Spaces:
Runtime error
Runtime error
| SYSTEM_PROMPT = "As an AI, my job is to help users create lesson plans that are both pedagogically sound and assessment-friendly. I should provide clear and concise prompts that help users create lesson plans with ten sections, including an explanation of the pedagogy and an assessment mechanism." | |
| TITLE = "Lesson Plan Generator" | |
| EXAMPLE_INPUT = """Create a lesson plan for a 9th-grade English class on the theme of "Identity" """ | |
| import gradio as gr | |
| from gradio_client import Client | |
| import os | |
| import requests | |
| tulu = "https://tonic1-tulu.hf.space/--replicas/vhgch/" | |
| def predict_beta(message, chatbot=[], system_prompt=""): | |
| client = Client(tulu) | |
| try: | |
| max_new_tokens = 350 | |
| temperature = 0.4 | |
| top_p = 0.9 | |
| repetition_penalty = 0.9 | |
| advanced = False | |
| # Making the prediction | |
| result = client.predict( | |
| message, | |
| system_prompt, | |
| max_new_tokens, | |
| temperature, | |
| top_p, | |
| repetition_penalty, | |
| advanced, | |
| fn_index=0 | |
| ) | |
| print("Raw API Response:", result) # Debugging print | |
| if result is not None: | |
| print("Processed bot_message:", result) # Debugging print | |
| return result | |
| else: | |
| print("No response or empty response from the model.") # Debugging print | |
| return None | |
| except Exception as e: | |
| error_msg = f"An error occurred: {str(e)}" | |
| print(error_msg) # Debugging print | |
| return None | |
| def test_preview_chatbot(message, history): | |
| response = predict_beta(message, history, SYSTEM_PROMPT) | |
| return response | |
| welcome_preview_message = f""" | |
| Welcome to **{TITLE}** using [Allen AI/Tulu](https://huggingface.co/allenai/tulu-2-dpo-13b) ! Say something like: | |
| ''{EXAMPLE_INPUT}'' | |
| """ | |
| chatbot_preview = gr.Chatbot(layout="panel", value=[(None, welcome_preview_message)]) | |
| textbox_preview = gr.Textbox(scale=7, container=False, value=EXAMPLE_INPUT) | |
| demo = gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview) | |
| demo.launch() |