Update main.py

main.py

@@ -1,27 +1,42 @@
-from ctransformers import AutoModelForCausalLM
 from fastapi import FastAPI, Form
+from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
+from transformers import AutoModelForCausalLM
 
-#Model loading
-llm = AutoModelForCausalLM.from_pretrained("zephyr-7b-beta.Q4_K_S.gguf",
-model_type='mistral',
-max_new_tokens = 1096,
-threads = 3,
+# Model loading
+llm = AutoModelForCausalLM.from_pretrained(
+    "zephyr-7b-beta.Q4_K_S.gguf",
+    model_type='mistral',
+    max_new_tokens=1096,
+    threads=3,
 )
-   
 
-#Pydantic object
-class validation(BaseModel):
+# Pydantic object
+class Validation(BaseModel):
     prompt: str
-    
-#Fast API
+
+# Fast API
 app = FastAPI()
 
-#Zephyr completion
+# Set up CORS
+origins = [
+    "http://localhost",           # Replace with the address of your Flutter web app
+    "http://localhost:55345",     # Add the port used by your Flutter web app
+]
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=origins,
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Zephyr completion
 @app.post("/llm_on_cpu")
-async def stream(item: validation):
+async def stream(item: Validation):
     system_prompt = 'Below is an instruction that describes a task. Write a response that appropriately completes the request.'
     E_INST = "</s>"
-    user, assistant = "<|user|>", "<|assistant|>"
+    user, assistant = "", ""
     prompt = f"{system_prompt}{E_INST}\n{user}\n{item.prompt.strip()}{E_INST}\n{assistant}\n"
     return llm(prompt)