| import gradio as gr | |
| import requests | |
| import json | |
| import os | |
| API_KEY = os.getenv('API_KEY') | |
| INVOKE_URL = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/functions/0e349b44-440a-44e1-93e9-abe8dcb27158" | |
| FETCH_URL_FORMAT = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/status/" | |
| headers = { | |
| "Authorization": f"Bearer {API_KEY}", | |
| "Accept": "application/json", | |
| "Content-Type": "application/json", | |
| } | |
| BASE_SYSTEM_MESSAGE = "I carefully provide accurate, factual, thoughtful, nuanced answers and am brilliant at reasoning." | |
| def user(message, history, system_message=None): | |
| print(f"User message: {message}") | |
| history = history or [] | |
| if system_message: | |
| history.append({"role": "system", "content": system_message}) | |
| history.append({"role": "user", "content": message}) | |
| return history | |
| def call_nvidia_api(history, max_tokens, temperature, top_p): | |
| payload = { | |
| "messages": history, | |
| "temperature": temperature, | |
| "top_p": top_p, | |
| "max_tokens": max_tokens, | |
| "stream": False | |
| } | |
| print(f"Payload enviado: {payload}") | |
| session = requests.Session() | |
| response = session.post(INVOKE_URL, headers=headers, json=payload) | |
| while response.status_code == 202: | |
| request_id = response.headers.get("NVCF-REQID") | |
| fetch_url = FETCH_URL_FORMAT + request_id | |
| response = session.get(fetch_url, headers=headers) | |
| response.raise_for_status() | |
| response_body = response.json() | |
| print(f"Payload recebido: {response_body}") | |
| if response_body["choices"]: | |
| assistant_message = response_body["choices"][0]["message"]["content"] | |
| history.append({"role": "assistant", "content": assistant_message}) | |
| return history | |
| def chat(history, system_message, max_tokens, temperature, top_p, top_k, repetition_penalty): | |
| print("Starting chat...") | |
| updated_history = user(None, history, system_message) | |
| updated_history = call_nvidia_api(updated_history, max_tokens, temperature, top_p) | |
| return updated_history, "" | |
| def update_chatbot(message, chat_history, system_message, max_tokens, temperature, top_p): | |
| print("Updating chatbot...") | |
| chat_history = user(message, chat_history, system_message if not chat_history else None) | |
| chat_history = call_nvidia_api(chat_history, max_tokens, temperature, top_p) | |
| return chat_history | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown("LLAMA 2 70B Free Demo") | |
| description = """ | |
| <div style="text-align: center; font-size: 1.5em; margin-bottom: 20px;"> | |
| <strong>Explore the Capabilities of LLAMA 2 70B</strong> | |
| </div> | |
| <p>Llama 2 is a large language AI model capable of generating text and code in response to prompts.</p> | |
| <p><strong>How to Use:</strong></p> | |
| <ol> | |
| <li>Enter your <strong>message</strong> in the textbox to start a conversation or ask a question.</li> | |
| <li>Adjust the parameters in the "Additional Inputs" accordion to control the model's behavior.</li> | |
| <li>Use the buttons below the chatbot to submit your query, clear the chat history, or perform other actions.</li> | |
| </ol> | |
| <p><strong>Powered by NVIDIA's cutting-edge AI API, LLAMA 2 70B offers an unparalleled opportunity to interact with an AI model of exceptional conversational ability, accessible to everyone at no cost.</strong></p> | |
| <p><strong>HF Created by:</strong> @artificialguybr (<a href="https://twitter.com/artificialguybr">Twitter</a>)</p> | |
| <p><strong>Discover more:</strong> <a href="https://artificialguy.com">artificialguy.com</a></p> | |
| """ | |
| gr.Markdown(description) | |
| chat_history_state = gr.State([]) | |
| system_msg = gr.Textbox(BASE_SYSTEM_MESSAGE, label="System Message", placeholder="System prompt.", lines=5) | |
| max_tokens = gr.Slider(20, 1024, label="Max Tokens", step=20, value=1024) | |
| temperature = gr.Slider(0.0, 1.0, label="Temperature", step=0.1, value=0.2) | |
| top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.7) | |
| chatbot = gr.ChatInterface( | |
| fn=lambda message, history: update_chatbot(message, history, system_msg.value, max_tokens.value, temperature.value, top_p.value), | |
| additional_inputs=[system_msg, max_tokens, temperature, top_p], | |
| title="LLAMA 2 70B Chatbot", | |
| submit_btn="Submit", | |
| clear_btn="🗑️ Clear", | |
| ) | |
| def clear_chat(): | |
| chat_history_state.value = [] | |
| chatbot.textbox.value = "" | |
| chatbot.clear(outputs=[chat_history_state, chatbot.textbox]) | |
| demo.launch() |