Dataprep Microservice with Elasticsearch¶
🚀1. Start Microservice with Python(Option 1)¶
1.1 Install Requirements¶
pip install -r requirements.txt
1.2 Setup Environment Variables¶
export ES_CONNECTION_STRING=http://localhost:9200
export INDEX_NAME=${your_index_name}
1.3 Start Elasticsearch¶
Please refer to this readme.
1.4 Start Document Preparation Microservice for Elasticsearch with Python Script¶
Start document preparation microservice for Elasticsearch with below command.
python prepare_doc_elastic.py
🚀2. Start Microservice with Docker (Option 2)¶
2.1 Start Elasticsearch¶
Please refer to this readme.
2.2 Setup Environment Variables¶
export ES_CONNECTION_STRING=http://localhost:9200
export INDEX_NAME=${your_index_name}
2.3 Build Docker Image¶
cd GenAIComps
docker build -t opea/dataprep-elasticsearch:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/elasticsearch/langchain/Dockerfile .
2.4 Run Docker with CLI (Option A)¶
docker run --name="dataprep-elasticsearch" -p 6011:6011 --ipc=host -e http_proxy=$http_proxy -e https_proxy=$https_proxy -e ES_CONNECTION_STRING=$ES_CONNECTION_STRING -e INDEX_NAME=$INDEX_NAME -e TEI_ENDPOINT=$TEI_ENDPOINT opea/dataprep-elastic:latest
2.5 Run with Docker Compose (Option B)¶
cd comps/dataprep/elasticsearch/langchain
docker compose -f docker-compose-dataprep-elastic.yaml up -d
🚀3. Consume Microservice¶
3.1 Consume Upload API¶
Once document preparation microservice for Elasticsearch is started, user can use below command to invoke the microservice to convert the document to embedding and save to the database.
curl -X POST \
-H "Content-Type: application/json" \
-d '{"path":"/path/to/document"}' \
http://localhost:6011/v1/dataprep
3.2 Consume get_file API¶
To get uploaded file structures, use the following command:
curl -X POST \
-H "Content-Type: application/json" \
http://localhost:6011/v1/dataprep/get_file
Then you will get the response JSON like this:
[
{
"name": "uploaded_file_1.txt",
"id": "uploaded_file_1.txt",
"type": "File",
"parent": ""
},
{
"name": "uploaded_file_2.txt",
"id": "uploaded_file_2.txt",
"type": "File",
"parent": ""
}
]
4.3 Consume delete_file API¶
To delete uploaded file/link, use the following command.
The file_path
here should be the id
get from /v1/dataprep/get_file
API.
# delete link
curl -X POST \
-H "Content-Type: application/json" \
-d '{"file_path": "https://www.ces.tech/.txt"}' \
http://localhost:6011/v1/dataprep/delete_file
# delete file
curl -X POST \
-H "Content-Type: application/json" \
-d '{"file_path": "uploaded_file_1.txt"}' \
http://localhost:6011/v1/dataprep/delete_file
# delete all files and links
curl -X POST \
-H "Content-Type: application/json" \
-d '{"file_path": "all"}' \
http://localhost:6011/v1/dataprep/delete_file