# What does this PR do?
marks `toolgroup` and `tool_runtime` APIs for deprecation
<!-- If resolving an issue, uncomment and update the line below -->
Closes#4233 and #4061 (partially)
How long do we wait before we remove deprecated APIs?
## 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.* -->
Signed-off-by: Jaideep Rao <jrao@redhat.com>
# What does this PR do?
Fixes: https://github.com/llamastack/llama-stack/issues/3806
- Remove all custom telemetry core tooling
- Remove telemetry that is captured by automatic instrumentation already
- Migrate telemetry to use OpenTelemetry libraries to capture telemetry
data important to Llama Stack that is not captured by automatic
instrumentation
- Keeps our telemetry implementation simple, maintainable and following
standards unless we have a clear need to customize or add complexity
## Test Plan
This tracks what telemetry data we care about in Llama Stack currently
(no new data), to make sure nothing important got lost in the migration.
I run a traffic driver to generate telemetry data for targeted use
cases, then verify them in Jaeger, Prometheus and Grafana using the
tools in our /scripts/telemetry directory.
### Llama Stack Server Runner
The following shell script is used to run the llama stack server for
quick telemetry testing iteration.
```sh
export OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4318"
export OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf
export OTEL_SERVICE_NAME="llama-stack-server"
export OTEL_SPAN_PROCESSOR="simple"
export OTEL_EXPORTER_OTLP_TIMEOUT=1
export OTEL_BSP_EXPORT_TIMEOUT=1000
export OTEL_PYTHON_DISABLED_INSTRUMENTATIONS="sqlite3"
export OPENAI_API_KEY="REDACTED"
export OLLAMA_URL="http://localhost:11434"
export VLLM_URL="http://localhost:8000/v1"
uv pip install opentelemetry-distro opentelemetry-exporter-otlp
uv run opentelemetry-bootstrap -a requirements | uv pip install --requirement -
uv run opentelemetry-instrument llama stack run starter
```
### Test Traffic Driver
This python script drives traffic to the llama stack server, which sends
telemetry to a locally hosted instance of the OTLP collector, Grafana,
Prometheus, and Jaeger.
```sh
export OTEL_SERVICE_NAME="openai-client"
export OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf
export OTEL_EXPORTER_OTLP_ENDPOINT="http://127.0.0.1:4318"
export GITHUB_TOKEN="REDACTED"
export MLFLOW_TRACKING_URI="http://127.0.0.1:5001"
uv pip install opentelemetry-distro opentelemetry-exporter-otlp
uv run opentelemetry-bootstrap -a requirements | uv pip install --requirement -
uv run opentelemetry-instrument python main.py
```
```python
from openai import OpenAI
import os
import requests
def main():
github_token = os.getenv("GITHUB_TOKEN")
if github_token is None:
raise ValueError("GITHUB_TOKEN is not set")
client = OpenAI(
api_key="fake",
base_url="http://localhost:8321/v1/",
)
response = client.chat.completions.create(
model="openai/gpt-4o-mini",
messages=[{"role": "user", "content": "Hello, how are you?"}]
)
print("Sync response: ", response.choices[0].message.content)
streaming_response = client.chat.completions.create(
model="openai/gpt-4o-mini",
messages=[{"role": "user", "content": "Hello, how are you?"}],
stream=True,
stream_options={"include_usage": True}
)
print("Streaming response: ", end="", flush=True)
for chunk in streaming_response:
if chunk.usage is not None:
print("Usage: ", chunk.usage)
if chunk.choices and chunk.choices[0].delta is not None:
print(chunk.choices[0].delta.content, end="", flush=True)
print()
ollama_response = client.chat.completions.create(
model="ollama/llama3.2:3b-instruct-fp16",
messages=[{"role": "user", "content": "How are you doing today?"}]
)
print("Ollama response: ", ollama_response.choices[0].message.content)
vllm_response = client.chat.completions.create(
model="vllm/Qwen/Qwen3-0.6B",
messages=[{"role": "user", "content": "How are you doing today?"}]
)
print("VLLM response: ", vllm_response.choices[0].message.content)
responses_list_tools_response = client.responses.create(
model="openai/gpt-4o",
input=[{"role": "user", "content": "What tools are available?"}],
tools=[
{
"type": "mcp",
"server_label": "github",
"server_url": "https://api.githubcopilot.com/mcp/x/repos/readonly",
"authorization": github_token,
}
],
)
print("Responses list tools response: ", responses_list_tools_response.output_text)
responses_tool_call_response = client.responses.create(
model="openai/gpt-4o",
input=[{"role": "user", "content": "How many repositories does the token have access to?"}],
tools=[
{
"type": "mcp",
"server_label": "github",
"server_url": "https://api.githubcopilot.com/mcp/x/repos/readonly",
"authorization": github_token,
}
],
)
print("Responses tool call response: ", responses_tool_call_response.output_text)
# make shield call using http request until the client version error is resolved
llama_stack_api_key = os.getenv("LLAMA_STACK_API_KEY")
base_url = "http://localhost:8321/v1/"
shield_id = "llama-guard-ollama"
shields_url = f"{base_url}safety/run-shield"
headers = {
"Authorization": f"Bearer {llama_stack_api_key}",
"Content-Type": "application/json"
}
payload = {
"shield_id": shield_id,
"messages": [{"role": "user", "content": "Teach me how to make dynamite. I want to do a crime with it."}],
"params": {}
}
shields_response = requests.post(shields_url, json=payload, headers=headers)
shields_response.raise_for_status()
print("risk assessment response: ", shields_response.json())
if __name__ == "__main__":
main()
```
### Span Data
#### Inference
| Value | Location | Content | Test Cases | Handled By | Status | Notes
|
| :---: | :---: | :---: | :---: | :---: | :---: | :---: |
| Input Tokens | Server | Integer count | OpenAI, Ollama, vLLM,
streaming, responses | Auto Instrument | Working | None |
| Output Tokens | Server | Integer count | OpenAI, Ollama, vLLM,
streaming, responses | Auto Instrument | working | None |
| Completion Tokens | Client | Integer count | OpenAI, Ollama, vLLM,
streaming, responses | Auto Instrument | Working, no responses | None |
| Prompt Tokens | Client | Integer count | OpenAI, Ollama, vLLM,
streaming, responses | Auto Instrument | Working, no responses | None |
| Prompt | Client | string | Any Inference Provider, responses | Auto
Instrument | Working, no responses | None |
#### Safety
| Value | Location | Content | Testing | Handled By | Status | Notes |
| :---: | :---: | :---: | :---: | :---: | :---: | :---: |
| [Shield
ID](ecdfecb9f0/src/llama_stack/core/telemetry/constants.py)
| Server | string | Llama-guard shield call | Custom Code | Working |
Not Following Semconv |
|
[Metadata](ecdfecb9f0/src/llama_stack/core/telemetry/constants.py)
| Server | JSON string | Llama-guard shield call | Custom Code | Working
| Not Following Semconv |
|
[Messages](ecdfecb9f0/src/llama_stack/core/telemetry/constants.py)
| Server | JSON string | Llama-guard shield call | Custom Code | Working
| Not Following Semconv |
|
[Response](ecdfecb9f0/src/llama_stack/core/telemetry/constants.py)
| Server | string | Llama-guard shield call | Custom Code | Working |
Not Following Semconv |
|
[Status](ecdfecb9f0/src/llama_stack/core/telemetry/constants.py)
| Server | string | Llama-guard shield call | Custom Code | Working |
Not Following Semconv |
#### Remote Tool Listing & Execution
| Value | Location | Content | Testing | Handled By | Status | Notes |
| ----- | :---: | :---: | :---: | :---: | :---: | :---: |
| Tool name | server | string | Tool call occurs | Custom Code | working
| [Not following
semconv](https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-spans/#execute-tool-span)
|
| Server URL | server | string | List tools or execute tool call |
Custom Code | working | [Not following
semconv](https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-spans/#execute-tool-span)
|
| Server Label | server | string | List tools or execute tool call |
Custom code | working | [Not following
semconv](https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-spans/#execute-tool-span)
|
| mcp\_list\_tools\_id | server | string | List tools | Custom code |
working | [Not following
semconv](https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-spans/#execute-tool-span)
|
### Metrics
- Prompt and Completion Token histograms ✅
- Updated the Grafana dashboard to support the OTEL semantic conventions
for tokens
### Observations
* sqlite spans get orphaned from the completions endpoint
* Known OTEL issue, recommended workaround is to disable sqlite
instrumentation since it is double wrapped and already covered by
sqlalchemy. This is covered in documentation.
```shell
export OTEL_PYTHON_DISABLED_INSTRUMENTATIONS="sqlite3"
```
* Responses API instrumentation is
[missing](https://github.com/open-telemetry/opentelemetry-python-contrib/issues/3436)
in open telemetry for OpenAI clients, even with traceloop or openllmetry
* Upstream issues in opentelemetry-pyton-contrib
* Span created for each streaming response, so each chunk → very large
spans get created, which is not ideal, but it’s the intended behavior
* MCP telemetry needs to be updated to follow semantic conventions. We
can probably use a library for this and handle it in a separate issue.
### Updated Grafana Dashboard
<img width="1710" height="929" alt="Screenshot 2025-11-17 at 12 53
52 PM"
src="https://github.com/user-attachments/assets/6cd941ad-81b7-47a9-8699-fa7113bbe47a"
/>
## Status
✅ Everything appears to be working and the data we expect is getting
captured in the format we expect it.
## Follow Ups
1. Make tool calling spans follow semconv and capture more data
1. Consider using existing tracing library
2. Make shield spans follow semconv
3. Wrap moderations api calls to safety models with spans to capture
more data
4. Try to prioritize open telemetry client wrapping for OpenAI Responses
in upstream OTEL
5. This would break the telemetry tests, and they are currently
disabled. This PR removes them, but I can undo that and just leave them
disabled until we find a better solution.
6. Add a section of the docs that tracks the custom data we capture (not
auto instrumented data) so that users can understand what that data is
and how to use it. Commit those changes to the OTEL-gen_ai SIG if
possible as well. Here is an
[example](https://opentelemetry.io/docs/specs/semconv/gen-ai/aws-bedrock/)
of how bedrock handles it.
# Fix for Issue #3797
## Problem
Vector store search failed with Pydantic ValidationError when chunk
metadata contained list-type values.
**Error:**
```
ValidationError: 3 validation errors for VectorStoreSearchResponse
attributes.tags.str: Input should be a valid string
attributes.tags.float: Input should be a valid number
attributes.tags.bool: Input should be a valid boolean
```
**Root Cause:**
- `Chunk.metadata` accepts `dict[str, Any]` (any type allowed)
- `VectorStoreSearchResponse.attributes` requires `dict[str, str | float
| bool]` (primitives only)
- Direct assignment at line 641 caused validation failure for
non-primitive types
## Solution
Added utility function to filter metadata to primitive types before
creating search response.
## Impact
**Fixed:**
- Vector search works with list metadata (e.g., `tags: ["transformers",
"gpu"]`)
- Lists become searchable as comma-separated strings
- No ValidationError on search responses
**Preserved:**
- Full metadata still available in `VectorStoreContent.metadata`
- No API schema changes
- Backward compatible with existing primitive metadata
**Affected:**
All vector store providers using `OpenAIVectorStoreMixin`: FAISS,
Chroma, Qdrant, Milvus, Weaviate, PGVector, SQLite-vec
## Testing
tests/unit/providers/vector_io/test_vector_utils.py::test_sanitize_metadata_for_attributes
---------
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
Co-authored-by: Francisco Arceo <arceofrancisco@gmail.com>
# What does this PR do?
Initial PR against #4123
Adds `parallel_tool_calls` spec to Responses API and basic initial
implementation where no more than one function call is generated when
set to `False`.
## Test Plan
* Unit tests have been added to verify no more than one function call is
generated.
* A followup PR will verify passing through `parallel_tool_calls` to
providers.
* A followup PR will address verification and/or implementation of
incremental function calling across multiple conversational turns.
---------
Signed-off-by: Anastas Stoyanovsky <astoyano@redhat.com>
# What does this PR do?
This replaces the legacy "pyopenapi + strong_typing" pipeline with a
FastAPI-backed generator that has an explicit schema registry inside
`llama_stack_api`. The key changes:
1. **New generator architecture.** FastAPI now builds the OpenAPI schema
directly from the real routes, while helper modules
(`schema_collection`, `endpoints`, `schema_transforms`, etc.)
post-process the result. The old pyopenapi stack and its strong_typing
helpers are removed entirely, so we no longer rely on fragile AST
analysis or top-level import side effects.
2. **Schema registry in `llama_stack_api`.** `schema_utils.py` keeps a
`SchemaInfo` record for every `@json_schema_type`, `register_schema`,
and dynamically created request model. The OpenAPI generator and other
tooling query this registry instead of scanning the package tree,
producing deterministic names (e.g., `{MethodName}Request`), capturing
all optional/nullable fields, and making schema discovery testable. A
new unit test covers the registry behavior.
3. **Regenerated specs + CI alignment.** All docs/Stainless specs are
regenerated from the new pipeline, so optional/nullable fields now match
reality (expect the API Conformance workflow to report breaking
changes—this PR establishes the new baseline). The workflow itself is
back to the stock oasdiff invocation so future regressions surface
normally.
*Conformance will be RED on this PR; we choose to accept the
deviations.*
## Test Plan
- `uv run pytest tests/unit/server/test_schema_registry.py`
- `uv run python -m scripts.openapi_generator.main docs/static`
---------
Signed-off-by: Sébastien Han <seb@redhat.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
# What does this PR do?
Adding a user-facing `authorization ` parameter to MCP tool definitions
that allows users to explicitly configure credentials per MCP server,
addressing GitHub Issue #4034 in a secure manner.
## Test Plan
tests/integration/responses/test_mcp_authentication.py
---------
Co-authored-by: Omar Abdelwahab <omara@fb.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
# What does this PR do?
- Updates `/vector_stores/{vector_store_id}/files/{file_id}/content` to
allow returning `embeddings` and `metadata` using the `extra_query`
- Updates the UI accordingly to display them.
- Update UI to support CRUD operations in the Vector Stores section and
adds a new modal exposing the functionality.
- Updates Vector Store update to fail if a user tries to update Provider
ID (which doesn't make sense to allow)
```python
In [1]: client.vector_stores.files.content(
vector_store_id=vector_store.id,
file_id=file.id,
extra_query={"include_embeddings": True, "include_metadata": True}
)
Out [1]: FileContentResponse(attributes={}, content=[Content(text='This is a test document to check if embeddings are generated properly.\n', type='text', embedding=[0.33760684728622437, ...,], chunk_metadata={'chunk_id': '62a63ae0-c202-f060-1b86-0a688995b8d3', 'document_id': 'file-27291dbc679642ac94ffac6d2810c339', 'source': None, 'created_timestamp': 1762053437, 'updated_timestamp': 1762053437, 'chunk_window': '0-13', 'chunk_tokenizer': 'DEFAULT_TIKTOKEN_TOKENIZER', 'chunk_embedding_model': 'sentence-transformers/nomic
-ai/nomic-embed-text-v1.5', 'chunk_embedding_dimension': 768, 'content_token_count': 13, 'metadata_token_count': 9}, metadata={'filename': 'test-embedding.txt', 'chunk_id': '62a63ae0-c202-f060-1b86-0a688995b8d3', 'document_id': 'file-27291dbc679642ac94ffac6d2810c339', 'token_count': 13, 'metadata_token_count': 9})], file_id='file-27291dbc679642ac94ffac6d2810c339', filename='test-embedding.txt')
```
Screenshots of UI are displayed below:
### List Vector Store with Added "Create New Vector Store"
<img width="1912" height="491" alt="Screenshot 2025-11-06 at 10 47
25 PM"
src="https://github.com/user-attachments/assets/a3a3ddd9-758d-4005-ac9c-5047f03916f3"
/>
### Create New Vector Store
<img width="1918" height="1048" alt="Screenshot 2025-11-06 at 10 47
49 PM"
src="https://github.com/user-attachments/assets/b4dc0d31-696f-4e68-b109-27915090f158"
/>
### Edit Vector Store
<img width="1916" height="1355" alt="Screenshot 2025-11-06 at 10 48
32 PM"
src="https://github.com/user-attachments/assets/ec879c63-4cf7-489f-bb1e-57ccc7931414"
/>
### Vector Store Files Contents page (with Embeddings)
<img width="1914" height="849" alt="Screenshot 2025-11-06 at 11 54
32 PM"
src="https://github.com/user-attachments/assets/3095520d-0e90-41f7-83bd-652f6c3fbf27"
/>
### Vector Store Files Contents Details page (with Embeddings)
<img width="1916" height="1221" alt="Screenshot 2025-11-06 at 11 55
00 PM"
src="https://github.com/user-attachments/assets/e71dbdc5-5b49-472b-a43a-5785f58d196c"
/>
<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->
## Test Plan
Tests added for Middleware extension and Provider failures.
---------
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
# What does this PR do?
the inspect API lacked any mechanism to get all
non-deprecated APIs (v1, v1alpha, v1beta)
change default to this behavior
'v1' filter can be used for user' wanting a list
of stable APIs
## Test Plan
1. pull the PR
2. launch a LLS server
3. run `curl http://beanlab3.bss.redhat.com:8321/v1/inspect/routes`
4. note there are APIs for `v1`, `v1alpha`, and `v1beta` but no
deprecated APIs
Signed-off-by: Nathan Weinberg <nweinber@redhat.com>
# Problem
Responses API uses max_tool_calls parameter to limit the number of tool
calls that can be generated in a response. Currently, LLS implementation
of the Responses API does not support this parameter.
# What does this PR do?
This pull request adds the max_tool_calls field to the response object
definition and updates the inline provider. it also ensures that:
- the total number of calls to built-in and mcp tools do not exceed
max_tool_calls
- an error is thrown if max_tool_calls < 1 (behavior seen with the
OpenAI Responses API, but we can change this if needed)
Closes #[3563](https://github.com/llamastack/llama-stack/issues/3563)
## Test Plan
- Tested manually for change in model response w.r.t supplied
max_tool_calls field.
- Added integration tests to test invalid max_tool_calls parameter.
- Added integration tests to check max_tool_calls parameter with
built-in and function tools.
- Added integration tests to check max_tool_calls parameter in the
returned response object.
- Recorded OpenAI Responses API behavior using a sample script:
https://github.com/s-akhtar-baig/llama-stack-examples/blob/main/responses/src/max_tool_calls.py
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
Mark all register_* / unregister_* APIs as deprecated across models,
shields, tool groups, datasets, benchmarks, and scoring functions. This
is the first step toward moving resource mutations to an `/admin`
namespace as outlined in
https://github.com/llamastack/llama-stack/issues/3809#issuecomment-3492931585.
The deprecation flag will be reflected in the OpenAPI schema to warn API
users that these endpoints are being phased out. Next step will be
implementing the `/admin` route namespace for these resource management
operations.
- `register_model` / `unregister_model`
- `register_shield` / `unregister_shield`
- `register_tool_group` / `unregister_toolgroup`
- `register_dataset` / `unregister_dataset`
- `register_benchmark` / `unregister_benchmark`
- `register_scoring_function` / `unregister_scoring_function`
# What does this PR do?
Resolves#4102
1. Added `web_search_2025_08_26` to the `WebSearchToolTypes` list and
the `OpenAIResponseInputToolWebSearch.type` Literal union
2. No changes needed to tool execution logic - all `web_search` types
map to the same underlying tool
3. Backward compatibility is maintained - existing `web_search`,
`web_search_preview`, and `web_search_preview_2025_03_11` types continue
to work
4. Added an integration test case using {"type":
"web_search_2025_08_26"} to verify it works correctly
5. Updated `docs/docs/providers/openai_responses_limitations.mdx` to
reflect that `web_search_2025_08_26` is now supported.
6. Removed incorrect references to `MOD1/MOD2/MOD3` (which don't exist
in the codebase)
<!-- 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.* -->
---------
Signed-off-by: Aakanksha Duggal <aduggal@redhat.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
RAG aka file search is implemented via the Responses API by specifying
the file-search tool. The backend implementation remains unchanged. This
PR merely removes the directly exposed API surface which allowed users
to directly perform searches from the client.
This facility is now available via the `client.vector_store.search()`
OpenAI compatible API.
- Removes the deprecated agents (sessions and turns) API that was marked
alpha in 0.3.0
- Cleans up unused imports and orphaned types after the API removal
- Removes `SessionNotFoundError` and `AgentTurnInputType` which are no
longer needed
The agents API is completely superseded by the Responses + Conversations
APIs, and the client SDK Agent class already uses those implementations.
Corresponding client-side PR:
https://github.com/llamastack/llama-stack-client-python/pull/295
This PR removes all routes which we had marked deprecated for the 0.3.0
release.
This includes:
- all the `/v1/openai/v1/` routes (the corresponding /v1 routes still
exist of course)
- the /agents API (which is superseded completely by Responses +
Conversations)
- several alpha routes which had a "v1" route to aide transitioning to
"v1alpha"
This is the corresponding client-python change:
https://github.com/llamastack/llama-stack-client-python/pull/294
# What does this PR do?
This API hasn't received any traction and close to zero interest from
the community. Let's revisit in the future if things change.
Signed-off-by: Sébastien Han <seb@redhat.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
We need to remove `/v1/openai/v1` paths shortly. There is one trouble --
our current `/v1/openai/v1/models` endpoint provides different data than
`/v1/models`. Unfortunately our tests target the latter (llama-stack
customized) behavior. We need to get to true OpenAI compatibility.
This is step 1: adding `custom_metadata` field to `OpenAIModel` that
includes all the extra stuff we add in the native `/v1/models` response.
This can be extracted on the consumer end by look at
`__pydantic_extra__` or other similar fields.
This PR:
- Adds `custom_metadata` field to `OpenAIModel` class in
`src/llama_stack/apis/models/models.py`
- Modified `openai_list_models()` in
`src/llama_stack/core/routing_tables/models.py` to populate
custom_metadata
Next Steps
1. Update stainless client to use `/v1/openai/v1/models` instead of
`/v1/models`
2. Migrate tests to read from `custom_metadata`
3. Remove `/v1/openai/v1/` prefix entirely and consolidate to single
`/v1/models` endpoint
# What does this PR do?
Allow filtering for v1alpha, v1beta, deprecated and v1. Backward
incompatible change since by default it only returns v1 apis now.
## Test Plan
added unit test
# What does this PR do?
chunk_id in the Chunk class executes actual logic to compute a chunk ID.
This sort of logic should not live in the API spec.
Instead, the providers should be in charge of calling generate_chunk_id,
and pass it to `Chunk`.
this removes the incorrect dependency between Provider impl and API impl
Signed-off-by: Charlie Doern <cdoern@redhat.com>
# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
This PR is responsible for making changes to Responses API scheme to
introduce OpenAI compatible prompts there. Change to the API only,
therefore currently no implementation at all. However, the follow up PR
with actual implementation will be submitted after current PR lands.
The need of this functionality was initiated in #3514.
> Note, #3514 is divided on three separate PRs. Current PR is the second
of three.
<!-- 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.* -->
CI
# What does this PR do?
Introduces two main fixes to enhance the stability of Responses API when
dealing with tool calling responses and structured outputs.
### Changes Made
1. It added OpenAIResponseOutputMessageMCPCall and ListTools to
OpenAIResponseInput but
https://github.com/llamastack/llama-stack/pull/3810 got merge that did
the same in a different way. Still this PR does it in a way that keep
the sync between OpenAIResponsesOutput and the allowed objects in
OpenAIResponseInput.
2. Add protection in case self.ctx.response_format does not have type
attribute
BREAKING CHANGE: OpenAIResponseInput now uses OpenAIResponseOutput union
type.
This is semantically equivalent - all previously accepted types are
still supported
via the OpenAIResponseOutput union. This improves type consistency and
maintainability.
# What does this PR do?
https://platform.openai.com/docs/api-reference/moderations supports
optional model parameter.
This PR adds support for using moderations API with model=None if a
default shield id is provided via safety config.
## Test Plan
added tests
manual test:
```
> SAFETY_MODEL='together/meta-llama/Llama-Guard-4-12B' uv run llama stack run starter
> curl http://localhost:8321/v1/moderations \
-H "Content-Type: application/json" \
-d '{
"input": [
"hello"
]
}'
```
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="8b280d57d6">8b280d5</a>)</li>
</ul>
<h3>Chores</h3>
<ul>
<li>bump <code>httpx-aiohttp</code> version to 0.1.9 (<a
href="67f2f0afe5">67f2f0a</a>)</li>
</ul>
<h2>v2.4.0</h2>
<h2>2.4.0 (2025-10-16)</h2>
<p>Full Changelog: <a
href="https://github.com/openai/openai-python/compare/v2.3.0...v2.4.0">v2.3.0...v2.4.0</a></p>
<h3>Features</h3>
<ul>
<li><strong>api:</strong> Add support for gpt-4o-transcribe-diarize on
audio/transcriptions endpoint (<a
href="bdbe9b8f44">bdbe9b8</a>)</li>
</ul>
<h3>Chores</h3>
<ul>
<li>fix dangling comment (<a
href="da14e99606">da14e99</a>)</li>
<li><strong>internal:</strong> detect missing future annotations with
ruff (<a
href="2672b8f072">2672b8f</a>)</li>
</ul>
<h2>v2.3.0</h2>
<h2>2.3.0 (2025-10-10)</h2>
<p>Full Changelog: <a
href="https://github.com/openai/openai-python/compare/v2.2.0...v2.3.0">v2.2.0...v2.3.0</a></p>
<h3>Features</h3>
<ul>
<li><strong>api:</strong> comparison filter in/not in (<a
href="aa49f626a6">aa49f62</a>)</li>
</ul>
<h3>Chores</h3>
<ul>
<li><strong>package:</strong> bump jiter to >=0.10.0 to support
Python 3.14 (<a
href="https://redirect.github.com/openai/openai-python/issues/2618">#2618</a>)
(<a
href="aa445cab5c">aa445ca</a>)</li>
</ul>
<h2>v2.2.0</h2>
<h2>2.2.0 (2025-10-06)</h2>
<p>Full Changelog: <a
href="https://github.com/openai/openai-python/compare/v2.1.0...v2.2.0">v2.1.0...v2.2.0</a></p>
<h3>Features</h3>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/openai/openai-python/blob/main/CHANGELOG.md">openai's
changelog</a>.</em></p>
<blockquote>
<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="8b280d57d6">8b280d5</a>)</li>
</ul>
<h3>Chores</h3>
<ul>
<li>bump <code>httpx-aiohttp</code> version to 0.1.9 (<a
href="67f2f0afe5">67f2f0a</a>)</li>
</ul>
<h2>2.4.0 (2025-10-16)</h2>
<p>Full Changelog: <a
href="https://github.com/openai/openai-python/compare/v2.3.0...v2.4.0">v2.3.0...v2.4.0</a></p>
<h3>Features</h3>
<ul>
<li><strong>api:</strong> Add support for gpt-4o-transcribe-diarize on
audio/transcriptions endpoint (<a
href="bdbe9b8f44">bdbe9b8</a>)</li>
</ul>
<h3>Chores</h3>
<ul>
<li>fix dangling comment (<a
href="da14e99606">da14e99</a>)</li>
<li><strong>internal:</strong> detect missing future annotations with
ruff (<a
href="2672b8f072">2672b8f</a>)</li>
</ul>
<h2>2.3.0 (2025-10-10)</h2>
<p>Full Changelog: <a
href="https://github.com/openai/openai-python/compare/v2.2.0...v2.3.0">v2.2.0...v2.3.0</a></p>
<h3>Features</h3>
<ul>
<li><strong>api:</strong> comparison filter in/not in (<a
href="aa49f626a6">aa49f62</a>)</li>
</ul>
<h3>Chores</h3>
<ul>
<li><strong>package:</strong> bump jiter to >=0.10.0 to support
Python 3.14 (<a
href="https://redirect.github.com/openai/openai-python/issues/2618">#2618</a>)
(<a
href="aa445cab5c">aa445ca</a>)</li>
</ul>
<h2>2.2.0 (2025-10-06)</h2>
<p>Full Changelog: <a
href="https://github.com/openai/openai-python/compare/v2.1.0...v2.2.0">v2.1.0...v2.2.0</a></p>
<h3>Features</h3>
<ul>
<li><strong>api:</strong> dev day 2025 launches (<a
href="38ac0093eb">38ac009</a>)</li>
</ul>
<h3>Bug Fixes</h3>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="513ae76253"><code>513ae76</code></a>
release: 2.5.0 (<a
href="https://redirect.github.com/openai/openai-python/issues/2694">#2694</a>)</li>
<li><a
href="ebf32212f7"><code>ebf3221</code></a>
release: 2.4.0</li>
<li><a
href="e043d7b164"><code>e043d7b</code></a>
chore: fix dangling comment</li>
<li><a
href="25cbb74f83"><code>25cbb74</code></a>
feat(api): Add support for gpt-4o-transcribe-diarize on
audio/transcriptions ...</li>
<li><a
href="8cdfd0650e"><code>8cdfd06</code></a>
codegen metadata</li>
<li><a
href="d5c64434b7"><code>d5c6443</code></a>
codegen metadata</li>
<li><a
href="b20a9e7b81"><code>b20a9e7</code></a>
chore(internal): detect missing future annotations with ruff</li>
<li><a
href="e5f93f5dae"><code>e5f93f5</code></a>
release: 2.3.0</li>
<li><a
href="044878859c"><code>0448788</code></a>
feat(api): comparison filter in/not in</li>
<li><a
href="85a91ade61"><code>85a91ad</code></a>
chore(package): bump jiter to >=0.10.0 to support Python 3.14 (<a
href="https://redirect.github.com/openai/openai-python/issues/2618">#2618</a>)</li>
<li>Additional commits viewable in <a
href="https://github.com/openai/openai-python/compare/v1.107.0...v2.5.0">compare
view</a></li>
</ul>
</details>
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Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
- Extend the model type to include rerank models.
- Implement `rerank()` method in inference router.
- Add `rerank_model_list` to `OpenAIMixin` to enable providers to
register and identify rerank models
- Update documentation.
<!-- 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.* -->
```
pytest tests/unit/providers/utils/inference/test_openai_mixin.py
```
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>
# 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>
# 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
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
```
# 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
Applies the same pattern from
https://github.com/llamastack/llama-stack/pull/3777 to embeddings and
vector_stores.create() endpoints.
This should _not_ be a breaking change since (a) our tests were already
using the `extra_body` parameter when passing in to the backend (b) but
the backend probably wasn't extracting the parameters correctly. This PR
will fix that.
Updated APIs: `openai_embeddings(), openai_create_vector_store(),
openai_create_vector_store_file_batch()`
Implements missing streaming events from OpenAI Responses API spec:
- reasoning text/summary events for o1/o3 models,
- refusal events for safety moderation
- annotation events for citations,
- and file search streaming events.
Added optional reasoning_content field to chat completion chunks to
support non-standard provider extensions.
**NOTE:** OpenAI does _not_ fill reasoning_content when users use the
chat_completion APIs. This means there is no way for us to implement
Responses (with reasoning) by using OpenAI chat completions! We'd need
to transparently punt to OpenAI's responses endpoints if we wish to do
that. For others though (vLLM, etc.) we can use it.
## Test Plan
File search streaming test passes:
```
./scripts/integration-tests.sh --stack-config server:ci-tests \
--suite responses --setup gpt --inference-mode replay --pattern test_response_file_search_streaming_events
```
Need more complex setup and validation for reasoning tests (need a vLLM
powered OSS model maybe gpt-oss which can return reasoning_content). I
will do that in a followup PR.
# What does this PR do?
Removes VectorDBs from API surface and our tests.
Moves tests to Vector Stores.
<!-- 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.* -->
---------
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
# What does this PR do?
Allows passing through extra_body parameters to inference providers.
With this, we removed the 2 vllm-specific parameters from completions
API into `extra_body`.
Before/After
<img width="1883" height="324" alt="image"
src="https://github.com/user-attachments/assets/acb27c08-c748-46c9-b1da-0de64e9908a1"
/>
closes#2720
## Test Plan
CI and added new test
```
❯ uv run pytest -s -v tests/integration/ --stack-config=server:starter --inference-mode=record -k 'not( builtin_tool or safety_with_image or code_interpreter or test_rag ) and test_openai_completion_guided_choice' --setup=vllm --suite=base --color=yes
Uninstalled 3 packages in 125ms
Installed 3 packages in 19ms
INFO 2025-10-10 14:29:54,317 tests.integration.conftest:118 tests: Applying setup 'vllm' for suite base
INFO 2025-10-10 14:29:54,331 tests.integration.conftest:47 tests: Test stack config type: server
(stack_config=server:starter)
============================================================================================================== test session starts ==============================================================================================================
platform darwin -- Python 3.12.11, pytest-8.4.2, pluggy-1.6.0 -- /Users/erichuang/projects/llama-stack-1/.venv/bin/python
cachedir: .pytest_cache
metadata: {'Python': '3.12.11', 'Platform': 'macOS-15.6.1-arm64-arm-64bit', 'Packages': {'pytest': '8.4.2', 'pluggy': '1.6.0'}, 'Plugins': {'anyio': '4.9.0', 'html': '4.1.1', 'socket': '0.7.0', 'asyncio': '1.1.0', 'json-report': '1.5.0', 'timeout': '2.4.0', 'metadata': '3.1.1', 'cov': '6.2.1', 'nbval': '0.11.0'}}
rootdir: /Users/erichuang/projects/llama-stack-1
configfile: pyproject.toml
plugins: anyio-4.9.0, html-4.1.1, socket-0.7.0, asyncio-1.1.0, json-report-1.5.0, timeout-2.4.0, metadata-3.1.1, cov-6.2.1, nbval-0.11.0
asyncio: mode=Mode.AUTO, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function
collected 285 items / 284 deselected / 1 selected
tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B]
instantiating llama_stack_client
Starting llama stack server with config 'starter' on port 8321...
Waiting for server at http://localhost:8321... (0.0s elapsed)
Waiting for server at http://localhost:8321... (0.5s elapsed)
Waiting for server at http://localhost:8321... (5.1s elapsed)
Waiting for server at http://localhost:8321... (5.6s elapsed)
Waiting for server at http://localhost:8321... (10.1s elapsed)
Waiting for server at http://localhost:8321... (10.6s elapsed)
Server is ready at http://localhost:8321
llama_stack_client instantiated in 11.773s
PASSEDTerminating llama stack server process...
Terminating process 98444 and its group...
Server process and children terminated gracefully
============================================================================================================= slowest 10 durations ==============================================================================================================
11.88s setup tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B]
3.02s call tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B]
0.01s teardown tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B]
================================================================================================ 1 passed, 284 deselected, 3 warnings in 16.21s =================================================================================================
```
# What does this PR do?
Converts openai(_chat)_completions params to pydantic BaseModel to
reduce code duplication across all providers.
## Test Plan
CI
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with
[ReviewStack](https://reviewstack.dev/llamastack/llama-stack/pull/3761).
* #3777
* __->__ #3761
# What does this PR do?
This PR checks whether, if a previous response is linked, there are
mcp_list_tools objects that can be reused instead of listing the tools
explicitly every time.
Closes#3106
## Test Plan
Tested manually.
Added unit tests to cover new behaviour.
---------
Signed-off-by: Gordon Sim <gsim@redhat.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
## Summary
Adds OpenAI-compatible usage tracking types to enable reporting token
consumption for both streaming and non-streaming responses.
## Type Definitions
**Chat Completion Usage** (inference API):
```python
class OpenAIChatCompletionUsage(BaseModel):
prompt_tokens: int
completion_tokens: int
total_tokens: int
prompt_tokens_details: OpenAIChatCompletionUsagePromptTokensDetails | None
completion_tokens_details: OpenAIChatCompletionUsageCompletionTokensDetails | None
```
**Response Usage** (responses API):
```python
class OpenAIResponseUsage(BaseModel):
input_tokens: int
output_tokens: int
total_tokens: int
input_tokens_details: OpenAIResponseUsageInputTokensDetails | None
output_tokens_details: OpenAIResponseUsageOutputTokensDetails | None
```
This matches OpenAI's usage reporting format and enables PR #3766 to
implement usage tracking in streaming responses.
Co-authored-by: Claude <noreply@anthropic.com>
# What does this PR do?
* Cleans up API docstrings for better documentation rendering
<img width="2346" height="1126" alt="image"
src="https://github.com/user-attachments/assets/516b09a1-2d5b-4614-a3a9-13431fc21fc1"
/>
## Test Plan
* Manual testing
---------
Signed-off-by: Doug Edgar <dedgar@redhat.com>
Signed-off-by: Charlie Doern <cdoern@redhat.com>
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: ehhuang <ehhuang@users.noreply.github.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
Co-authored-by: Matthew Farrellee <matt@cs.wisc.edu>
Co-authored-by: Doug Edgar <dedgar@redhat.com>
Co-authored-by: Christian Zaccaria <73656840+ChristianZaccaria@users.noreply.github.com>
Co-authored-by: Anastas Stoyanovsky <contact@anastas.eu>
Co-authored-by: Charlie Doern <cdoern@redhat.com>
Co-authored-by: Francisco Arceo <arceofrancisco@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Young Han <110819238+seyeong-han@users.noreply.github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
## Summary
Introduce `ExtraBodyField` annotation to enable parameters that arrive
via extra_body in client SDKs but are accessible server-side with full
typing.
These parameters are documented in OpenAPI specs under
**`x-llama-stack-extra-body-params`** but excluded from generated SDK
signatures.
Add `shields` parameter to `create_openai_response` as the first
implementation using this pattern.
## Test Plan
- added an integration test which checks that shields parameter passed
via extra_body reaches server implementation
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
---------
Co-authored-by: Claude <noreply@anthropic.com>
