Update main.py

main.py

@@ -1,20 +1,16 @@
-from fastapi import FastAPI, File, UploadFile, Form, Request
-from fastapi.responses import HTMLResponse, FileResponse
-from fastapi.staticfiles import StaticFiles
+from fastapi import FastAPI, Request
 from fastapi.templating import Jinja2Templates
 from huggingface_hub import InferenceClient
-import random
 
-API_URL = "https://api-inference.huggingface.co/models/"
+app = FastAPI()
+templates = Jinja2Templates(directory="templates")
 
 client = InferenceClient(
     "mistralai/Mistral-7B-Instruct-v0.1"
 )
 
-app = FastAPI()
-
 
-def format_prompt(message, history):
+async def format_prompt(message, history):
     prompt = "<s>"
     for user_prompt, bot_response in history:
         prompt += f"[INST] {user_prompt} [/INST]"
@@ -23,56 +19,39 @@ def format_prompt(message, history):
     return prompt
 
 
-def generate(prompt, history, temperature=0.9, max_new_tokens=512, top_p=0.95, repetition_penalty=1.0):
+async def generate(
+    prompt: str,
+    temperature: float = 0.9,
+    max_new_tokens: int = 256,
+    top_p: float = 0.95,
+    repetition_penalty: float = 1.0,
+):
     temperature = float(temperature)
     if temperature < 1e-2:
         temperature = 1e-2
     top_p = float(top_p)
 
-    generate_kwargs = dict(
-        temperature=temperature,
-        max_new_tokens=max_new_tokens,
-        top_p=top_p,
-        repetition_penalty=repetition_penalty,
-        do_sample=True,
-        seed=random.randint(0, 10**7),
-    )
-
-    formatted_prompt = format_prompt(prompt, history)
-
-    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
-    output = ""
-    word = ""
+    generate_kwargs = {
+        "temperature": temperature,
+        "max_new_tokens": max_new_tokens,
+        "top_p": top_p,
+        "repetition_penalty": repetition_penalty,
+        "do_sample": True,
+        "seed": 42,
+    }
 
-    for response in stream:
-        token_text = response.token.text.strip()
-        if token_text != "":
-            # Decode the token text to handle encoded characters
-            decoded_text = token_text.encode("utf-8", "backslashreplace").decode("utf-8")
+    formatted_prompt = await format_prompt(prompt, [])
 
-            # Add the decoded letter to the current word
-            word += decoded_text
+    response = client.text_generation(formatted_prompt, **generate_kwargs, stream=False, details=False, return_full_text=True)
+    return response
 
-            # If the token is a space or the end of the stream, add the word to the output and reset the word
-            if token_text == " " or response.is_end_of_stream:
-                output += word + " "
-                word = ""
 
-    return output
+@app.get("/")
+async def index(request: Request):
+    return templates.TemplateResponse("index.html", {"request": request})
 
 
 @app.post("/generate/")
-async def generate_chat(request: Request, prompt: str = Form(...), history: str = Form(...), temperature: float = Form(0.9), max_new_tokens: int = Form(512), top_p: float = Form(0.95), repetition_penalty: float = Form(1.0)):
-    history = eval(history)  # Convert history string back to list
-    response = generate(prompt, history, temperature, max_new_tokens, top_p, repetition_penalty)
-    
-    # Concatenate the generated response strings into a single coherent response
-    coherent_response = " ".join(response)
-    
-    return {"response": coherent_response}
-
-app.mount("/", StaticFiles(directory="static", html=True), name="static")
-
-@app.get("/")
-def index() -> FileResponse:
-    return FileResponse(path="/app/static/index.html", media_type="text/html")
+async def chatbot_response(prompt: str):
+    response = await generate(prompt)
+    return {"response": response}