app-gg.py

# ╔════════════════════════════════════════════════════════════════════════════╗
# ║             PIPELINE v27: UI LIMPA & ESTRUTURA DE ABAS                     ║
# ║        Layout: Chat (Aba 1) | Debug (Aba 2) | Config (Aba 3)               ║
# ╚════════════════════════════════════════════════════════════════════════════╝

import os
import json
import re
import time
from datetime import datetime
import gradio as gr
import google.generativeai as genai

# ==================== 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")

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

# ==================== 3. ENGINE DE EXECUÇÃO ====================

def executar_no(timeline, config):
    modelo = model_pro if config.get("modelo") == "pro" else model_flash
    contexto = json.dumps(timeline, ensure_ascii=False, indent=2)
    prompt = f"--- TIMELINE ---\n{contexto}\n----------------\nAGENTE: {config['nome']}\nMISSÃO: {config['missao']}"
    
    log = f"\n🔸 {config['nome']}..."
    try:
        inicio = time.time()
        resp = modelo.generate_content(prompt)
        out = resp.text
        tempo = time.time() - inicio
        
        content = json.loads(out.strip().replace('```json','').replace('```','')) if config['tipo_saida']=='json' else out
        log += f" (OK - {tempo:.2f}s)"
        return {"role": "assistant", "agent": config['nome'], "content": content}, log, out
    except Exception as e:
        return {"role": "system", "error": str(e)}, f" (ERRO: {e})", str(e)

# ==================== 4. ORQUESTRADOR ====================

def orquestrador(texto, arquivo, history, json_config):
    # 1. Input Check
    anexo = ler_anexo(arquivo)
    full_input = f"{texto}\n{anexo}".strip()
    
    if not full_input:
        yield history, {}, "Sem input."
        return

    # 2. Setup
    history = history + [[texto + (" 📎" if arquivo else ""), None]]
    try: protocolo = json.loads(json_config)
    except: 
        history[-1][1] = "❌ Erro no JSON de Configuração."
        yield history, {}, "Erro JSON"
        return

    timeline = [{"role": "user", "content": full_input}]
    logs = f"🚀 START: {datetime.now().strftime('%H:%M:%S')}\n"
    history[-1][1] = "⏳ Iniciando análise..."
    yield history, timeline, logs

    # 3. Loop
    final_response = ""
    for cfg in protocolo:
        history[-1][1] = f"⚙️ {cfg['nome']} trabalhando..."
        yield history, timeline, logs
        
        res, log_add, raw = executar_no(timeline, cfg)
        timeline.append(res)
        logs += log_add + "\n"
        
        if cfg['tipo_saida'] == 'texto':
            final_response = res['content']
            history[-1][1] = final_response # Mostra texto progressivo se fosse stream, aqui mostra final
        
        yield history, timeline, logs

    logs += "✅ FIM."
    yield history, timeline, logs

# ==================== 5. UI LIMPA (v27) ====================

def ui_clean():
    css = """
    footer {display: none !important;} 
    .contain {border: none !important;}
    """
    
    config_init = carregar_protocolo()

    with gr.Blocks(title="AI Forensics", css=css, theme=gr.themes.Soft()) as app:
        
        with gr.Tabs():
            
            # === ABA 1: CHAT (LIMPO) ===
            with gr.Tab("💬 Investigador"):
                chatbot = gr.Chatbot(
                    label="", 
                    show_label=False, 
                    height=600, 
                    show_copy_button=True,
                    render_markdown=True
                )
                
                with gr.Row():
                    with gr.Column(scale=10):
                        txt_in = gr.Textbox(
                            show_label=False, 
                            placeholder="Descreva o caso ou instrução...", 
                            lines=1,
                            max_lines=5,
                            container=False
                        )
                    with gr.Column(scale=1, min_width=50):
                        file_in = gr.UploadButton(
                            "📎", 
                            file_types=[".txt", ".md", ".csv", ".json"],
                            size="sm"
                        )
                    with gr.Column(scale=1, min_width=80):
                        btn_send = gr.Button("Enviar", variant="primary", size="sm")
                
                # Feedback visual sutil do arquivo
                file_status = gr.Markdown("", visible=True)
                file_in.upload(lambda x: f"📎 Anexo: {os.path.basename(x.name)}", file_in, file_status)

            # === ABA 2: DEPURAÇÃO (ESCONDIDO) ===
            with gr.Tab("🕵️ Depuração"):
                with gr.Row():
                    out_dna = gr.JSON(label="DNA (Timeline)")
                    out_logs = gr.Textbox(label="Logs do Sistema", lines=20)

            # === ABA 3: CONFIG (TÉCNICO) ===
            with gr.Tab("⚙️ Config"):
                with gr.Row():
                    btn_save = gr.Button("Salvar Config")
                    lbl_save = gr.Label(show_label=False)
                code_json = gr.Code(value=config_init, language="json", label="protocolo.json")
                btn_save.click(salvar_protocolo, code_json, lbl_save)

        # === TRIGGERS ===
        # Enter ou Botão Enviar
        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: (None, ""), # Limpa input e label do arquivo após envio
                outputs=[txt_in, file_status] 
            )

    return app

if __name__ == "__main__":
    ui_clean().launch()