Commit graph

9 commits

Author SHA1 Message Date
Hardik Shah
127bac6869
fix: Default to port 8321 everywhere (#1734)
As titled, moved all instances of 5001 to 8321
2025-03-20 15:50:41 -07:00
Hardik Shah
581e8ae562
fix: docker run with --pull always to fetch the latest image (#1733)
As titled
2025-03-20 15:35:48 -07:00
Ashwin Bharambe
04de2f84e9
fix: register provider model name and HF alias in run.yaml (#1304)
Each model known to the system has two identifiers: 

- the `provider_resource_id` (what the provider calls it) -- e.g.,
`accounts/fireworks/models/llama-v3p1-8b-instruct`
- the `identifier` (`model_id`) under which it is registered and gets
routed to the appropriate provider.

We have so far used the HuggingFace repo alias as the standardized
identifier you can use to refer to the model. So in the above example,
we'd use `meta-llama/Llama-3.1-8B-Instruct` as the name under which it
gets registered. This makes it convenient for users to refer to these
models across providers.

However, we forgot to register the _actual_ provider model ID also. You
should be able to route via `provider_resource_id` also, of course.

This change fixes this (somewhat grave) omission.

*Note*: this change is additive -- more aliases work now compared to
before.

## Test Plan

Run the following for distro=(ollama fireworks together)
```
LLAMA_STACK_CONFIG=$distro \
   pytest -s -v tests/client-sdk/inference/test_text_inference.py \
   --inference-model=meta-llama/Llama-3.1-8B-Instruct --vision-inference-model=""
```
2025-02-27 16:39:23 -08:00
Ellis Tarn
afca9d92f9
fix: Readthedocs cannot parse comments, resulting in docs bugs (#1033) 2025-02-10 16:35:16 -05:00
Hardik Shah
a84e7669f0
feat: Add a new template for dell (#978)
- Added new template `dell` and its documentation 
- Update docs 
- [minor] uv fix i came across 
- codegen for all templates 

Tested with 

```bash
export INFERENCE_PORT=8181
export DEH_URL=http://0.0.0.0:$INFERENCE_PORT
export INFERENCE_MODEL=meta-llama/Llama-3.1-8B-Instruct
export CHROMADB_HOST=localhost
export CHROMADB_PORT=6601
export CHROMA_URL=[http://$CHROMADB_HOST:$CHROMADB_PORT](about:blank)
export CUDA_VISIBLE_DEVICES=0
export LLAMA_STACK_PORT=8321

# build the stack template 
llama stack build --template=dell 

# start the TGI inference server 
podman run --rm -it --network host -v $HOME/.cache/huggingface:/data -e HF_TOKEN=$HF_TOKEN -p $INFERENCE_PORT:$INFERENCE_PORT --gpus $CUDA_VISIBLE_DEVICES [ghcr.io/huggingface/text-generation-inference](http://ghcr.io/huggingface/text-generation-inference) --dtype bfloat16 --usage-stats off --sharded false --cuda-memory-fraction 0.7 --model-id $INFERENCE_MODEL --port $INFERENCE_PORT --hostname 0.0.0.0

# start chroma-db for vector-io ( aka RAG )
podman run --rm -it --network host --name chromadb -v .:/chroma/chroma -e IS_PERSISTENT=TRUE chromadb/chroma:latest --port $CHROMADB_PORT --host $(hostname)

# build docker 
llama stack build --template=dell --image-type=container

# run llama stack server ( via docker )
podman run -it \
--network host \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
# NOTE: mount the llama-stack / llama-model directories if testing local changes 
-v /home/hjshah/git/llama-stack:/app/llama-stack-source -v /home/hjshah/git/llama-models:/app/llama-models-source \ localhost/distribution-dell:dev \
--port $LLAMA_STACK_PORT  \
--env INFERENCE_MODEL=$INFERENCE_MODEL \
--env DEH_URL=$DEH_URL \
--env CHROMA_URL=$CHROMA_URL

# test the server 
cd <PATH_TO_LLAMA_STACK_REPO>
LLAMA_STACK_BASE_URL=http://0.0.0.0:$LLAMA_STACK_PORT pytest -s -v tests/client-sdk/agents/test_agents.py

```

---------

Co-authored-by: Hardik Shah <hjshah@fb.com>
2025-02-06 14:14:39 -08:00
Hardik Shah
a7b929f17e
Sec fixes as raised by bandit (#917)
minor fixes to hashlib and jinja
2025-01-31 13:44:26 -08:00
snova-edwardm
7fe2592795
SambaNova supports Llama 3.3 (#905)
# What does this PR do?

- Fix typo
- Support Llama 3.3 70B

## Test Plan

Run the following scripts and obtain the test results

Script
```
pytest -s -v --providers inference=sambanova llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_streaming --env SAMBANOVA_API_KEY={API_KEY}
```

Result
```
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_streaming[-sambanova] PASSED

=========================================== 1 passed, 1 warning in 1.26s ============================================
```

Script
```
pytest -s -v --providers inference=sambanova llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_non_streaming --env SAMBANOVA_API_KEY={API_KEY}
```

Result
```
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_non_streaming[-sambanova] PASSED

=========================================== 1 passed, 1 warning in 0.52s ============================================
```

## Sources

Please link relevant resources if necessary.


## Before submitting

- [N] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [Y] Ran pre-commit to handle lint / formatting issues.
- [Y] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
      Pull Request section?
- [Y] Updated relevant documentation.
- [N] Wrote necessary unit or integration tests.
2025-01-30 09:24:46 -08:00
Hardik Shah
2cebb24d3a
Update doc templates for running safety on self-hosted templates (#874) 2025-01-24 11:28:20 -08:00
snova-edwardm
22dc684da6
Sambanova inference provider (#555)
# What does this PR do?

This PR adds SambaNova as one of the Provider

- Add SambaNova as a provider

## Test Plan
Test the functional command
```
pytest -s -v --providers inference=sambanova llama_stack/providers/tests/inference/test_embeddings.py llama_stack/providers/tests/inference/test_prompt_adapter.py llama_stack/providers/tests/inference/test_text_inference.py llama_stack/providers/tests/inference/test_vision_inference.py --env SAMBANOVA_API_KEY=<sambanova-api-key>
```

Test the distribution template:
```
# Docker
LLAMA_STACK_PORT=5001
docker run -it -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
  llamastack/distribution-sambanova \
  --port $LLAMA_STACK_PORT \
  --env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY

# Conda
llama stack build --template sambanova --image-type conda
llama stack run ./run.yaml \
  --port $LLAMA_STACK_PORT \
  --env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY
```

## Source
[SambaNova API Documentation](https://cloud.sambanova.ai/apis)

## Before submitting

- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [Y] Ran pre-commit to handle lint / formatting issues.
- [Y] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
      Pull Request section?
- [Y] Updated relevant documentation.
- [Y ] Wrote necessary unit or integration tests.

---------

Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
2025-01-23 12:20:28 -08:00