# What does this PR do?
This PR adds support for the require_approval on an mcp tool definition
passed to create response in the Responses API. This allows the caller
to indicate whether they want to approve calls to that server, or let
them be called without approval.
Closes#3443
## Test Plan
Tested both approval and denial.
Added automated integration test for both cases.
---------
Signed-off-by: Gordon Sim <gsim@redhat.com>
Co-authored-by: Matthew Farrellee <matt@cs.wisc.edu>
# What does this PR do?
* Updates the safety guide in Zero to Hero series to use Moderations API
and the latest safety models
* Fixes an image link
Closes#2557
## Test Plan
* Manual testing
# What does this PR do?
* Adds canonical project information and links to client SDK / k8s
operator / app examples repos to the front page
* Fixes some button rendering errors
Closes#3618
## Test Plan
Local rebuild of the documentation server
https://github.com/llamastack/llama-stack/pull/3604 broke multipart form
data field parsing for the Files API since it changed its shape -- so as
to match the API exactly to the OpenAI spec even in the generated client
code.
The underlying reason is that multipart/form-data cannot transport
structured nested fields. Each field must be str-serialized. The client
(specifically the OpenAI client whose behavior we must match),
transports sub-fields as `expires_after[anchor]` and
`expires_after[seconds]`, etc. We must be able to handle these fields
somehow on the server without compromising the shape of the YAML spec.
This PR "fixes" this by adding a dependency to convert the data. The
main trade-off here is that we must add this `Depends()` annotation on
every provider implementation for Files. This is a headache, but a much
more reasonable one (in my opinion) given the alternatives.
## Test Plan
Tests as shown in
https://github.com/llamastack/llama-stack/pull/3604#issuecomment-3351090653
pass.
# What does this PR do?
agents is likely to be deprecated in favor of responses. Lets level it
as alpha to indicate the lack of longterm support
keep v1 route for backwards compat.
Closes#3611
Signed-off-by: Charlie Doern <cdoern@redhat.com>
# What does this PR do?
migrate safety api implementation from /inference/chat-completion to
/v1/chat/completions
## Test Plan
ci w/ recordings
---------
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
# What does this PR do?
Add llamastack + CrewAI integration example notebook
<!-- 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.* -->
Tested in local jupyternotebook and it works.
# What does this PR do?
Fixes error:
```
[ERROR] Error executing endpoint route='/v1/openai/v1/responses'
method='post': Error code: 400 - {'error': {'message': "Invalid schema for function 'pods_exec': In context=('properties', 'command'), array
schema missing items.", 'type': 'invalid_request_error', 'param': 'tools[7].function.parameters', 'code': 'invalid_function_parameters'}}
```
From script:
```
#!/usr/bin/env python3
"""
Script to test Responses API with kubernetes-mcp-server.
This script:
1. Connects to the llama stack server
2. Uses the Responses API with MCP tools
3. Asks for the list of Kubernetes namespaces using the kubernetes-mcp-server
"""
import json
from openai import OpenAI
# Connect to the llama stack server
base_url = "http://localhost:8321/v1/openai/v1"
client = OpenAI(base_url=base_url, api_key="fake")
# Define the MCP tool pointing to the kubernetes-mcp-server
# The kubernetes-mcp-server is running on port 3000 with SSE endpoint at /sse
mcp_server_url = "http://localhost:3000/sse"
tools = [
{
"type": "mcp",
"server_label": "k8s",
"server_url": mcp_server_url,
}
]
# Create a response request asking for k8s namespaces
print("Sending request to list Kubernetes namespaces...")
print(f"Using MCP server at: {mcp_server_url}")
print("Available tools will be listed automatically by the MCP server.")
print()
response = client.responses.create(
# model="meta-llama/Llama-3.2-3B-Instruct", # Using the vllm model
model="openai/gpt-4o",
input="what are all the Kubernetes namespaces? Use tool call to `namespaces_list`. make sure to adhere to the tool calling format.",
tools=tools,
stream=False,
)
print("\n" + "=" * 80)
print("RESPONSE OUTPUT:")
print("=" * 80)
# Print the output
for i, output in enumerate(response.output):
print(f"\n[Output {i + 1}] Type: {output.type}")
if output.type == "mcp_list_tools":
print(f" Server: {output.server_label}")
print(f" Tools available: {[t.name for t in output.tools]}")
elif output.type == "mcp_call":
print(f" Tool called: {output.name}")
print(f" Arguments: {output.arguments}")
print(f" Result: {output.output}")
if output.error:
print(f" Error: {output.error}")
elif output.type == "message":
print(f" Role: {output.role}")
print(f" Content: {output.content}")
print("\n" + "=" * 80)
print("FINAL RESPONSE TEXT:")
print("=" * 80)
print(response.output_text)
```
## Test Plan
new unit tests
script now runs successfully
The `/v1/openai/v1` prefix is annoying and now unnecessary given our
clearer focus on how to think about the API surface.
Let's kill it for the 0.3.0 update.
To make client-side changes feasible, we will do this in two parts. This
part adds a new route (sans `/openai/v1`) so the existing client
continues to work since the server supports both.
The next PR will be client-side (Stainless) changes which I will be
making shortly.
The final PR will remove the `/openai/v1` routes.
Note that all these changes will happen rapidly within this release
cycle. The entire set _will be backwards incompatible_.
# What does this PR do?
Refs: https://github.com/llamastack/llama-stack/issues/3420
When telemetry is enabled the router uncondionally expects the usage
attribute to be availble and fails if it is not present.
Usage is not currently being requested by litellm_openai_mixin.py for
streaming requests when using the responses API which means that
providers like vertexai fail if telemetry is enabled and streaming is
used.
This is part of the required fix. Other part is in liteLLM, will plan to
submit PR for that soon.
## Test Plan
I applied this change along with the change for litellm in a llama stack
deployment and validated that I could make streaming requests through
the responses API to a gemini model and they would succeed instead of
failing due to the missing usage attribute when telemetry is enabled.
Signed-off-by: Michael Dawson <midawson@redhat.com>
# What does this PR do?
now that /v1/inference/completion has been removed, no docs should refer
to it
this cleans up remaining references
## Test Plan
ci
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
# What does this PR do?
* Updates image paths for images in docs/resources/ to proper static
image locations
## Test Plan
* `npm run build` builds documentation properly
# What does this PR do?
move the eval=inline::meta-reference implementation to use
openai_completion/openai_chat_completion
note: this breaks backward compatibility if eval setup used sampling
params' repetition_penalty or strategy
## Test Plan
ci w/ new recordings
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
# What does this PR do?
we skip embedding tests when the embedding_model_id isn't provided. same
for completion / chat tests when text_model_id isn't given.
instead of failing safety tests when a shield_id isn't provided, we'll
skip them too.
## Test Plan
ci
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
# What does this PR do?
inference/rerank is the one route in the API intended to not be
deprecated. Level it as v1alpha.
Additionally, remove `experimental` and opt to instead use `v1alpha`
which itself implies an experimental state based on the original
proposal
Signed-off-by: Charlie Doern <cdoern@redhat.com>
