forked from phoenix-oss/llama-stack-mirror
9d574f4aee
# What does this PR do? - update playground callsites for v1 api changes ## Test Plan ``` cd llama_stack/distribution/ui streamlit run app.py ``` https://github.com/user-attachments/assets/eace11c6-600a-42dc-b4e7-6948a706509f ## Sources Please link relevant resources if necessary. ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Ran pre-commit to handle lint / formatting issues. - [ ] Read the [contributor guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md), Pull Request section? - [ ] Updated relevant documentation. - [ ] Wrote necessary unit or integration tests. |
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| __init__.py | ||
| app.py | ||
| README.md | ||
| requirements.txt | ||
(Experimental) LLama Stack UI
Docker Setup
⚠️ This is a work in progress.
Developer Setup
- Start up Llama Stack API server. More details here.
llama stack build --template together --image-type conda
llama stack run together
- (Optional) Register datasets and eval tasks as resources. If you want to run pre-configured evaluation flows (e.g. Evaluations (Generation + Scoring) Page).
$ llama-stack-client datasets register \
--dataset-id "mmlu" \
--provider-id "huggingface" \
--url "https://huggingface.co/datasets/llamastack/evals" \
--metadata '{"path": "llamastack/evals", "name": "evals__mmlu__details", "split": "train"}' \
--schema '{"input_query": {"type": "string"}, "expected_answer": {"type": "string", "chat_completion_input": {"type": "string"}}}'
$ llama-stack-client eval_tasks register \
--eval-task-id meta-reference-mmlu \
--provider-id meta-reference \
--dataset-id mmlu \
--scoring-functions basic::regex_parser_multiple_choice_answer
- Start Streamlit UI
cd llama_stack/distribution/ui
pip install -r requirements.txt
streamlit run app.py