Upload app.py
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app.py
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| 1 |
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import os
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| 2 |
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import gradio as gr
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| 3 |
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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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+
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
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class HfApiModel:
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def __init__(self, model_name="tiiuae/falcon-7b-instruct", api_key=None):
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self.model_name = model_name
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self.api_key = api_key or os.getenv("HF_TOKEN")
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if not self.api_key:
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raise ValueError("HF_TOKEN environment variable is missing.")
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def __call__(self, prompt):
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# Safely flatten and convert to string
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if hasattr(prompt, "content"):
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prompt = prompt.content
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elif isinstance(prompt, list):
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flat_parts = []
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for m in prompt:
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if isinstance(m, list):
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flat_parts.extend(str(sub) for sub in m)
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elif hasattr(m, "content"):
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flat_parts.append(str(m.content))
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else:
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flat_parts.append(str(m))
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prompt = " ".join(flat_parts)
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else:
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prompt = str(prompt)
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url = f"https://api-inference.huggingface.co/models/{self.model_name}"
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headers = {"Authorization": f"Bearer {self.api_key}"}
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payload = {
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"inputs": prompt,
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"options": {"wait_for_model": True}
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}
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response = requests.post(url, headers=headers, json=payload, timeout=60)
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response.raise_for_status()
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output = response.json()
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try:
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return output[0]["generated_text"]
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except Exception:
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return f"ERROR: {output}"
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def generate(self, prompt, **kwargs):
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return self.__call__(prompt)
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class BasicAgent:
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def __init__(self):
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print("β
BasicAgent initialized.")
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self.agent = CodeAgent(
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tools=[DuckDuckGoSearchTool()],
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model=HfApiModel(model_name="tiiuae/falcon-7b-instruct")
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)
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SYSTEM_PROMPT = """You are a general AI assistant. I will ask you a question. Report your thoughts, and
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finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER].
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YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated
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list of numbers and/or strings.
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If you are asked for a number, don't use comma to write your number neither use units such as $ or
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| 65 |
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percent sign unless specified otherwise.
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If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the
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digits in plain text unless specified otherwise.
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If you are asked for a comma separated list, apply the above rules depending of whether the element
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to be put in the list is a number or a string.
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"""
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self.agent.prompt_templates["system_prompt"] += SYSTEM_PROMPT
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| 72 |
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def __call__(self, question: str) -> str:
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print(f"π₯ Agent received question: {question[:60]}...")
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final_answer = self.agent.run(question)
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print(f"π€ Agent returning answer: {final_answer}")
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| 77 |
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return final_answer
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| 78 |
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| 79 |
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def run_and_submit_all(profile: gr.OAuthProfile | None):
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| 80 |
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space_id = os.getenv("SPACE_ID")
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| 82 |
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if profile:
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username = profile.username
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print(f"π Logged in as: {username}")
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else:
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return "β οΈ Please login with Hugging Face to continue.", None
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| 87 |
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| 88 |
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questions_url = f"{DEFAULT_API_URL}/questions"
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submit_url = f"{DEFAULT_API_URL}/submit"
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| 90 |
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| 91 |
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try:
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agent = BasicAgent()
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except Exception as e:
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return f"β Agent initialization failed: {e}", None
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agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else "Unknown"
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try:
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response = requests.get(questions_url, timeout=15)
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| 100 |
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response.raise_for_status()
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| 101 |
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questions_data = response.json()
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if not questions_data:
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return "β No questions received from the server.", None
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| 104 |
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except Exception as e:
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return f"β Failed to fetch questions: {e}", None
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| 106 |
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answers_payload = []
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| 108 |
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results_log = []
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| 109 |
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| 110 |
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for item in questions_data:
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| 111 |
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task_id = item.get("task_id")
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| 112 |
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question_text = item.get("question")
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| 113 |
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if not task_id or question_text is None:
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| 114 |
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continue
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| 115 |
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try:
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| 116 |
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submitted_answer = agent(question_text)
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| 117 |
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except Exception as e:
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| 118 |
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submitted_answer = f"AGENT ERROR: {e}"
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| 119 |
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answers_payload.append({
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| 120 |
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"task_id": task_id,
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| 121 |
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"submitted_answer": submitted_answer
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| 122 |
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})
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| 123 |
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results_log.append({
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| 124 |
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"Task ID": task_id,
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| 125 |
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"Question": question_text,
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| 126 |
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"Submitted Answer": submitted_answer
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| 127 |
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})
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| 128 |
+
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| 129 |
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if not answers_payload:
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return "β οΈ Agent failed to generate any answers.", pd.DataFrame(results_log)
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| 131 |
+
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| 132 |
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submission_data = {
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| 133 |
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"username": username.strip(),
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| 134 |
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"agent_code": agent_code,
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| 135 |
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"answers": answers_payload
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| 136 |
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}
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| 137 |
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| 138 |
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try:
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| 139 |
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response = requests.post(submit_url, json=submission_data, timeout=60)
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| 140 |
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response.raise_for_status()
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| 141 |
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result_data = response.json()
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| 142 |
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status = (
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| 143 |
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f"β
Submission Successful!\n"
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| 144 |
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f"User: {result_data.get('username')}\n"
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| 145 |
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f"Score: {result_data.get('score', '?')}% "
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| 146 |
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f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')})\n"
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| 147 |
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f"Message: {result_data.get('message', 'No message.')}"
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| 148 |
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)
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| 149 |
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return status, pd.DataFrame(results_log)
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| 150 |
+
except Exception as e:
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| 151 |
+
return f"β Submission failed: {e}", pd.DataFrame(results_log)
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| 152 |
+
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| 153 |
+
# Gradio UI
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| 154 |
+
with gr.Blocks() as demo:
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| 155 |
+
gr.Markdown("# π€ Basic Agent Evaluation Runner")
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| 156 |
+
gr.Markdown("Clone this space, log in, and run your agent on the questions. Modify `BasicAgent` logic if needed.")
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| 157 |
+
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| 158 |
+
gr.LoginButton()
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| 159 |
+
run_button = gr.Button("βΆοΈ Run Evaluation & Submit All Answers")
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| 160 |
+
status_output = gr.Textbox(label="π Run Status", lines=5, interactive=False)
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| 161 |
+
results_table = gr.DataFrame(label="π Results", wrap=True)
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| 162 |
+
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| 163 |
+
run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
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| 164 |
+
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| 165 |
+
if __name__ == "__main__":
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| 166 |
+
print("π Launching Gradio app...")
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| 167 |
+
demo.launch(debug=True, share=False)
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