Spaces:
Sleeping
Sleeping
| import os | |
| import gradio as gr | |
| import requests | |
| import pandas as pd | |
| from my_agent import GeminiAgentContainer | |
| from markdownify import markdownify as to_markdown | |
| import time | |
| import json | |
| # (Keep Constants as is) | |
| # --- Constants --- | |
| DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space" | |
| # --- Global Variables --- | |
| questions = None | |
| results_log = [] | |
| answers_by_task = {} | |
| def load_questions(questions_url): | |
| print(f"Fetching questions from: {questions_url}") | |
| try: | |
| response = requests.get(questions_url, timeout=15) | |
| response.raise_for_status() | |
| questions_data = response.json() | |
| if not questions_data: | |
| print("Fetched questions list is empty or invalid.") | |
| return None | |
| print(f"Fetched {len(questions_data)} questions.") | |
| except requests.exceptions.RequestException as e: | |
| print(f"Error fetching questions: {e}") | |
| return None | |
| except requests.exceptions.JSONDecodeError as e: | |
| print(f"Error decoding JSON response from questions endpoint: {e}") | |
| print(f"Response text: {response.text[:500]}") | |
| return None | |
| except Exception as e: | |
| print(f"An unexpected error occurred fetching questions: {e}") | |
| return None | |
| return questions_data | |
| def answer_one(agent, question_data): | |
| """ | |
| Runs the agent on a single question and returns the result. | |
| """ | |
| task_id = question_data.get("task_id") | |
| question_text = question_data.get("question") | |
| filename = question_data.get("file_name") | |
| payload = None | |
| submitted_answer = None | |
| agent_error = None | |
| try: | |
| if not task_id or question_text is None: | |
| raise ValueError(f"Missing task_id or question in item: {question_data}") | |
| if filename: | |
| file_prompt = f"\nThere is an attached file with task id `{task_id}` available.\n" | |
| question_text = file_prompt + question_text | |
| submitted_answer = agent(question_text) | |
| payload = {"task_id": task_id, "submitted_answer": submitted_answer} | |
| except Exception as e: | |
| print(agent) | |
| print(f"Error running agent on task {task_id}: {e}") | |
| agent_error = f"AGENT ERROR: {e}" | |
| finally: | |
| log_entry = { | |
| "Task ID": task_id, | |
| "Question": question_text, | |
| "Submitted Answer": submitted_answer or agent_error, | |
| } | |
| return payload, log_entry | |
| def _submit_all(username, agent_code, answers_payload, submit_url): | |
| # Prepare Submission | |
| submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload} | |
| status_update = f"Submitting {len(answers_payload)} answers for user '{username}'..." | |
| print(status_update) | |
| # Submit Answers | |
| print(f"Submitting {len(answers_payload)} answers to: {submit_url}") | |
| try: | |
| response = requests.post(submit_url, json=submission_data, timeout=60) | |
| response.raise_for_status() | |
| result_data = response.json() | |
| final_status = ( | |
| f"Submission Successful!\n" | |
| f"User: {result_data.get('username')}\n" | |
| f"Overall Score: {result_data.get('score', 'N/A')}% " | |
| f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n" | |
| f"Message: {result_data.get('message', 'No message received.')}" | |
| ) | |
| print(final_status) | |
| return final_status | |
| except requests.exceptions.HTTPError as e: | |
| error_detail = f"Server responded with status {e.response.status_code}." | |
| try: | |
| error_json = e.response.json() | |
| error_detail += f" Detail: {error_json.get('detail', e.response.text)}" | |
| except requests.exceptions.JSONDecodeError: | |
| error_detail += f" Response: {e.response.text[:500]}" | |
| status_message = f"Submission Failed: {error_detail}" | |
| print(status_message) | |
| return status_message | |
| except requests.exceptions.Timeout: | |
| status_message = "Submission Failed: The request timed out." | |
| print(status_message) | |
| return status_message | |
| except requests.exceptions.RequestException as e: | |
| status_message = f"Submission Failed: Network error - {e}" | |
| print(status_message) | |
| return status_message | |
| except Exception as e: | |
| status_message = f"An unexpected error occurred during submission: {e}" | |
| print(status_message) | |
| return status_message | |
| def prepare_agent(api_key=None): | |
| # 1. Instantiate Agent ( modify this part to create your agent) | |
| try: | |
| agent = GeminiAgentContainer(api_key=api_key) | |
| print(agent.system_prompt) | |
| except Exception as e: | |
| print(f"Error instantiating agent: {e}") | |
| return None | |
| return agent | |
| def save_answers_to_file(): | |
| """ | |
| Submits the answers to a local file named with the current epoch time. | |
| """ | |
| if not answers_by_task: | |
| return ("Nothing to save, no answers found.") | |
| answers_payload = list(answers_by_task.values()) | |
| file_path = f"answers-{int(time.time())}.json" | |
| print(f"Saving answers to file: {file_path}") | |
| try: | |
| with open(file_path, "w") as file: | |
| json.dump(answers_payload, file, indent=4) | |
| submit_status = (f"Answers successfully written to {file_path}") | |
| except Exception as e: | |
| submit_status = (f"Error writing answers to file: {e}") | |
| print(submit_status) | |
| return submit_status | |
| def run_all(api_key: str | None = None): | |
| """ | |
| Fetches all questions, runs the BasicAgent on them, | |
| """ | |
| questions_url = f"{DEFAULT_API_URL}/questions" | |
| agent = prepare_agent(api_key) | |
| questions_data = load_questions(questions_url) | |
| # 3. Run your Agent | |
| print(f"Running agent on {len(questions_data)} questions...") | |
| for item in questions_data: | |
| payload_data, log_entry = answer_one(agent, item) | |
| if payload_data: | |
| task_id = payload_data.get("task_id") | |
| answers_by_task[task_id] = payload_data | |
| results_log.append(log_entry) | |
| time.sleep(3) | |
| if not answers_by_task: | |
| final_status = "Agent did not produce any answers to submit." | |
| else: | |
| final_status = f"Agent finished, {len(answers_by_task)} answers produced." | |
| print(final_status) | |
| return final_status, pd.DataFrame(results_log) | |
| def submit_all( profile: gr.OAuthProfile | None): | |
| """ | |
| Submits all answers and displays the results. | |
| """ | |
| submit_url = f"{DEFAULT_API_URL}/submit" | |
| if profile: | |
| username= f"{profile.username}" | |
| print(f"User logged in: {username}") | |
| else: | |
| print("User not logged in.") | |
| return "Please Login to Hugging Face with the button." | |
| # --- Determine HF Space Runtime URL and Repo URL --- | |
| space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code | |
| if not answers_by_task: | |
| submit_status = "No answers to submit." | |
| else: | |
| # 4. Submit all answers | |
| # 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) | |
| agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" | |
| submit_status = _submit_all(username, agent_code, list(answers_by_task.values()), submit_url) | |
| return submit_status | |
| # --- Build Gradio Interface using Blocks --- | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Basic Agent Evaluation Runner") | |
| gr.Markdown( | |
| """ | |
| **Instructions:** | |
| 1. Please use your own Gemini API key to run the agent. You can find your API key in your [Gemini account settings](https://gemini.com/account/settings). | |
| 2. Click 'Run Evaluation' to fetch questions, run the agent, and see the answers. | |
| 3. Click 'Submit All Answers' to submit the answers to the server. | |
| """ | |
| ) | |
| gr.LoginButton() | |
| api_key_input = gr.Textbox( | |
| label="Gemini API Key", | |
| placeholder="Enter your Gemini API key here", | |
| type="password", | |
| lines=1, | |
| visible=True | |
| ) | |
| run_button = gr.Button("Run Evaluation") | |
| save_button = gr.Button("Save Answers to File") | |
| submit_button = gr.Button("Submit All Answers") | |
| status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False) | |
| results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True) | |
| run_button.click( | |
| fn=run_all, | |
| inputs=[api_key_input], | |
| outputs=[status_output, results_table] | |
| ) | |
| save_button.click( | |
| fn=save_answers_to_file, | |
| outputs=[status_output] | |
| ) | |
| submit_button.click( | |
| fn=submit_all, | |
| outputs=[status_output] | |
| ) | |
| if __name__ == "__main__": | |
| print("\n" + "-"*30 + " App Starting " + "-"*30) | |
| # Check for SPACE_HOST and SPACE_ID at startup for information | |
| space_host_startup = os.getenv("SPACE_HOST") | |
| space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup | |
| if space_host_startup: | |
| print(f"✅ SPACE_HOST found: {space_host_startup}") | |
| print(f" Runtime URL should be: https://{space_host_startup}.hf.space") | |
| else: | |
| print("ℹ️ SPACE_HOST environment variable not found (running locally?).") | |
| if space_id_startup: # Print repo URLs if SPACE_ID is found | |
| print(f"✅ SPACE_ID found: {space_id_startup}") | |
| print(f" Repo URL: https://huggingface.co/spaces/{space_id_startup}") | |
| print(f" Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main") | |
| else: | |
| print("ℹ️ SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.") | |
| print(f"API KEY: {os.getenv('GOOGLE_API_KEY')}") | |
| print("-"*(60 + len(" App Starting ")) + "\n") | |
| print("Launching Gradio Interface for Basic Agent Evaluation...") | |
| demo.launch(debug=True, share=False) | |