forked from phoenix-oss/llama-stack-mirror
928a39d17b
Groq has never supported raw completions anyhow. So this makes it easier to switch it to LiteLLM. All our test suite passes. I also updated all the openai-compat providers so they work with api keys passed from headers. `provider_data` ## Test Plan ```bash LLAMA_STACK_CONFIG=groq \ pytest -s -v tests/client-sdk/inference/test_text_inference.py \ --inference-model=groq/llama-3.3-70b-versatile --vision-inference-model="" ``` Also tested (openai, anthropic, gemini) providers. No regressions.
77 lines
2 KiB
Markdown
77 lines
2 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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# Groq 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-groq` 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::groq` |
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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` |
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| vector_io | `inline::faiss` |
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### Environment Variables
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The following environment variables can be configured:
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- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
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- `GROQ_API_KEY`: Groq 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/Llama-3.1-8B-Instruct (groq/llama3-8b-8192)`
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- `meta-llama/Llama-3.1-8B-Instruct (groq/llama-3.1-8b-instant)`
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- `meta-llama/Llama-3-70B-Instruct (groq/llama3-70b-8192)`
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- `meta-llama/Llama-3.3-70B-Instruct (groq/llama-3.3-70b-versatile)`
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- `meta-llama/Llama-3.2-3B-Instruct (groq/llama-3.2-3b-preview)`
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### Prerequisite: API Keys
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Make sure you have access to a Groq API Key. You can get one by visiting [Groq](https://api.groq.com/).
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## Running Llama Stack with Groq
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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-groq \
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--port $LLAMA_STACK_PORT \
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--env GROQ_API_KEY=$GROQ_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 groq --image-type conda
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llama stack run ./run.yaml \
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--port $LLAMA_STACK_PORT \
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--env GROQ_API_KEY=$GROQ_API_KEY
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```
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