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# ADR 008: Extensible-Jan-with-Docker | ||
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## Changelog | ||
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- 2023-10-24: Initial draft | ||
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## Authors | ||
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- @vuonghoainam | ||
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## Status | ||
Proposed | ||
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## Context | ||
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What is the issue that we're seeing that is motivating this decision or change? | ||
- The A.I world is moving fast with multiple runtime/ prebaked environment. We or the builder cannot cover just everything but rather we should adopt it and facillitate it as much as possible within Jan. | ||
- For `Run your own A.I`: Builder can build app on Jan (NodeJS env) and connect to external endpoint which serves the real A.I | ||
- e.g 1: Nitro acting as proxy to `triton-inference-server` running within a Docker container controlled by Jan app | ||
- e.g 2: Original models can be in many formats (pytorch, paddlepaddle). In order to run it with the most optimized version locally, there must be a step to transpile the model ([Ollama import model](https://github.com/jmorganca/ollama/blob/main/docs/import.md), Tensorrt). Btw Jan can prebuilt it and let user pull but later | ||
- For `Build your own A.I`: User can fine tune model locally (of course Jan help it with remote but later) | ||
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## Decision | ||
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What is the change that we're proposing and/or doing? | ||
- Add Docker client as Core module - [Docker node](https://github.com/apocas/dockerode) | ||
- 2 example A.I app (adr-002) to demonstrate it and actually use! | ||
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## Consequences | ||
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What becomes easier or more difficult to do because of this change? | ||
- We can extend limitlessly :D | ||
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## Alternatives | ||
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## Reference |
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