Create app.py

app.py

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+import gradio as gr
+import requests
+import json
+
+# Definir variáveis de ambiente ou substituir com sua chave de API real
+API_KEY = "Sua_API_KEY_aqui"
+INVOKE_URL = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/functions/df2bee43-fb69-42b9-9ee5-f4eabbeaf3a8"
+
+headers = {
+    "Authorization": f"Bearer {API_KEY}",
+    "accept": "text/event-stream",
+    "content-type": "application/json",
+}
+
+BASE_SYSTEM_MESSAGE = "I carefully provide accurate, factual, thoughtful, nuanced answers and am brilliant at reasoning."
+
+def clear_chat(chat_history_state, chat_message):
+    chat_history_state = []
+    chat_message = ''
+    return chat_history_state, chat_message
+
+def user(message, history):
+    history = history or []
+    history.append({"role": "user", "content": message})
+    return "", history
+
+def call_api(history, max_tokens, temperature, top_p, seed=42):
+    payload = {
+        "messages": history,
+        "temperature": temperature,
+        "top_p": top_p,
+        "max_tokens": max_tokens,
+        "seed": seed,
+        "stream": True
+    }
+    response = requests.post(INVOKE_URL, headers=headers, json=payload, stream=True)
+    full_response = ""
+    for line in response.iter_lines():
+        if line:
+            decoded_line = line.decode("utf-8")
+            if "data:" in decoded_line:
+                json_data = json.loads(decoded_line.replace("data:", ""))
+                if "choices" in json_data and len(json_data["choices"]) > 0:
+                    deltas = json_data["choices"][0].get("delta", {})
+                    if "content" in deltas:
+                        full_response += deltas["content"]
+    return full_response
+
+def chat(history, system_message, max_tokens, temperature, top_p, top_k, repetition_penalty):
+    system_message_to_use = system_message if system_message.strip() else BASE_SYSTEM_MESSAGE
+    if history and "role" in history[-1] and history[-1]["role"] == "user":
+        history.append({"role": "system", "content": system_message_to_use})
+    assistant_response = call_api(history, max_tokens, temperature, top_p)
+    if assistant_response:
+        history.append({"role": "assistant", "content": assistant_response})
+    return history, "", ""
+
+# Gradio interface setup
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("## Your Chatbot Interface")
+    chatbot = gr.Chatbot()
+    message = gr.Textbox(label="What do you want to chat about?", placeholder="Ask me anything.", lines=3)
+    submit = gr.Button(value="Send message")
+    clear = gr.Button(value="New topic")
+    system_msg = gr.Textbox(BASE_SYSTEM_MESSAGE, label="System Message", placeholder="System prompt.", lines=5)
+    max_tokens = gr.Slider(20, 512, label="Max Tokens", step=20, value=500)
+    temperature = gr.Slider(0.0, 1.0, label="Temperature", step=0.1, value=0.7)
+    top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.95)
+    chat_history_state = gr.State([])
+
+    def update_chatbot(interface, inputs, outputs):
+        message, chat_history = inputs
+        _, chat_history, _ = user(message, chat_history)
+        chat_history, _, _ = chat(chat_history, system_msg.value, max_tokens.value, temperature.value, top_p.value, 40, 1.1)
+        outputs[0].update(chat_history)
+        outputs[1].update(chat_history)
+        outputs[2].update("")
+
+    submit.click(
+        fn=update_chatbot,
+        inputs=[message, chat_history_state],
+        outputs=[chatbot, chat_history_state, message]
+    )
+
+    clear.click(
+        fn=lambda: clear_chat([], ""),
+        inputs=[chat_history_state, message],
+        outputs=[chat_history_state, message]
+    )
+
+demo.launch()