Update app.py
Browse files
app.py
CHANGED
@@ -2,6 +2,8 @@ import os
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import gradio as gr
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import requests
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import pandas as pd
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from langchain_core.messages import HumanMessage
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from langgraph_agent import build_graph
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@@ -101,6 +103,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
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# 3. Run your Agent
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results_log = []
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answers_payload = []
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print(f"Running agent on {len(questions_data)} questions...")
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for item in questions_data:
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task_id = item.get("task_id")
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@@ -110,10 +113,11 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
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continue
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try:
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submitted_answer = agent(question_text, task_id=task_id)
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print(f"
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answers_payload.append({
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"task_id": task_id,
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"
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})
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results_log.append({
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"Task ID": task_id,
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@@ -122,6 +126,11 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
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})
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except Exception as e:
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print(f"Error running agent on task {task_id}: {e}")
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results_log.append({
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"Task ID": task_id,
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"Question": question_text,
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@@ -132,18 +141,28 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
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print("Agent did not produce any answers to submit.")
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return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
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#
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"username": username.strip(),
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"agent_code": agent_code
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"answers": answers_payload
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}
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print(f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'...")
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# 5. Submit
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print(f"Submitting
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try:
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response = requests.post(submit_url,
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response.raise_for_status()
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result_data = response.json()
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final_status = (
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import gradio as gr
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import requests
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import pandas as pd
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import json
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import io
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from langchain_core.messages import HumanMessage
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from langgraph_agent import build_graph
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# 3. Run your Agent
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results_log = []
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answers_payload = []
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print(f"Running agent on {len(questions_data)} questions...")
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for item in questions_data:
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task_id = item.get("task_id")
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continue
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try:
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submitted_answer = agent(question_text, task_id=task_id)
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print(f"Answer for task {task_id}: '{submitted_answer}'")
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answers_payload.append({
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"task_id": task_id,
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"model_answer": submitted_answer,
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# "reasoning_trace": None # Optional: add reasoning trace if available
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})
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results_log.append({
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"Task ID": task_id,
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})
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except Exception as e:
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print(f"Error running agent on task {task_id}: {e}")
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answers_payload.append({
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"task_id": task_id,
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"model_answer": f"AGENT ERROR: {e}",
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# "reasoning_trace": None
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})
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results_log.append({
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"Task ID": task_id,
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"Question": question_text,
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print("Agent did not produce any answers to submit.")
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return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
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# Serialize to JSON Lines string
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json_lines_str = "\n".join(json.dumps(ans) for ans in answers_payload)
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# Prepare file-like object for upload
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file_like = io.BytesIO(json_lines_str.encode("utf-8"))
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file_like.name = "submission.jsonl" # Filename required for multipart upload
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# Prepare multipart form data
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files = {
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"file": (file_like.name, file_like, "application/jsonl")
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}
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data = {
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"username": username.strip(),
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"agent_code": agent_code
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}
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print(f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'...")
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# 5. Submit
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print(f"Submitting answers to: {submit_url}")
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try:
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response = requests.post(submit_url, data=data, files=files, timeout=60)
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response.raise_for_status()
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result_data = response.json()
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final_status = (
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