Commit graph

3 commits

Author SHA1 Message Date
Ashwin Bharambe
eb2d8a31a5
Add a RoutableProvider protocol, support for multiple routing keys (#163)
* Update configure.py to use multiple routing keys for safety
* Refactor distribution/datatypes into a providers/datatypes
* Cleanup
2024-09-30 17:30:21 -07:00
Ashwin Bharambe
0d2eb3bd25 Use inference APIs for running llama guard
Test Plan:

First, start a TGI container with `meta-llama/Llama-Guard-3-8B` model
serving on port 5099. See https://github.com/meta-llama/llama-stack/pull/53 and its
description for how.

Then run llama-stack with the following run config:

```
image_name: safety
docker_image: null
conda_env: safety
apis_to_serve:
- models
- inference
- shields
- safety
api_providers:
  inference:
    providers:
    - remote::tgi
  safety:
    providers:
    - meta-reference
  telemetry:
    provider_id: meta-reference
    config: {}
routing_table:
  inference:
  - provider_id: remote::tgi
    config:
      url: http://localhost:5099
      api_token: null
      hf_endpoint_name: null
    routing_key: Llama-Guard-3-8B
  safety:
  - provider_id: meta-reference
    config:
      llama_guard_shield:
        model: Llama-Guard-3-8B
        excluded_categories: []
        disable_input_check: false
        disable_output_check: false
      prompt_guard_shield: null
    routing_key: llama_guard
```

Now simply run `python -m llama_stack.apis.safety.client localhost
<port>` and check that the llama_guard shield calls run correctly. (The
injection_shield calls fail as expected since we have not set up a
router for them.)
2024-09-24 17:02:57 -07:00
Ashwin Bharambe
ec4fc800cc
[API Updates] Model / shield / memory-bank routing + agent persistence + support for private headers (#92)
This is yet another of those large PRs (hopefully we will have less and less of them as things mature fast). This one introduces substantial improvements and some simplifications to the stack.

Most important bits:

* Agents reference implementation now has support for session / turn persistence. The default implementation uses sqlite but there's also support for using Redis.

* We have re-architected the structure of the Stack APIs to allow for more flexible routing. The motivating use cases are:
  - routing model A to ollama and model B to a remote provider like Together
  - routing shield A to local impl while shield B to a remote provider like Bedrock
  - routing a vector memory bank to Weaviate while routing a keyvalue memory bank to Redis

* Support for provider specific parameters to be passed from the clients. A client can pass data using `x_llamastack_provider_data` parameter which can be type-checked and provided to the Adapter implementations.
2024-09-23 14:22:22 -07:00