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langchain/.devcontainer/docker-compose.yaml

31 lines
720 B
YAML

version: '3'
services:
langchain:
build:
dockerfile: libs/langchain/dev.Dockerfile
Update dev container (#6189) Fixes https://github.com/hwchase17/langchain/issues/6172 As described in https://github.com/hwchase17/langchain/issues/6172, I'd love to help update the dev container in this project. **Summary of changes:** - Dev container now builds (the current container in this repo won't build for me) - Dockerfile updates - Update image to our [currently-maintained Python image](https://github.com/devcontainers/images/tree/main/src/python/.devcontainer) (`mcr.microsoft.com/devcontainers/python`) rather than the deprecated image from vscode-dev-containers - Move Dockerfile to root of repo - in order for `COPY` to work properly, it needs the files (in this case, `pyproject.toml` and `poetry.toml`) in the same directory - devcontainer.json updates - Removed `customizations` and `remoteUser` since they should be covered by the updated image in the Dockerfile - Update comments - Update docker-compose.yaml to properly point to updated Dockerfile - Add a .gitattributes to avoid line ending conversions, which can result in hundreds of pending changes ([info](https://code.visualstudio.com/docs/devcontainers/tips-and-tricks#_resolving-git-line-ending-issues-in-containers-resulting-in-many-modified-files)) - Add a README in the .devcontainer folder and info on the dev container in the contributing.md **Outstanding questions:** - Is it expected for `poetry install` to take some time? It takes about 30 minutes for this dev container to finish building in a Codespace, but a user should only have to experience this once. Through some online investigation, this doesn't seem unusual - Versions of poetry newer than 1.3.2 failed every time - based on some of the guidance in contributing.md and other online resources, it seemed changing poetry versions might be a good solution. 1.3.2 is from Jan 2023 --------- Co-authored-by: bamurtaugh <brmurtau@microsoft.com> Co-authored-by: Samruddhi Khandale <samruddhikhandale@github.com>
1 year ago
context: ..
volumes:
community[minor]: Add ApertureDB as a vectorstore (#24088) Thank you for contributing to LangChain! - [X] *ApertureDB as vectorstore**: "community: Add ApertureDB as a vectorestore" - **Description:** this change provides a new community integration that uses ApertureData's ApertureDB as a vector store. - **Issue:** none - **Dependencies:** depends on ApertureDB Python SDK - **Twitter handle:** ApertureData - [X] **Add tests and docs**: If you're adding a new integration, please include 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. Integration tests rely on a local run of a public docker image. Example notebook additionally relies on a local Ollama server. - [X] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ All lint tests pass. Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17. --------- Co-authored-by: Gautam <gautam@aperturedata.io>
2 months ago
# Update this to wherever you want VS Code to mount the folder of your project
- ..:/workspaces/langchain:cached
networks:
community[minor]: Add ApertureDB as a vectorstore (#24088) Thank you for contributing to LangChain! - [X] *ApertureDB as vectorstore**: "community: Add ApertureDB as a vectorestore" - **Description:** this change provides a new community integration that uses ApertureData's ApertureDB as a vector store. - **Issue:** none - **Dependencies:** depends on ApertureDB Python SDK - **Twitter handle:** ApertureData - [X] **Add tests and docs**: If you're adding a new integration, please include 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. Integration tests rely on a local run of a public docker image. Example notebook additionally relies on a local Ollama server. - [X] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ All lint tests pass. Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17. --------- Co-authored-by: Gautam <gautam@aperturedata.io>
2 months ago
- langchain-network
# environment:
# MONGO_ROOT_USERNAME: root
# MONGO_ROOT_PASSWORD: example123
# depends_on:
# - mongo
# mongo:
# image: mongo
# restart: unless-stopped
# environment:
# MONGO_INITDB_ROOT_USERNAME: root
# MONGO_INITDB_ROOT_PASSWORD: example123
# ports:
# - "27017:27017"
# networks:
# - langchain-network
networks:
langchain-network:
driver: bridge