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from pydantic import BaseModel
from fastapi.middleware.cors import CORSMiddleware
from transformers import AutoModel
from typing import List
import os, platform, time
# Your model loading and app initialization code
model = AutoModel.from_pretrained('jinaai/jina-embeddings-v2-base-en', trust_remote_code=True)
class Validation(BaseModel):
prompt: List[str]
def generate_embeddings(x):
start_time = time.time()
embeddings = model.encode(x).tolist()
end_time = time.time()
time_taken = end_time - start_time # Calculate the time taken
return {
"embeddings": embeddings,
"time_taken": f"{time_taken:.2f} seconds",
"Number_of_sentence_processed": len(x)
}
from TextGen import app
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.get("/", tags=["Home"])
def api_home():
return {'detail': 'Welcome to FastAPI TextGen Tutorial!'}
@app.post("/api/generate", summary="Generate embeddings", tags=["Generate"], response_model=Validation)
def inference(input_prompt: List[str]):
return generate_embeddings(prompt=input_prompt)
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