Update app.py
Browse files
app.py
CHANGED
@@ -119,7 +119,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None, openai_key: str, google_
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space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
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if profile:
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username= f"{profile.username}"
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print(f"User logged in: {username}")
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else:
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print("User not logged in.")
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@@ -131,11 +131,11 @@ def run_and_submit_all(profile: gr.OAuthProfile | None, openai_key: str, google_
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# 1. Instantiate Agent ( modify this part to create your agent)
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try:
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agent = Agent(agent_instance)
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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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agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
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print(agent_code)
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@@ -167,17 +167,16 @@ def run_and_submit_all(profile: gr.OAuthProfile | None, openai_key: str, google_
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for item in questions_data:
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task_id = item.get("task_id")
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question_text = item.get("question")
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file_name = item.get("file_name", "")
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if not task_id or question_text is 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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submitted_answer = agent(question_text
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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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-
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-
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if not answers_payload:
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print("Agent did not produce any answers to submit.")
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@@ -238,16 +237,14 @@ with gr.Blocks() as demo:
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gr.Markdown(
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"""
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**Instructions:**
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-
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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. Enter your OpenAI and Google API keys below (
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4. 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 (
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This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a
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"""
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)
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@@ -255,33 +252,15 @@ with gr.Blocks() as demo:
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openai_key_box = gr.Textbox(label="OpenAI API Key", type="password", placeholder="sk-...", lines=1)
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google_key_box = gr.Textbox(label="Google API Key", type="password", placeholder="AIza...", lines=1)
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set_keys_btn = gr.Button("Set API Keys")
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status_api_keys = gr.Textbox(label="API Key Status", lines=1, interactive=False)
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def set_api_keys(openai_key, google_key):
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if openai_key:
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os.environ["OPENAI_API_KEY"] = openai_key
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if google_key:
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os.environ["GOOGLE_API_KEY"] = google_key
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if openai_key or google_key:
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return "API keys set for this session."
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return "No API keys provided."
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set_keys_btn.click(
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fn=set_api_keys,
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inputs=[openai_key_box, google_key_box],
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outputs=status_api_keys
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)
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run_button = gr.Button("Run Evaluation & Submit All Answers")
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status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
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# Removed max_rows=10 from DataFrame constructor
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results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
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run_button.click(
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fn=run_and_submit_all,
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inputs=[
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outputs=[status_output, results_table]
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)
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space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
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if profile:
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username = f"{profile.username}"
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print(f"User logged in: {username}")
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else:
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print("User not logged in.")
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# 1. Instantiate Agent ( modify this part to create your agent)
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try:
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agent = Agent(build_supervisor_agent(openai_key, google_key))
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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 ( useful 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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for item in questions_data:
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task_id = item.get("task_id")
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question_text = item.get("question")
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if not task_id or question_text is 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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submitted_answer = agent(question_text)
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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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print(f"Error running agent on task {task_id}: {e}")
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results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
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if not answers_payload:
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print("Agent did not produce any answers to submit.")
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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. Enter your OpenAI and Google API keys below (if required by your agent).
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4. 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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+
This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance, for the delay process of the submit button, a solution could be to cache the answers and submit in a separate action or even to answer the questions in async.
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"""
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)
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openai_key_box = gr.Textbox(label="OpenAI API Key", type="password", placeholder="sk-...", lines=1)
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google_key_box = gr.Textbox(label="Google API Key", type="password", placeholder="AIza...", lines=1)
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run_button = gr.Button("Run Evaluation & Submit All Answers")
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status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
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results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
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run_button.click(
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fn=run_and_submit_all,
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inputs=[openai_key_box, google_key_box],
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outputs=[status_output, results_table]
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)
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