This extracts the existing logic to convert chunks to
VectorStoreContent objects into a reusable method and uses that when
returning our list of Vector Store File contents.
It also adds an xfail test for deleting vector store files, as that's
not implemented yet but parking the implementation of that for now.
Signed-off-by: Ben Browning <bbrownin@redhat.com>
This requires some more bookkeeping data, some additional storage (of
the chunks we created for this file), and is implemented for faiss and sqlite-vec.
Signed-off-by: Ben Browning <bbrownin@redhat.com>
This wires up the `file_ids` from the vector store create request to
actually attach all those files at creation time. This also required
smarter handling of the file_ids and file_count metadata handling to
ensure we update the in-memory cache and persistent representation of
those as we attach those files. And, expand that logic to handle
errors during file attachment to persist the failed status.
Signed-off-by: Ben Browning <bbrownin@redhat.com>
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.
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
```
Signed-off-by: Ben Browning <bbrownin@redhat.com>
# What does this PR do?
Do not force 384 for the embedding dimension, use the one provided by
the test run.
## Test Plan
```
pytest -s -vvv tests/integration/vector_io/test_vector_io.py --stack-config=http://localhost:8321 \
-k "not(builtin_tool or safety_with_image or code_interpreter or test_rag)" \
--text-model="meta-llama/Llama-3.2-3B-Instruct" \
--embedding-model=granite-embedding-125m --embedding-dimension=768
Uninstalled 1 package in 16ms
Installed 1 package in 11ms
INFO 2025-06-18 10:52:03,314 tests.integration.conftest:59 tests: Setting DISABLE_CODE_SANDBOX=1 for macOS
/Users/leseb/Documents/AI/llama-stack/.venv/lib/python3.10/site-packages/pytest_asyncio/plugin.py:207: PytestDeprecationWarning: The configuration option "asyncio_default_fixture_loop_scope" is unset.
The event loop scope for asynchronous fixtures will default to the fixture caching scope. Future versions of pytest-asyncio will default the loop scope for asynchronous fixtures to function scope. Set the default fixture loop scope explicitly in order to avoid unexpected behavior in the future. Valid fixture loop scopes are: "function", "class", "module", "package", "session"
warnings.warn(PytestDeprecationWarning(_DEFAULT_FIXTURE_LOOP_SCOPE_UNSET))
================================================= test session starts =================================================
platform darwin -- Python 3.10.16, pytest-8.3.4, pluggy-1.5.0 -- /Users/leseb/Documents/AI/llama-stack/.venv/bin/python
cachedir: .pytest_cache
metadata: {'Python': '3.10.16', 'Platform': 'macOS-15.5-arm64-arm-64bit', 'Packages': {'pytest': '8.3.4', 'pluggy': '1.5.0'}, 'Plugins': {'cov': '6.0.0', 'html': '4.1.1', 'json-report': '1.5.0', 'timeout': '2.4.0', 'metadata': '3.1.1', 'asyncio': '0.25.3', 'anyio': '4.8.0', 'nbval': '0.11.0'}}
rootdir: /Users/leseb/Documents/AI/llama-stack
configfile: pyproject.toml
plugins: cov-6.0.0, html-4.1.1, json-report-1.5.0, timeout-2.4.0, metadata-3.1.1, asyncio-0.25.3, anyio-4.8.0, nbval-0.11.0
asyncio: mode=strict, asyncio_default_fixture_loop_scope=None
collected 8 items
tests/integration/vector_io/test_vector_io.py::test_vector_db_retrieve[emb=granite-embedding-125m:dim=768] PASSED
tests/integration/vector_io/test_vector_io.py::test_vector_db_register[emb=granite-embedding-125m:dim=768] PASSED
tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case0] PASSED
tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case1] PASSED
tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case2] PASSED
tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case3] PASSED
tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case4] PASSED
tests/integration/vector_io/test_vector_io.py::test_insert_chunks_with_precomputed_embeddings[emb=granite-embedding-125m:dim=768] PASSED
================================================== 8 passed in 5.50s ==================================================
```
Signed-off-by: Sébastien Han <seb@redhat.com>
https://github.com/meta-llama/llama-stack-client-python/pull/238 updated
llama-stack-client to also support Open AI endpoints for embeddings,
files, vector-stores. This updates the test to test all configs --
openai sdk, llama stack sdk and library-as-client.
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?
Fixes provider weaviate `query_vector` function for when the distance
between the query embedding and an embedding within the vector db is 0
(identical vectors). Catches `ZeroDivisionError` and then sets `score`
to infinity, which represent maximum similarity.
<!-- If resolving an issue, uncomment and update the line below -->
Closes [#2381]
## Test Plan
Checkout this PR
Execute this code and there will no longer be a `ZeroDivisionError`
exception
```
from llama_stack_client import LlamaStackClient
base_url = "http://localhost:8321"
client = LlamaStackClient(base_url=base_url)
models = client.models.list()
embedding_model = (
em := next(m for m in models if m.model_type == "embedding")
).identifier
embedding_dimension = 384
_ = client.vector_dbs.register(
vector_db_id="foo_db",
embedding_model=embedding_model,
embedding_dimension=embedding_dimension,
provider_id="weaviate",
)
chunk = {
"content": "foo",
"mime_type": "text/plain",
"metadata": {
"document_id": "foo-id"
}
}
client.vector_io.insert(vector_db_id="foo_db", chunks=[chunk])
client.vector_io.query(vector_db_id="foo_db", query="foo")
```
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?
Since we moved the move tests/client-sdk to tests/api in
https://github.com/meta-llama/llama-stack/pull/1376. The N999 rule is
not needed anymore. And furthermore in
abfbaf3c1b
[//]: # (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.*]
[//]: # (## Documentation)
Signed-off-by: Sébastien Han <seb@redhat.com>
