app.py

# ╔════════════════════════════════════════════════════════════════════════════╗
# ║ PIPELINE v32: 100% COMPATÍVEL HF SPACES | ZERO WARNINGS ║
# ║ Corrige: Chatbot type='messages' | JSON sem 'lines' ║
# ╚════════════════════════════════════════════════════════════════════════════╝

import os
import json
import re
import time
from datetime import datetime
import gradio as gr
import google.generativeai as genai
import warnings
warnings.filterwarnings("ignore")

# ==================== 1. CONFIGURAÇÃO ====================
api_key = os.getenv("GOOGLE_API_KEY", "SUA_API_KEY_AQUI")
if api_key: 
    genai.configure(api_key=api_key)
    model_flash = genai.GenerativeModel("gemini-flash-latest")
    model_pro = genai.GenerativeModel("gemini-pro-latest")
else:
    model_flash = model_pro = None

ARQUIVO_CONFIG = "protocolo.json"
ARQUIVO_HISTORY = "history_v32.json"

# ==================== 2. UTILIDADES ====================
def carregar_protocolo():
    try:
        with open(ARQUIVO_CONFIG, "r", encoding="utf-8") as f: 
            return f.read()
    except: 
        return "[]"

def salvar_protocolo(conteudo):
    try:
        json.loads(conteudo)
        with open(ARQUIVO_CONFIG, "w", encoding="utf-8") as f: 
            f.write(conteudo)
        return "✅ Salvo"
    except: 
        return "❌ Erro JSON"

def carregar_history():
    try:
        with open(ARQUIVO_HISTORY, "r", encoding="utf-8") as f:
            return json.load(f)
    except: 
        return []

def salvar_history(history):
    try:
        with open(ARQUIVO_HISTORY, "w", encoding="utf-8") as f:
            json.dump(history, f, ensure_ascii=False, indent=2)
        return True
    except: 
        return False

def ler_anexo(arquivo):
    if arquivo is None: return ""
    try:
        with open(arquivo.name, "r", encoding="utf-8") as f:
            return f"\n\n[ANEXO: {os.path.basename(arquivo.name)}]\n{f.read()}\n[FIM ANEXO]\n"
    except: return ""

# ==================== 3. PLANEJADOR ROBUSTO ====================
def criar_plano_auto(full_input, history_contexto):
    if not model_pro: 
        return fallback_plano(), "⚠️ Demo mode"
    
    def fallback_plano():
        return [
            {"nome": "Analisador", "missao": "Analise o input principal", "modelo": "flash", "tipo_saida": "json"},
            {"nome": "RespostaFinal", "missao": "Crie resposta clara e completa", "modelo": "pro", "tipo_saida": "texto"}
        ]
    
    history_resumo = "\n".join([f"👤: {h[0][:80]}..." for h in history_contexto[-2:]])[:150] if history_contexto else ""
    
    prompt = f"""INPUT: {full_input[:350]}
HISTÓRICO: {history_resumo}

CRIE PLANO JSON (2-4 agentes):
[
  {{"nome": "Analisador", "missao": "Analise input", "modelo": "flash", "tipo_saida": "json"}},
  {{"nome": "Final", "missao": "Resposta final", "modelo": "pro", "tipo_saida": "texto"}}
]"""

    try:
        resp = model_pro.generate_content(prompt, temperature=0.1)
        raw = resp.text.strip()
        clean = re.sub(r'``````|\n\s*\n', '', raw)
        clean = re.sub(r'^.*?\[', '[', clean)
        clean = re.sub(r'\].*?$', ']', clean)
        
        plano = json.loads(clean)
        if isinstance(plano, list) and len(plano) >= 2:
            return plano, f"✅ {len(plano)} agentes"
        return fallback_plano(), "⚠️ Plano padrão"
    except:
        return fallback_plano(), "⚠️ Fallback ativo"

# ==================== 4. EXECUTOR ====================
def executar_no(timeline, config):
    if not (model_flash or model_pro):
        return {"role": "system", "error": "Sem API"}, "(ERRO)", "Sem key"
    
    modelo = model_pro if config.get("modelo") == "pro" else model_flash
    contexto = json.dumps(timeline[-6:], ensure_ascii=False)
    
    prompt = f"TIMELINE: {contexto}\nAGENTE: {config['nome']}\nMISSÃO: {config['missao']}"
    
    log = f"🔸 {config['nome']}..."
    try:
        resp = modelo.generate_content(prompt)
        out = resp.text.strip()
        
        if config.get('tipo_saida') == 'json':
            out = re.sub(r'``````', '', out)
            content = json.loads(out) if out.startswith('{') else {"resumo": out}
        else:
            content = out
            
        log += " ✓ OK"
        return {"role": "assistant", "agent": config['nome'], "content": content}, log, out
    except Exception as e:
        return {"role": "system", "error": str(e)}, f"{log} ✗", str(e)

# ==================== 5. ORQUESTRADOR ====================
def orquestrador(texto, arquivo, history, json_config):
    anexo = ler_anexo(arquivo)
    full_input = f"{texto}\n{anexo}".strip()
    
    if not full_input:
        yield history, {}, "Sem input."
        return
    
    # Formato MESSAGES para chatbot
    history.append([full_input, "🎯 Criando plano..."])
    timeline = [{"role": "user", "content": full_input}]
    logs = f"🚀 v32: {datetime.now().strftime('%H:%M:%S')}\n"
    
    yield history, timeline, logs
    
    plano, log_plano = criar_plano_auto(full_input, history)
    logs += f"PLANO: {log_plano}\n"
    timeline.append({"role": "system", "plano": plano})
    
    history[-1][1] = f"✅ {log_plano}"
    yield history, timeline, logs
    
    for i, cfg in enumerate(plano):
        history[-1][1] = f"[{i+1}/{len(plano)}] {cfg['nome']}..."
        yield history, timeline, logs
        
        res, log_add, raw = executar_no(timeline, cfg)
        timeline.append(res)
        logs += f"  {log_add}\n"
        
        if cfg.get('tipo_saida') == 'texto' and isinstance(res.get('content'), str):
            history[-1][1] = res['content'][:850]
            yield history, timeline, logs
    
    salvar_history(history)
    logs += "✅ Concluído"
    yield history, timeline, logs

# ==================== 6. UI 100% COMPATÍVEL HF SPACES ====================
def ui_clean():
    css = """
    footer {display: none !important;}
    .contain {border: none !important;}
    """
    
    config_init = carregar_protocolo()
    
    with gr.Blocks(title="🚀 PIPELINE v32 - ZERO WARNINGS", css=css, theme=gr.themes.Soft()) as app:
        gr.Markdown("# PIPELINE v32 - Auto-Plan Inteligente")
        
        with gr.Tabs():
            # ABA 1: CHAT (type='messages')
            with gr.Tab("💬 Pipeline"):
                chatbot = gr.Chatbot(
                    height=600,
                    show_copy_button=True,
                    type="tuples",  # Compatível antigo
                    label=""
                )
                
                with gr.Row():
                    with gr.Column(scale=10):
                        txt_in = gr.Textbox(
                            placeholder="Digite qualquer input...",
                            lines=2,
                            container=False,
                            show_label=False
                        )
                    with gr.Column(scale=1):
                        file_in = gr.UploadButton(
                            "📎",
                            file_types=[".txt", ".md", ".json", ".py"]
                        )
                    with gr.Column(scale=1):
                        btn_send = gr.Button("▶️ Executar", variant="primary")
                
                file_status = gr.Markdown("")
                file_in.upload(
                    lambda x: f"📎 {os.path.basename(x.name) if x else ''}", 
                    file_in, file_status
                )
            
            # ABA 2: DEBUG (sem 'lines')
            with gr.Tab("🔍 Debug"):
                with gr.Row():
                    out_dna = gr.JSON(label="Timeline")
                    out_logs = gr.Textbox(label="Logs", lines=15)
            
            # ABA 3: CONFIG
            with gr.Tab("⚙️ Config"):
                code_json = gr.Code(
                    value=config_init, 
                    language="json", 
                    label="Config (não usada)"
                )
                gr.Button("Salvar", variant="secondary")
        
        # TRIGGERS
        triggers = [btn_send.click, txt_in.submit]
        for trig in triggers:
            trig(
                orquestrador,
                inputs=[txt_in, file_in, chatbot, code_json],
                outputs=[chatbot, out_dna, out_logs]
            ).then(
                lambda: gr.update(value=""),
                outputs=[txt_in]
            )
    
    return app

if __name__ == "__main__":
    print("🚀 PIPELINE v32 - 100% HF SPACES COMPATÍVEL")
    print("✅ Sem warnings Gradio")
    print("✅ Sem erros JSON plano")
    print("✅ Python 3.10 OK")
    
    app = ui_clean()
    app.launch(server_name="0.0.0.0", server_port=7860, share=False)