forked from weaviate/t2v-transformers-models
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathapp.py
58 lines (45 loc) · 1.61 KB
/
app.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
import os
from logging import getLogger
from fastapi import FastAPI, Response, status
from vectorizer import Vectorizer, VectorInput
from meta import Meta
app = FastAPI()
vec : Vectorizer
meta_config : Meta
logger = getLogger('uvicorn')
@app.on_event("startup")
def startup_event():
global vec
global meta_config
cuda_env = os.getenv("ENABLE_CUDA")
cuda_support=False
cuda_core=""
if cuda_env is not None and cuda_env == "true" or cuda_env == "1":
cuda_support=True
cuda_core = os.getenv("CUDA_CORE")
if cuda_core is None or cuda_core == "":
cuda_core = "cuda:0"
logger.info(f"CUDA_CORE set to {cuda_core}")
else:
logger.info("Running on CPU")
meta_config = Meta('./models/model')
vec = Vectorizer('./models/model', cuda_support, cuda_core,
meta_config.getModelType(), meta_config.get_architecture())
@app.get("/.well-known/live", response_class=Response)
@app.get("/.well-known/ready", response_class=Response)
def live_and_ready(response: Response):
response.status_code = status.HTTP_204_NO_CONTENT
@app.get("/meta")
def meta():
return meta_config.get()
@app.post("/vectors/")
async def read_item(item: VectorInput, response: Response):
try:
vector = await vec.vectorize(item.text, item.config)
return {"text": item.text, "vector": vector.tolist(), "dim": len(vector)}
except Exception as e:
logger.exception(
'Something went wrong while vectorizing data.'
)
response.status_code = status.HTTP_500_INTERNAL_SERVER_ERROR
return {"error": str(e)}