# What does this PR do?
COPY with chmod does not work, see
https://github.com/containers/buildah/issues/4614. Also Docker arguably
implements it.
Anyway, this command is not even needed since later don't we do:
```
RUN mkdir -p /.llama /.cache && chmod -R g+rw /app /.llama /.cache
```
And providers.d will get the right modes.
<!-- 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] -->
## Test Plan
Build with CONTAINER_BINARY=podman and success
Signed-off-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
The current authorized sql store implementation does not respect
user.principal (only checks attributes). This PR addresses that.
## Test Plan
Added test cases to integration tests.
While investigating the `uv.lock` changes made in
https://github.com/meta-llama/llama-stack/pull/2695 I noticed several of
the pre-commit hook versions were out of date
This PR updates them and fixes some new `ruff` errors
---------
Signed-off-by: Nathan Weinberg <nweinber@redhat.com>
# What does this PR do?
currently when logging the run yaml, if there are path objects in the
object they are represented as:
```
external_providers_dir: !!python/object/apply:pathlib.PosixPath
- '~'
- .llama
- providers.d
```
now, with a config.model_dump(mode="json"), it works properly
```
external_providers_dir: ~/.llama/providers.d
```
Signed-off-by: Charlie Doern <cdoern@redhat.com>
# What does this PR do?
We are now testing the safety capability with the starter image. This
includes a few changes:
* Enable the safety integration test
* Relax the shield model requirements from llama-guard to make it work
with llama-guard3:8b coming from Ollama
* Expose a shield for each inference provider in the starter distro. The
shield will only be registered if the provider is enabled.
Closes: https://github.com/meta-llama/llama-stack/issues/2528
Signed-off-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
currently when a template is used, we still use `--config`.
`server.py` has a dedicated `--template` flag and logic, use that
instead
Signed-off-by: Charlie Doern <cdoern@redhat.com>
# What does this PR do?
* Removes a bunch of distros
* Removed distros were added into the "starter" distribution
* Doc for "starter" has been added
* Partially reverts https://github.com/meta-llama/llama-stack/pull/2482
since inference providers are disabled by default and can be turned on
manually via env variable.
* Disables safety in starter distro
Closes: https://github.com/meta-llama/llama-stack/issues/2502.
~Needs: https://github.com/meta-llama/llama-stack/pull/2482 for Ollama
to work properly in the CI.~
TODO:
- [ ] We can only update `install.sh` when we get a new release.
- [x] Update providers documentation
- [ ] Update notebooks to reference starter instead of ollama
Signed-off-by: Sébastien Han <seb@redhat.com>
Resolves access control error visibility issues where 500 errors were
returned instead of proper 403 responses with actionable error messages.
• Enhance AccessDeniedError with detailed context and improve exception
handling
• Enhanced AccessDeniedError class to include user, action, and resource
context
- Added constructor parameters for action, resource, and user
- Generate detailed error messages showing user principal, attributes,
and attempted resource
- Backward compatible with existing usage (falls back to generic
message)
• Updated exception handling in server.py
- Import AccessDeniedError from access_control module
- Return proper 403 status codes with detailed error messages
- Separate handling for PermissionError (generic) vs AccessDeniedError
(detailed)
• Enhanced error context at raise sites
- Updated routing_tables/common.py to pass action, resource, and user
context
- Updated agents persistence to include context in access denied errors
- Provides better debugging information for access control issues
• Added comprehensive unit tests
- Created tests/unit/server/test_server.py with 13 test cases
- Covers AccessDeniedError with and without context
- Tests all exception types (ValidationError, BadRequestError,
AuthenticationRequiredError, etc.)
- Validates proper HTTP status codes and error message formats
# 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] -->
## Test Plan
```
server:
port: 8321
access_policy:
- permit:
principal: admin
actions: [create, read, delete]
when: user with admin in groups
- permit:
actions: [read]
when: user with system:authenticated in roles
```
then:
```
curl --request POST --url http://localhost:8321/v1/vector-dbs \
--header "Authorization: Bearer your-bearer" \
--data '{
"vector_db_id": "my_demo_vector_db",
"embedding_model": "ibm-granite/granite-embedding-125m-english",
"embedding_dimension": 768,
"provider_id": "milvus"
}'
```
depending if user is in group admin or not, you should get the
`AccessDeniedError`. Before this PR, this was leading to an error 500
and `Traceback` displayed in the logs.
After the PR, logs display a simpler error (unless DEBUG logging is set)
and a 403 Forbidden error is returned on the HTTP side.
---------
Signed-off-by: Akram Ben Aissi <<akram.benaissi@gmail.com>>
# What does this PR do?
https://github.com/meta-llama/llama-stack/pull/2490 broke postgres_demo,
as the config expected a str but the value was converted to int.
This PR:
1. Updates the type of port in sqlstore to be int
2. template generation uses `dict` instead of `StackRunConfig` so as to
avoid failing pydantic typechecks.
3. Adds `replace_env_vars` to StackRunConfig instantiation in
`configure.py` (not sure why this wasn't needed before).
## Test Plan
`llama stack build --template postgres_demo --image-type conda --run`
# What does this PR do?
We were not using conditionals correctly, conditionals can only be used
when the env variable is set, so `${env.ENVIRONMENT:+}` would return
None is ENVIRONMENT is not set.
If you want to create a conditional value, you need to do
`${env.ENVIRONMENT:=}`, this will pick the value of ENVIRONMENT if set,
otherwise will return None.
Closes: https://github.com/meta-llama/llama-stack/issues/2564
Signed-off-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
Fixes an error when inferring dataset provider_id with metadata
Closes #[2506](https://github.com/meta-llama/llama-stack/issues/2506)
Signed-off-by: Juanma Barea <juanmabareamartinez@gmail.com>
# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
- conditionally created folder /.llama/providers.d if
external_providers_dir is set
- do not create /.cache folder, not in use anywhere
- combine chmod and copy to one command
<!-- 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.* -->
updated test:
```
export CONTAINER_BINARY=podman
LLAMA_STACK_DIR=. uv run llama stack build --template remote-vllm --image-type container --image-name <name>
```
log:
```
Containerfile created successfully in /tmp/tmp.rPMunE39Aw/Containerfile
FROM python:3.11-slim
WORKDIR /app
RUN apt-get update && apt-get install -y iputils-ping net-tools iproute2 dnsutils telnet curl wget telnet git procps psmisc lsof traceroute bubblewrap gcc && rm -rf /var/lib/apt/lists/*
ENV UV_SYSTEM_PYTHON=1
RUN pip install uv
RUN uv pip install --no-cache sentencepiece pillow pypdf transformers pythainlp faiss-cpu opentelemetry-sdk requests datasets chardet scipy nltk numpy matplotlib psycopg2-binary aiosqlite langdetect autoevals tree_sitter tqdm pandas chromadb-client opentelemetry-exporter-otlp-proto-http redis scikit-learn openai pymongo emoji sqlalchemy[asyncio] mcp aiosqlite fastapi fire httpx uvicorn opentelemetry-sdk opentelemetry-exporter-otlp-proto-http
RUN uv pip install --no-cache sentence-transformers --no-deps
RUN uv pip install --no-cache torch torchvision --index-url https://download.pytorch.org/whl/cpu
# Allows running as non-root user
RUN mkdir -p /.llama/providers.d /.cache
RUN uv pip install --no-cache llama-stack
RUN pip uninstall -y uv
ENTRYPOINT ["python", "-m", "llama_stack.distribution.server.server", "--template", "remote-vllm"]
RUN chmod -R g+rw /app /.llama /.cache
PWD: /tmp/llama-stack
Containerfile: /tmp/tmp.rPMunE39Aw/Containerfile
+ podman build --progress=plain --security-opt label=disable --platform linux/amd64 -t distribution-remote-vllm:0.2.12 -f /tmp/tmp.rPMunE39Aw/Containerfile /tmp/llama-stack
....
Success!
Build Successful!
You can find the newly-built template here: /tmp/llama-stack/llama_stack/templates/remote-vllm/run.yaml
You can run the new Llama Stack distro via: llama stack run /tmp/llama-stack/llama_stack/templates/remote-vllm/run.yaml --image-type container
```
```
podman tag localhost/distribution-remote-vllm:dev quay.io/wenzhou/distribution-remote-vllm:2492_2
podman push quay.io/wenzhou/distribution-remote-vllm:2492_2
docker run --rm -p 8321:8321 -e INFERENCE_MODEL="meta-llama/Llama-2-7b-chat-hf" -e VLLM_URL="http://localhost:8000/v1" quay.io/wenzhou/distribution-remote-vllm:2492_2 --port 8321
INFO 2025-06-26 13:47:31,813 __main__:436 server: Using template remote-vllm config file:
/app/llama-stack-source/llama_stack/templates/remote-vllm/run.yaml
INFO 2025-06-26 13:47:31,818 __main__:438 server: Run configuration:
INFO 2025-06-26 13:47:31,826 __main__:440 server: apis:
- agents
- datasetio
- eval
- inference
- safety
- scoring
- telemetry
- tool_runtime
- vector_io
benchmarks: []
container_image: null
....
```
-----
previous test:
local run` >llama stack build --template remote-vllm --image-type
container`
image stored in `quay.io/wenzhou/distribution-remote-vllm:2492`
---------
Signed-off-by: Wen Zhou <wenzhou@redhat.com>
# What does this PR do?
Some templates were still using the old environment variable substition
syntax instead of the new one and were not getting substituted properly.
Also, some places didn't handle the new None vs old empty string ("")
values that come from the conditional environment variable substitution.
This gets the starter and remote-vllm distributions starting again, and
I tested various permutations of the starter as chroma and pgvector
needed some adjustments to their config classes to handle the new
possible `None` values. And, I had to tweak our `Provider` class to also
handle `None` values, for cases where we disable providers in the
starter config via environment variables.
This may not have caught everything that was missed, but I did grep
around quite a bit to try and find anything lingering.
## Test Plan
The following permutations now all run (or attempt to run to the point
of complaining that they can't connect to chroma, vllm, etc) when before
they failed immediately on startup because of bad environment variable
substitions:
```
uv run llama stack run llama_stack/templates/starter/run.yaml
ENABLE_SQLITE_VEC=true uv run llama stack run llama_stack/templates/starter/run.yaml
ENABLE_PGVECTOR=true uv run llama stack run llama_stack/templates/starter/run.yaml
ENABLE_CHROMADB=true uv run llama stack run llama_stack/templates/starter/run.yaml
uv run llama stack run llama_stack/templates/remote-vllm/run.yaml
```
<!-- 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: Ben Browning <bbrownin@redhat.com>
Co-authored-by: raghotham <rsm@meta.com>
# What does this PR do?
This commit significantly improves the environment variable substitution
functionality in Llama Stack configuration files:
* The version field in configuration files has been changed from string
to integer type for better type consistency across build and run
configurations.
* The environment variable substitution system for ${env.FOO:} was fixed
and properly returns an error
* The environment variable substitution system for ${env.FOO+} returns
None instead of an empty strings, it better matches type annotations in
config fields
* The system includes automatic type conversion for boolean, integer,
and float values.
* The error messages have been enhanced to provide clearer guidance when
environment variables are missing, including suggestions for using
default values or conditional syntax.
* Comprehensive documentation has been added to the configuration guide
explaining all supported syntax patterns, best practices, and runtime
override capabilities.
* Multiple provider configurations have been updated to use the new
conditional syntax for optional API keys, making the system more
flexible for different deployment scenarios. The telemetry configuration
has been improved to properly handle optional endpoints with appropriate
validation, ensuring that required endpoints are specified when their
corresponding sinks are enabled.
* There were many instances of ${env.NVIDIA_API_KEY:} that should have
caused the code to fail. However, due to a bug, the distro server was
still being started, and early validation wasn’t triggered. As a result,
failures were likely being handled downstream by the providers. I’ve
maintained similar behavior by using ${env.NVIDIA_API_KEY:+}, though I
believe this is incorrect for many configurations. I’ll leave it to each
provider to correct it as needed.
* Environment variable substitution now uses the same syntax as Bash
parameter expansion.
Signed-off-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
We still had a few enum declared to behave like string as well as enum.
Let's use StrEnum for those.
Signed-off-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
* Given that our API packages use "import *" in `__init.py__` we don't
need to do `from llama_stack.apis.models.models` but simply from
llama_stack.apis.models. The decision to use `import *` is debatable and
should probably be revisited at one point.
* Remove unneeded Ruff F401 rule
* Consolidate Ruff F403 rule in the pyprojectfrom
llama_stack.apis.models.models
Signed-off-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
Our starter distro required Ollama to be running (and a large list of
models available in that Ollama) to successfully start. This adjusts
things so that Ollama does not have to be running to use the starter
template / distro.
To accomplish this, a few changes were needed:
* The Ollama provider is now configurable whether it raises an Exception
or just logs a warning when it cannot reach the Ollama server on
startup. The default is to raise an exception (same as previous
behavior), but in the starter template we adjust this to just log a
warning so that we can bring the stack up without needing a running
Ollama server.
* The starter template no longer specifies a default list of models for
Ollama, as any models specified there need to actually be pulled and
available in Ollama. Instead, it adds a new
`OLLAMA_INFERENCE_MODEL` environment variable where users can provide an
optional model to register with the Ollama provider on startup.
Additional models can also be registered via the typical
`models.register(...)` at runtime.
* The vLLM template was adjusted to also allow an optional
`VLLM_INFERENCE_MODEL` specified on startup, so that the behavior
between vLLM and Ollama was consistent here to make it easy to get up
and running quickly.
* The default vector store was changed from sqlite-vec to faiss.
sqlite-vec can enabled via setting the `ENABLE_SQLITE_VEC` environment
variable, like we do for chromadb and pgvector. This is due to
sqlite-vec not shipping proper arm64 binaries, like we previously fixed
in #1530 for the ollama distribution.
## Test Plan
With this change, the following scenarios now work with the starter
template that did not before:
* no Ollama running
* Ollama running but not all of the Llama models pulled locally
* Ollama running with a custom model registered on startup
* vLLM running with a custom model registered on startup
* running the starter template on linux/arm64, like when running
containers on Mac without rosetta emulation
---------
Signed-off-by: Ben Browning <bbrownin@redhat.com>
# What does this PR do?
Add search_mode parameter (vector/keyword/hybrid) to
openai_search_vector_store method. Fixes OpenAPI
code generation by using str instead of Literal type.
Closes: #2459
## 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: Varsha Prasad Narsing <varshaprasad96@gmail.com>
# What does this PR do?
Closes#2495
Changes:
- Delay the `COPY run.yaml` into docker image step until after external
provider handling
- Split the check for `external_providers_dir` into “non-empty” and
“directory exists"
## Test Plan
0. Create and Activate venv
1. Create a `simple_build.yaml`
```yaml
version: '2'
distribution_spec:
providers:
inference:
- remote::openai
image_type: container
image_name: openai-stack
```
2. Run llama stack build:
```bash
llama stack build --config simple_build.yaml
```
3. Run the docker container:
```bash
docker run \
-p 8321:8321 \
-e OPENAI_API_KEY=$OPENAI_API_KEY \
openai_stack:0.2.12
```
This should show server is running.
```
INFO 2025-06-23 19:07:57,832 llama_stack.distribution.distribution:151 core: Loading external providers from /.llama/providers.d
INFO 2025-06-23 19:07:59,324 __main__:572 server: Listening on ['::', '0.0.0.0']:8321
INFO: Started server process [1]
INFO: Waiting for application startup.
INFO 2025-06-23 19:07:59,336 __main__:156 server: Starting up
INFO: Application startup complete.
INFO: Uvicorn running on http://['::', '0.0.0.0']:8321 (Press CTRL+C to quit)
```
Notice the first line:
```
Loading external providers from /.llama/providers.d
```
This is expected behaviour.
Co-authored-by: Rohan Awhad <rawhad@redhat.com>
# What does this PR do?
Inference/Response stores now store user attributes when inserting, and
respects them when fetching.
## Test Plan
pytest tests/unit/utils/test_sqlstore.py
# What does this PR do?
This adds the ability to list, retrieve, update, and delete Vector Store
Files. It implements these new APIs for the faiss and sqlite-vec
providers, since those are the two that also have the rest of the vector
store files implementation.
Closes#2445
## Test Plan
### test_openai_vector_stores Integration Tests
There are a number of new integration tests added, which I ran for each
provider as outlined below.
faiss (from ollama distro):
```
INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" \
llama stack run llama_stack/templates/ollama/run.yaml
LLAMA_STACK_CONFIG=http://localhost:8321 \
pytest -sv tests/integration/vector_io/test_openai_vector_stores.py \
--embedding-model=all-MiniLM-L6-v2
```
sqlite-vec (from starter distro):
```
llama stack run llama_stack/templates/starter/run.yaml
LLAMA_STACK_CONFIG=http://localhost:8321 \
pytest -sv tests/integration/vector_io/test_openai_vector_stores.py \
--embedding-model=all-MiniLM-L6-v2
```
### file_search verification tests
I also ensured the file_search verification tests continue to work, both
for faiss and sqlite-vec.
faiss (ollama distro):
```
INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" \
llama stack run llama_stack/templates/ollama/run.yaml
pytest -sv tests/verifications/openai_api/test_responses.py \
-k'file_search' \
--base-url=http://localhost:8321/v1/openai/v1 \
--model=meta-llama/Llama-3.2-3B-Instruct
```
sqlite-vec (starter distro):
```
llama stack run llama_stack/templates/starter/run.yaml
pytest -sv tests/verifications/openai_api/test_responses.py \
-k'file_search' \
--base-url=http://localhost:8321/v1/openai/v1 \
--model=together/meta-llama/Llama-3.2-3B-Instruct-Turbo
```
---------
Signed-off-by: Ben Browning <bbrownin@redhat.com>
# What does this PR do?
dropped python3.10, updated pyproject and dependencies, and also removed
some blocks of code with special handling for enum.StrEnum
Closes#2458
Signed-off-by: Charlie Doern <cdoern@redhat.com>
# What does this PR do?
Move to use vector_stores.search for file search tool in Responses,
which supports filters.
closes#2435
## Test Plan
Added e2e test with fitlers.
myenv ❯ llama stack run llama_stack/templates/fireworks/run.yaml
pytest -sv tests/verifications/openai_api/test_responses.py \
-k 'file_search and filters' \
--base-url=http://localhost:8321/v1/openai/v1 \
--model=meta-llama/Llama-3.3-70B-Instruct
# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
To add health check for faiss inline vector_io provider.
I tried adding `async def health(self) -> HealthResponse:` like in
inference provider, but it didn't worked for `inline->vector_io->faiss`
provider. And via debug logs, I understood the critical issue, that the
health responses are being stored with the API name as the key, not as a
nested dictionary with provider IDs. This means that all providers of
the same API type (e.g., "vector_io") will share the same health
response, and only the last one processed will be visible in the API
response.
I've created a patch file that fixes this issue by:
- Storing the original get_providers_health method
- Creating a patched version that correctly maps health responses to
providers
- Applying the patch to the `ProviderImpl` class
Not an expert, so please let me know, if there can be any other
workaround using which I can get the health status updated directly from
`faiss.py`.
<!-- 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.* -->
Added unit tests to test the provider patch implementation in the PR.
Adding a screenshot with the FAISS inline vector_io health status as
"OK"
When trying to `list` vector_stores , if we cannot retrieve one, log an
error and return all the ones that are valid.
### Test Plan
```
pytest -sv --stack-config=http://localhost:8321 tests/integration/vector_io/test_openai_vector_stores.py --embedding-model all-MiniLM-L6-v2
```
Also tested for `--stack-config fireworks`
…path
# What does this PR do?
Closes#1847
Changes:
- llama_stack/apis/common/responses.py: adds optional `url` field to
PaginatedResponse
- llama_stack/distribution/server/server.py: automatically populate the
URL field with route path
## Test Plan
- Built and ran llama stack server using the following cmds:
```bash
export INFERENCE_MODEL=llama3.1:8b
llama stack build --run --template ollama --image-type container
llama stack run llama_stack/templates/ollama/run.yaml
```
- Ran `curl` to test if we are seeing the `url` param in response:
```bash
curl -X 'GET' \
'http://localhost:8321/v1/agents' \
-H 'accept: application/json'
```
- Expected and Received Output:
`{"data":[],"has_more":false,"url":"/v1/agents"}`
---------
Co-authored-by: Rohan Awhad <rawhad@redhat.com>
For code completion apps need "fill in the middle" capabilities.
Added option of `suffix` to `openai_completion` to enable this.
Updated ollama provider to showcase the same.
### Test Plan
```
pytest -sv --stack-config="inference=ollama" tests/integration/inference/test_openai_completion.py --text-model qwen2.5-coder:1.5b -k test_openai_completion_non_streaming_suffix
```
### OpenAI Sample script
```
from openai import OpenAI
client = OpenAI(base_url="http://localhost:8321/v1/openai/v1")
response = client.completions.create(
model="qwen2.5-coder:1.5b",
prompt="The capital of ",
suffix="is Paris.",
max_tokens=10,
)
print(response.choices[0].text)
```
### Output
```
France is ____.
To answer this question, we
```
# What does this PR do?
This is an initial working prototype of wiring up the `file_search`
builtin tool for the Responses API to our existing rag knowledge search
tool.
This is me seeing what I could pull together on top of the bits we
already have merged. This may not be the ideal way to implement this,
and things like how I shuffle the vector store ids from the original
response API tool request to the actual tool execution feel a bit hacky
(grep for `tool_kwargs["vector_db_ids"]` in `_execute_tool_call` to see
what I mean).
## Test Plan
I stubbed in some new tests to exercise this using text and pdf
documents.
Note that this is currently under tests/verification only because it
sometimes flakes with tool calling of the small Llama-3.2-3B model we
run in CI (and that I use as an example below). We'd want to make the
test a bit more robust in some way if we moved this over to
tests/integration and ran it in CI.
### OpenAI SaaS (to verify test correctness)
```
pytest -sv tests/verifications/openai_api/test_responses.py \
-k 'file_search' \
--base-url=https://api.openai.com/v1 \
--model=gpt-4o
```
### Fireworks with faiss vector store
```
llama stack run llama_stack/templates/fireworks/run.yaml
pytest -sv tests/verifications/openai_api/test_responses.py \
-k 'file_search' \
--base-url=http://localhost:8321/v1/openai/v1 \
--model=meta-llama/Llama-3.3-70B-Instruct
```
### Ollama with faiss vector store
This sometimes flakes on Ollama because the quantized small model
doesn't always choose to call the tool to answer the user's question.
But, it often works.
```
ollama run llama3.2:3b
INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" \
llama stack run ./llama_stack/templates/ollama/run.yaml \
--image-type venv \
--env OLLAMA_URL="http://0.0.0.0:11434"
pytest -sv tests/verifications/openai_api/test_responses.py \
-k'file_search' \
--base-url=http://localhost:8321/v1/openai/v1 \
--model=meta-llama/Llama-3.2-3B-Instruct
```
### OpenAI provider with sqlite-vec vector store
```
llama stack run ./llama_stack/templates/starter/run.yaml --image-type venv
pytest -sv tests/verifications/openai_api/test_responses.py \
-k 'file_search' \
--base-url=http://localhost:8321/v1/openai/v1 \
--model=openai/gpt-4o-mini
```
### Ensure existing vector store integration tests still pass
```
ollama run llama3.2:3b
INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" \
llama stack run ./llama_stack/templates/ollama/run.yaml \
--image-type venv \
--env OLLAMA_URL="http://0.0.0.0:11434"
LLAMA_STACK_CONFIG=http://localhost:8321 \
pytest -sv tests/integration/vector_io \
--text-model "meta-llama/Llama-3.2-3B-Instruct" \
--embedding-model=all-MiniLM-L6-v2
```
---------
Signed-off-by: Ben Browning <bbrownin@redhat.com>
Though the jwks endpoint does not usually require authentication, it
does in a kubernetes cluster. While the cluster can be configured to
allow anonymous access to that endpoint, this avoids the need to do so.
Updated the `search` functionality return response to match openai.
## Test Plan
```
pytest -sv --stack-config=http://localhost:8321 tests/integration/vector_io/test_openai_vector_stores.py --embedding-model all-MiniLM-L6-v2
```
# What does this PR do?
The test wasn't using the correct virtual environment. Also augment the
console width for logs.
Signed-off-by: Sébastien Han <seb@redhat.com>
Extracts common OpenAI vector-store code into its own mixin so that all
providers can share the same core logic.
This also makes it easy for Llama Stack to support both vector-stores
and Llama Stack APIs in the interim so that both share the same
underlying vector-dbs.
Each provider contains storage specific logic to `create / edit / delete
/ list` vector dbs while the plumbing logic is standardized in the
common code.
Ensured that this works well with both faiss and sqllite-vec.
### Test Plan
```
llama stack run starter
pytest -sv --stack-config http://localhost:8321 tests/integration/vector_io/test_openai_vector_stores.py --embedding-model all-MiniLM-L6-v2
```
Adding OpenAI compat `/v1/vector-store` apis.
This PR implements the `faiss` provider with followup PRs coming up for
other providers.
Added routes to create, update, delete, list vector stores.
Also added route to search a vector store
Inserting into vector stores is missing and will be a follow up diff.
### Test Plan
- Added new integration test for testing the faiss provider
```
pytest -sv --stack-config http://localhost:8321 tests/integration/vector_io/test_openai_vector_stores.py --embedding-model all-MiniLM-L6-v2
```
# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
To add health status check for remote VLLM
<!-- 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.* -->
PR includes the unit test to test the added health check implementation
feature.
