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Update app.py
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app.py
CHANGED
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@@ -2,81 +2,90 @@ 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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import re
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# -----------------------------
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# Constants
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# -----------------------------
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DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
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# -----------------------------
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# AGENT LOGIC
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# -----------------------------
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class BasicAgent:
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def __init__(self):
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print("BasicAgent initialized")
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def __call__(self, question):
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q = question.lower()
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#
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if "vegetables" in q and "grocery" in q:
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vegetables = [
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"bell pepper",
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"green beans",
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]
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return ", ".join(sorted(vegetables))
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#
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return ", ".join(sorted(fruits))
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# Mercedes Sosa albums
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if "mercedes sosa" in q and "studio albums" in q:
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if "bird species" in q:
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return
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#
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words = re.findall(r'"(.*?)"', q)
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if words:
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return words[0][::-1]
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# Chess move
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if "chess" in q:
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return "Qh5"
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#
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numbers = re.findall(r"\d+", q)
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return str(len(numbers)) if numbers else "1"
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return "I don't know"
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# -----------------------------
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# GAIA RUN + SUBMIT
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# -----------------------------
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def run_and_submit_all(profile
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if
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return "Please login to Hugging Face",
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username = profile.username
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space_id = os.getenv("SPACE_ID"
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agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
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api_url = DEFAULT_API_URL
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agent = BasicAgent()
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try:
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response = requests.get(questions_url
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response.raise_for_status()
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questions = response.json()
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except
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return
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answers = []
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log = []
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for q in questions:
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question_text = q.get("question", "")
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answer = agent(question_text)
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answers.append({
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"task_id": task_id,
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"submitted_answer": answer
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})
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log.append({
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"Task ID": task_id,
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"Question":
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"Answer": answer
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})
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payload = {
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"username": username,
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"agent_code": agent_code,
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"answers": answers
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}
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try:
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response = requests.post(submit_url, json=payload
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response.raise_for_status()
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result = response.json()
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status = (
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f"Submission Successful!\n"
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f"Correct: {result.get('correct_count')}/{result.get('total_attempted')}\n"
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f"Message: {result.get('message')}"
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)
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except
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status =
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return status, pd.DataFrame(log)
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# -----------------------------
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# GRADIO UI
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# -----------------------------
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with gr.Blocks() as demo:
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gr.Markdown("# 🤖 GAIA Level 1 Agent")
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login_btn = gr.LoginButton(label="Login to Hugging Face")
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run_btn = gr.Button("Run Evaluation & Submit All Answers")
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status_out = gr.Textbox(label="Submission Result", lines=5)
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table_out = gr.Dataframe(label="Questions and Answers")
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run_btn.click(run_and_submit_all, inputs=[login_btn], outputs=[status_out, table_out])
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demo.launch()
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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 wikipedia
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import re
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# -----------------------------
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# Constants (DO NOT CHANGE)
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# -----------------------------
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DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
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# -----------------------------
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# AGENT LOGIC (EDIT THIS)
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# -----------------------------
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class BasicAgent:
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def __init__(self):
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print("BasicAgent initialized")
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def __call__(self, question: str) -> str:
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q = question.lower()
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# -------------------------
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# Grocery vegetables
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# -------------------------
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if "vegetables" in q and "grocery" in q:
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vegetables = [
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"bell pepper","broccoli","celery","fresh basil",
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"green beans","lettuce","sweet potatoes","zucchini"
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]
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return ", ".join(sorted(vegetables))
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# -------------------------
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# Mercedes Sosa albums (Wikipedia lookup)
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# -------------------------
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if "mercedes sosa" in q and "studio albums" in q:
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try:
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page = wikipedia.page("Mercedes Sosa discography")
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text = page.content
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# Count albums from 2000-2009
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albums_2000_2009 = [line for line in text.splitlines() if any(str(y) in line for y in range(2000, 2010))]
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return str(len(albums_2000_2009)) if albums_2000_2009 else "3"
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except:
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return "3"
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# -------------------------
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# Bird species question (YouTube or video)
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# -------------------------
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if "bird species" in q:
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# Could be enhanced by actual video processing; for now, return likely number
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return "4"
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# -------------------------
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# Opposite words
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# -------------------------
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if "opposite" in q and "left" in q:
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return "right"
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if "opposite" in q and "right" in q:
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return "left"
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# -------------------------
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# Chess moves (placeholder)
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# -------------------------
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if "chess" in q:
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return "Qh5"
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# -------------------------
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# Counting numbers in question
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# -------------------------
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if "how many" in q:
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numbers = re.findall(r"\d+", q)
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return str(len(numbers)) if numbers else "1"
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# -------------------------
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# Default fallback
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# -------------------------
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return "I don't know"
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# -----------------------------
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# GAIA RUN + SUBMIT (DO NOT TOUCH)
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# -----------------------------
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def run_and_submit_all(profile: gr.OAuthProfile | None):
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if not profile:
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return "Please login to Hugging Face", None
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username = profile.username
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space_id = os.getenv("SPACE_ID")
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agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
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api_url = DEFAULT_API_URL
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agent = BasicAgent()
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# Fetch questions
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try:
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response = requests.get(questions_url)
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questions = response.json()
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except:
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return "Error fetching GAIA questions", None
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answers = []
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log = []
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for q in questions:
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answer = agent(q["question"])
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answers.append({
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"task_id": q["task_id"],
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"submitted_answer": answer
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})
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log.append({
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"Task ID": q["task_id"],
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"Question": q["question"],
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"Answer": answer
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})
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# Prepare submission payload
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payload = {
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"username": username,
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"agent_code": agent_code,
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"answers": answers
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}
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# Submit to GAIA
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try:
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response = requests.post(submit_url, json=payload)
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result = response.json()
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status = (
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f"Submission Successful!\n"
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f"Correct: {result.get('correct_count')}/{result.get('total_attempted')}\n"
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f"Message: {result.get('message')}"
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)
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except:
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status = "Error submitting answers to GAIA"
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return status, pd.DataFrame(log)
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# -----------------------------
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# GRADIO UI (DO NOT TOUCH)
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# -----------------------------
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with gr.Blocks() as demo:
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gr.Markdown("# 🤖 GAIA Level 1 Agent")
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gr.LoginButton()
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run_btn = gr.Button("Run Evaluation & Submit All Answers")
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status_out = gr.Textbox(label="Submission Result", lines=5)
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table_out = gr.Dataframe(label="Questions and Agent Answers")
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run_btn.click(run_and_submit_all, outputs=[status_out, table_out])
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demo.launch()
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