASGI app with AG-UI protocol
-app = AGUIApp(agent)
-
-
-if __name__ == "__main__":
-    port = int(os.getenv("PORT", "8000"))
-    uvicorn.run(app, host="0.0.0.0", port=port)

web/agent/src/agent.py

@@ -0,0 +1,62 @@
+"""
+PydanticAI agent with MCP tools from Cavepedia server.
+"""
+
+import logging
+import httpx
+
+from pydantic_ai import Agent
+from pydantic_ai.models.google import GoogleModel
+
+# Set up logging
+logging.basicConfig(level=logging.DEBUG)
+logger = logging.getLogger(__name__)
+
+MCP_URL = "https://mcp.caving.dev/mcp"
+
+logger.info("Initializing Cavepedia agent...")
+
+def check_mcp_available(url: str, timeout: float = 5.0) -> bool:
+    """Check if MCP server is reachable."""
+    try:
+        # Just check if we can connect - don't need a full MCP handshake
+        response = httpx.get(url, timeout=timeout, follow_redirects=True)
+        # Any response (even 4xx/5xx) means server is reachable
+        # 502 means upstream is down, so treat as unavailable
+        if response.status_code == 502:
+            logger.warning(f"MCP server returned 502 Bad Gateway")
+            return False
+        return True
+    except Exception as e:
+        logger.warning(f"MCP server not reachable: {e}")
+        return False
+
+# Try to configure MCP if server is available
+toolsets = []
+if check_mcp_available(MCP_URL):
+    try:
+        from pydantic_ai.mcp import MCPServerStreamableHTTP
+        mcp_server = MCPServerStreamableHTTP(
+            url=MCP_URL,
+            timeout=30.0,
+        )
+        toolsets.append(mcp_server)
+        logger.info(f"MCP server configured: {MCP_URL}")
+    except Exception as e:
+        logger.warning(f"Could not configure MCP server: {e}")
+else:
+    logger.info("MCP server unavailable - running without MCP tools")
+
+# Create the agent with Google Gemini model
+agent = Agent(
+    model=GoogleModel("gemini-2.5-pro"),
+    toolsets=toolsets if toolsets else None,
+    instructions="""You are a helpful caving assistant. Help users with all aspects of caving including cave exploration, safety, surveying techniques, cave locations, geology, equipment, history, conservation, and any other caving-related topics.
+
+IMPORTANT RULES:
+1. Always cite your sources at the end of each response when possible.
+2. If you're not certain about information, say so clearly. Do NOT make up information or hallucinate facts.
+3. Provide accurate, helpful, and safety-conscious information.""",
+)
+
+logger.info(f"Agent initialized successfully (MCP: {'enabled' if toolsets else 'disabled'})")

web/agent/src/main.py

@@ -0,0 +1,32 @@
+"""
+Self-hosted PydanticAI agent server using AG-UI protocol.
+"""
+
+import os
+import logging
+from dotenv import load_dotenv
+
+# Set up logging
+logging.basicConfig(
+    level=logging.DEBUG,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+)
+logger = logging.getLogger(__name__)
+
+# Load environment variables BEFORE importing agent
+load_dotenv()
+
+import uvicorn
+from src.agent import agent
+
+logger.info("Creating AG-UI app...")
+
+# Convert PydanticAI agent to ASGI app with AG-UI protocol
+app = agent.to_ag_ui(debug=True)
+
+logger.info("AG-UI app created successfully")
+
+
+if __name__ == "__main__":
+    port = int(os.getenv("PORT", "8000"))
+    uvicorn.run(app, host="127.0.0.1", port=port)