quick_specific_agent_test.py

import os
import sys
import tempfile
import requests
from basic_agent import BasicAgent, DEFAULT_API_URL
from langchain_core.messages import HumanMessage
from langfuse.langchain import CallbackHandler

# Initialize Langfuse CallbackHandler for LangGraph/Langchain (tracing)
try:
    langfuse_handler = CallbackHandler()
except Exception as e:
    print(f"Warning: Could not initialize Langfuse handler: {e}")
    langfuse_handler = None

# Default Task ID (replace with your desired one or pass via CLI)
DEFAULT_TASK_ID = "f918266a-b3e0-4914-865d-4faa564f1aef"

def fetch_question_by_id(task_id: str, api_base: str = DEFAULT_API_URL):
    """Return JSON of a question for a given task_id.

    The scoring API does not (yet) expose an explicit /question/{id} endpoint,
    so we fetch the full /questions list and filter locally. This works fine
    because the list is small (<100 items).
    """
    try:
        resp = requests.get(f"{api_base}/questions", timeout=30)
        resp.raise_for_status()
        questions = resp.json()
    except Exception as e:
        raise RuntimeError(f"Failed to fetch questions list: {e}") from e

    for q in questions:
        if str(q.get("task_id")) == str(task_id):
            return q

    raise ValueError(f"Task ID {task_id} not found in /questions list.")


def maybe_download_file(task_id: str, api_base: str = DEFAULT_API_URL) -> str | None:
    """Try to download the file associated with a given task id. Returns local path or None."""
    url = f"{api_base}/files/{task_id}"
    try:
        resp = requests.get(url, timeout=60)
        if resp.status_code != 200:
            print(f"No file associated with task {task_id} (status {resp.status_code}).")
            return None
        # Create temp file with same name from headers if available
        filename = resp.headers.get("content-disposition", "").split("filename=")[-1].strip("\"") or f"{task_id}_attachment"
        tmp_path = os.path.join(tempfile.gettempdir(), filename)
        with open(tmp_path, "wb") as f:
            f.write(resp.content)
        print(f"Downloaded attachment to {tmp_path}")
        return tmp_path
    except requests.HTTPError as e:
        print(f"Could not download file for task {task_id}: {e}")
    except Exception as e:
        print(f"Error downloading file: {e}")
    return None


def main():
    # Determine the task ID (CLI arg > env var > default)
    task_id = (
        sys.argv[1] if len(sys.argv) > 1 else os.environ.get("TASK_ID", DEFAULT_TASK_ID)
    )
    print(f"Using task ID: {task_id}")

    q = fetch_question_by_id(task_id)
    question_text = q["question"]

    print("\n=== Specific Question ===")
    print(f"Task ID : {task_id}")
    print(f"Question: {question_text}")

    # Attempt to get attachment if any
    maybe_download_file(task_id)

    # Run the agent
    agent = BasicAgent()
    result = agent.agent.invoke({"messages": [HumanMessage(content=question_text)]}, config={"callbacks": [langfuse_handler]})
    if isinstance(result, dict) and "messages" in result and result["messages"]:
        answer = result["messages"][-1].content.strip()
    else:
        answer = str(result)
    print("\n=== Agent Answer ===")
    print(answer)


if __name__ == "__main__":
    main()