Update app.py

app.py

@@ -1,14 +1,25 @@
-from fastapi import FastAPI, Request
-from fastapi.responses import JSONResponse
-import json
+from fastapi import FastAPI, Request, HTTPException
+from pydantic import BaseModel
 from huggingface_hub import InferenceClient
+import json
+from typing import List, Dict, Tuple
 
 app = FastAPI()
 
 # Inisialisasi HuggingFace client
 client = InferenceClient("meta-llama/Meta-Llama-3-8B-Instruct")
 
-def chat_llama(chat_history):
+class ChatRequest(BaseModel):
+    chat_history: List[Dict[str, str]]
+
+class ChatMemRequest(BaseModel):
+    message: str
+    chat_history: List[Tuple[str, str]]
+
+class ProcessJsonRequest(BaseModel):
+    json_input: str
+
+def chat_llama(chat_history: List[Dict[str, str]]) -> List[Dict[str, str]]:
     chat_completion = client.chat_completion(
         messages=chat_history,
         max_tokens=500,
@@ -16,12 +27,11 @@ def chat_llama(chat_history):
     chat_history.append({"role": "assistant", "content": chat_completion.choices[0].message.content})
     return chat_history
 
-def chat_mem(message, chat_history):
+def chat_mem(message: str, chat_history: List[Tuple[str, str]]) -> Tuple[str, List[Tuple[str, str]]]:
     chat_history_role = [{"role": "system", "content": "You are a helpful assistant."}]
-    if chat_history:
-        for i in range(len(chat_history)):
-            chat_history_role.append({"role": "user", "content": chat_history[i][0]})
-            chat_history_role.append({"role": "assistant", "content": chat_history[i][1]})
+    for user_msg, assistant_msg in chat_history:
+        chat_history_role.append({"role": "user", "content": user_msg})
+        chat_history_role.append({"role": "assistant", "content": assistant_msg})
     chat_history_role.append({"role": "user", "content": message})
     
     chat_completion = client.chat_completion(
@@ -36,7 +46,7 @@ def chat_mem(message, chat_history):
 
     return "", chat_history
 
-def process_json(json_input):
+def process_json(json_input: str) -> Tuple[str, str]:
     try:
         chat_history = json.loads(json_input)
         if not isinstance(chat_history, list):
@@ -48,34 +58,24 @@ def process_json(json_input):
     return json.dumps(chat_history, indent=2), ""
 
 @app.post("/chat_llama")
-async def chat_llama_endpoint(request: Request):
-    data = await request.json()
-    chat_history = data.get('chat_history', [])
+async def chat_llama_endpoint(request: ChatRequest):
+    chat_history = request.chat_history
     response = chat_llama(chat_history)
-    return JSONResponse(content=response)
+    return {"chat_history": response}
 
 @app.post("/chat_mem")
-async def chat_mem_endpoint(request: Request):
-    data = await request.json()
-    message = data.get('message', '')
-    chat_history = data.get('chat_history', [])
+async def chat_mem_endpoint(request: ChatMemRequest):
+    message = request.message
+    chat_history = request.chat_history
     response = chat_mem(message, chat_history)
-    return JSONResponse(content=response)
+    return {"message": response[0], "chat_history": response[1]}
 
 @app.post("/process_json")
-async def process_json_endpoint(request: Request):
-    data = await request.json()
-    json_input = data.get('json_input', '')
+async def process_json_endpoint(request: ProcessJsonRequest):
+    json_input = request.json_input
     response = process_json(json_input)
-    return JSONResponse(content=response)
-
-def schedule_task():
-    print("Scheduled task is running")
-
-# Tambahkan tugas terjadwal menggunakan univcron
-univcron.every(10).seconds.do(schedule_task)
+    return {"output_json": response[0], "error_message": response[1]}
 
 if __name__ == "__main__":
     import uvicorn
-    # Jalankan server FastAPI
     uvicorn.run(app, host="0.0.0.0", port=7860)