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This commit introduces the LangflowConnectorService class, which facilitates the management and processing of connector documents using the Langflow service. It includes methods for initializing the service, retrieving connectors, processing documents, and syncing files. The implementation emphasizes asynchronous processing and robust error handling, enhancing the overall maintainability and documentation of the codebase. |
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|---|---|---|
| .github/workflows | ||
| documents | ||
| flows | ||
| frontend | ||
| keys | ||
| securityconfig | ||
| src | ||
| .dockerignore | ||
| .DS_Store | ||
| .env.example | ||
| .gitignore | ||
| .python-version | ||
| docker-compose-cpu.yml | ||
| docker-compose.yml | ||
| Dockerfile | ||
| Dockerfile.backend | ||
| Dockerfile.frontend | ||
| Dockerfile.langflow | ||
| Makefile | ||
| pyproject.toml | ||
| README.md | ||
| uv.lock | ||
| warm_up_docling.py | ||
OpenRAG
getting started
Set up your secrets:
cp .env.example .env
Populate the values in .env
Requirements:
Docker or podman with compose installed.
Run OpenRAG:
docker compose build
docker compose up
CPU only:
docker compose -f docker-compose-cpu.yml up
If you need to reset state:
docker compose up --build --force-recreate --remove-orphans
For podman on mac you may have to increase your VM memory (podman stats should not show limit at only 2gb):
podman machine stop
podman machine rm
podman machine init --memory 8192 # example: 8 GB
podman machine start