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llama-stack/llama_stack/distribution/ui
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Ilya Kolchinsky 79fc81f78f
fix: Playground RAG page errors (#1928) 
# What does this PR do?
This PR fixes two issues with the RAG page of the Playground UI:

1. When the user modifies a configurable setting via a widget (e.g.,
system prompt, temperature, etc.), the agent is not recreated. Thus, the
change has no effect and the user gets no indication of that.
2. After the first issue is fixed, it becomes possible to recreate the
agent mid-conversation or even mid-generation. To mitigate this, widgets
related to agent configuration are now disabled when a conversation is
in progress (i.e., when the chat is non-empty). They are automatically
enabled again when the user resets the chat history.

## Test Plan

- Launch the Playground and go to the RAG page;
- Select the vector DB ID;
- Send a message to the agent via the chat;
- The widgets in charge of the agent parameters will become disabled at
this point;
- Send a second message asking the model about the content of the first
message;
- The reply will indicate that the two messages were sent over the same
session, that is, the agent was not recreated;
- Click the 'Clear Chat' button;
- All widgets will be enabled and a new agent will be created (which can
be validated by sending another message).
2025-04-10 13:38:31 -07:00
..
modules fix: add tavily_search option to playground api (#1909) 2025-04-09 15:56:41 +02:00
page fix: Playground RAG page errors (#1928) 2025-04-10 13:38:31 -07:00
__init__.py move playground ui to llama-stack repo (#536) 2024-11-26 22:04:21 -08:00
app.py feat: Add tools page to playground (#1904) 2025-04-09 15:26:52 +02:00
Containerfile fix: Playground Container Issue (#1868) 2025-04-09 11:45:15 +02:00
README.md chore: simplify running the demo UI (#1907) 2025-04-09 11:22:29 -07:00
requirements.txt chore: simplify running the demo UI (#1907) 2025-04-09 11:22:29 -07:00

README.md

(Experimental) LLama Stack UI

Docker Setup

⚠️ This is a work in progress.

Developer Setup

  1. Start up Llama Stack API server. More details here.
llama stack build --template together --image-type conda

llama stack run together
  1. (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
  1. Start Streamlit UI
uv run --with ".[ui]" streamlit run llama_stack/distribution/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)