llama-stack-mirror/llama_stack/providers
Alexey Rybak 326cbba579
feat(agents): add agent naming functionality (#1922)
# What does this PR do?
Allow users to name an agent and use the name in telemetry instead of
relying on randomly generated agent_ids. This improves the developer
experience by making it easier to find specific agents in telemetry
logs.

Closes #1832

## Test Plan

- Added tests to verify the agent name is properly stored and retrieved
- Ran `uv run -- pytest -v
tests/integration/telemetry/test_telemetry.py::test_agent_name_filtering`
from the root of the project and made sure the tests pass
- Ran `uv run -- pytest -v
tests/integration/telemetry/test_telemetry.py::test_agent_query_spans`
to verify existing code without agent names still works correctly

## Use Example
```
agent = Agent(
    llama_stack_client, 
    model=text_model_id, 
    name="CustomerSupportAgent",  # New parameter
    instructions="You are a helpful customer support assistant"
)
session_id = agent.create_session(f"test-session-{uuid4()}")
```

## Implementation Notes
- Agent names are optional string parameters with no additional
validation
- Names are not required to be unique - multiple agents can have the
same name
- The agent_id remains the unique identifier for an agent

---------

Co-authored-by: raghotham <raghotham@gmail.com>
2025-04-17 07:02:47 -07:00
..
inline feat(agents): add agent naming functionality (#1922) 2025-04-17 07:02:47 -07:00
registry fix: use torchao 0.8.0 for inference (#1925) 2025-04-10 13:39:20 -07:00
remote chore: add meta/llama-3.3-70b-instruct as supported nvidia inference provider model (#1985) 2025-04-17 06:50:40 -07:00
tests refactor: move all llama code to models/llama out of meta reference (#1887) 2025-04-07 15:03:58 -07:00
utils feat: Implement async job execution for torchtune training (#1437) 2025-04-14 08:59:11 -07:00
__init__.py API Updates (#73) 2024-09-17 19:51:35 -07:00
datatypes.py feat: add health to all providers through providers endpoint (#1418) 2025-04-14 11:59:36 +02:00