# What does this PR do?
- updated the notebooks to reflect past changes up to llama-stack 0.0.53
- updated readme to provide accurate and up-to-date info
- improve the current zero to hero by integrating an example using
together api
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] Ran pre-commit to handle lint / formatting issues.
- [x] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
Pull Request section?
- [ ] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.
---------
Co-authored-by: Sanyam Bhutani <sanyambhutani@meta.com>
# What does this PR do?
In short, provide a summary of what this PR does and why. Usually, the
relevant context should be present in a linked issue.
Add Kotlin package link into readme docs
# What does this PR do?
It shows a complete zero-setup Colab using the Llama Stack server
implemented and powered by together.ai: using Llama Stack Client API to
run inference, agent and 3.2 models. Good for a quick start guide.
- [ ] Addresses issue (#issue)
## Test Plan
Please describe:
- tests you ran to verify your changes with result summaries.
- provide instructions so it can be reproduced.
## Sources
Please link relevant resources if necessary.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Ran pre-commit to handle lint / formatting issues.
- [ ] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
Pull Request section?
- [ ] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.
* API Keys passed from Client instead of distro configuration
* delete distribution registry
* Rename the "package" word away
* Introduce a "Router" layer for providers
Some providers need to be factorized and considered as thin routing
layers on top of other providers. Consider two examples:
- The inference API should be a routing layer over inference providers,
routed using the "model" key
- The memory banks API is another instance where various memory bank
types will be provided by independent providers (e.g., a vector store
is served by Chroma while a keyvalue memory can be served by Redis or
PGVector)
This commit introduces a generalized routing layer for this purpose.
* update `apis_to_serve`
* llama_toolchain -> llama_stack
* Codemod from llama_toolchain -> llama_stack
- added providers/registry
- cleaned up api/ subdirectories and moved impls away
- restructured api/api.py
- from llama_stack.apis.<api> import foo should work now
- update imports to do llama_stack.apis.<api>
- update many other imports
- added __init__, fixed some registry imports
- updated registry imports
- create_agentic_system -> create_agent
- AgenticSystem -> Agent
* Moved some stuff out of common/; re-generated OpenAPI spec
* llama-toolchain -> llama-stack (hyphens)
* add control plane API
* add redis adapter + sqlite provider
* move core -> distribution
* Some more toolchain -> stack changes
* small naming shenanigans
* Removing custom tool and agent utilities and moving them client side
* Move control plane to distribution server for now
* Remove control plane from API list
* no codeshield dependency randomly plzzzzz
* Add "fire" as a dependency
* add back event loggers
* stack configure fixes
* use brave instead of bing in the example client
* add init file so it gets packaged
* add init files so it gets packaged
* Update MANIFEST
* bug fix
---------
Co-authored-by: Hardik Shah <hjshah@fb.com>
Co-authored-by: Xi Yan <xiyan@meta.com>
Co-authored-by: Ashwin Bharambe <ashwin@meta.com>
* Add distribution CLI scaffolding
* More progress towards `llama distribution install`
* getting closer to a distro definition, distro install + configure works
* Distribution server now functioning
* read existing configuration, save enums properly
* Remove inference uvicorn server entrypoint and llama inference CLI command
* updated dependency and client model name
* Improved exception handling
* local imports for faster cli
* undo a typo, add a passthrough distribution
* implement full-passthrough in the server
* add safety adapters, configuration handling, server + clients
* cleanup, moving stuff to common, nuke utils
* Add a Path() wrapper at the earliest place
* fixes
* Bring agentic system api to toolchain
Add adapter dependencies and resolve adapters using a topological sort
* refactor to reduce size of `agentic_system`
* move straggler files and fix some important existing bugs
* ApiSurface -> Api
* refactor a method out
* Adapter -> Provider
* Make each inference provider into its own subdirectory
* installation fixes
* Rename Distribution -> DistributionSpec, simplify RemoteProviders
* dict key instead of attr
* update inference config to take model and not model_dir
* Fix passthrough streaming, send headers properly not part of body :facepalm
* update safety to use model sku ids and not model dirs
* Update cli_reference.md
* minor fixes
* add DistributionConfig, fix a bug in model download
* Make install + start scripts do proper configuration automatically
* Update CLI_reference
* Nuke fp8_requirements, fold fbgemm into common requirements
* Update README, add newline between API surface configurations
* Refactor download functionality out of the Command so can be reused
* Add `llama model download` alias for `llama download`
* Show message about checksum file so users can check themselves
* Simpler intro statements
* get ollama working
* Reduce a bunch of dependencies from toolchain
Some improvements to the distribution install script
* Avoid using `conda run` since it buffers everything
* update dependencies and rely on LLAMA_TOOLCHAIN_DIR for dev purposes
* add validation for configuration input
* resort imports
* make optional subclasses default to yes for configuration
* Remove additional_pip_packages; move deps to providers
* for inline make 8b model the default
* Add scripts to MANIFEST
* allow installing from test.pypi.org
* Fix#2 to help with testing packages
* Must install llama-models at that same version first
* fix PIP_ARGS
---------
Co-authored-by: Hardik Shah <hjshah@fb.com>
Co-authored-by: Hardik Shah <hjshah@meta.com>
