mirror of https://github.com/meta-llama/llama-stack.git synced 2025-06-27 18:50:41 +00:00

Ashwin Bharambe abfbaf3c1b

refactor(test): move tools, evals, datasetio, scoring and post training tests (#1401 )

All of the tests from `llama_stack/providers/tests/` are now moved to
`tests/integration`.

I converted the `tools`, `scoring` and `datasetio` tests to use API.
However, `eval` and `post_training` proved to be a bit challenging to
leaving those. I think `post_training` should be relatively
straightforward also.

As part of this, I noticed that `wolfram_alpha` tool wasn't added to
some of our commonly used distros so I added it. I am going to remove a
lot of code duplication from distros next so while this looks like a
one-off right now, it will go away and be there uniformly for all
distros.

2025-03-04 14:53:47 -08:00

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Fireworks Distribution

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self

The llamastack/distribution-fireworks distribution consists of the following provider configurations.

API	Provider(s)
agents	`inline::meta-reference`
datasetio	`remote::huggingface`, `inline::localfs`
eval	`inline::meta-reference`
inference	`remote::fireworks`, `inline::sentence-transformers`
safety	`inline::llama-guard`
scoring	`inline::basic`, `inline::llm-as-judge`, `inline::braintrust`
telemetry	`inline::meta-reference`
tool_runtime	`remote::brave-search`, `remote::tavily-search`, `remote::wolfram-alpha`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol`
vector_io	`inline::faiss`, `remote::chromadb`, `remote::pgvector`

Environment Variables

The following environment variables can be configured:

LLAMA_STACK_PORT: Port for the Llama Stack distribution server (default: 5001)
FIREWORKS_API_KEY: Fireworks.AI API Key (default: ``)

Models

The following models are available by default:

accounts/fireworks/models/llama-v3p1-8b-instruct (aliases: meta-llama/Llama-3.1-8B-Instruct)
accounts/fireworks/models/llama-v3p1-70b-instruct (aliases: meta-llama/Llama-3.1-70B-Instruct)
accounts/fireworks/models/llama-v3p1-405b-instruct (aliases: meta-llama/Llama-3.1-405B-Instruct-FP8)
accounts/fireworks/models/llama-v3p2-1b-instruct (aliases: meta-llama/Llama-3.2-1B-Instruct)
accounts/fireworks/models/llama-v3p2-3b-instruct (aliases: meta-llama/Llama-3.2-3B-Instruct)
accounts/fireworks/models/llama-v3p2-11b-vision-instruct (aliases: meta-llama/Llama-3.2-11B-Vision-Instruct)
accounts/fireworks/models/llama-v3p2-90b-vision-instruct (aliases: meta-llama/Llama-3.2-90B-Vision-Instruct)
accounts/fireworks/models/llama-v3p3-70b-instruct (aliases: meta-llama/Llama-3.3-70B-Instruct)
accounts/fireworks/models/llama-guard-3-8b (aliases: meta-llama/Llama-Guard-3-8B)
accounts/fireworks/models/llama-guard-3-11b-vision (aliases: meta-llama/Llama-Guard-3-11B-Vision)
nomic-ai/nomic-embed-text-v1.5

Prerequisite: API Keys

Make sure you have access to a Fireworks API Key. You can get one by visiting fireworks.ai.

Running Llama Stack with Fireworks

You can do this via Conda (build code) or Docker which has a pre-built image.

Via Docker

This method allows you to get started quickly without having to build the distribution code.

LLAMA_STACK_PORT=5001
docker run \
  -it \
  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
  llamastack/distribution-fireworks \
  --port $LLAMA_STACK_PORT \
  --env FIREWORKS_API_KEY=$FIREWORKS_API_KEY

Via Conda

llama stack build --template fireworks --image-type conda
llama stack run ./run.yaml \
  --port $LLAMA_STACK_PORT \
  --env FIREWORKS_API_KEY=$FIREWORKS_API_KEY

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