feat: lite deep researcher implementation

src/workflow.py

@@ -0,0 +1,81 @@
+import logging
+from src.graph import build_graph
+
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,  # Default level is INFO
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+)
+
+
+def enable_debug_logging():
+    """Enable debug level logging for more detailed execution information."""
+    logging.getLogger("src").setLevel(logging.DEBUG)
+
+
+logger = logging.getLogger(__name__)
+
+# Create the graph
+graph = build_graph()
+
+
+def run_agent_workflow(
+    user_input: str,
+    debug: bool = False,
+    max_plan_iterations: int = 1,
+    max_step_num: int = 3,
+):
+    """Run the agent workflow with the given user input.
+
+    Args:
+        user_input: The user's query or request
+        debug: If True, enables debug level logging
+        max_plan_iterations: Maximum number of plan iterations
+        max_step_num: Maximum number of steps in a plan
+
+    Returns:
+        The final state after the workflow completes
+    """
+    if not user_input:
+        raise ValueError("Input could not be empty")
+
+    if debug:
+        enable_debug_logging()
+
+    logger.info(f"Starting workflow with user input: {user_input}")
+    initial_state = {
+        # Runtime Variables
+        "messages": [{"role": "user", "content": user_input}],
+    }
+    config = {
+        "configurable": {
+            "thread_id": "default",
+            "max_plan_iterations": max_plan_iterations,
+            "max_step_num": max_step_num,
+        },
+        "recursion_limit": 100,
+    }
+    last_message_cnt = 0
+    for s in graph.stream(input=initial_state, config=config, stream_mode="values"):
+        try:
+            if isinstance(s, dict) and "messages" in s:
+                if len(s["messages"]) <= last_message_cnt:
+                    continue
+                last_message_cnt = len(s["messages"])
+                message = s["messages"][-1]
+                if isinstance(message, tuple):
+                    print(message)
+                else:
+                    message.pretty_print()
+            else:
+                # For any other output format
+                print(f"Output: {s}")
+        except Exception as e:
+            logger.error(f"Error processing stream output: {e}")
+            print(f"Error processing output: {str(e)}")
+
+    logger.info("Workflow completed successfully")
+
+
+if __name__ == "__main__":
+    print(graph.get_graph(xray=True).draw_mermaid())