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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() |