Create main.py

main.py

@@ -0,0 +1,67 @@
+import os
+import random
+from typing import List, Tuple
+from fastapi import FastAPI, Form, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+from huggingface_hub import InferenceClient
+
+# Initialize FastAPI app
+app = FastAPI()
+
+# Allow CORS for your frontend application
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Change this to your frontend's URL in production
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Initialize Hugging Face Inference Client
+client = InferenceClient("mistralai/Mistral-Nemo-Instruct-2407")
+
+def format_prompt(message: str, history: List[Tuple[str, str]]) -> str:
+    prompt = "<s>"
+    for user_prompt, bot_response in history:
+        prompt += f"[INST] {user_prompt} [/INST]"
+        prompt += f" {bot_response}</s> "
+    prompt += f"[INST] {message} [/INST]"
+    return prompt
+
+@app.post("/generate/")
+async def generate(
+    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)
+):
+    try:
+        # Parse history from JSON string to list of tuples
+        chat_history = eval(history)
+
+        # Format the prompt
+        formatted_prompt = format_prompt(prompt, chat_history)
+
+        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),
+        )
+
+        # Generate text using the model
+        stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+        output = ""
+
+        for response in stream:
+            output += response.token.text
+
+        return JSONResponse(content={"response": output})
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))