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5 commits

Author SHA1 Message Date
Botao Chen
cb42e1d9d4 commit 2025-03-11 20:37:42 -07:00
Botao Chen
ca2922a455 temp commit 2025-03-11 15:40:35 -07:00
Sébastien Han
803bf0e029
fix: solve ruff B008 warnings (#1444) 
# What does this PR do?

The commit addresses the Ruff warning B008 by refactoring the code to
avoid calling SamplingParams() directly in function argument defaults.
Instead, it either uses Field(default_factory=SamplingParams) for
Pydantic models or sets the default to None and instantiates
SamplingParams inside the function body when the argument is None.

Signed-off-by: Sébastien Han <seb@redhat.com>
 2025-03-06 16:48:35 -08:00
Ashwin Bharambe
81ce39a607
feat(api): Add options for supporting various embedding models (#1192) 
We need to support:
- asymmetric embedding models (#934)
- truncation policies (#933)
- varying dimensional output (#932) 

## Test Plan

```bash
$ cd llama_stack/providers/tests/inference
$ pytest -s -v -k fireworks test_embeddings.py \
   --inference-model nomic-ai/nomic-embed-text-v1.5 --env EMBEDDING_DIMENSION=784
$  pytest -s -v -k together test_embeddings.py \
   --inference-model togethercomputer/m2-bert-80M-8k-retrieval --env EMBEDDING_DIMENSION=784
$ pytest -s -v -k ollama test_embeddings.py \
   --inference-model all-minilm:latest --env EMBEDDING_DIMENSION=784
```
 2025-02-20 22:27:12 -08:00
Botao Chen
2b995c22eb
feat: inference passthrough provider (#1166) 
##  What does this PR do?
In this PR, we implement a passthrough inference provider that works for
any endpoints that respect llama stack inference API definition.

## Test Plan
config some endpoint that respect llama stack inference API definition
and got the inference results successfully

<img width="1268" alt="Screenshot 2025-02-19 at 8 52 51 PM"
src="https://github.com/user-attachments/assets/447816e4-ea7a-4365-b90c-386dc7dcf4a1"
/>
 2025-02-19 21:47:00 -08:00