sort imports

.github/workflows/ci.yaml

@@ -30,9 +30,9 @@ jobs:
  - name: Run tests
  run: |
  poetry run coverage run -m unittest discover ./app/tests/
- poetry run coverage report -m
+ poetry run coverage report
+ poetry run coverage xml
  working-directory: ${{ github.workspace }}
 
  - name: Upload coverage report
  uses: codecov/codecov-action@v2
-

README.md

@@ -1,3 +1,5 @@
+[![CI](https://github.com/weni-ai/SentenX/actions/workflows/ci.yaml/badge.svg)](https://github.com/weni-ai/SentenX/actions/workflows/ci.yaml)
+
 # SentenX
 
 microservice that uses a sentence transformer model to index and search records.
@@ -52,7 +54,7 @@ uvicorn app.main:main_app.api --reload
 
 ### Docker compose
 
-to start sentenx with elasticsearch on with docker compose:
+to start sentenx with elasticsearch with docker compose:
 
 setup `AWS_SECRET_ACCESS_KEY` and `AWS_ACCESS_KEY_ID` on `docker-compose.yml`
 ```
@@ -66,7 +68,7 @@ docker compose down
 
 to start with rebuild after any change on source:
 ```
-docker compose up -d --
+docker compose up -d --build
 ```
 
 
@@ -167,7 +169,7 @@ status: 200
  "products": [
  {
  "facebook_id": "1",
- "title": "leite em pó 200g",
+ "title": "massa para bolo de baunilha",
  "org_id": "1",
  "channel_id": "5",
  "catalog_id": "asdfgh4321",

app/handlers/products.py

@@ -1,8 +1,9 @@
 from fastapi import APIRouter, HTTPException
 from fastapi.logger import logger
+from pydantic import BaseModel
+
 from app.handlers import IDocumentHandler
 from app.indexer import IDocumentIndexer
-from pydantic import BaseModel
 
 
 class Product(BaseModel):

app/indexer/products.py

@@ -1,4 +1,5 @@
 from langchain.docstore.document import Document
+
 from app.handlers.products import Product
 from app.indexer import IDocumentIndexer
 from app.store import IStorage

app/main.py

@@ -1,3 +1,8 @@
+from fastapi import FastAPI
+from langchain.embeddings import SagemakerEndpointEmbeddings, HuggingFaceHubEmbeddings
+from langchain.embeddings.base import Embeddings
+from langchain.vectorstores import ElasticVectorSearch, VectorStore
+
 from app.handlers import IDocumentHandler
 from app.handlers.products import ProductsHandler
 from app.indexer import IDocumentIndexer
@@ -6,11 +11,6 @@
 from app.config import AppConfig
 from app.util import ContentHandler
 
-from fastapi import FastAPI
-from langchain.embeddings import SagemakerEndpointEmbeddings, HuggingFaceHubEmbeddings
-from langchain.embeddings.base import Embeddings
-from langchain.vectorstores import ElasticVectorSearch, VectorStore
-
 
 class App:
  api: FastAPI

app/store/elasticsearch_vector_store.py

@@ -1,5 +1,6 @@
 from langchain.vectorstores import VectorStore
 from langchain.docstore.document import Document
+
 from app.store import IStorage
 
 

app/util.py

@@ -1,4 +1,5 @@
 import json
+
 from langchain.embeddings.sagemaker_endpoint import EmbeddingsContentHandler