Update app.py

app.py

@@ -1,3 +1,67 @@
+# from fastapi import FastAPI, HTTPException
+# from pydantic import BaseModel
+# from huggingface_hub import InferenceClient
+# import os
+
+# app = FastAPI()
+
+# # Get the token from the environment variable
+# hf_token = os.environ.get("HF_TOKEN")
+
+# client = InferenceClient("HuggingFaceH4/zephyr-7b-beta", token=hf_token)
+
+# class ChatRequest(BaseModel):
+#     message: str
+#     system_message: str = "You are a friendly Chatbot."
+#     max_tokens: int = 512
+#     temperature: float = 0.7
+#     top_p: float = 0.95
+
+# class ChatResponse(BaseModel):
+#     response: str
+
+# @app.post("/chat", response_model=ChatResponse)
+# async def chat(request: ChatRequest):
+#     try:
+#         messages = []
+#         messages.append({"role": "system", "content": request.system_message})
+#         messages.append({"role": "user", "content": request.message})
+
+#         response = client.chat_completion(
+#             messages,
+#             max_tokens=request.max_tokens,
+#             temperature=request.temperature,
+#             top_p=request.top_p,
+#         )
+    
+#         return {"response": response}
+    
+#     except Exception as e:
+#         raise HTTPException(status_code=500, detail=str(e))
+
+# from fastapi import FastAPI
+# from fastapi.responses import JSONResponse
+# from fastapi import Request
+# from huggingface_hub import InferenceClient
+
+# app = FastAPI()
+
+# @app.post("/")
+# async def greet_json(request: Request):
+#     input_data = await request.json()
+#     # number = input_data.get("number")
+ 
+#     # tripled_number = number * 2
+#     # return {"message": f"Your input number is: {number}, your doubled number is: {tripled_number}"}
+#     user_input = input_data.get("user_input")
+    
+#     client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+#     # Get the response from the model
+#     response = client(user_input)
+    
+#     # assistant_response = client.text_generation(user_input)
+#     assistant_response = "I am assistant."
+#     return {"assistant_message": f"Your input message is: {user_input}, assistant_response is: {response}"}
 from fastapi import FastAPI, HTTPException
 from pydantic import BaseModel
 from huggingface_hub import InferenceClient
@@ -8,10 +72,16 @@ app = FastAPI()
 # Get the token from the environment variable
 hf_token = os.environ.get("HF_TOKEN")
 
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta", token=hf_token)
+if hf_token:
+    client = InferenceClient("HuggingFaceH4/zephyr-7b-beta", token=hf_token)
+else:
+    raise ValueError("HF_TOKEN environment variable not set. Please add it as a secret in your Hugging Face Space.")
+
+# Rest of your code...
 
 class ChatRequest(BaseModel):
     message: str
+    history: list[tuple[str, str]] = []
     system_message: str = "You are a friendly Chatbot."
     max_tokens: int = 512
     temperature: float = 0.7
@@ -23,18 +93,25 @@ class ChatResponse(BaseModel):
 @app.post("/chat", response_model=ChatResponse)
 async def chat(request: ChatRequest):
     try:
-        messages = []
-        messages.append({"role": "system", "content": request.system_message})
+        messages = [{"role": "system", "content": request.system_message}]
+        for val in request.history:
+            if val[0]:
+                messages.append({"role": "user", "content": val[0]})
+            if val[1]:
+                messages.append({"role": "assistant", "content": val[1]})
         messages.append({"role": "user", "content": request.message})
 
-        response = client.chat_completion(
+        response = ""
+        for message in client.chat_completion(
             messages,
             max_tokens=request.max_tokens,
+            stream=True,
             temperature=request.temperature,
             top_p=request.top_p,
-        )
-    
+        ):
+            token = message.choices[0].delta.content
+            response += token
+
         return {"response": response}
-    
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e))