Update app.py
#100
by
DenviWorking
- opened
app.py
CHANGED
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@@ -1,8 +1,10 @@
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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 inspect
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import pandas as pd
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# (Keep Constants as is)
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# --- Constants ---
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@@ -10,20 +12,15 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
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# --- Basic Agent Definition ---
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# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
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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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print(f"Agent received question (first 50 chars): {question[:50]}...")
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fixed_answer = "This is a default answer."
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print(f"Agent returning fixed answer: {fixed_answer}")
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return fixed_answer
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def run_and_submit_all( profile: gr.OAuthProfile | None):
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"""
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Fetches all questions, runs the BasicAgent on them, submits all answers,
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and displays the results.
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"""
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# --- Determine HF Space Runtime URL and Repo URL ---
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space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
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@@ -36,14 +33,15 @@ def run_and_submit_all( profile: gr.OAuthProfile | 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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-
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# 1. Instantiate Agent ( modify this part to create your agent)
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try:
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except Exception as e:
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# In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
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agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
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print(agent_code)
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@@ -51,7 +49,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
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# 2. Fetch Questions
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print(f"Fetching questions from: {questions_url}")
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try:
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response = requests.get(questions_url, timeout=
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response.raise_for_status()
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questions_data = response.json()
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if not questions_data:
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@@ -80,7 +78,15 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
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print(f"Skipping item with missing task_id or question: {item}")
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continue
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try:
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-
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answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
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results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
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except Exception as e:
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@@ -146,11 +152,9 @@ with gr.Blocks() as demo:
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gr.Markdown(
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"""
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**Instructions:**
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1. Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
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2. Log in to your Hugging Face account using the button below. This uses your HF username for submission.
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3. Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
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---
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**Disclaimers:**
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Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
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@@ -173,6 +177,7 @@ with gr.Blocks() as demo:
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if __name__ == "__main__":
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print("\n" + "-"*30 + " App Starting " + "-"*30)
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# Check for SPACE_HOST and SPACE_ID at startup for information
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space_host_startup = os.getenv("SPACE_HOST")
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space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
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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 dotenv.main import load_dotenv
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import agent
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import asyncio
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# (Keep Constants as is)
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# --- Constants ---
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# --- Basic Agent Definition ---
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# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
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def run_and_submit_all( profile: gr.OAuthProfile | None):
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"""
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Fetches all questions, runs the BasicAgent on them, submits all answers,
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and displays the results.
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"""
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load_dotenv()
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# --- Determine HF Space Runtime URL and Repo URL ---
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space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
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api_url = DEFAULT_API_URL
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questions_url = f"{api_url}/questions"
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files_url = f"{api_url}/files"
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submit_url = f"{api_url}/submit"
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# 1. Instantiate Agent ( modify this part to create your agent)
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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"Error instantiating agent: {e}")
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# return f"Error initializing agent: {e}", None
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# In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
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agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
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print(agent_code)
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# 2. Fetch Questions
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print(f"Fetching questions from: {questions_url}")
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try:
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response = requests.get(questions_url, timeout=60)
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response.raise_for_status()
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questions_data = response.json()
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if not questions_data:
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print(f"Skipping item with missing task_id or question: {item}")
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continue
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try:
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file_url = f"{files_url}/{task_id}"
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if "application/json" in requests.get(file_url).headers.get("Content-Type"):
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file_url = None
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agent_output = asyncio.run(agent.main(question_text, file_url))
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submitted_answer = str(agent_output)
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if 'FINAL ANSWER:' in submitted_answer:
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submitted_answer = submitted_answer.split('FINAL ANSWER:')[1].strip()
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answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
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results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
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except Exception as e:
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gr.Markdown(
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"""
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**Instructions:**
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1. Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
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2. Log in to your Hugging Face account using the button below. This uses your HF username for submission.
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3. Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
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---
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**Disclaimers:**
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Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
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if __name__ == "__main__":
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print("\n" + "-"*30 + " App Starting " + "-"*30)
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# Check for SPACE_HOST and SPACE_ID at startup for information
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space_host_startup = os.getenv("SPACE_HOST")
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space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
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