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ef0736527d
This is a sweeping change to clean up some gunk around our "Tool" definitions. First, we had two types `Tool` and `ToolDef`. The first of these was a "Resource" type for the registry but we had stopped registering tools inside the Registry long back (and only registered ToolGroups.) The latter was for specifying tools for the Agents API. This PR removes the former and adds an optional `toolgroup_id` field to the latter. Secondly, as pointed out by @bbrowning in https://github.com/llamastack/llama-stack/pull/3003#issuecomment-3245270132, we were doing a lossy conversion from a full JSON schema from the MCP tool specification into our ToolDefinition to send it to the model. There is no necessity to do this -- we ourselves aren't doing any execution at all but merely passing it to the chat completions API which supports this. By doing this (and by doing it poorly), we encountered limitations like not supporting array items, or not resolving $refs, etc. To fix this, we replaced the `parameters` field by `{ input_schema, output_schema }` which can be full blown JSON schemas. Finally, there were some types in our llama-related chat format conversion which needed some cleanup. We are taking this opportunity to clean those up. This PR is a substantial breaking change to the API. However, given our window for introducing breaking changes, this suits us just fine. I will be landing a concurrent `llama-stack-client` change as well since API shapes are changing. |
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| .. | ||
| modules | ||
| page | ||
| __init__.py | ||
| app.py | ||
| Containerfile | ||
| 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 --distro together --image-type venv
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 benchmarks 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
uv run --with ".[ui]" streamlit run llama_stack.core/ui/app.py
Environment Variables
| Environment Variable | Description | Default Value |
|---|---|---|
| LLAMA_STACK_ENDPOINT | The endpoint for the Llama Stack | http://localhost:8321 |
| FIREWORKS_API_KEY | API key for Fireworks provider | (empty string) |
| TOGETHER_API_KEY | API key for Together provider | (empty string) |
| SAMBANOVA_API_KEY | API key for SambaNova provider | (empty string) |
| OPENAI_API_KEY | API key for OpenAI provider | (empty string) |