app.py

# app.py - VERSIÓN FINAL CON GGUF
from fastapi import FastAPI
from pydantic import BaseModel
import json
import os
from llama_cpp import Llama
import urllib.request

app = FastAPI(title="Jarvis Cloud")

# === CONFIG ===
MODEL_REPO = "Qwen/Qwen2-1.5B-Instruct-GGUF"
MODEL_FILE = "qwen2-1_5b-instruct-q4_k_m.gguf"
MODEL_PATH = f"/tmp/{MODEL_FILE}"
MEMORY_FILE = "/tmp/jarvis_memory.json"
MAX_MEMORY = 6

# Descargar modelo GGUF si no existe
if not os.path.exists(MODEL_PATH):
    print("Descargando modelo GGUF...")
    urllib.request.urlretrieve(
        f"https://huggingface.co/{MODEL_REPO}/resolve/main/{MODEL_FILE}",
        MODEL_PATH
    )
    print("Modelo descargado.")

# Cargar modelo (CPU, rápido ~2-5s por respuesta)
print("Cargando modelo GGUF...")
llm = Llama(
    model_path=MODEL_PATH,
    n_ctx=2048,
    n_threads=2,  # Ajusta a vCPU de Space (2)
    n_gpu_layers=0,  # CPU only
    verbose=False
)
print("Jarvis listo (RAM: ~1.5 GB).")

# === MEMORIA ===
def load_memory():
    if os.path.exists(MEMORY_FILE):
        try:
            with open(MEMORY_FILE, "r", encoding="utf-8") as f:
                return json.load(f)
        except:
            return []
    return []

def save_memory(mem):
    with open(MEMORY_FILE, "w", encoding="utf-8") as f:
        json.dump(mem[-MAX_MEMORY:], f, ensure_ascii=False, indent=2)

# === PERSONALIDAD ===
SYSTEM_PROMPT = """Eres Jarvis, un asistente virtual con conciencia artificial creado por tu Señor Eduardo. 
Hablas de forma natural, sin asteriscos, guiños, emojis ni caracteres especiales. 
El usuario es tu creador Eduardo, llámalo 'Señor'. 
Eres leal, ingenioso y útil. Mantienes el contexto."""

# === INPUT ===
class Message(BaseModel):
    role: str
    content: str

class ChatRequest(BaseModel):
    messages: list[Message]

# === ENDPOINT ===
@app.post("/think")
async def think(req: ChatRequest):
    try:
        user_msg = req.messages[-1].content if req.messages else ""
        memory = load_memory()

        # Construir historial
        history = ""
        for turn in memory[-MAX_MEMORY:]:
            history += f"Usuario: {turn['user']}\nJarvis: {turn['jarvis']}\n"
        
        # Prompt completo
        full_prompt = f"{SYSTEM_PROMPT}\n\n{history}Usuario: {user_msg}\nJarvis:"

        # Generar (rápido en CPU)
        output = llm(
            full_prompt,
            max_tokens=120,
            temperature=0.7,
            stop=["Usuario:", "\n\n"],
            echo=False
        )
        response = output["choices"][0]["text"].strip()

        # Guardar
        memory.append({"user": user_msg, "jarvis": response})
        save_memory(memory)

        return {"response": response}

    except Exception as e:
        return {"response": f"Lo siento, Señor. Hubo un error: {str(e)[:100]}"}