First commit

files/agent_over_mcp.py

@@ -0,0 +1,115 @@
+import sys
+import os
+import json
+import asyncio
+
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_community.chat_models.oci_generative_ai import ChatOCIGenAI
+from langgraph.prebuilt import create_react_agent
+from langchain_core.messages import HumanMessage, AIMessage
+from langchain_mcp_adapters.client import MultiServerMCPClient
+
+# Configuration File
+with open("./config", "r") as f:
+    config_data = json.load(f)
+
+# Memory Management for the OCI Resource Parameters
+class MemoryState:
+    def __init__(self):
+        self.messages = []
+
+# Define the language model
+llm = ChatOCIGenAI(
+    model_id="cohere.command-r-08-2024",
+    service_endpoint=config_data["llm_endpoint"],
+    compartment_id=config_data["compartment_id"],
+    auth_profile=config_data["oci_profile"],
+    model_kwargs={"temperature": 0.1, "top_p": 0.75, "max_tokens": 2000}
+)
+
+# Prompt
+prompt = ChatPromptTemplate.from_messages([
+    ("system", """
+        You are an OCI Operations Agent with access to MCP tools (server `oci-ops`).
+        Your goal is to provision and manage OCI resources **without requiring the user to know OCIDs**.
+                
+        INTERACTION RULES:
+        1) Wait until the user ask to create a resource
+        2) If all the parameters has the ocid information, create the resource
+        3) If all the parameters were filled by the user, create the resource
+        4) If a parameter given is a name and needs to be converted to a OCID, search for it automatically
+        5) If a parameter is missing, ask for the information
+        6) Do not wait for a response from creation. Inform "Creation of resource is Done."
+        
+        IMPORTANT RULES:
+        1) Never invent OCIDs. Prefer to ask succinct follow-ups.
+        2) Prefer to reuse defaults from memory when appropriate
+        
+        OUTPUT STYLE:
+        - Questions: short, one parameter at a time.
+        - Show: mini-summary with final values.
+        - Candidate lists: numbered, with name (type) — ocid — score when available.
+    """),
+    ("placeholder", "{messages}")
+])
+
+# Run the client with the MCP server
+async def main():
+    client = MultiServerMCPClient(
+        {
+            "oci-ops": {
+                "command": sys.executable,
+                "args": ["server_mcp.py"],
+                "transport": "stdio",
+                "env": {
+                    "PATH": os.environ.get("PATH", "") + os.pathsep + os.path.expanduser("~/.local/bin"),
+                    "OCI_CLI_BIN": config_data["OCI_CLI_BIN"],
+                    "OCI_CLI_PROFILE": config_data["oci_profile"],
+                },
+            },
+        }
+    )
+
+    tools = await client.get_tools()
+    if not tools:
+        print("❌ No MCP tools were loaded. Please check if the server is running.")
+        return
+
+    print("🛠️ Loaded tools:", [t.name for t in tools])
+
+    # Creating the LangGraph agent with in-memory state
+    memory_state = MemoryState()
+    memory_state.messages = []
+
+    agent_executor = create_react_agent(
+        model=llm,
+        tools=tools,
+        prompt=prompt,
+    )
+
+    print("🤖 READY")
+    while True:
+        query = input("You: ")
+        if query.lower() in ["quit", "exit"]:
+            break
+        if not query.strip():
+            continue
+
+        memory_state.messages.append(HumanMessage(content=query))
+        try:
+            result = await agent_executor.ainvoke({"messages": memory_state.messages})
+            new_messages = result.get("messages", [])
+
+            # Store new messages
+            memory_state.messages.extend(new_messages)
+
+            print("Assist:", new_messages[-1].content)
+
+            formatted_messages = prompt.format_messages()
+
+        except Exception as e:
+            print("Error:", e)
+
+# Run the agent with asyncio
+if __name__ == "__main__":
+    asyncio.run(main())