Create app.py

app.py

@@ -0,0 +1,85 @@
+import gradio as gr
+import os
+import json
+import requests
+
+GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
+GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
+
+SYSTEM_MESSAGE = os.environ.get("System_Prompt")
+MODEL_NAME = "meta-llama/llama-4-maverick-17b-128e-instruct"
+MAX_TOKENS = 1024
+TEMPERATURE = 0.7
+TOP_P = 0.95
+
+def respond(message, history: list[tuple[str, str]]):
+
+    messages = [{"role": "system", "content": SYSTEM_MESSAGE}]
+    
+    for user_msg, assistant_msg in history:
+        if user_msg:
+            messages.append({"role": "user", "content": user_msg})
+        if assistant_msg:
+            messages.append({"role": "assistant", "content": assistant_msg})
+    
+    messages.append({"role": "user", "content": message})
+    
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {GROQ_API_KEY}"
+    }
+    
+    payload = {
+        "model": MODEL_NAME,
+        "messages": messages,
+        "max_tokens": MAX_TOKENS,
+        "temperature": TEMPERATURE,
+        "top_p": TOP_P,
+        "stream": True
+    }
+    
+    response = requests.post(
+        GROQ_API_URL,
+        headers=headers,
+        json=payload,
+        stream=True
+    )
+    
+    
+    accumulated_response = ""
+    for line in response.iter_lines():
+        if line:
+            
+            line_text = line.decode('utf-8')
+            if line_text.startswith("data: "):
+                data_str = line_text[6:]  
+                
+                
+                if data_str == "[DONE]":
+                    break
+                
+                try:
+                    data = json.loads(data_str)
+                    if 'choices' in data and len(data['choices']) > 0:
+                        delta = data['choices'][0].get('delta', {})
+                        if 'content' in delta and delta['content']:
+                            token = delta['content']
+                            accumulated_response += token
+                            yield accumulated_response
+                except json.JSONDecodeError:
+                    continue
+    
+    if not accumulated_response:
+        yield "Lo siento, ocurrió un error al procesar tu solicitud."
+
+demo = gr.ChatInterface(
+    respond,
+    examples=[["¡Bienvenido a Barcenas Gran Bajio!"],
+              ["¿Cuál es el objetivo principal de El Gran Bajío Network?"],
+              ["¿Qué beneficios clave obtengo al ser miembro?"],
+              ["¿Qué tipo de actividades o conexiones fomenta la red?"]
+             ]
+)
+
+if __name__ == "__main__":
+    demo.launch()