message
Browse files- main.py +3 -3
- services/sms_service.py +2 -2
main.py
CHANGED
@@ -2,9 +2,9 @@
|
|
2 |
from fastapi import FastAPI, HTTPException
|
3 |
from pydantic import BaseModel
|
4 |
import numpy as np
|
5 |
-
from
|
6 |
-
from
|
7 |
-
from
|
8 |
|
9 |
# Initialize FastAPI
|
10 |
app = FastAPI()
|
|
|
2 |
from fastapi import FastAPI, HTTPException
|
3 |
from pydantic import BaseModel
|
4 |
import numpy as np
|
5 |
+
from services.sms_service import classify_sms, load_trained_model
|
6 |
+
from schemas.input_schemas import CosineSimilarityInput, CosineSimilarityOutput
|
7 |
+
from schemas.input_schemas import EmbeddingInput, EmbeddingOutput
|
8 |
|
9 |
# Initialize FastAPI
|
10 |
app = FastAPI()
|
services/sms_service.py
CHANGED
@@ -3,8 +3,8 @@ import pickle
|
|
3 |
import numpy as np
|
4 |
from sklearn.feature_extraction.text import TfidfVectorizer
|
5 |
from fastapi import HTTPException
|
6 |
-
from
|
7 |
-
from
|
8 |
|
9 |
# Load the trained model and vectorizer
|
10 |
def load_model():
|
|
|
3 |
import numpy as np
|
4 |
from sklearn.feature_extraction.text import TfidfVectorizer
|
5 |
from fastapi import HTTPException
|
6 |
+
from schemas.input_schemas import CosineSimilarityResponse
|
7 |
+
from schemas.input_schemas import EmbeddingResponse
|
8 |
|
9 |
# Load the trained model and vectorizer
|
10 |
def load_model():
|