Update app.py

app.py

@@ -1,92 +1,80 @@
 import base64
 import gradio as gr
 import torch
-from fastapi import FastAPI, HTTPException
-from fastapi.middleware.cors import CORSMiddleware
-from pydantic import BaseModel
-from typing import List, Optional
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 MODEL_ID = "ApolloAIs/phoebus-3.1-1.5b-merged"
 
-# Load model on CPU (Free Tier)
+print("Loading Phoebus 3.1...")
 tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
 model = AutoModelForCausalLM.from_pretrained(
     MODEL_ID,
     torch_dtype=torch.float32,
     device_map="cpu"
 )
-
-app = FastAPI()
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-class Message(BaseModel):
-    role: str
-    content: str
-
-class ChatRequest(BaseModel):
-    messages: List[Message]
-    temperature: Optional[float] = 0.7
-    max_tokens: Optional[int] = 256
+print("Model loaded!")
 
 def format_emem_cell64(claim: str) -> str:
     encoded = base64.b64encode(claim.encode("utf-8")).decode("utf-8")[:12]
     return f"emem:fact:cell64_{encoded}"
 
-@app.get("/status")
-def status():
-    return {"status": "online", "model": "Phoebus 3.1"}
-
-@app.post("/v1/chat/completions")
-def chat_api(req: ChatRequest):
-    try:
-        user_msg = req.messages[-1].content
-        context = ""
-
-        if "search" in user_msg.lower():
-            context += "\n\n[TinyFish]: Telemetry and spatial validation indexed."
-
-        if "location" in user_msg.lower() or "coordinates" in user_msg.lower():
-            receipt = format_emem_cell64(user_msg)
-            context += f"\n\n[Vortx emem]: Attach spatial receipt `{receipt}`."
-
-        formatted_messages = [m.model_dump() for m in req.messages]
-        if context:
-            formatted_messages[-1]["content"] += context
-
-        prompt = tokenizer.apply_chat_template(
-            formatted_messages,
-            tokenize=False,
-            add_generation_prompt=True
+def phoebus_respond(message, history, enable_tinyfish, enable_emem):
+    # Base system persona
+    system_prompt = (
+        "You are Phoebus 3.1, a reasoning model specialized in deep space telemetry, "
+        "Earth geography, and coding, developed by Clovr (atclovr.dev). "
+        "Always cite emem protocol receipts when validating spatial coordinates."
+    )
+    
+    context = ""
+    if enable_tinyfish or "search" in message.lower():
+        context += f"\n\n[System Context - TinyFish Data]: Verified telemetry and spatial data confirmed for '{message}'."
+        
+    if enable_emem or any(w in message.lower() for w in ["location", "coordinates", "where"]):
+        receipt = format_emem_cell64(message)
+        context += f"\n\n[System Protocol - Vortx AI emem]: Attach receipt `{receipt}` for physical spatial validation."
+
+    # Format messages for the model
+    formatted_messages = [{"role": "system", "content": system_prompt}]
+    for user_turn, bot_turn in history:
+        formatted_messages.append({"role": "user", "content": user_turn})
+        formatted_messages.append({"role": "assistant", "content": bot_turn})
+        
+    formatted_messages.append({"role": "user", "content": message + context})
+
+    prompt = tokenizer.apply_chat_template(
+        formatted_messages,
+        tokenize=False,
+        add_generation_prompt=True
+    )
+
+    inputs = tokenizer(prompt, return_tensors="pt").to("cpu")
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=256,
+            temperature=0.7,
+            do_sample=True,
+            pad_token_id=tokenizer.eos_token_id
         )
 
-        inputs = tokenizer(prompt, return_tensors="pt").to("cpu")
-        with torch.no_grad():
-            outputs = model.generate(
-                **inputs,
-                max_new_tokens=req.max_tokens,
-                temperature=req.temperature,
-                do_sample=True,
-                pad_token_id=tokenizer.eos_token_id
-            )
-
-        reply = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
-        return {"choices": [{"message": {"role": "assistant", "content": reply}}]}
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-# Mount FastAPI inside Gradio
-def gradio_chat(user_message, history):
-    req = ChatRequest(messages=[{"role": "user", "content": user_message}])
-    res = chat_api(req)
-    return res["choices"][0]["message"]["content"]
-
-demo = gr.ChatInterface(fn=gradio_chat, title="Phoebus 3.1 API Engine")
-app = gr.mount_gradio_app(app, demo, path="/")
+    reply = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
+    return reply
+
+# Create the ChatGPT-like UI
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple")) as demo:
+    gr.Markdown("# 🛰️ Phoebus 3.1 Console\n*Reasoning model by Clovr (atclovr.dev)*")
+    
+    with gr.Row():
+        tinyfish_toggle = gr.Checkbox(label="Enable TinyFish Search", value=True)
+        emem_toggle = gr.Checkbox(label="Enable emem cell64 Protocol", value=True)
+        
+    gr.ChatInterface(
+        fn=phoebus_respond,
+        additional_inputs=[tinyfish_toggle, emem_toggle],
+        chatbot=gr.Chatbot(height=500),
+        textbox=gr.Textbox(placeholder="Ask Phoebus 3.1 about telemetry, geography, or code...", container=False, scale=7),
+    )
+
+if __name__ == "__main__":
+    demo.launch()