add deep research agent

tests/test_agents.py

@@ -194,7 +194,6 @@ async def test_browser_use_parallel():
     #     api_key=os.getenv("OPENAI_API_KEY", ""),
     # )
 
-
     # llm = utils.get_llm_model(
     #     provider="google",
     #     model_name="gemini-2.0-flash",
@@ -335,6 +334,70 @@ async def test_browser_use_parallel():
             await browser.close()
 
 
+async def test_deep_research_agent():
+    from src.agent.deep_research.deep_research_agent import DeepSearchAgent
+    from src.utils import llm_provider
+
+    llm = llm_provider.get_llm_model(
+        provider="azure_openai",
+        model_name="gpt-4o",
+        temperature=0.5,
+        base_url=os.getenv("AZURE_OPENAI_ENDPOINT", ""),
+        api_key=os.getenv("AZURE_OPENAI_API_KEY", ""),
+    )
+
+    mcp_server_config = {
+        "mcpServers": {
+            "desktop-commander": {
+                "command": "npx",
+                "args": [
+                    "-y",
+                    "@wonderwhy-er/desktop-commander"
+                ]
+            },
+        }
+    }
+
+    browser_config = {"headless": False, "window_width": 1280, "window_height": 1100, "use_own_browser": False}
+    agent = DeepSearchAgent(llm=llm, browser_config=browser_config, mcp_server_config=mcp_server_config)
+
+    research_topic = "Impact of Microplastics on Marine Ecosystems"
+    task_id_to_resume = None  # Set this to resume a previous task ID
+
+    print(f"Starting research on: {research_topic}")
+
+    try:
+        # Call run and wait for the final result dictionary
+        result = await agent.run(research_topic, task_id=task_id_to_resume)
+
+        print("\n--- Research Process Ended ---")
+        print(f"Status: {result.get('status')}")
+        print(f"Message: {result.get('message')}")
+        print(f"Task ID: {result.get('task_id')}")
+
+        # Check the final state for the report
+        final_state = result.get('final_state', {})
+        if final_state:
+            print("\n--- Final State Summary ---")
+            print(
+                f"  Plan Steps Completed: {sum(1 for item in final_state.get('research_plan', []) if item.get('status') == 'completed')}")
+            print(f"  Total Search Results Logged: {len(final_state.get('search_results', []))}")
+            if final_state.get("final_report"):
+                print("  Final Report: Generated (content omitted). You can find it in the output directory.")
+                # print("\n--- Final Report ---") # Optionally print report
+                # print(final_state["final_report"])
+            else:
+                print("  Final Report: Not generated.")
+        else:
+            print("Final state information not available.")
+
+
+    except Exception as e:
+        print(f"\n--- An unhandled error occurred outside the agent run ---")
+        print(e)
+
+
 if __name__ == "__main__":
     # asyncio.run(test_browser_use_agent())
-    asyncio.run(test_browser_use_parallel())
+    # asyncio.run(test_browser_use_parallel())
+    asyncio.run(test_deep_research_agent())

tests/test_controller.py

@@ -32,6 +32,7 @@ async def test_mcp_client():
     }
 
     mcp_tools, mcp_client = await setup_mcp_client_and_tools(test_server_config)
+
     for tool in mcp_tools:
         tool_param_model = create_tool_param_model(tool)
         print(tool.name)