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Update app.py
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app.py
CHANGED
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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 smolagents import CodeAgent, DuckDuckGoSearchTool
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from smolagents.models import
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# ---------------------------------------------------
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# Constants
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DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
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# ---------------------------------------------------
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# Agent
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# ---------------------------------------------------
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class BasicAgent:
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def __init__(self):
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print("Initializing
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)
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# Build agent
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self.agent = CodeAgent(
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tools=[
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DuckDuckGoSearchTool()
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],
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model=model,
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max_steps=
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verbosity_level=
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)
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print("Agent initialized
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-
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prompt = f"""
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You are
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- Think step-by-step.
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- Use web search if needed.
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- Solve the task accurately.
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- Return ONLY the final answer.
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-
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- No explanations
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Question:
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{question}
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result = self.agent.run(prompt)
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return "Could not determine the answer."
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return final_answer
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except Exception as e:
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print(f"Agent error: {e}")
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return
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# ---------------------------------------------------
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# ---------------------------------------------------
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def run_and_submit_all(profile: gr.OAuthProfile | None):
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# Get Space ID
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space_id = os.getenv("SPACE_ID")
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#
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if profile:
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username = profile.username
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print(f"Logged in as: {username}")
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else:
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return "Please login with Hugging Face
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# API URLs
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api_url = DEFAULT_API_URL
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questions_url = f"{api_url}/questions"
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submit_url = f"{api_url}/submit"
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# Initialize Agent
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# ---------------------------------------------------
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try:
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agent = BasicAgent()
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except Exception as e:
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print(f"
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return f"Error initializing agent: {e}", None
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#
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agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
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# ---------------------------------------------------
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except Exception as e:
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print(f"
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return f"Error fetching questions: {e}", None
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if not task_id or question_text is None:
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continue
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print(f"\nRunning task
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try:
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})
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# ---------------------------------------------------
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# Submit
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# ---------------------------------------------------
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submission_data = {
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"username": username.strip(),
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"answers": answers_payload
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}
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print("Submitting answers...")
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try:
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response = requests.post(
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submit_url,
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json=submission_data,
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except Exception as e:
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print(
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return
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# ---------------------------------------------------
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#
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# ---------------------------------------------------
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with gr.Blocks() as demo:
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"""
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This agent uses:
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- smolagents
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- DuckDuckGo
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- Qwen2.5-72B-Instruct
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"""
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)
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# HF Login
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gr.LoginButton()
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# Run Button
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run_button = gr.Button(
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"Run Evaluation & Submit"
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)
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# Outputs
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status_output = gr.Textbox(
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label="Submission Result",
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lines=8,
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wrap=True
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)
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# Button Action
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run_button.click(
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fn=run_and_submit_all,
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outputs=[
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)
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# ---------------------------------------------------
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# Launch
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# ---------------------------------------------------
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if __name__ == "__main__":
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print("\n==============================")
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print("Starting
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print("==============================\n")
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demo.launch(
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import os
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import re
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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 smolagents import CodeAgent, DuckDuckGoSearchTool
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from smolagents.models import OpenAIServerModel
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# ---------------------------------------------------
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# Constants
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DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
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# ---------------------------------------------------
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# Agent
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# ---------------------------------------------------
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class BasicAgent:
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def __init__(self):
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print("Initializing Groq Agent...")
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self.model = OpenAIServerModel(
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model_id="llama-3.3-70b-versatile",
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api_base="https://api.groq.com/openai/v1",
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api_key=os.getenv("GROQ_API_KEY")
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)
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self.agent = CodeAgent(
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tools=[
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DuckDuckGoSearchTool()
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],
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model=self.model,
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max_steps=3,
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verbosity_level=0
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)
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print("Groq Agent initialized.")
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# ---------------------------------------------------
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# Clean outputs for exact-match grading
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# ---------------------------------------------------
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def clean_answer(self, text):
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if text is None:
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return ""
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text = str(text)
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# remove markdown/code
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text = text.replace("```", "")
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text = text.replace("FINAL ANSWER:", "")
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text = text.replace("Answer:", "")
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# remove excessive whitespace
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text = re.sub(r"\s+", " ", text)
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# first line only
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text = text.split("\n")[0]
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# concise
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text = text.strip()
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return text[:300]
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# ---------------------------------------------------
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# Run agent
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# ---------------------------------------------------
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def __call__(self, question: str) -> str:
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prompt = f"""
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You are solving a GAIA benchmark question.
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IMPORTANT:
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- Return ONLY the final answer.
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- No reasoning.
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- No explanations.
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- No markdown.
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- No bullet points.
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- Be concise and accurate.
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- Use web search if needed.
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Question:
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{question}
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result = self.agent.run(prompt)
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cleaned = self.clean_answer(result)
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print(f"\nQUESTION:\n{question}")
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print(f"\nANSWER:\n{cleaned}")
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return cleaned
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except Exception as e:
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print(f"Agent error: {e}")
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return ""
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# ---------------------------------------------------
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# ---------------------------------------------------
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def run_and_submit_all(profile: gr.OAuthProfile | None):
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space_id = os.getenv("SPACE_ID")
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# Login check
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if profile:
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username = profile.username
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print(f"Logged in as: {username}")
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else:
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return "Please login with Hugging Face.", None
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api_url = DEFAULT_API_URL
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questions_url = f"{api_url}/questions"
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submit_url = f"{api_url}/submit"
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# Initialize Agent
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# ---------------------------------------------------
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try:
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agent = BasicAgent()
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except Exception as e:
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print(f"Initialization error: {e}")
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return f"Error initializing agent: {e}", None
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# Space repo link
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agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
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# ---------------------------------------------------
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except Exception as e:
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print(f"Question fetch error: {e}")
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return f"Error fetching questions: {e}", None
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if not task_id or question_text is None:
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continue
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print(f"\nRunning task {task_id}")
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try:
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})
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# ---------------------------------------------------
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# Submit
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# ---------------------------------------------------
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submission_data = {
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"username": username.strip(),
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"answers": answers_payload
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}
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try:
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print("Submitting answers...")
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response = requests.post(
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submit_url,
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json=submission_data,
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except Exception as e:
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error_message = f"Submission failed: {e}"
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print(error_message)
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return error_message, pd.DataFrame(results_log)
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# ---------------------------------------------------
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# UI
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# ---------------------------------------------------
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with gr.Blocks() as demo:
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"""
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This agent uses:
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- Groq API
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- Llama 3.3 70B
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- smolagents
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- DuckDuckGo Search
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"""
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)
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gr.LoginButton()
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run_button = gr.Button(
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"Run Evaluation & Submit"
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)
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status_output = gr.Textbox(
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label="Submission Result",
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lines=8,
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wrap=True
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)
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run_button.click(
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fn=run_and_submit_all,
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outputs=[
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)
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# ---------------------------------------------------
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# Launch
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# ---------------------------------------------------
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if __name__ == "__main__":
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print("\n==============================")
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print("Starting Groq Agent...")
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print("==============================\n")
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demo.launch(
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