Commit graph

7 commits

Author SHA1 Message Date
Dinesh Yeduguru
c23363d561
Add ability to query and export spans to dataset (#574)
This PR adds two new methods to the telemetry API:
1) Gives the ability to query spans directly instead of first querying
traces and then using that to get spans
2) Another method save_spans_to_dataset, which builds on the query spans
to save it on dataset.

This give the ability to saves spans that are part of an agent session
to a dataset.

The unique aspect of this API is that we dont require each provider of
telemetry to implement this method. Hence, its implemented in the
protocol class itself. This required the protocol check to be slightly
modified.
2024-12-05 21:07:30 -08:00
Dinesh Yeduguru
fcd6449519
Telemetry API redesign (#525)
# What does this PR do?
Change the Telemetry API to be able to support different use cases like
returning traces for the UI and ability to export for Evals.
Other changes:
* Add a new trace_protocol decorator to decorate all our API methods so
that any call to them will automatically get traced across all impls.
* There is some issue with the decorator pattern of span creation when
using async generators, where there are multiple yields with in the same
context. I think its much more explicit by using the explicit context
manager pattern using with. I moved the span creations in agent instance
to be using with
* Inject session id at the turn level, which should quickly give us all
traces across turns for a given session

Addresses #509

## Test Plan
```
llama stack run /Users/dineshyv/.llama/distributions/llamastack-together/together-run.yaml
PYTHONPATH=. python -m examples.agents.rag_with_memory_bank localhost 5000


 curl -X POST 'http://localhost:5000/alpha/telemetry/query-traces' \
-H 'Content-Type: application/json' \
-d '{
  "attribute_filters": [
    {
      "key": "session_id",
      "op": "eq",
      "value": "dd667b87-ca4b-4d30-9265-5a0de318fc65" }],
  "limit": 100,
  "offset": 0,
  "order_by": ["start_time"]
}' | jq .
[
  {
    "trace_id": "6902f54b83b4b48be18a6f422b13e16f",
    "root_span_id": "5f37b85543afc15a",
    "start_time": "2024-12-04T08:08:30.501587",
    "end_time": "2024-12-04T08:08:36.026463"
  },
  {
    "trace_id": "92227dac84c0615ed741be393813fb5f",
    "root_span_id": "af7c5bb46665c2c8",
    "start_time": "2024-12-04T08:08:36.031170",
    "end_time": "2024-12-04T08:08:41.693301"
  },
  {
    "trace_id": "7d578a6edac62f204ab479fba82f77b6",
    "root_span_id": "1d935e3362676896",
    "start_time": "2024-12-04T08:08:41.695204",
    "end_time": "2024-12-04T08:08:47.228016"
  },
  {
    "trace_id": "dbd767d76991bc816f9f078907dc9ff2",
    "root_span_id": "f5a7ee76683b9602",
    "start_time": "2024-12-04T08:08:47.234578",
    "end_time": "2024-12-04T08:08:53.189412"
  }
]


curl -X POST 'http://localhost:5000/alpha/telemetry/get-span-tree' \
-H 'Content-Type: application/json' \
-d '{ "span_id" : "6cceb4b48a156913", "max_depth": 2, "attributes_to_return": ["input"] }' | jq .
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100   875  100   790  100    85  18462   1986 --:--:-- --:--:-- --:--:-- 20833
{
  "span_id": "6cceb4b48a156913",
  "trace_id": "dafa796f6aaf925f511c04cd7c67fdda",
  "parent_span_id": "892a66d726c7f990",
  "name": "retrieve_rag_context",
  "start_time": "2024-12-04T09:28:21.781995",
  "end_time": "2024-12-04T09:28:21.913352",
  "attributes": {
    "input": [
      "{\"role\":\"system\",\"content\":\"You are a helpful assistant\"}",
      "{\"role\":\"user\",\"content\":\"What are the top 5 topics that were explained in the documentation? Only list succinct bullet points.\",\"context\":null}"
    ]
  },
  "children": [
    {
      "span_id": "1a2df181854064a8",
      "trace_id": "dafa796f6aaf925f511c04cd7c67fdda",
      "parent_span_id": "6cceb4b48a156913",
      "name": "MemoryRouter.query_documents",
      "start_time": "2024-12-04T09:28:21.787620",
      "end_time": "2024-12-04T09:28:21.906512",
      "attributes": {
        "input": null
      },
      "children": [],
      "status": "ok"
    }
  ],
  "status": "ok"
}

```

<img width="1677" alt="Screenshot 2024-12-04 at 9 42 56 AM"
src="https://github.com/user-attachments/assets/4d3cea93-05ce-415a-93d9-4b1628631bf8">
2024-12-04 11:22:45 -08:00
Ashwin Bharambe
3d7561e55c
Rename all inline providers with an inline:: prefix (#423) 2024-11-11 22:19:16 -08:00
Ashwin Bharambe
994732e2e0
impls -> inline, adapters -> remote (#381) 2024-11-06 14:54:05 -08:00
Ashwin Bharambe
fe4aabd690 provider_id => provider_type, adapter_id => adapter_type 2024-10-02 14:05:59 -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
Ashwin Bharambe
9487ad8294
API Updates (#73)
* API Keys passed from Client instead of distro configuration

* delete distribution registry

* Rename the "package" word away

* Introduce a "Router" layer for providers

Some providers need to be factorized and considered as thin routing
layers on top of other providers. Consider two examples:

- The inference API should be a routing layer over inference providers,
  routed using the "model" key
- The memory banks API is another instance where various memory bank
  types will be provided by independent providers (e.g., a vector store
  is served by Chroma while a keyvalue memory can be served by Redis or
  PGVector)

This commit introduces a generalized routing layer for this purpose.

* update `apis_to_serve`

* llama_toolchain -> llama_stack

* Codemod from llama_toolchain -> llama_stack

- added providers/registry
- cleaned up api/ subdirectories and moved impls away
- restructured api/api.py
- from llama_stack.apis.<api> import foo should work now
- update imports to do llama_stack.apis.<api>
- update many other imports
- added __init__, fixed some registry imports
- updated registry imports
- create_agentic_system -> create_agent
- AgenticSystem -> Agent

* Moved some stuff out of common/; re-generated OpenAPI spec

* llama-toolchain -> llama-stack (hyphens)

* add control plane API

* add redis adapter + sqlite provider

* move core -> distribution

* Some more toolchain -> stack changes

* small naming shenanigans

* Removing custom tool and agent utilities and moving them client side

* Move control plane to distribution server for now

* Remove control plane from API list

* no codeshield dependency randomly plzzzzz

* Add "fire" as a dependency

* add back event loggers

* stack configure fixes

* use brave instead of bing in the example client

* add init file so it gets packaged

* add init files so it gets packaged

* Update MANIFEST

* bug fix

---------

Co-authored-by: Hardik Shah <hjshah@fb.com>
Co-authored-by: Xi Yan <xiyan@meta.com>
Co-authored-by: Ashwin Bharambe <ashwin@meta.com>
2024-09-17 19:51:35 -07:00
Renamed from llama_toolchain/telemetry/providers.py (Browse further)