interface_sage_gradio.py

# --- interface_sage_gradio.py ---
import gradio as gr
import numpy as np
import replicate
from sentence_transformers import SentenceTransformer
from transformers import pipeline
import os
import json

# === Configurações ===
replicate_client = replicate.Client(api_token=os.environ["REPLICATE_API_TOKEN"])
EMBEDDING_MODEL = SentenceTransformer("all-MiniLM-L6-v2")
GPT = pipeline("text-generation", model="gpt2-large")

MODEL = "gnai-creator/sage-two:f236bf1fc94263e266db57a32ea4014aef91c0ca6a34ac0e98ba1b0e83ca09af"
RESET_PASSWORD = os.environ.get("PASSWORD", "")

JUDGMENT_MAP = {
    "reflection": [0, 1, 2],
    "anger": [3, 4],
    "hope": [5, 6],
    "denial": [7],
    "intuition": [10, 11],
    "skepticism": [15],
    "acceptance": [20],
    "despair": [30],
    "justice": [40, 41, 42],
    "transcendence": [60, 61, 62]
}

PROMPTS = {
    "reflection": "As an ancient sage before eternity, poetically reflect on:",
    "anger": "With restrained fury and sharp words, express your indignation about:",
    "hope": "With the stars' glow and the faith of the righteous, speak of the light in:",
    "denial": "Firmly deny, as one who sees beyond illusion, the truth in:",
    "intuition": "Whisper with mysticism and metaphors what your soul feels about:",
    "skepticism": "With cold logic and analytical eyes, deeply question:",
    "acceptance": "With the serenity of a monk and the pace of the wind, accept and comment:",
    "despair": "With empty eyes and an exhausted heart, murmur about the pain in:",
    "justice": "Raise your voice with nobility and purpose. Speak about justice in:",
    "transcendence": "As a being beyond existence, reveal a fragment of the infinite about:"
}

def run_sage_two(sequence, reset=False):
    output = replicate_client.run(
        MODEL,
        input={"sequence": sequence, "reset": reset}
    )
    if isinstance(output, dict):
        return [float(x) for x in output["output"]]
    elif isinstance(output, list):
        return [float(x) for x in output]
    else:
        raise ValueError(f"Unexpected output format: {output}")

def interpret_vector(vector):
    intensity = {}
    for name, idxs in JUDGMENT_MAP.items():
        values = [vector[i] for i in idxs if i < len(vector)]
        if values:
            intensity[name] = float(np.mean(values))
    return max(intensity, key=intensity.get)

def question_to_response(question, reset=False):
    embedding = EMBEDDING_MODEL.encode(question)
    sequence = [[embedding.tolist() for _ in range(10)]]
    sequence_str = json.dumps(sequence)
    vector = run_sage_two(sequence_str, reset=reset)
    intention = interpret_vector(vector)
    prompt = PROMPTS.get(intention, "With ancient wisdom, respond to this question:") + " " + question
    response = GPT(prompt, max_length=250, max_new_tokens=200, num_return_sequences=1)[0]["generated_text"]
    return response.strip(), intention

def respond(question, reset_flag, password, chat_history):
    if reset_flag and password != RESET_PASSWORD:
        response = "Senha incorreta. A memória não foi resetada.\n\n"
        intention = "error"
        noreset_response, noreset_intention = question_to_response(question, reset=False)
        response += noreset_response
        if noreset_intention != "error":
            response += f"\n\n🛡 Symbolic Intention: **{noreset_intention}**"
        chat_history.append((question, response))
        return chat_history, chat_history
    else:
        response, intention = question_to_response(question, reset=reset_flag)
        full_response = f"{response}\n\n🛡 Symbolic Intention: **{intention}**" if intention != "error" else response
        chat_history.append((question, full_response))
        return chat_history, chat_history

with gr.Blocks() as demo:
    gr.Markdown("""
    # SAGE-2: Symbolic Adaptive General Engine

    Ask anything. SAGE will interpret your symbolic intention before responding.
    """)

    chatbot = gr.Chatbot(label="SAGE responds")
    inp = gr.Textbox(label="Your question")
    reset_checkbox = gr.Checkbox(label="Reset symbolic consciousness?")
    password_box = gr.Textbox(label="Password", type="password")
    state = gr.State([])

    btn = gr.Button("Ask")
    btn.click(fn=respond, inputs=[inp, reset_checkbox, password_box, state], outputs=[chatbot, state])

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