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| # ============================================================================= | |
| # MEETUP DEMO - AwesomeAgent (LangGraph + LLM Tools) | |
| # | |
| # TABLE OF CONTENTS | |
| # [1] Gradio GUI | |
| # ============================================================================= | |
| import os | |
| import gradio as gr | |
| import pandas as pd | |
| import requests | |
| from dotenv import load_dotenv | |
| from langfuse import get_client | |
| from agents.assistant_agent import AwesomeAgent | |
| load_dotenv() | |
| langfuse = get_client() | |
| # Verify connection | |
| if langfuse.auth_check(): | |
| print("Langfuse client is authenticated and ready!") | |
| else: | |
| print("Authentication failed. Please check your credentials and host.") | |
| # (Keep Constants as is) | |
| # --- Constants --- | |
| DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space" | |
| def get_local_file( | |
| api_url: str, task_id: str, file_name: str, folder: str = "downloads" | |
| ) -> str | None: | |
| if not file_name: | |
| return None | |
| os.makedirs(folder, exist_ok=True) | |
| local_path = os.path.join(folder, file_name) | |
| if os.path.exists(local_path): | |
| return local_path | |
| try: | |
| url = f"{api_url}/file={file_name}" | |
| r = requests.get(url, timeout=15) | |
| r.raise_for_status() | |
| except Exception: | |
| url = f"{api_url}/files/{task_id}" | |
| r = requests.get(url, timeout=15) | |
| r.raise_for_status() | |
| with open(local_path, "wb") as f: | |
| f.write(r.content) | |
| return local_path | |
| # Questions available here : https://agents-course-unit4-scoring.hf.space/questions | |
| # File available here : cca530fc-4052-43b2-b130-b30968d8aa44.png | |
| def run_and_submit_all(profile: gr.OAuthProfile | None): | |
| """ | |
| Fetches all questions, runs the BasicAgent on them, submits all answers, | |
| and displays the results. | |
| """ | |
| # --- 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 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.", None | |
| api_url = DEFAULT_API_URL | |
| questions_url = f"{api_url}/questions" | |
| submit_url = f"{api_url}/submit" | |
| # 1. Instantiate Agent ( modify this part to create your agent) | |
| try: | |
| agent = AwesomeAgent() | |
| except Exception as e: | |
| print(f"Error instantiating agent: {e}") | |
| return f"Error initializing agent: {e}", None | |
| # 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" | |
| print(agent_code) | |
| # 2. Fetch Questions | |
| 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.") | |
| return "Fetched questions list is empty or invalid format.", None | |
| print(f"Fetched {len(questions_data)} questions.") | |
| except requests.exceptions.RequestException as e: | |
| print(f"Error fetching questions: {e}") | |
| return f"Error fetching questions: {e}", 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 f"Error decoding server response for questions: {e}", None | |
| except Exception as e: | |
| print(f"An unexpected error occurred fetching questions: {e}") | |
| return f"An unexpected error occurred fetching questions: {e}", None | |
| # 3. Run your Agent | |
| results_log = [] | |
| answers_payload = [] | |
| print(f"Running agent on {len(questions_data)} questions...") | |
| ############################################################################################################ | |
| # TODO: REMOVE THIS PART - AVOID ASKING 50 QUESTIONS | |
| # questions_data = questions_data[:5] # the top 5 | |
| # questions_data = [questions_data[18]] # the 19th question | |
| keep = {1, 3, 7, 12, 16} | |
| questions_data[:] = [x for i, x in enumerate(questions_data, start=1) if i in keep] | |
| ############################################################################################################ | |
| for item in questions_data: | |
| task_id = item.get("task_id") | |
| question_text = item.get("question") | |
| file_name = item.get("file_name") | |
| if not task_id or question_text is None: | |
| print(f"Skipping item with missing task_id or question: {item}") | |
| continue | |
| try: | |
| input_file = get_local_file(api_url, task_id, file_name) | |
| submitted_answer = agent(question_text, input_file) | |
| answers_payload.append( | |
| {"task_id": task_id, "submitted_answer": submitted_answer} | |
| ) | |
| results_log.append( | |
| { | |
| "Task ID": task_id, | |
| "Question": question_text, | |
| "Submitted Answer": submitted_answer, | |
| } | |
| ) | |
| except Exception as e: | |
| print(f"Error running agent on task {task_id}: {e}") | |
| results_log.append( | |
| { | |
| "Task ID": task_id, | |
| "Question": question_text, | |
| "Submitted Answer": f"AGENT ERROR: {e}", | |
| } | |
| ) | |
| if not answers_payload: | |
| print("Agent did not produce any answers to submit.") | |
| return "Agent did not produce any answers to submit.", pd.DataFrame(results_log) | |
| # ############################################################################################################ | |
| # # TODO: REMOVE THIS PART - AVOID SUBMISSION | |
| # results_df = pd.DataFrame(results_log) | |
| # status = ( | |
| # f"✅ Dry run complete: processed {len(answers_payload)} question(s). " | |
| # f"Submission skipped." | |
| # ) | |
| # return status, results_df | |
| # ############################################################################################################ | |
| # 4. Prepare Submission | |
| submission_data = { | |
| "username": username.strip(), | |
| "agent_code": agent_code, | |
| "answers": answers_payload, | |
| } | |
| status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..." | |
| print(status_update) | |
| # 5. Submit | |
| 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("Submission successful.") | |
| results_df = pd.DataFrame(results_log) | |
| return final_status, results_df | |
| 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) | |
| results_df = pd.DataFrame(results_log) | |
| return status_message, results_df | |
| except requests.exceptions.Timeout: | |
| status_message = "Submission Failed: The request timed out." | |
| print(status_message) | |
| results_df = pd.DataFrame(results_log) | |
| return status_message, results_df | |
| except requests.exceptions.RequestException as e: | |
| status_message = f"Submission Failed: Network error - {e}" | |
| print(status_message) | |
| results_df = pd.DataFrame(results_log) | |
| return status_message, results_df | |
| except Exception as e: | |
| status_message = f"An unexpected error occurred during submission: {e}" | |
| print(status_message) | |
| results_df = pd.DataFrame(results_log) | |
| return status_message, results_df | |
| # [1] Gradio GUI - Build Gradio Interface using Blocks | |
| # --- | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# GAÏA Agent Evaluation Runner") | |
| gr.Markdown( | |
| """ | |
| **Instructions:** | |
| 1. Log in to your Hugging Face account using the button below. | |
| 2. Click 'Run Evaluation & Submit All Answers' to fetch questions, run the agent, submit answers, and see the score. | |
| **Disclaimers:** | |
| 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). | |
| """ | |
| ) | |
| gr.LoginButton() | |
| run_button = gr.Button("Run Evaluation & Submit All Answers") | |
| status_output = gr.Textbox( | |
| label="Run Status / Submission Result", lines=5, interactive=False | |
| ) | |
| # Removed max_rows=10 from DataFrame constructor | |
| results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True) | |
| run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table]) | |
| 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("-" * (60 + len(" App Starting ")) + "\n") | |
| print("Launching Gradio Interface for Basic Agent Evaluation...") | |
| demo.launch(debug=True, share=False) | |