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| import os | |
| import requests | |
| requests.adapters.DEFAULT_TIMEOUT = 60 | |
| from dotenv import load_dotenv, find_dotenv | |
| _ = load_dotenv(find_dotenv()) # read local .env file | |
| hf_api_key = os.environ['HF_API_KEY'] | |
| # Helper function | |
| import requests, json | |
| from text_generation import Client | |
| #FalcomLM-instruct endpoint on the text_generation library | |
| URL = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta" | |
| client = Client(URL, timeout=120) | |
| #Back to Lesson 2, time flies! | |
| import gradio as gr | |
| def generate(input, slider): | |
| output = client.generate(input, max_new_tokens=slider).generated_text | |
| return output | |
| def format_chat_prompt(message, chat_history, instruction): | |
| prompt = f"System:{instruction}" | |
| for turn in chat_history: | |
| user_message, bot_message = turn | |
| prompt = f"{prompt}\nUser: {user_message}\nAssistant: {bot_message}" | |
| prompt = f"{prompt}\nUser: {message}\nAssistant:" | |
| return prompt | |
| def respond(message, chat_history, instruction, temperature=0.7): | |
| prompt = format_chat_prompt(message, chat_history, instruction) | |
| chat_history = chat_history + [[message, ""]] | |
| stream = client.generate_stream(prompt, | |
| max_new_tokens=1024, | |
| stop_sequences=["\nUser:", "<|endoftext|>"], | |
| temperature=temperature) | |
| #stop_sequences to not generate the user answer | |
| acc_text = "" | |
| #Streaming the tokens | |
| for idx, response in enumerate(stream): | |
| text_token = response.token.text | |
| if response.details: | |
| return | |
| if idx == 0 and text_token.startswith(" "): | |
| text_token = text_token[1:] | |
| acc_text += text_token | |
| last_turn = list(chat_history.pop(-1)) | |
| last_turn[-1] += acc_text | |
| chat_history = chat_history + [last_turn] | |
| yield "", chat_history | |
| acc_text = "" | |
| def loadGUI(): | |
| with gr.Blocks() as demo: | |
| chatbot = gr.Chatbot(height=240) #just to fit the notebook | |
| msg = gr.Textbox(label="Prompt") | |
| with gr.Accordion(label="Advanced options",open=False): | |
| system = gr.Textbox(label="System message", lines=2, value="A conversation between a user and an LLM-based AI assistant. The assistant gives helpful and honest answers.") | |
| temperature = gr.Slider(label="temperature", minimum=0.1, maximum=1, value=0.7, step=0.1) | |
| btn = gr.Button("Submit") | |
| clear = gr.ClearButton(components=[msg, chatbot], value="Clear console") | |
| btn.click(respond, inputs=[msg, chatbot, system], outputs=[msg, chatbot]) | |
| msg.submit(respond, inputs=[msg, chatbot, system], outputs=[msg, chatbot]) #Press enter to submit | |
| gr.close_all() | |
| demo.queue().launch(share=True) | |
| def main(): | |
| loadGUI() | |
| if __name__ == "__main__": | |
| main() | |