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import gradio as gr |
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import requests |
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import os |
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import json |
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API_KEY = os.getenv('API_KEY') |
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INVOKE_URL = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/functions/df2bee43-fb69-42b9-9ee5-f4eabbeaf3a8" |
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FETCH_URL_FORMAT = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/status/" |
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headers = { |
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"Authorization": f"Bearer {API_KEY}", |
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"Accept": "application/json", |
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"Content-Type": "application/json", |
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} |
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BASE_SYSTEM_MESSAGE = "I carefully provide accurate, factual, thoughtful, nuanced answers and am brilliant at reasoning." |
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def call_nvidia_api(history, system_message, max_tokens, temperature, top_p): |
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messages = [{"role": "system", "content": system_message}] if system_message else [] |
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messages.extend([{"role": "user", "content": msg[0]}, {"role": "assistant", "content": msg[1]}] for msg in history if msg[1]) |
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payload = { |
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"messages": messages, |
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"temperature": temperature, |
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"top_p": top_p, |
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"max_tokens": max_tokens, |
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"stream": False |
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} |
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session = requests.Session() |
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response = session.post(INVOKE_URL, headers=headers, json=payload) |
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while response.status_code == 202: |
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request_id = response.headers.get("NVCF-REQID") |
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fetch_url = FETCH_URL_FORMAT + request_id |
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response = session.get(fetch_url, headers=headers) |
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response.raise_for_status() |
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response_body = response.json() |
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if response_body.get("choices"): |
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assistant_message = response_body["choices"][0]["message"]["content"] |
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return assistant_message, response_body["choices"][0] |
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else: |
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return "Desculpe, ocorreu um erro ao gerar a resposta.", None |
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def chatbot_submit(message, chat_history_ui, chat_history_api, system_message, max_tokens_val, temperature_val, top_p_val): |
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print("Updating chatbot...") |
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assistant_message, api_response = call_nvidia_api(chat_history_api, system_message, max_tokens_val, temperature_val, top_p_val) |
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chat_history_ui.append([message, assistant_message]) |
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if api_response: |
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chat_history_api.append(api_response) |
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return assistant_message, chat_history_ui, chat_history_api |
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system_msg = gr.Textbox(BASE_SYSTEM_MESSAGE, label="System Message", placeholder="System prompt.", lines=5) |
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max_tokens = gr.Slider(20, 1024, label="Max Tokens", step=20, value=1024) |
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temperature = gr.Slider(0.0, 1.0, label="Temperature", step=0.1, value=0.2) |
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top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.7) |
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with gr.Blocks() as demo: |
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chat_history_state_ui = gr.State([]) |
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chat_history_state_api = gr.State([]) |
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chatbot = gr.ChatInterface( |
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fn=chatbot_submit, |
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inputs=[gr.Textbox(label="Your Message"), chat_history_state_ui, chat_history_state_api, system_msg, max_tokens, temperature, top_p], |
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outputs=[gr.Text(label="Assistant Response"), chat_history_state_ui, chat_history_state_api], |
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title="Chatbot Interface" |
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description="""<div style="text-align: center; font-size: 1.5em; margin-bottom: 20px;"> |
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<strong>Explore the Capabilities of LLAMA 2 70B</strong> |
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</div> |
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<p>Llama 2 is a large language AI model capable of generating text and code in response to prompts.</p> |
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<p><strong>How to Use:</strong></p> |
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<ol> |
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<li>Enter your <strong>message</strong> in the textbox to start a conversation or ask a question.</li> |
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<li>Adjust the parameters in the "Additional Inputs" accordion to control the model's behavior.</li> |
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<li>Use the buttons below the chatbot to submit your query, clear the chat history, or perform other actions.</li> |
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</ol> |
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<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> |
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<p><strong>HF Created by:</strong> @artificialguybr (<a href="https://twitter.com/artificialguybr">Twitter</a>)</p> |
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<p><strong>Discover more:</strong> <a href="https://artificialguy.com">artificialguy.com</a></p>""", |
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submit_btn="Submit", |
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clear_btn="🗑️ Clear", |
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) |
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demo.launch() |
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