Update app.py

app.py

@@ -1,62 +1,145 @@
-import torch
 from fastapi import FastAPI, Request
 from fastapi.responses import JSONResponse
+from pydantic import BaseModel
 import gradio as gr
-from diffusers import StableDiffusionPipeline
-import base64
-from io import BytesIO
-from PIL import Image
+import os
+import requests
 import nest_asyncio
 import uvicorn
+import re
+
+# ✅ API config
+API_KEY = os.environ.get("OPENROUTER_API_KEY")
+MODEL = "deepseek/deepseek-chat-v3-0324:free"
 
-# ✅ Create FastAPI app
 app = FastAPI()
 
-# ✅ Load the Stable Diffusion v1.5 model (faster than SDXL)
-model_id = "runwayml/stable-diffusion-v1-5"
-pipe = StableDiffusionPipeline.from_pretrained(
-    model_id,
-    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
-    use_safetensors=True,
-).to("cuda" if torch.cuda.is_available() else "cpu")
-
-# ✅ Image generation function
-def generate_image(prompt: str):
-    result = pipe(prompt=prompt, guidance_scale=7.5, num_inference_steps=25)
-    image = result.images[0]
-
-    # Convert image to base64
-    buffered = BytesIO()
-    image.save(buffered, format="PNG")
-    img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
-    return img_str
-
-# ✅ Gradio UI function (optional visual test)
-def gradio_ui(prompt):
-    img_str = generate_image(prompt)
-    return Image.open(BytesIO(base64.b64decode(img_str)))
-
-# ✅ Gradio Interface
-gr_interface = gr.Interface(fn=gradio_ui, inputs="text", outputs="image", title="Fast SD v1.5 Generator")
-
-# ✅ API route for programmatic access
-@app.post("/generate-image")
-async def generate(request: Request):
-    data = await request.json()
-    prompt = data.get("prompt")
-    if not prompt:
-        return JSONResponse(status_code=400, content={"error": "Missing prompt"})
+# ✅ Chat Function
+def chat_fn(message, history):
+    headers = {
+        "Authorization": f"Bearer {API_KEY}",
+        "Content-Type": "application/json"
+    }
+
+    messages = [
+        {
+            "role": "system",
+            "content": (
+                "You are a coding assistant with a focus on programming tasks. You should provide clear, friendly, "
+                "and concise responses to coding questions or tasks. If you're unsure, say: 'I’m not sure about that. Could you rephrase?'"
+            )
+        }
+    ]
+
+    for user, assistant in history:
+        messages.append({"role": "user", "content": user})
+        messages.append({"role": "assistant", "content": assistant})
+
+    messages.append({"role": "user", "content": message + "\n\nReply in a natural tone."})
+
+    payload = {
+        "model": MODEL,
+        "messages": messages,
+        "max_tokens": 16384,
+        "temperature": 0.7,
+        "top_p": 0.9
+    }
+
+    try:
+        response = requests.post(
+            "https://openrouter.ai/api/v1/chat/completions",
+            headers=headers,
+            json=payload,
+            timeout=300
+        )
+        response.raise_for_status()
+        reply = response.json()["choices"][0]["message"]["content"]
+    except Exception as e:
+        reply = f"⚠️ API error: {str(e)[:200]}"
+
+    return reply.strip()
+
+# ✅ /chat API endpoint
+@app.post("/chat")
+async def chat_api(request: Request):
+    body = await request.json()
+    message = body.get("message", "").strip()
+    history = body.get("history", [])
+
+    if not message:
+        return JSONResponse(content={"response": "⚠️ Please enter a valid message."})
+
+    response = chat_fn(message, history)
+    return JSONResponse(content={"response": response})
+
+
+# ✅ New: /code-check endpoint for Monaco Editor integration
+class CodePayload(BaseModel):
+    code: str
+
+@app.post("/code-check")
+async def code_check(request: Request):
+    body = await request.json()
+    code = body.get("code", "")
+
+    if not code.strip():
+        return JSONResponse(content={"suggestions": []})
+
+    headers = {
+        "Authorization": f"Bearer {API_KEY}",
+        "Content-Type": "application/json"
+    }
+
+    prompt = (
+        "Analyze the following code. Identify syntax issues or improvements.\n"
+        "Return a JSON array of suggestions with these keys:\n"
+        "- message\n"
+        "- severity ('error' or 'hint')\n"
+        "- fix (string to replace)\n"
+        "- line (1-based)\n"
+        "- startColumn, endColumn\n\n"
+        f"Code:\n{code}\n\n"
+        "Respond ONLY with the JSON array."
+    )
+
+    payload = {
+        "model": MODEL,
+        "messages": [
+            {"role": "system", "content": "You are a code analysis tool."},
+            {"role": "user", "content": prompt}
+        ],
+        "temperature": 0.3,
+        "top_p": 0.9,
+        "max_tokens": 2048
+    }
 
     try:
-        img_base64 = generate_image(prompt)
-        return {"image_base64": img_base64}
+        response = requests.post("https://openrouter.ai/api/v1/chat/completions", headers=headers, json=payload)
+        response.raise_for_status()
+        raw = response.json()["choices"][0]["message"]["content"]
+
+        # Try to extract JSON array from output
+        match = re.search(r"\[\s*{.*?}\s*\]", raw, re.DOTALL)
+        suggestions = eval(match.group(0)) if match else []
+
+        return JSONResponse(content={"suggestions": suggestions})
+
     except Exception as e:
-        return JSONResponse(status_code=500, content={"error": str(e)})
+        return JSONResponse(content={"suggestions": [], "error": str(e)}, status_code=500)
+
+
+# ✅ Gradio interface
+demo = gr.ChatInterface(
+    fn=chat_fn,
+    title="💬 CODEX MIRXA KAMRAN",
+    description="Ask coding or general programming questions! Short, natural, and helpful responses.",
+    theme="soft"
+)
 
-# ✅ Mount Gradio UI at / for Spaces or browser
-app = gr.mount_gradio_app(app, gr_interface, path="/")
+# ✅ Mount Gradio on FastAPI
+app = gr.mount_gradio_app(app, demo, path="/")
 
-# ✅ Local run only (disabled on Hugging Face Spaces automatically)
+# ✅ Local debug (won't run on HF Spaces, but okay locally)
 if __name__ == "__main__":
     nest_asyncio.apply()
     uvicorn.run(app, host="0.0.0.0", port=7860)