# What does this PR do?
Updated quickstart `demo_script.py` to use OpenAI APIs, which is simply:
```python
import io, requests
from openai import OpenAI
url="https://www.paulgraham.com/greatwork.html"
client = OpenAI(base_url="http://localhost:8321/v1/", api_key="none")
vs = client.vector_stores.create()
response = requests.get(url)
pseudo_file = io.BytesIO(str(response.content).encode('utf-8'))
uploaded_file = client.files.create(file=(url, pseudo_file, "text/html"), purpose="assistants")
client.vector_stores.files.create(vector_store_id=vs.id, file_id=uploaded_file.id)
resp = client.responses.create(
model="openai/gpt-4o",
input="How do you do great work? Use the existing knowledge_search tool.",
tools=[{"type": "file_search", "vector_store_ids": [vs.id]}],
include=["file_search_call.results"],
)
print(resp)
```
<!-- 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>
# 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>
## Summary
- Link pre-commit bot comment to workflow run instead of PR for better
debugging
- Dump docker container logs before removal to ensure logs are actually
captured
## Changes
1. **Pre-commit bot**: Changed the initial bot comment to link
"pre-commit hooks" text to the actual workflow run URL instead of just
having the PR number auto-link
2. **Docker logs**: Moved docker container log dumping from GitHub
Actions to the integration-tests.sh script's stop_container() function,
ensuring logs are captured before container removal
## Test plan
- Pre-commit bot comment will now have a clickable link to the workflow
run
- Docker container logs will be successfully captured in CI runs
# What does this PR do?
similarly to `alpha:` move `v1beta` routes under a `beta` group so the
client will have `client.beta`
From what I can tell, the openapi.stainless.yml file is hand written
while the openapi.yml file is generated and copied using the shell
script so I did this by hand.
Signed-off-by: Charlie Doern <cdoern@redhat.com>
Bumps
[@types/node](https://github.com/DefinitelyTyped/DefinitelyTyped/tree/HEAD/types/node)
from 24.3.0 to 24.8.1.
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Bumps [fastapi](https://github.com/fastapi/fastapi) from 0.116.1 to
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<blockquote>
<h2>0.119.0</h2>
<p>FastAPI now (temporarily) supports both Pydantic v2 models and
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from pydantic import BaseModel as BaseModelV2
from pydantic.v1 import BaseModel
<p>class Item(BaseModel):<br />
name: str<br />
description: str | None = None</p>
<p>class ItemV2(BaseModelV2):<br />
title: str<br />
summary: str | None = None</p>
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<p><a
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</code></pre></p>
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<ul>
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<li>🐛 Fix tagged discriminated union not recognized as body field. PR <a
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