# What does this PR do?
metadata is conflicting with the default embedding model set on server
side via extra body, removing the check and just letting metadata take
precedence over extra body
`ValueError: Embedding model inconsistent between metadata
('text-embedding-3-small') and extra_body
('sentence-transformers/nomic-ai/nomic-embed-text-v1.5')`
## Test Plan
CI
# What does this PR do?
Fix segfault with load model
The cc-vec integration failed with segfault when used with default
embedding model on macOS
`model_id: nomic-ai/nomic-embed-text-v1.5` and `provider_id:
sentence-transformers`
Checked crash report and see this is due to torch OPENMP settings.
Constrainting to 1 thread works without crashes.
## Test Plan
Tested with cc-vec integration
1. start server llama stack run starter
2. Do the setup in https://github.com/raghotham/cc-vec to set env
variables and try
`uv run cc-vec index --url-patterns "%.github.io" --vector-store-name
"ml-research" --limit 50 --chunk-size 800 --overlap 400`
- Moved environment variable parsing and `setup_logging()` call from
module level to proper initialization points
- Added explicit `setup_logging()` calls in `server.py::create_app()`
and `library_client.py::AsyncLlamaStackAsLibraryClient.__init__()`
Module-level side effects are bad practice and can cause issues with
import order, testing, and circular dependencies. The previous
implementation ran logging setup on every import of the log module,
which is unpredictable and difficult to control.
---------
Co-authored-by: Claude <noreply@anthropic.com>
Kill the `builtin::rag` tool group completely since it is no longer
targeted. We use the Responses implementation for knowledge_search which
uses the `openai_vector_stores` pathway.
---------
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Bumps
[@types/node](https://github.com/DefinitelyTyped/DefinitelyTyped/tree/HEAD/types/node)
from 24.3.0 to 24.8.1.
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/DefinitelyTyped/DefinitelyTyped/commits/HEAD/types/node">compare
view</a></li>
</ul>
</details>
<br />
[](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores)
Dependabot will resolve any conflicts with this PR as long as you don't
alter it yourself. You can also trigger a rebase manually by commenting
`@dependabot rebase`.
[//]: # (dependabot-automerge-start)
[//]: # (dependabot-automerge-end)
---
<details>
<summary>Dependabot commands and options</summary>
<br />
You can trigger Dependabot actions by commenting on this PR:
- `@dependabot rebase` will rebase this PR
- `@dependabot recreate` will recreate this PR, overwriting any edits
that have been made to it
- `@dependabot merge` will merge this PR after your CI passes on it
- `@dependabot squash and merge` will squash and merge this PR after
your CI passes on it
- `@dependabot cancel merge` will cancel a previously requested merge
and block automerging
- `@dependabot reopen` will reopen this PR if it is closed
- `@dependabot close` will close this PR and stop Dependabot recreating
it. You can achieve the same result by closing it manually
- `@dependabot show <dependency name> ignore conditions` will show all
of the ignore conditions of the specified dependency
- `@dependabot ignore this major version` will close this PR and stop
Dependabot creating any more for this major version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this minor version` will close this PR and stop
Dependabot creating any more for this minor version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this dependency` will close this PR and stop
Dependabot creating any more for this dependency (unless you reopen the
PR or upgrade to it yourself)
</details>
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
**NOTE: this is a backwards incompatible change to the run-configs.**
A small QOL update, but this will prove useful when I do a rename for
"vector_dbs" to "vector_stores" next.
Moves all the `models, shields, ...` keys in run-config under a
`registered_resources` sub-key.
# What does this PR do?
Refactor setting default vector store provider and embedding model to
use an optional `vector_stores` config in the `StackRunConfig` and clean
up code to do so (had to add back in some pieces of VectorDB). Also
added remote Qdrant and Weaviate to starter distro (based on other PR
where inference providers were added for UX).
New config is simply (default for Starter distro):
```yaml
vector_stores:
default_provider_id: faiss
default_embedding_model:
provider_id: sentence-transformers
model_id: nomic-ai/nomic-embed-text-v1.5
```
## Test Plan
CI and Unit tests.
---------
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
**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.
# Problem
The current inline provider appends the user provided instructions to
messages as a system prompt, but the returned response object does not
contain the instructions field (as specified in the OpenAI responses
spec).
# What does this PR do?
This pull request adds the instruction field to the response object
definition and updates the inline provider. It also ensures that
instructions from previous response is not carried over to the next
response (as specified in the openAI spec).
Closes #[3566](https://github.com/llamastack/llama-stack/issues/3566)
## Test Plan
- Tested manually for change in model response w.r.t supplied
instructions field.
- Added unit test to check that the instructions from previous response
is not carried over to the next response.
- Added integration tests to check instructions parameter in the
returned response object.
- Added new recordings for the integration tests.
---------
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
fix: nested claims mapping in OAuth2 token validation
The get_attributes_from_claims function was only checking for top-level
claim keys, causing token validation to fail when using nested claims
like "resource_access.llamastack.roles" (common in Keycloak JWT tokens).
Updated the function to support dot notation for traversing nested claim
structures. Give precedence to dot notation over literal keys with dots
in claims mapping.
Added test coverage.
Closes: #3812
Signed-off-by: Derek Higgins <derekh@redhat.com>
# What does this PR do?
removes error:
ConnectionError: HTTPConnectionPool(host='localhost', port=4318): Max
retries exceeded with url: /v1/traces
(Caused by NewConnectionError('<urllib3.connection.HTTPConnection object
at 0x10fd98e60>: Failed to establish a
new connection: [Errno 61] Connection refused'))
## Test Plan
uv run llama stack run starter
curl http://localhost:8321/v1/models
observe no error in server logs
# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->
- Fix examples in the NVIDIA inference documentation to align with
current API requirements.
## Test Plan
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->
N/A
Bumps [jest](https://github.com/jestjs/jest/tree/HEAD/packages/jest) and
[@types/jest](https://github.com/DefinitelyTyped/DefinitelyTyped/tree/HEAD/types/jest).
These dependencies needed to be updated together.
Updates `jest` from 29.7.0 to 30.2.0
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/jestjs/jest/releases">jest's
releases</a>.</em></p>
<blockquote>
<h2>30.2.0</h2>
<h3>Chore & Maintenance</h3>
<ul>
<li><code>[*]</code> Update example repo for testing React Native
projects (<a
href="https://redirect.github.com/jestjs/jest/pull/15832">#15832</a>)</li>
<li><code>[*]</code> Update <code>jest-watch-typeahead</code> to v3 (<a
href="https://redirect.github.com/jestjs/jest/pull/15830">#15830</a>)</li>
</ul>
<h2>Features</h2>
<ul>
<li><code>[jest-environment-jsdom-abstract]</code> Add support for JSDOM
v27 (<a
href="https://redirect.github.com/jestjs/jest/pull/15834">#15834</a>)</li>
</ul>
<h3>Fixes</h3>
<ul>
<li><code>[babel-jest]</code> Export the <code>TransformerConfig</code>
interface (<a
href="https://redirect.github.com/jestjs/jest/pull/15820">#15820</a>)</li>
<li><code>[jest-config]</code> Fix <code>jest.config.ts</code> with TS
loader specified in docblock pragma (<a
href="https://redirect.github.com/jestjs/jest/pull/15839">#15839</a>)</li>
</ul>
<h2>30.1.3</h2>
<h3>Fixes</h3>
<ul>
<li>Fix <code>unstable_mockModule</code> with <code>node:</code>
prefixed core modules.</li>
</ul>
<h2>30.1.2</h2>
<h3>Fixes</h3>
<ul>
<li><code>[jest-snapshot-utils]</code> Correct snapshot header regexp to
work with newline across OSes (<a
href="https://redirect.github.com/jestjs/jest/pull/15803">#15803</a>)</li>
</ul>
<h2>30.1.1</h2>
<h3>Fixes</h3>
<ul>
<li><code>[jest-snapshot-utils]</code> Fix deprecated goo.gl snapshot
warning not handling Windows end-of-line sequences (<a
href="https://redirect.github.com/jestjs/jest/pull/15800">#15800</a>)</li>
</ul>
<h2>30.1.0</h2>
<h2>Features</h2>
<ul>
<li><code>[jest-leak-detector]</code> Configurable GC aggressiveness
regarding to V8 heap snapshot generation (<a
href="https://redirect.github.com/jestjs/jest/pull/15793/">#15793</a>)</li>
<li><code>[jest-runtime]</code> Reduce redundant ReferenceError
messages</li>
<li><code>[jest-core]</code> Include test modules that failed to load
when --onlyFailures is active</li>
</ul>
<h3>Fixes</h3>
<ul>
<li>`[jest-snapshot-utils] Fix deprecated goo.gl snapshot guide link not
getting replaced with fully canonical URL (<a
href="https://redirect.github.com/jestjs/jest/pull/15787">#15787</a>)</li>
<li><code>[jest-circus]</code> Fix <code>it.concurrent</code> not
working with <code>describe.skip</code> (<a
href="https://redirect.github.com/jestjs/jest/pull/15765">#15765</a>)</li>
<li><code>[jest-snapshot]</code> Fix mangled inline snapshot updates
when used with Prettier 3 and CRLF line endings</li>
<li><code>[jest-runtime]</code> Importing from
<code>@jest/globals</code> in more than one file no longer breaks
relative paths (<a
href="https://redirect.github.com/jestjs/jest/issues/15772">#15772</a>)</li>
</ul>
<h1>Chore</h1>
<ul>
<li><code>[expect]</code> Update docblock for <code>toContain()</code>
to display info on substring check (<a
href="https://redirect.github.com/jestjs/jest/pull/15789">#15789</a>)</li>
</ul>
<h2>30.0.2</h2>
<h2>What's Changed</h2>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/jestjs/jest/blob/main/CHANGELOG.md">jest's
changelog</a>.</em></p>
<blockquote>
<h2>30.2.0</h2>
<h3>Chore & Maintenance</h3>
<ul>
<li><code>[*]</code> Update example repo for testing React Native
projects (<a
href="https://redirect.github.com/jestjs/jest/pull/15832">#15832</a>)</li>
<li><code>[*]</code> Update <code>jest-watch-typeahead</code> to v3 (<a
href="https://redirect.github.com/jestjs/jest/pull/15830">#15830</a>)</li>
</ul>
<h2>Features</h2>
<ul>
<li><code>[jest-environment-jsdom-abstract]</code> Add support for JSDOM
v27 (<a
href="https://redirect.github.com/jestjs/jest/pull/15834">#15834</a>)</li>
</ul>
<h3>Fixes</h3>
<ul>
<li><code>[jest-matcher-utils]</code> Fix infinite recursion with
self-referential getters in <code>deepCyclicCopyReplaceable</code> (<a
href="https://redirect.github.com/jestjs/jest/pull/15831">#15831</a>)</li>
<li><code>[babel-jest]</code> Export the <code>TransformerConfig</code>
interface (<a
href="https://redirect.github.com/jestjs/jest/pull/15820">#15820</a>)</li>
<li><code>[jest-config]</code> Fix <code>jest.config.ts</code> with TS
loader specified in docblock pragma (<a
href="https://redirect.github.com/jestjs/jest/pull/15839">#15839</a>)</li>
</ul>
<h2>30.1.3</h2>
<h3>Fixes</h3>
<ul>
<li>Fix <code>unstable_mockModule</code> with <code>node:</code>
prefixed core modules.</li>
</ul>
<h2>30.1.2</h2>
<h3>Fixes</h3>
<ul>
<li><code>[jest-snapshot-utils]</code> Correct snapshot header regexp to
work with newline across OSes (<a
href="https://redirect.github.com/jestjs/jest/pull/15803">#15803</a>)</li>
</ul>
<h2>30.1.1</h2>
<h3>Fixes</h3>
<ul>
<li><code>[jest-snapshot-utils]</code> Fix deprecated goo.gl snapshot
warning not handling Windows end-of-line sequences (<a
href="https://redirect.github.com/jestjs/jest/pull/15800">#15800</a>)</li>
<li><code>[jest-snapshot-utils]</code> Improve messaging about goo.gl
snapshot link change (<a
href="https://redirect.github.com/jestjs/jest/pull/15821">#15821</a>)</li>
</ul>
<h2>30.1.0</h2>
<h2>Features</h2>
<ul>
<li><code>[jest-leak-detector]</code> Configurable GC aggressiveness
regarding to V8 heap snapshot generation (<a
href="https://redirect.github.com/jestjs/jest/pull/15793/">#15793</a>)</li>
<li><code>[jest-runtime]</code> Reduce redundant ReferenceError
messages</li>
<li><code>[jest-core]</code> Include test modules that failed to load
when --onlyFailures is active</li>
</ul>
<h3>Fixes</h3>
<ul>
<li><code>[jest-snapshot-utils]</code> Fix deprecated goo.gl snapshot
guide link not getting replaced with fully canonical URL (<a
href="https://redirect.github.com/jestjs/jest/pull/15787">#15787</a>)</li>
<li><code>[jest-circus]</code> Fix <code>it.concurrent</code> not
working with <code>describe.skip</code> (<a
href="https://redirect.github.com/jestjs/jest/pull/15765">#15765</a>)</li>
<li><code>[jest-snapshot]</code> Fix mangled inline snapshot updates
when used with Prettier 3 and CRLF line endings</li>
<li><code>[jest-runtime]</code> Importing from
<code>@jest/globals</code> in more than one file no longer breaks
relative paths (<a
href="https://redirect.github.com/jestjs/jest/issues/15772">#15772</a>)</li>
</ul>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="855864e3f9"><code>855864e</code></a>
v30.2.0</li>
<li><a
href="da9b532f04"><code>da9b532</code></a>
v30.1.3</li>
<li><a
href="ebfa31cc97"><code>ebfa31c</code></a>
v30.1.2</li>
<li><a
href="d347c0f3f8"><code>d347c0f</code></a>
v30.1.1</li>
<li><a
href="4d5f41d088"><code>4d5f41d</code></a>
v30.1.0</li>
<li><a
href="22236cf58b"><code>22236cf</code></a>
v30.0.5</li>
<li><a
href="f4296d2bc8"><code>f4296d2</code></a>
v30.0.4</li>
<li><a
href="d4a6c94daf"><code>d4a6c94</code></a>
v30.0.3</li>
<li><a
href="393acbfac3"><code>393acbf</code></a>
v30.0.2</li>
<li><a
href="5ce865b406"><code>5ce865b</code></a>
v30.0.1</li>
<li>Additional commits viewable in <a
href="https://github.com/jestjs/jest/commits/v30.2.0/packages/jest">compare
view</a></li>
</ul>
</details>
<br />
Updates `@types/jest` from 29.5.14 to 30.0.0
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/DefinitelyTyped/DefinitelyTyped/commits/HEAD/types/jest">compare
view</a></li>
</ul>
</details>
<br />
Dependabot will resolve any conflicts with this PR as long as you don't
alter it yourself. You can also trigger a rebase manually by commenting
`@dependabot rebase`.
[//]: # (dependabot-automerge-start)
[//]: # (dependabot-automerge-end)
---
<details>
<summary>Dependabot commands and options</summary>
<br />
You can trigger Dependabot actions by commenting on this PR:
- `@dependabot rebase` will rebase this PR
- `@dependabot recreate` will recreate this PR, overwriting any edits
that have been made to it
- `@dependabot merge` will merge this PR after your CI passes on it
- `@dependabot squash and merge` will squash and merge this PR after
your CI passes on it
- `@dependabot cancel merge` will cancel a previously requested merge
and block automerging
- `@dependabot reopen` will reopen this PR if it is closed
- `@dependabot close` will close this PR and stop Dependabot recreating
it. You can achieve the same result by closing it manually
- `@dependabot show <dependency name> ignore conditions` will show all
of the ignore conditions of the specified dependency
- `@dependabot ignore this major version` will close this PR and stop
Dependabot creating any more for this major version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this minor version` will close this PR and stop
Dependabot creating any more for this minor version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this dependency` will close this PR and stop
Dependabot creating any more for this dependency (unless you reopen the
PR or upgrade to it yourself)
</details>
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Bumps
[jest-environment-jsdom](https://github.com/jestjs/jest/tree/HEAD/packages/jest-environment-jsdom)
from 30.1.2 to 30.2.0.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/jestjs/jest/releases">jest-environment-jsdom's
releases</a>.</em></p>
<blockquote>
<h2>30.2.0</h2>
<h3>Chore & Maintenance</h3>
<ul>
<li><code>[*]</code> Update example repo for testing React Native
projects (<a
href="https://redirect.github.com/jestjs/jest/pull/15832">#15832</a>)</li>
<li><code>[*]</code> Update <code>jest-watch-typeahead</code> to v3 (<a
href="https://redirect.github.com/jestjs/jest/pull/15830">#15830</a>)</li>
</ul>
<h2>Features</h2>
<ul>
<li><code>[jest-environment-jsdom-abstract]</code> Add support for JSDOM
v27 (<a
href="https://redirect.github.com/jestjs/jest/pull/15834">#15834</a>)</li>
</ul>
<h3>Fixes</h3>
<ul>
<li><code>[babel-jest]</code> Export the <code>TransformerConfig</code>
interface (<a
href="https://redirect.github.com/jestjs/jest/pull/15820">#15820</a>)</li>
<li><code>[jest-config]</code> Fix <code>jest.config.ts</code> with TS
loader specified in docblock pragma (<a
href="https://redirect.github.com/jestjs/jest/pull/15839">#15839</a>)</li>
</ul>
<h2>30.1.3</h2>
<h3>Fixes</h3>
<ul>
<li>Fix <code>unstable_mockModule</code> with <code>node:</code>
prefixed core modules.</li>
</ul>
</blockquote>
</details>
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/jestjs/jest/blob/main/CHANGELOG.md">jest-environment-jsdom's
changelog</a>.</em></p>
<blockquote>
<h2>30.2.0</h2>
<h3>Chore & Maintenance</h3>
<ul>
<li><code>[*]</code> Update example repo for testing React Native
projects (<a
href="https://redirect.github.com/jestjs/jest/pull/15832">#15832</a>)</li>
<li><code>[*]</code> Update <code>jest-watch-typeahead</code> to v3 (<a
href="https://redirect.github.com/jestjs/jest/pull/15830">#15830</a>)</li>
</ul>
<h2>Features</h2>
<ul>
<li><code>[jest-environment-jsdom-abstract]</code> Add support for JSDOM
v27 (<a
href="https://redirect.github.com/jestjs/jest/pull/15834">#15834</a>)</li>
</ul>
<h3>Fixes</h3>
<ul>
<li><code>[jest-matcher-utils]</code> Fix infinite recursion with
self-referential getters in <code>deepCyclicCopyReplaceable</code> (<a
href="https://redirect.github.com/jestjs/jest/pull/15831">#15831</a>)</li>
<li><code>[babel-jest]</code> Export the <code>TransformerConfig</code>
interface (<a
href="https://redirect.github.com/jestjs/jest/pull/15820">#15820</a>)</li>
<li><code>[jest-config]</code> Fix <code>jest.config.ts</code> with TS
loader specified in docblock pragma (<a
href="https://redirect.github.com/jestjs/jest/pull/15839">#15839</a>)</li>
</ul>
<h2>30.1.3</h2>
<h3>Fixes</h3>
<ul>
<li>Fix <code>unstable_mockModule</code> with <code>node:</code>
prefixed core modules.</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="855864e3f9"><code>855864e</code></a>
v30.2.0</li>
<li>See full diff in <a
href="https://github.com/jestjs/jest/commits/v30.2.0/packages/jest-environment-jsdom">compare
view</a></li>
</ul>
</details>
<br />
[](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores)
Dependabot will resolve any conflicts with this PR as long as you don't
alter it yourself. You can also trigger a rebase manually by commenting
`@dependabot rebase`.
[//]: # (dependabot-automerge-start)
[//]: # (dependabot-automerge-end)
---
<details>
<summary>Dependabot commands and options</summary>
<br />
You can trigger Dependabot actions by commenting on this PR:
- `@dependabot rebase` will rebase this PR
- `@dependabot recreate` will recreate this PR, overwriting any edits
that have been made to it
- `@dependabot merge` will merge this PR after your CI passes on it
- `@dependabot squash and merge` will squash and merge this PR after
your CI passes on it
- `@dependabot cancel merge` will cancel a previously requested merge
and block automerging
- `@dependabot reopen` will reopen this PR if it is closed
- `@dependabot close` will close this PR and stop Dependabot recreating
it. You can achieve the same result by closing it manually
- `@dependabot show <dependency name> ignore conditions` will show all
of the ignore conditions of the specified dependency
- `@dependabot ignore this major version` will close this PR and stop
Dependabot creating any more for this major version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this minor version` will close this PR and stop
Dependabot creating any more for this minor version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this dependency` will close this PR and stop
Dependabot creating any more for this dependency (unless you reopen the
PR or upgrade to it yourself)
</details>
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
# What does this PR do?
Adds a test and a standardized way to build future tests out for
telemetry in llama stack.
Contributes to https://github.com/llamastack/llama-stack/issues/3806
## Test Plan
This is the test plan 😎
# What does this PR do?
remove telemetry as a providable API from the codebase. This includes
removing it from generated distributions but also the provider registry,
the router, etc
since `setup_logger` is tied pretty strictly to `Api.telemetry` being in
impls we still need an "instantiated provider" in our implementations.
However it should not be auto-routed or provided. So in
validate_and_prepare_providers (called from resolve_impls) I made it so
that if run_config.telemetry.enabled, we set up the meta-reference
"provider" internally to be used so that log_event will work when
called.
This is the neatest way I think we can remove telemetry from the
provider configs but also not need to rip apart the whole "telemetry is
a provider" logic just yet, but we can do it internally later without
disrupting users.
so telemetry is removed from the registry such that if a user puts
`telemetry:` as an API in their build/run config it will err out, but
can still be used by us internally as we go through this transition.
relates to #3806
Signed-off-by: Charlie Doern <cdoern@redhat.com>
As indicated in the title. Our `starter` distribution enables all remote
providers _very intentionally_ because we believe it creates an easier,
more welcoming experience to new folks using the software. If we do
that, and then slam the logs with errors making them question their life
choices, it is not so good :)
Note that this fix is limited in scope. If you ever try to actually
instantiate the OpenAI client from a code path without an API key being
present, you deserve to fail hard.
## Test Plan
Run `llama stack run starter` with `OPENAI_API_KEY` set. No more wall of
text, just one message saying "listed 96 models".
a bunch of logger.info()s are good for server code to help debug in
production, but we don't want them killing our unit test output :)
---------
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
**!!BREAKING CHANGE!!**
The lookup is also straightforward -- we always look for this identifier
and don't try to find a match for something without the provider_id
prefix.
Note that, this ideally means we need to update the `register_model()`
API also (we should kill "identifier" from there) but I am not doing
that as part of this PR.
## Test Plan
Existing unit tests
Wanted to re-enable Responses CI but it seems to hang for some reason
due to some interactions with conversations_store or responses_store.
## Test Plan
```
# library client
./scripts/integration-tests.sh --stack-config ci-tests --suite responses
# server
./scripts/integration-tests.sh --stack-config server:ci-tests --suite responses
```
# What does this PR do?
Have closed the previous PR due to merge conflicts with multiple PRs
Addressed all comments from
https://github.com/llamastack/llama-stack/pull/3768 (sorry for carrying
over to this one)
## Test Plan
Added UTs and integration tests
Handle a base case when no stored messages exist because no Response
call has been made.
## Test Plan
```
./scripts/integration-tests.sh --stack-config server:ci-tests \
--suite responses --inference-mode record-if-missing --pattern test_conversation_responses
```
Fixed KeyError when chunks don't have document_id in metadata or
chunk_metadata. Updated logging to safely extract document_id using
getattr and RAG memory to handle different document_id locations. Added
test for missing document_id scenarios.
Fixes issue #3494 where /v1/vector-io/insert would crash with KeyError.
Fixed KeyError when chunks don't have document_id in metadata or
chunk_metadata. Updated logging to safely extract document_id using
getattr and RAG memory to handle different document_id locations. Added
test for missing document_id scenarios.
# What does this PR do?
Fixes a KeyError crash in `/v1/vector-io/insert` when chunks are missing
`document_id` fields. The API
was failing even though `document_id` is optional according to the
schema.
Closes#3494
## Test Plan
**Before fix:**
- POST to `/v1/vector-io/insert` with chunks → 500 KeyError
- Happened regardless of where `document_id` was placed
**After fix:**
- Same request works fine → 200 OK
- Tested with Postman using FAISS backend
- Added unit test covering missing `document_id` scenarios
This PR updates the Conversation item related types and improves a
couple critical parts of the implemenation:
- it creates a streaming output item for the final assistant message
output by
the model. until now we only added content parts and included that
message in the final response.
- rewrites the conversation update code completely to account for items
other than messages (tool calls, outputs, etc.)
## Test Plan
Used the test script from
https://github.com/llamastack/llama-stack-client-python/pull/281 for
this
```
TEST_API_BASE_URL=http://localhost:8321/v1 \
pytest tests/integration/test_agent_turn_step_events.py::test_client_side_function_tool -xvs
```
# Add support for Google Gemini `gemini-embedding-001` embedding model
and correctly registers model type
MR message created with the assistance of Claude-4.5-sonnet
This resolves https://github.com/llamastack/llama-stack/issues/3755
## What does this PR do?
This PR adds support for the `gemini-embedding-001` Google embedding
model to the llama-stack Gemini provider. This model provides
high-dimensional embeddings (3072 dimensions) compared to the existing
`text-embedding-004` model (768 dimensions). Old embeddings models (such
as text-embedding-004) will be deprecated soon according to Google
([Link](https://developers.googleblog.com/en/gemini-embedding-available-gemini-api/))
## Problem
The Gemini provider only supported the `text-embedding-004` embedding
model. The newer `gemini-embedding-001` model, which provides
higher-dimensional embeddings for improved semantic representation, was
not available through llama-stack.
## Solution
This PR consists of three commits that implement, fix the model
registration, and enable embedding generation:
### Commit 1: Initial addition of gemini-embedding-001
Added metadata for `gemini-embedding-001` to the
`embedding_model_metadata` dictionary:
```python
embedding_model_metadata: dict[str, dict[str, int]] = {
"text-embedding-004": {"embedding_dimension": 768, "context_length": 2048},
"gemini-embedding-001": {"embedding_dimension": 3072, "context_length": 2048}, # NEW
}
```
**Issue discovered:** The model was not being registered correctly
because the dictionary keys didn't match the model IDs returned by
Gemini's API.
### Commit 2: Fix model ID matching with `models/` prefix
Updated both dictionary keys to include the `models/` prefix to match
Gemini's OpenAI-compatible API response format:
```python
embedding_model_metadata: dict[str, dict[str, int]] = {
"models/text-embedding-004": {"embedding_dimension": 768, "context_length": 2048}, # UPDATED
"models/gemini-embedding-001": {"embedding_dimension": 3072, "context_length": 2048}, # UPDATED
}
```
**Root cause:** Gemini's OpenAI-compatible API returns model IDs with
the `models/` prefix (e.g., `models/text-embedding-004`). The
`OpenAIMixin.list_models()` method directly matches these IDs against
the `embedding_model_metadata` dictionary keys. Without the prefix, the
models were being registered as LLMs instead of embedding models.
### Commit 3: Fix embedding generation for providers without usage stats
Fixed a bug in `OpenAIMixin.openai_embeddings()` that prevented
embedding generation for providers (like Gemini) that don't return usage
statistics:
```python
# Before (Line 351-354):
usage = OpenAIEmbeddingUsage(
prompt_tokens=response.usage.prompt_tokens, # ← Crashed with AttributeError
total_tokens=response.usage.total_tokens,
)
# After (Lines 351-362):
if response.usage:
usage = OpenAIEmbeddingUsage(
prompt_tokens=response.usage.prompt_tokens,
total_tokens=response.usage.total_tokens,
)
else:
usage = OpenAIEmbeddingUsage(
prompt_tokens=0, # Default when not provided
total_tokens=0, # Default when not provided
)
```
**Impact:** This fix enables embedding generation for **all** Gemini
embedding models, not just the newly added one.
## Changes
### Modified Files
**`llama_stack/providers/remote/inference/gemini/gemini.py`**
- Line 17: Updated `text-embedding-004` key to
`models/text-embedding-004`
- Line 18: Added `models/gemini-embedding-001` with correct metadata
**`llama_stack/providers/utils/inference/openai_mixin.py`**
- Lines 351-362: Added null check for `response.usage` to handle
providers without usage statistics
## Key Technical Details
### Model ID Matching Flow
1. `list_provider_model_ids()` calls Gemini's `/v1/models` endpoint
2. API returns model IDs like: `models/text-embedding-004`,
`models/gemini-embedding-001`
3. `OpenAIMixin.list_models()` (line 410) checks: `if metadata :=
self.embedding_model_metadata.get(provider_model_id)`
4. If matched, registers as `model_type: "embedding"` with metadata;
otherwise registers as `model_type: "llm"`
### Why Both Keys Needed the Prefix
The `text-embedding-004` model was already working because there was
likely separate configuration or manual registration handling it. For
auto-discovery to work correctly for **both** models, both keys must
match the API's model ID format exactly.
## How to test this PR
Verified the changes by:
1. **Model Auto-Discovery**: Started llama-stack server and confirmed
models are auto-discovered from Gemini API
2. **Model Registration**: Confirmed both embedding models are correctly
registered and visible
```bash
curl http://localhost:8325/v1/models | jq '.data[] | select(.provider_id == "gemini" and .model_type == "embedding")'
```
**Results:**
- ✅ `gemini/models/text-embedding-004` - 768 dimensions - `model_type:
"embedding"`
- ✅ `gemini/models/gemini-embedding-001` - 3072 dimensions -
`model_type: "embedding"`
3. **Before Fix (Commit 1)**: Models appeared as `model_type: "llm"`
without embedding metadata
4. **After Fix (Commit 2)**: Models correctly identified as `model_type:
"embedding"` with proper metadata
5. **Generate Embeddings**: Verified embedding generation works
```bash
curl -X POST http://localhost:8325/v1/embeddings \
-H "Content-Type: application/json" \
-d '{"model": "gemini/models/gemini-embedding-001", "input": "test"}' | \
jq '.data[0].embedding | length'
```
# What does this PR do?
Enables automatic embedding model detection for vector stores and by
using a `default_configured` boolean that can be defined in the
`run.yaml`.
<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->
## Test Plan
- Unit tests
- Integration tests
- Simple example below:
Spin up the stack:
```bash
uv run llama stack build --distro starter --image-type venv --run
```
Then test with OpenAI's client:
```python
from openai import OpenAI
client = OpenAI(base_url="http://localhost:8321/v1/", api_key="none")
vs = client.vector_stores.create()
```
Previously you needed:
```python
vs = client.vector_stores.create(
extra_body={
"embedding_model": "sentence-transformers/all-MiniLM-L6-v2",
"embedding_dimension": 384,
}
)
```
The `extra_body` is now unnecessary.
---------
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
Previously, the NVIDIA inference provider implemented a custom
`openai_embeddings` method with a hardcoded `input_type="query"`
parameter, which is required by NVIDIA asymmetric embedding
models([https://github.com/llamastack/llama-stack/pull/3205](https://github.com/llamastack/llama-stack/pull/3205)).
Recently `extra_body` parameter is added to the embeddings API
([https://github.com/llamastack/llama-stack/pull/3794](https://github.com/llamastack/llama-stack/pull/3794)).
So, this PR updates the NVIDIA inference provider to use the base
`OpenAIMixin.openai_embeddings` method instead and pass the `input_type`
through the `extra_body` parameter for asymmetric embedding models.
<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->
## Test Plan
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->
Run the following command for the ```embedding_model```:
```nvidia/llama-3.2-nv-embedqa-1b-v2```, ```nvidia/nv-embedqa-e5-v5```,
```nvidia/nv-embedqa-mistral-7b-v2```, and
```snowflake/arctic-embed-l```.
```
pytest -s -v tests/integration/inference/test_openai_embeddings.py --stack-config="inference=nvidia" --embedding-model={embedding_model} --env NVIDIA_API_KEY={nvidia_api_key} --env NVIDIA_BASE_URL="https://integrate.api.nvidia.com" --inference-mode=record
```
# What does this PR do?
As discussed on discord, we do not need to reinvent the wheel for
telemetry. Instead we'll lean into the canonical OTEL stack.
Logs/traces/metrics will still be sent via OTEL - they just won't be
stored on, queried through Stack.
This is the first of many PRs to remove telemetry API from Stack.
1) removed webmethod decorators to remove from API spec
2) removed tests as @iamemilio is adding them on otel directly.
## Test Plan
# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
The purpose of this PR is to replace the Llama Stack's default embedding
model by nomic-embed-text-v1.5.
These are the key reasons why Llama Stack community decided to switch
from all-MiniLM-L6-v2 to nomic-embed-text-v1.5:
1. The training data for
[all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2#training-data)
includes a lot of data sets with various licensing terms, so it is
tricky to know when/whether it is appropriate to use this model for
commercial applications.
2. The model is not particularly competitive on major benchmarks. For
example, if you look at the [MTEB
Leaderboard](https://huggingface.co/spaces/mteb/leaderboard) and click
on Miscellaneous/BEIR to see English information retrieval accuracy, you
see that the top of the leaderboard is dominated by enormous models but
also that there are many, many models of relatively modest size whith
much higher Retrieval scores. If you want to look closely at the data, I
recommend clicking "Download Table" because it is easier to browse that
way.
More discussion info can be founded
[here](https://github.com/llamastack/llama-stack/issues/2418)
<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->
Closes#2418
## Test Plan
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->
1. Run `./scripts/unit-tests.sh`
2. Integration tests via CI wokrflow
---------
Signed-off-by: Sébastien Han <seb@redhat.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Francisco Arceo <arceofrancisco@gmail.com>
Co-authored-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
This PR fixes issues with the WatsonX provider so it works correctly
with LiteLLM.
The main problem was that WatsonX requests failed because the provider
data validator didn’t properly handle the API key and project ID. This
was fixed by updating the WatsonXProviderDataValidator and ensuring the
provider data is loaded correctly.
The openai_chat_completion method was also updated to match the behavior
of other providers while adding WatsonX-specific fields like project_id.
It still calls await super().openai_chat_completion.__func__(self,
params) to keep the existing setup and tracing logic.
After these changes, WatsonX requests now run correctly.
## Test Plan
The changes were tested by running chat completion requests and
confirming that credentials and project parameters are passed correctly.
I have tested with my WatsonX credentials, by using the cli with `uv run
llama-stack-client inference chat-completion --session`
---------
Signed-off-by: Sébastien Han <seb@redhat.com>
Co-authored-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
This commit migrates the authentication system from python-jose to PyJWT
to eliminate the dependency on the archived rsa package. The migration
includes:
- Refactored OAuth2TokenAuthProvider to use PyJWT's PyJWKClient for
clean JWKS handling
- Removed manual JWKS fetching, caching and key extraction logic in
favor of PyJWT's built-in functionality
The new implementation is cleaner, more maintainable, and follows PyJWT
best practices while maintaining full backward compatibility.
## Test Plan
Unit tests. Auth CI.
---------
Signed-off-by: Sébastien Han <seb@redhat.com>
