Update app.py

app.py

@@ -4,26 +4,32 @@ from llama_cpp import Llama
 
 app = FastAPI()
 
-import os
-
-
-
-
 qwen3_gguf_llm = Llama.from_pretrained(
-	repo_id="unsloth/Qwen3-0.6B-GGUF",
-	filename="Qwen3-0.6B-UD-Q8_K_XL.gguf",
+    repo_id="unsloth/Qwen3-0.6B-GGUF",
+    filename="Qwen3-0.6B-UD-Q8_K_XL.gguf",
 )
 
 class PromptRequest(BaseModel):
     prompt: str
 
 class GenerateResponse(BaseModel):
-    reasoning_content: str = ""
     generated_text: str
 
+# Simple in-memory conversation memory (list of messages)
+conversation_history = []
+
 @app.post("/generate/qwen3-0.6b-gguf", response_model=GenerateResponse)
 async def generate_qwen3_gguf_endpoint(request: PromptRequest):
-    messages = [{"role": "user", "content": request.prompt}]
-    response = qwen3_gguf_llm.create_chat_completion(messages=messages)
-    generated_text = response['choices'][0]['message']['content']
-    return GenerateResponse(generated_text=generated_text)
+    # Append user message to history
+    conversation_history.append({"role": "user", "content": request.prompt})
+
+    # Call the model with full conversation history
+    response = qwen3_gguf_llm.create_chat_completion(messages=conversation_history)
+
+    # Extract assistant reply
+    assistant_message = response['choices'][0]['message']['content']
+
+    # Append assistant reply to history
+    conversation_history.append({"role": "assistant", "content": assistant_message})
+
+    return GenerateResponse(generated_text=assistant_message)