files 2

interface_sage_gradio.py

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+# --- 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()