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">
This commit is contained in:
Dinesh Yeduguru 2024-12-04 11:22:45 -08:00 committed by GitHub
parent 16769256b7
commit fcd6449519
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GPG key ID: B5690EEEBB952194
34 changed files with 1551 additions and 245 deletions

View file

@ -3,14 +3,17 @@
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import Optional
from typing import Any, Dict, List, Optional
import pandas
from llama_models.llama3.api.datatypes import * # noqa: F403
from llama_stack.apis.datasetio import * # noqa: F403
import base64
import os
from abc import ABC, abstractmethod
from dataclasses import dataclass
from urllib.parse import urlparse
from llama_stack.providers.datatypes import DatasetsProtocolPrivate
from llama_stack.providers.utils.datasetio.url_utils import get_dataframe_from_url
@ -131,3 +134,41 @@ class LocalFSDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
total_count=len(rows),
next_page_token=str(end),
)
async def append_rows(self, dataset_id: str, rows: List[Dict[str, Any]]) -> None:
dataset_info = self.dataset_infos.get(dataset_id)
if dataset_info is None:
raise ValueError(f"Dataset with id {dataset_id} not found")
dataset_impl = dataset_info.dataset_impl
dataset_impl.load()
new_rows_df = pandas.DataFrame(rows)
new_rows_df = dataset_impl._validate_dataset_schema(new_rows_df)
dataset_impl.df = pandas.concat(
[dataset_impl.df, new_rows_df], ignore_index=True
)
url = str(dataset_info.dataset_def.url)
parsed_url = urlparse(url)
if parsed_url.scheme == "file" or not parsed_url.scheme:
file_path = parsed_url.path
os.makedirs(os.path.dirname(file_path), exist_ok=True)
dataset_impl.df.to_csv(file_path, index=False)
elif parsed_url.scheme == "data":
# For data URLs, we need to update the base64-encoded content
if not parsed_url.path.startswith("text/csv;base64,"):
raise ValueError("Data URL must be a base64-encoded CSV")
csv_buffer = dataset_impl.df.to_csv(index=False)
base64_content = base64.b64encode(csv_buffer.encode("utf-8")).decode(
"utf-8"
)
dataset_info.dataset_def.url = URL(
uri=f"data:text/csv;base64,{base64_content}"
)
else:
raise ValueError(
f"Unsupported URL scheme: {parsed_url.scheme}. Only file:// and data: URLs are supported for writing."
)