forked from phoenix-oss/llama-stack-mirror
abfbaf3c1b
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.
83 lines
2.8 KiB
Markdown
83 lines
2.8 KiB
Markdown
---
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orphan: true
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---
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<!-- This file was auto-generated by distro_codegen.py, please edit source -->
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# Together Distribution
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```{toctree}
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:maxdepth: 2
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:hidden:
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self
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```
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The `llamastack/distribution-together` distribution consists of the following provider configurations.
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| API | Provider(s) |
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|-----|-------------|
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| agents | `inline::meta-reference` |
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| datasetio | `remote::huggingface`, `inline::localfs` |
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| eval | `inline::meta-reference` |
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| inference | `remote::together`, `inline::sentence-transformers` |
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| safety | `inline::llama-guard` |
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| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
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| telemetry | `inline::meta-reference` |
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| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol`, `remote::wolfram-alpha` |
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| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
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### Environment Variables
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The following environment variables can be configured:
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- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
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- `TOGETHER_API_KEY`: Together.AI API Key (default: ``)
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### Models
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The following models are available by default:
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- `meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo (aliases: meta-llama/Llama-3.1-8B-Instruct)`
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- `meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo (aliases: meta-llama/Llama-3.1-70B-Instruct)`
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- `meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo (aliases: meta-llama/Llama-3.1-405B-Instruct-FP8)`
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- `meta-llama/Llama-3.2-3B-Instruct-Turbo (aliases: meta-llama/Llama-3.2-3B-Instruct)`
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- `meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo (aliases: meta-llama/Llama-3.2-11B-Vision-Instruct)`
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- `meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo (aliases: meta-llama/Llama-3.2-90B-Vision-Instruct)`
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- `meta-llama/Llama-3.3-70B-Instruct-Turbo (aliases: meta-llama/Llama-3.3-70B-Instruct)`
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- `meta-llama/Meta-Llama-Guard-3-8B (aliases: meta-llama/Llama-Guard-3-8B)`
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- `meta-llama/Llama-Guard-3-11B-Vision-Turbo (aliases: meta-llama/Llama-Guard-3-11B-Vision)`
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- `togethercomputer/m2-bert-80M-8k-retrieval `
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- `togethercomputer/m2-bert-80M-32k-retrieval `
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### Prerequisite: API Keys
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Make sure you have access to a Together API Key. You can get one by visiting [together.xyz](https://together.xyz/).
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## Running Llama Stack with Together
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You can do this via Conda (build code) or Docker which has a pre-built image.
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### Via Docker
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This method allows you to get started quickly without having to build the distribution code.
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```bash
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LLAMA_STACK_PORT=5001
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docker run \
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-it \
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-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
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llamastack/distribution-together \
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--port $LLAMA_STACK_PORT \
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--env TOGETHER_API_KEY=$TOGETHER_API_KEY
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```
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### Via Conda
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```bash
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llama stack build --template together --image-type conda
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llama stack run ./run.yaml \
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--port $LLAMA_STACK_PORT \
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--env TOGETHER_API_KEY=$TOGETHER_API_KEY
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```
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