Create app.py

app.py

@@ -0,0 +1,71 @@
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from typing import List, Optional
+from huggingface_hub import hf_hub_download
+from llama_cpp import Llama
+import uvicorn
+
+app = FastAPI(title="ChemLLM CPU OpenAI API")
+
+print("Завантаження GGUF моделі...")
+model_path = hf_hub_download(
+    repo_id="RichardErkhov/AI4Chem___ChemLLM-7B-Chat-1_5-DPO-gguf", 
+    filename="ChemLLM-7B-Chat-1_5-DPO.Q4_K_M.gguf"
+)
+
+llm = Llama(model_path=model_path, n_ctx=2048, n_threads=4)
+print("Модель успішно завантажена на CPU!")
+
+class ChatMessage(BaseModel):
+    role: str
+    content: str
+
+class ChatCompletionRequest(BaseModel):
+    model: str
+    messages: List[ChatMessage]
+    temperature: Optional[float] = 0.7
+    max_tokens: Optional[int] = 256
+
+@app.post("/v1/chat/completions")
+async def chat_completions(request: ChatCompletionRequest):
+    try:
+        full_prompt = ""
+        for msg in request.messages:
+            if msg.role == "user":
+                full_prompt += f"<|User|>:{msg.content}"
+            elif msg.role == "assistant":
+                full_prompt += f"<|Bot|>:{msg.content}"
+        full_prompt += "<|Bot|>:"
+
+        # Виклик генерації на CPU
+        output = llm(
+            full_prompt,
+            max_tokens=request.max_tokens,
+            temperature=request.temperature,
+            stop=["<|User|>", "<|Bot|>", "\n\n"]
+        )
+        
+        response_text = output["choices"][0]["text"].strip()
+
+        return {
+            "id": "chatcmpl-chem-cpu",
+            "object": "chat.completion",
+            "model": request.model,
+            "choices": [{
+                "index": 0,
+                "message": {
+                    "role": "assistant",
+                    "content": response_text
+                },
+                "finish_reason": "stop"
+            }]
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/")
+def health():
+    return {"status": "healthy", "hardware": "CPU"}
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)