๐ข๐ Text-to-SQL Microservice with Langchainยถ
This README provides set-up instructions and comprehensive details regarding the Text-to-SQL microservices via LangChain. In this configuration, we will employ PostgresDB as our example database to showcase this microservice.
๐ Start Microservice with Python๏ผOption 1๏ผยถ
Install Requirementsยถ
pip install -r requirements.txt
Start PostgresDB Serviceยถ
We will use Chinook sample database as a default to test the Text-to-SQL microservice. Chinook database is a sample database ideal for demos and testing ORM tools targeting single and multiple database servers.
export POSTGRES_USER=postgres
export POSTGRES_PASSWORD=testpwd
export POSTGRES_DB=chinook
cd comps/texttosql/langchain
docker run --name postgres-db --ipc=host -e POSTGRES_USER=${POSTGRES_USER} -e POSTGRES_HOST_AUTH_METHOD=trust -e POSTGRES_DB=${POSTGRES_DB} -e POSTGRES_PASSWORD=${POSTGRES_PASSWORD} -p 5442:5432 -d -v ./chinook.sql:/docker-entrypoint-initdb.d/chinook.sql postgres:latest
Start TGI Serviceยถ
export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
export LLM_MODEL_ID="mistralai/Mistral-7B-Instruct-v0.3"
export TGI_PORT=8008
docker run -d --name="texttosql-tgi-endpoint" --ipc=host -p $TGI_PORT:80 -v ./data:/data --shm-size 1g -e HF_TOKEN=${HUGGINGFACEHUB_API_TOKEN} -e model=${LLM_MODEL_ID} ghcr.io/huggingface/text-generation-inference:2.1.0 --model-id $LLM_MODEL_ID
Verify the TGI Serviceยถ
export your_ip=$(hostname -I | awk '{print $1}')
curl http://${your_ip}:${TGI_PORT}/generate \
-X POST \
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}' \
-H 'Content-Type: application/json'
Setup Environment Variablesยถ
export TGI_LLM_ENDPOINT="http://${your_ip}:${TGI_PORT}"
Start Text-to-SQL Microservice with Python Scriptยถ
Start Text-to-SQL microservice with below command.
python3 main.py
๐ Start Microservice with Docker (Option 2)ยถ
Start PostGreSQL Database Serviceยถ
Please refer to section Start PostgresDB Service
Start TGI Serviceยถ
Please refer to section Start TGI Service
Setup Environment Variablesยถ
export TGI_LLM_ENDPOINT="http://${your_ip}:${TGI_PORT}"
Build Docker Imageยถ
cd GenAIComps/
docker build -t opea/texttosql:latest -f comps/texttosql/langchain/Dockerfile .
Run Docker with CLI (Option A)ยถ
export TGI_LLM_ENDPOINT="http://${your_ip}:${TGI_PORT}"
docker run --runtime=runc --name="comps-langchain-texttosql" -p 9090:8080 --ipc=host -e llm_endpoint_url=${TGI_LLM_ENDPOINT} opea/texttosql:latest
Run via docker compose (Option B)ยถ
Setup Environment Variables.
export TGI_LLM_ENDPOINT=http://${your_ip}:${TGI_PORT} export HF_TOKEN=${HUGGINGFACEHUB_API_TOKEN} export LLM_MODEL_ID="mistralai/Mistral-7B-Instruct-v0.3" export POSTGRES_USER=postgres export POSTGRES_PASSWORD=testpwd export POSTGRES_DB=chinook
Start the services.
docker compose -f docker_compose_texttosql.yaml up
โ Invoke the microservice.ยถ
The Text-to-SQL microservice exposes the following API endpoints:
Test Database Connection
curl --location http://${your_ip}:9090/v1/postgres/health \ --header 'Content-Type: application/json' \ --data '{"user": "'${POSTGRES_USER}'","password": "'${POSTGRES_PASSWORD}'","host": "'${your_ip}'", "port": "5442", "database": "'${POSTGRES_DB}'"}'
Execute SQL Query from input text
curl http://${your_ip}:9090/v1/texttosql\ -X POST \ -d '{"input_text": "Find the total number of Albums.","conn_str": {"user": "'${POSTGRES_USER}'","password": "'${POSTGRES_PASSWORD}'","host": "'${your_ip}'", "port": "5442", "database": "'${POSTGRES_DB}'"}}' \ -H 'Content-Type: application/json'