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9 commits
| Author | SHA1 | Message | Date | |
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Charlie Doern
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4a3f9151e3 |
fix: rename StackRunConfig to StackConfig
since this object represents our config for list-deps, run, etc lets rename it to simply `StackConfig` Signed-off-by: Charlie Doern <cdoern@redhat.com> |
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Charlie Doern
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91f1b352b4
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chore: add storage sane defaults (#4182)
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# What does this PR do? since `StackRunConfig` requires certain parts of `StorageConfig`, it'd probably make sense to template in some defaults that will "just work" for most usecases specifically introduce`ServerStoresConfig` defaults for inference, metadata, conversations and prompts. We already actually funnel in defaults for these sections ad-hoc throughout the codebase additionally set some `backends` defaults for the `StorageConfig`. This will alleviate some weirdness for `--providers` for run/list-deps and also some work I have to better align our list-deps/run datatypes --------- Signed-off-by: Charlie Doern <cdoern@redhat.com> |
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Ashwin Bharambe
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bd5ad2963e
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refactor(storage): make { kvstore, sqlstore } as llama stack "internal" APIs (#4181)
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These primitives (used both by the Stack as well as provider implementations) can be thought of fruitfully as internal-only APIs which can themselves have multiple implementations. We use the new `llama_stack_api.internal` namespace for this. In addition: the change moves kv/sql store impls, configs, and dependency helpers under `core/storage` ## Testing `pytest tests/unit/utils/test_authorized_sqlstore.py`, other existing CI |
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Charlie Doern
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a078f089d9
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fix: rename llama_stack_api dir (#4155)
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# What does this PR do? the directory structure was src/llama-stack-api/llama_stack_api instead it should just be src/llama_stack_api to match the other packages. update the structure and pyproject/linting config --------- Signed-off-by: Charlie Doern <cdoern@redhat.com> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com> |
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Charlie Doern
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840ad75fe9
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feat: split API and provider specs into separate llama-stack-api pkg (#3895)
# What does this PR do? Extract API definitions and provider specifications into a standalone llama-stack-api package that can be published to PyPI independently of the main llama-stack server. see: https://github.com/llamastack/llama-stack/pull/2978 and https://github.com/llamastack/llama-stack/pull/2978#issuecomment-3145115942 Motivation External providers currently import from llama-stack, which overrides the installed version and causes dependency conflicts. This separation allows external providers to: - Install only the type definitions they need without server dependencies - Avoid version conflicts with the installed llama-stack package - Be versioned and released independently This enables us to re-enable external provider module tests that were previously blocked by these import conflicts. Changes - Created llama-stack-api package with minimal dependencies (pydantic, jsonschema) - Moved APIs, providers datatypes, strong_typing, and schema_utils - Updated all imports from llama_stack.* to llama_stack_api.* - Configured local editable install for development workflow - Updated linting and type-checking configuration for both packages Next Steps - Publish llama-stack-api to PyPI - Update external provider dependencies - Re-enable external provider module tests Pre-cursor PRs to this one: - #4093 - #3954 - #4064 These PRs moved key pieces _out_ of the Api pkg, limiting the scope of change here. relates to #3237 ## Test Plan Package builds successfully and can be imported independently. All pre-commit hooks pass with expected exclusions maintained. --------- Signed-off-by: Charlie Doern <cdoern@redhat.com> |
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Sébastien Han
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fd1603beef
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chore: remove unused classes (#4077)
# What does this PR do? These were maybe be included in the webmethod? The unit test was pointless too since the request was never used anywhere? This shouldn't be in the API definition, if we never consume it. ## Test Plan CI with pre-commit on OpenAPI spec generation. Signed-off-by: Sébastien Han <seb@redhat.com> |
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dependabot[bot]
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8885cea8d7
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fix(conversations)!: update Conversations API definitions (was: bump openai from 1.107.0 to 2.5.0) (#3847)
Bumps [openai](https://github.com/openai/openai-python) from 1.107.0 to 2.5.0. <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/openai/openai-python/releases">openai's releases</a>.</em></p> <blockquote> <h2>v2.5.0</h2> <h2>2.5.0 (2025-10-17)</h2> <p>Full Changelog: <a href="https://github.com/openai/openai-python/compare/v2.4.0...v2.5.0">v2.4.0...v2.5.0</a></p> <h3>Features</h3> <ul> <li><strong>api:</strong> api update (<a href=" |
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Ashwin Bharambe
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2c43285e22
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feat(stores)!: use backend storage references instead of configs (#3697)
**This PR changes configurations in a backward incompatible way.**
Run configs today repeat full SQLite/Postgres snippets everywhere a
store is needed, which means duplicated credentials, extra connection
pools, and lots of drift between files. This PR introduces named storage
backends so the stack and providers can share a single catalog and
reference those backends by name.
## Key Changes
- Add `storage.backends` to `StackRunConfig`, register each KV/SQL
backend once at startup, and validate that references point to the right
family.
- Move server stores under `storage.stores` with lightweight references
(backend + namespace/table) instead of full configs.
- Update every provider/config/doc to use the new reference style;
docs/codegen now surface the simplified YAML.
## Migration
Before:
```yaml
metadata_store:
type: sqlite
db_path: ~/.llama/distributions/foo/registry.db
inference_store:
type: postgres
host: ${env.POSTGRES_HOST}
port: ${env.POSTGRES_PORT}
db: ${env.POSTGRES_DB}
user: ${env.POSTGRES_USER}
password: ${env.POSTGRES_PASSWORD}
conversations_store:
type: postgres
host: ${env.POSTGRES_HOST}
port: ${env.POSTGRES_PORT}
db: ${env.POSTGRES_DB}
user: ${env.POSTGRES_USER}
password: ${env.POSTGRES_PASSWORD}
```
After:
```yaml
storage:
backends:
kv_default:
type: kv_sqlite
db_path: ~/.llama/distributions/foo/kvstore.db
sql_default:
type: sql_postgres
host: ${env.POSTGRES_HOST}
port: ${env.POSTGRES_PORT}
db: ${env.POSTGRES_DB}
user: ${env.POSTGRES_USER}
password: ${env.POSTGRES_PASSWORD}
stores:
metadata:
backend: kv_default
namespace: registry
inference:
backend: sql_default
table_name: inference_store
max_write_queue_size: 10000
num_writers: 4
conversations:
backend: sql_default
table_name: openai_conversations
```
Provider configs follow the same pattern—for example, a Chroma vector
adapter switches from:
```yaml
providers:
vector_io:
- provider_id: chromadb
provider_type: remote::chromadb
config:
url: ${env.CHROMADB_URL}
kvstore:
type: sqlite
db_path: ~/.llama/distributions/foo/chroma.db
```
to:
```yaml
providers:
vector_io:
- provider_id: chromadb
provider_type: remote::chromadb
config:
url: ${env.CHROMADB_URL}
persistence:
backend: kv_default
namespace: vector_io::chroma_remote
```
Once the backends are declared, everything else just points at them, so
rotating credentials or swapping to Postgres happens in one place and
the stack reuses a single connection pool.
|
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Francisco Arceo
|
a20e8eac8c
|
feat: Add OpenAI Conversations API (#3429)
# What does this PR do? Initial implementation for `Conversations` and `ConversationItems` using `AuthorizedSqlStore` with endpoints to: - CREATE - UPDATE - GET/RETRIEVE/LIST - DELETE Set `level=LLAMA_STACK_API_V1`. NOTE: This does not currently incorporate changes for Responses, that'll be done in a subsequent PR. Closes https://github.com/llamastack/llama-stack/issues/3235 ## Test Plan - Unit tests - Integration tests Also comparison of [OpenAPI spec for OpenAI API](https://github.com/openai/openai-openapi/tree/manual_spec) ```bash oasdiff breaking --fail-on ERR docs/static/llama-stack-spec.yaml https://raw.githubusercontent.com/openai/openai-openapi/refs/heads/manual_spec/openapi.yaml --strip-prefix-base "/v1/openai/v1" \ --match-path '(^/v1/openai/v1/conversations.*|^/conversations.*)' ``` Note I still have some uncertainty about this, I borrowed this info from @cdoern on https://github.com/llamastack/llama-stack/pull/3514 but need to spend more time to confirm it's working, at the moment it suggests it does. UPDATE on `oasdiff`, I investigated the OpenAI spec further and it looks like currently the spec does not list Conversations, so that analysis is useless. Noting for future reference. --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com> |