Commit graph

35 commits

Author SHA1 Message Date
ehhuang
2f38851751
chore: Revert "chore(telemetry): remove service_name entirely" (#1785)
Reverts meta-llama/llama-stack#1755 closes #1781
2025-03-25 14:42:05 -07:00
Dinesh Yeduguru
5eb15684b4
feat: use same trace ids in stack and otel (#1759)
# What does this PR do?
1) Uses otel compatible id generation for stack
2) Stack starts returning trace id info in the header of response
3) We inject the same trace id that we have into otel in order to force
it to use our trace ids.

## Test Plan
```
 curl -i --request POST \
  --url http://localhost:8321/v1/inference/chat-completion \
  --header 'content-type: application/json' \
  --data '{
  "model_id": "meta-llama/Llama-3.1-70B-Instruct",
  "messages": [
    {
      "role": "user",
      "content": {
        "type": "text",
        "text": "where do humans live"
      }
    }
  ],
  "stream": false
}'
HTTP/1.1 200 OK
date: Fri, 21 Mar 2025 21:51:19 GMT
server: uvicorn
content-length: 1712
content-type: application/json
x-trace-id: 595101ede31ece116ebe35b26d67e8cf

{"metrics":[{"metric":"prompt_tokens","value":10,"unit":null},{"metric":"completion_tokens","value":320,"unit":null},{"metric":"total_tokens","value":330,"unit":null}],"completion_message":{"role":"assistant","content":"Humans live on the planet Earth, specifically on its landmasses and in its oceans. Here's a breakdown of where humans live:\n\n1. **Continents:** Humans inhabit all seven continents:\n\t* Africa\n\t* Antarctica ( temporary residents, mostly scientists and researchers)\n\t* Asia\n\t* Australia\n\t* Europe\n\t* North America\n\t* South America\n2. **Countries:** There are 196 countries recognized by the United Nations, and humans live in almost all of them.\n3. **Cities and towns:** Many humans live in urban areas, such as cities and towns, which are often located near coastlines, rivers, or other bodies of water.\n4. **Rural areas:** Some humans live in rural areas, such as villages, farms, and countryside.\n5. **Islands:** Humans inhabit many islands around the world, including tropical islands, island nations, and islands in the Arctic and Antarctic regions.\n6. **Underwater habitats:** A few humans live in underwater habitats, such as research stations and submarines.\n7. **Space:** A small number of humans have lived in space, including astronauts on the International Space Station and those who have visited the Moon.\n\nIn terms of specific environments, humans live in a wide range of ecosystems, including:\n\n* Deserts\n* Forests\n* Grasslands\n* Mountains\n* Oceans\n* Rivers\n* Tundras\n* Wetlands\n\nOverall, humans are incredibly adaptable and can be found living in almost every corner of the globe.","stop_reason":"end_of_turn","tool_calls":[]},"logprobs":null}
```

Same trace id in Jaeger and sqlite:

![Screenshot 2025-03-21 at 2 51
53 PM](https://github.com/user-attachments/assets/38cc04b0-568c-4b9d-bccd-d3b90e581c27)
![Screenshot 2025-03-21 at 2 52
38 PM](https://github.com/user-attachments/assets/722383ad-6305-4020-8a1c-6cfdf381c25f)
2025-03-21 15:41:26 -07:00
ehhuang
b9fbfed216
chore(telemetry): remove service_name entirely (#1755)
# What does this PR do?


## Test Plan

LLAMA_STACK_CONFIG=dev pytest -s -v
tests/integration/agents/test_agents.py::test_custom_tool
--safety-shield meta-llama/Llama-Guard-3-8B --text-model
accounts/fireworks/models/llama-v3p1-8b-instruct

and verify trace in jaeger UI
https://llama-stack.readthedocs.io/en/latest/building_applications/telemetry.html#
2025-03-21 15:11:56 -07:00
ehhuang
34f89bfbd6
feat(telemetry): use zero-width space to avoid clutter (#1754)
# What does this PR do?
Before 
<img width="858" alt="image"
src="https://github.com/user-attachments/assets/6cefb1ae-5603-4818-85ea-a0c337b986bc"
/>

Note the redundant 'llama-stack' in front of every span

## Test Plan
<img width="1171" alt="image"
src="https://github.com/user-attachments/assets/bdc5fd5b-ff1f-4f10-8b40-cff2ea93dd1f"
/>
2025-03-21 12:02:10 -07:00
Dinesh Yeduguru
6104bd06a0
feat: add different sinks for otel traces and metrics (#1731)
# What does this PR do?
Since we now start recording and exporting metrics, we no longer can use
single OTEL endpoint to export both traces and metrics. This PR adds two
sinks: OTEL_TRACE and OTEL_METRIC to be able to selectively enable the
exporters.

## Test Plan
Start server with OTEL_TRACE as sink and verify traces show up in jaeger
![Screenshot 2025-03-20 at 3 12
25 PM](https://github.com/user-attachments/assets/51007f28-b5ed-4853-912a-965a5cfe83af)
2025-03-20 15:51:41 -07:00
Ihar Hrachyshka
515c16e352
chore: mypy violations cleanup for inline::{telemetry,tool_runtime,vector_io} (#1711)
# What does this PR do?

Clean up mypy violations for inline::{telemetry,tool_runtime,vector_io}.
This also makes API accept a tool call result without any content (like
RAG tool already may produce).

Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
2025-03-20 10:01:10 -07:00
Sébastien Han
98b1b15e0f
refactor: move all datetime.now() calls to UTC (#1589)
# What does this PR do?

Updated all instances of datetime.now() to use timezone.utc for
consistency in handling time across different systems. This ensures that
timestamps are always in Coordinated Universal Time (UTC), avoiding
issues with time zone discrepancies and promoting uniformity in
time-related data.

Signed-off-by: Sébastien Han <seb@redhat.com>
2025-03-13 15:34:53 -07:00
Ashwin Bharambe
d072b5fa0c
test: add unit test to ensure all config types are instantiable (#1601) 2025-03-12 22:29:58 -07:00
Dinesh Yeduguru
58d08d100e
feat: Add back inference metrics and preserve context variables across asyncio boundary (#1552)
# What does this PR do?
This PR adds back the changes in #1300  which were reverted in  #1476 .

It also adds logic to preserve context variables across asyncio
boundary. this is needed with the library client since the async
generator logic yields control to code outside the event loop, and on
resuming, does not have the same context as before and this requires
preserving the context vars.

address #1477 
## Test Plan


```
 curl --request POST \
  --url http://localhost:8321/v1/inference/chat-completion \
  --header 'content-type: application/json' \
  --data '{
  "model_id": "meta-llama/Llama-3.1-70B-Instruct",
  "messages": [
    {
      "role": "user",
      "content": {
        "type": "text",
        "text": "where do humans live"
      }
    }
  ],
  "stream": false
}' | jq .

{
  "metrics": [
    {
      "trace_id": "kCZwO3tyQC-FuAGb",
      "span_id": "bsP_5a5O",
      "timestamp": "2025-03-11T16:47:38.549084Z",
      "attributes": {
        "model_id": "meta-llama/Llama-3.1-70B-Instruct",
        "provider_id": "fireworks"
      },
      "type": "metric",
      "metric": "prompt_tokens",
      "value": 10,
      "unit": "tokens"
    },
    {
      "trace_id": "kCZwO3tyQC-FuAGb",
      "span_id": "bsP_5a5O",
      "timestamp": "2025-03-11T16:47:38.549449Z",
      "attributes": {
        "model_id": "meta-llama/Llama-3.1-70B-Instruct",
        "provider_id": "fireworks"
      },
      "type": "metric",
      "metric": "completion_tokens",
      "value": 369,
      "unit": "tokens"
    },
    {
      "trace_id": "kCZwO3tyQC-FuAGb",
      "span_id": "bsP_5a5O",
      "timestamp": "2025-03-11T16:47:38.549457Z",
      "attributes": {
        "model_id": "meta-llama/Llama-3.1-70B-Instruct",
        "provider_id": "fireworks"
      },
      "type": "metric",
      "metric": "total_tokens",
      "value": 379,
      "unit": "tokens"
    }
  ],
  "completion_message": {
    "role": "assistant",
    "content": "Humans live on the planet Earth, specifically on its landmasses and in its oceans. Here's a breakdown of where humans live:\n\n1. **Continents:** Humans inhabit all seven continents:\n\t* Africa\n\t* Antarctica ( temporary residents, mostly scientists and researchers)\n\t* Asia\n\t* Australia\n\t* Europe\n\t* North America\n\t* South America\n2. **Countries:** There are 196 countries recognized by the United Nations, and humans live in almost all of them.\n3. **Cities and towns:** Many humans live in urban areas, such as cities and towns, which are often located near coastlines, rivers, or other bodies of water.\n4. **Rural areas:** Some humans live in rural areas, such as villages, farms, and countryside.\n5. **Islands:** Humans inhabit many islands around the world, including those in the Pacific, Indian, and Atlantic Oceans.\n6. **Mountains and highlands:** Humans live in mountainous regions, such as the Himalayas, the Andes, and the Rocky Mountains.\n7. **Deserts:** Some humans live in desert regions, such as the Sahara, the Mojave, and the Atacama.\n8. **Coastal areas:** Many humans live in coastal areas, such as beaches, ports, and coastal cities.\n9. **Underwater habitats:** A few humans live in underwater habitats, such as research stations and submarines.\n10. **Space:** A small number of humans have lived in space, including astronauts on the International Space Station and those who have visited the Moon.\n\nOverall, humans can be found living in almost every environment on Earth, from the frozen tundra to the hottest deserts, and from the highest mountains to the deepest oceans.",
    "stop_reason": "end_of_turn",
    "tool_calls": []
  },
  "logprobs": null
}

```

Orignal repro no longer showing any error:
```
LLAMA_STACK_DISABLE_VERSION_CHECK=true llama stack run ~/.llama/distributions/fireworks/fireworks-run.yaml
python -m examples.agents.e2e_loop_with_client_tools localhost 8321
```

client logs:
https://gist.github.com/dineshyv/047c7e87b18a5792aa660e311ea53166
server logs:
https://gist.github.com/dineshyv/97a2174099619e9916c7c490be26e559
2025-03-12 12:01:03 -07:00
Dinesh Yeduguru
60e7f3d705
fix: Revert "feat: record token usage for inference API (#1300)" (#1476)
This reverts commit b8535417e0.

Test plan:
LLAMA_STACK_DISABLE_VERSION_CHECK=true llama stack run
~/.llama/distributions/together/together-run.yaml
python -m examples.agents.e2e_loop_with_client_tools localhost 8321
2025-03-07 10:16:47 -08:00
Dinesh Yeduguru
b8535417e0
feat: record token usage for inference API (#1300)
# What does this PR do?
Inference router computes the token usage related metrics for all
providers and returns the metrics as part of response and also logs to
telemetry.

## Test Plan
LLAMA_STACK_DISABLE_VERSION_CHECK=true llama stack run
~/.llama/distributions/fireworks/fireworks-run.yaml

```
curl --request POST \
  --url http://localhost:8321/v1/inference/chat-completion \
  --header 'content-type: application/json' \
  --data '{
  "model_id": "meta-llama/Llama-3.1-70B-Instruct",
  "messages": [
    {
      "role": "user",
      "content": {
        "type": "text",
        "text": "where do humans live"
      }
    }
  ],
  "stream": false
}' | jq .
{
  "metrics": [
    {
      "trace_id": "yjv1tf0jS1evOyPm",
      "span_id": "WqYKvg0_",
      "timestamp": "2025-02-27T18:55:10.770903Z",
      "attributes": {
        "model_id": "meta-llama/Llama-3.1-70B-Instruct",
        "provider_id": "fireworks"
      },
      "type": "metric",
      "metric": "prompt_tokens",
      "value": 10,
      "unit": "tokens"
    },
    {
      "trace_id": "yjv1tf0jS1evOyPm",
      "span_id": "WqYKvg0_",
      "timestamp": "2025-02-27T18:55:10.770916Z",
      "attributes": {
        "model_id": "meta-llama/Llama-3.1-70B-Instruct",
        "provider_id": "fireworks"
      },
      "type": "metric",
      "metric": "completion_tokens",
      "value": 411,
      "unit": "tokens"
    },
    {
      "trace_id": "yjv1tf0jS1evOyPm",
      "span_id": "WqYKvg0_",
      "timestamp": "2025-02-27T18:55:10.770919Z",
      "attributes": {
        "model_id": "meta-llama/Llama-3.1-70B-Instruct",
        "provider_id": "fireworks"
      },
      "type": "metric",
      "metric": "total_tokens",
      "value": 421,
      "unit": "tokens"
    }
  ],
  "completion_message": {
    "role": "assistant",
    "content": "Humans live in various parts of the world, inhabiting almost every continent, country, and region. Here's a breakdown of where humans live:\n\n1. **Continents:** Humans inhabit all seven continents:\n\t* Africa\n\t* Antarctica (research stations only)\n\t* Asia\n\t* Australia\n\t* Europe\n\t* North America\n\t* South America\n2. **Countries:** There are 196 countries recognized by the United Nations, and humans live in almost all of them.\n3. **Regions:** Humans live in diverse regions, including:\n\t* Deserts (e.g., Sahara, Mojave)\n\t* Forests (e.g., Amazon, Congo)\n\t* Grasslands (e.g., Prairies, Steppes)\n\t* Mountains (e.g., Himalayas, Andes)\n\t* Oceans (e.g., coastal areas, islands)\n\t* Tundras (e.g., Arctic, sub-Arctic)\n4. **Cities and towns:** Many humans live in urban areas, such as cities and towns, which are often located near:\n\t* Coastlines\n\t* Rivers\n\t* Lakes\n\t* Mountains\n5. **Rural areas:** Some humans live in rural areas, such as:\n\t* Villages\n\t* Farms\n\t* Countryside\n6. **Islands:** Humans inhabit many islands, including:\n\t* Tropical islands (e.g., Hawaii, Maldives)\n\t* Arctic islands (e.g., Greenland, Iceland)\n\t* Continental islands (e.g., Great Britain, Ireland)\n7. **Extreme environments:** Humans also live in extreme environments, such as:\n\t* High-altitude areas (e.g., Tibet, Andes)\n\t* Low-altitude areas (e.g., Death Valley, Dead Sea)\n\t* Areas with extreme temperatures (e.g., Arctic, Sahara)\n\nOverall, humans have adapted to live in a wide range of environments and ecosystems around the world.",
    "stop_reason": "end_of_turn",
    "tool_calls": []
  },
  "logprobs": null
}
```

```
 LLAMA_STACK_CONFIG=fireworks pytest -s -v tests/integration/inference

======================================================================== short test summary info =========================================================================
FAILED tests/integration/inference/test_text_inference.py::test_text_chat_completion_tool_calling_tools_not_in_request[txt=8B:vis=11B-inference:chat_completion:tool_calling_tools_absent-True] - ValueError: Unsupported tool prompt format: ToolPromptFormat.json
FAILED tests/integration/inference/test_text_inference.py::test_text_chat_completion_tool_calling_tools_not_in_request[txt=8B:vis=11B-inference:chat_completion:tool_calling_tools_absent-False] - ValueError: Unsupported tool prompt format: ToolPromptFormat.json
FAILED tests/integration/inference/test_vision_inference.py::test_image_chat_completion_non_streaming[txt=8B:vis=11B] - fireworks.client.error.InvalidRequestError: {'error': {'object': 'error', 'type': 'invalid_request_error', 'message': 'Failed to decode image cannot identify image f...
FAILED tests/integration/inference/test_vision_inference.py::test_image_chat_completion_streaming[txt=8B:vis=11B] - fireworks.client.error.InvalidRequestError: {'error': {'object': 'error', 'type': 'invalid_request_error', 'message': 'Failed to decode image cannot identify image f...
========================================================= 4 failed, 16 passed, 23 xfailed, 17 warnings in 44.36s =========================================================
```
2025-03-05 12:41:45 -08:00
Ashwin Bharambe
dd0db8038b
refactor(test): unify vector_io tests and make them configurable (#1398)
## Test Plan


`LLAMA_STACK_CONFIG=inference=sentence-transformers,vector_io=sqlite-vec
pytest -s -v test_vector_io.py --embedding-model all-miniLM-L6-V2
--inference-model='' --vision-inference-model=''`

```
test_vector_io.py::test_vector_db_retrieve[txt=:vis=:emb=all-miniLM-L6-V2] PASSED
test_vector_io.py::test_vector_db_register[txt=:vis=:emb=all-miniLM-L6-V2] PASSED
test_vector_io.py::test_insert_chunks[txt=:vis=:emb=all-miniLM-L6-V2-test_case0] PASSED
test_vector_io.py::test_insert_chunks[txt=:vis=:emb=all-miniLM-L6-V2-test_case1] PASSED
test_vector_io.py::test_insert_chunks[txt=:vis=:emb=all-miniLM-L6-V2-test_case2] PASSED
test_vector_io.py::test_insert_chunks[txt=:vis=:emb=all-miniLM-L6-V2-test_case3] PASSED
test_vector_io.py::test_insert_chunks[txt=:vis=:emb=all-miniLM-L6-V2-test_case4] PASSED
```

Same thing with:
- LLAMA_STACK_CONFIG=inference=sentence-transformers,vector_io=faiss
- LLAMA_STACK_CONFIG=fireworks

(Note that ergonomics will soon be improved re: cmd-line options and env
variables)
2025-03-04 13:37:45 -08:00
ehhuang
2faee24873
chore: better raise (#1335)
Summary:
addresses
https://github.com/meta-llama/llama-stack/pull/1282#discussion_r1972546802

Test Plan:
2025-02-28 16:41:20 -08:00
ehhuang
270d64007a
fix: sqlite conn (#1282)
# Summary:
Our tests sometimes error out with
```
========================== 11 passed, 342 warnings in 58.86s ==========================
Error exporting span to SQLite: Cannot operate on a closed database.
Fatal Python error: _enter_buffered_busy: could not acquire lock for <_io.BufferedWriter name='<stdout>'> at interpreter shutdown, possibly due to daemon threads
Python runtime state: finalizing (tstate=0x000000012af04280)

Current thread 0x00000001fa29c240 (most recent call first):
  <no Python frame>
```
Usually able to repro this by running 10 times.

The proposed fix is to use threadsafe var for creating sqlite connection
to ensure connection is only used by one thread. Not 100% if this is the
fix, but am not able to repro with this.

# Test Plan:
Run 10 times and saw no more errors
```
for i in {1..10}; do
  echo "=== Starting Run $i ==="
  LLAMA_STACK_CONFIG=fireworks pytest -s -v tests/client-sdk/agents/test_agents.py --safety-shield meta-llama/Llama-Guard-3-8B
  if [[ $? -ne 0 ]]; then
    echo "=== Run $i FAILED with exit code $? ==="
    break
  else
    echo "=== Run $i PASSED ==="
  fi
  echo
done
```
2025-02-26 14:44:31 -08:00
Sébastien Han
e4a1579e63
build: format codebase imports using ruff linter (#1028)
# What does this PR do?

- Configured ruff linter to automatically fix import sorting issues.
- Set --exit-non-zero-on-fix to ensure non-zero exit code when fixes are
applied.
- Enabled the 'I' selection to focus on import-related linting rules.
- Ran the linter, and formatted all codebase imports accordingly.
- Removed the black dep from the "dev" group since we use ruff

Signed-off-by: Sébastien Han <seb@redhat.com>

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
[Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.*]

[//]: # (## Documentation)
[//]: # (- [ ] Added a Changelog entry if the change is significant)

Signed-off-by: Sébastien Han <seb@redhat.com>
2025-02-13 10:06:21 -08:00
Yuan Tang
34ab7a3b6c
Fix precommit check after moving to ruff (#927)
Lint check in main branch is failing. This fixes the lint check after we
moved to ruff in https://github.com/meta-llama/llama-stack/pull/921. We
need to move to a `ruff.toml` file as well as fixing and ignoring some
additional checks.

Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
2025-02-02 06:46:45 -08:00
Dinesh Yeduguru
3c1a2c3d66
Fix telemetry init (#885)
# What does this PR do?

When you re-initialize the library client in a notebook, we were seeing
this error:
```
Getting traces for session_id=5c8d1969-0957-49d2-b852-32cbb8ef8caf
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
[<ipython-input-11-d74bb6cdd3ab>](https://localhost:8080/#) in <cell line: 0>()
      7 agent_logs = []
      8 
----> 9 for span in client.telemetry.query_spans(
     10     attribute_filters=[
     11         {"key": "session_id", "op": "eq", "value": session_id},

10 frames
[/usr/local/lib/python3.11/dist-packages/llama_stack/providers/inline/telemetry/meta_reference/telemetry.py](https://localhost:8080/#) in query_traces(self, attribute_filters, limit, offset, order_by)
    246     ) -> QueryTracesResponse:
    247         return QueryTracesResponse(
--> 248             data=await self.trace_store.query_traces(
    249                 attribute_filters=attribute_filters,
    250                 limit=limit,

AttributeError: 'TelemetryAdapter' object has no attribute 'trace_store'
```

This is happening because the we were skipping some required steps for
the object state as part of the global _TRACE_PROVIDER check. This PR
moves the initialization of the object state out of the TRACE_PROVIDER
init.
2025-01-27 11:20:28 -08:00
Ashwin Bharambe
eb60f04f86
optional api dependencies (#793)
Co-authored-by: Dinesh Yeduguru <yvdinesh@gmail.com>
2025-01-17 15:26:53 -08:00
Dinesh Yeduguru
59eeaf7f81
Idiomatic REST API: Telemetry (#786)
# What does this PR do?

Changes Telemetry API to follow more idiomatic REST


- [ ] Addresses issue (#issue)


## Test Plan

TBD, once i get an approval for rest endpoints
2025-01-16 12:08:46 -08:00
Dinesh Yeduguru
7fb2c1c48d
More idiomatic REST API (#765)
# What does this PR do?

This PR changes our API to follow more idiomatic REST API approaches of
having paths being resources and methods indicating the action being
performed.

Changes made to generator:
1) removed the prefix check of "get" as its not required and is actually
needed for other method types too
2) removed _ check on path since variables can have "_"



## Test Plan

LLAMA_STACK_BASE_URL=http://localhost:5000 pytest -v
tests/client-sdk/agents/test_agents.py
2025-01-15 13:20:09 -08:00
Dinesh Yeduguru
a174938fbd
Fix telemetry to work on reinstantiating new lib cli (#761)
# What does this PR do?

Since we maintain global state in our telemetry pipeline,
reinstantiating lib cli will cause us to add duplicate span processors
causing sqlite to lock out because of constraint violations since we now
have two span processor writing to sqlite. This PR changes the telemetry
adapter for otel to only instantiate the provider once and add the span
processsors only once.

Also fixes an issue llama stack build


## Test Plan

tested with notebook at
https://colab.research.google.com/drive/1ck7hXQxRl6UvT-ijNRZ-gMZxH1G3cN2d#scrollTo=9496f75c
2025-01-14 11:31:50 -08:00
Ashwin Bharambe
21357a6dee Kill autocomplete slop 2025-01-03 09:29:25 -08:00
Xi Yan
3c72c034e6
[remove import *] clean up import *'s (#689)
# What does this PR do?

- as title, cleaning up `import *`'s
- upgrade tests to make them more robust to bad model outputs
- remove import *'s in llama_stack/apis/* (skip __init__ modules)
<img width="465" alt="image"
src="https://github.com/user-attachments/assets/d8339c13-3b40-4ba5-9c53-0d2329726ee2"
/>

- run `sh run_openapi_generator.sh`, no types gets affected

## Test Plan

### Providers Tests

**agents**
```
pytest -v -s llama_stack/providers/tests/agents/test_agents.py -m "together" --safety-shield meta-llama/Llama-Guard-3-8B --inference-model meta-llama/Llama-3.1-405B-Instruct-FP8
```

**inference**
```bash
# meta-reference
torchrun $CONDA_PREFIX/bin/pytest -v -s -k "meta_reference" --inference-model="meta-llama/Llama-3.1-8B-Instruct" ./llama_stack/providers/tests/inference/test_text_inference.py
torchrun $CONDA_PREFIX/bin/pytest -v -s -k "meta_reference" --inference-model="meta-llama/Llama-3.2-11B-Vision-Instruct" ./llama_stack/providers/tests/inference/test_vision_inference.py

# together
pytest -v -s -k "together" --inference-model="meta-llama/Llama-3.1-8B-Instruct" ./llama_stack/providers/tests/inference/test_text_inference.py
pytest -v -s -k "together" --inference-model="meta-llama/Llama-3.2-11B-Vision-Instruct" ./llama_stack/providers/tests/inference/test_vision_inference.py

pytest ./llama_stack/providers/tests/inference/test_prompt_adapter.py 
```

**safety**
```
pytest -v -s llama_stack/providers/tests/safety/test_safety.py -m together --safety-shield meta-llama/Llama-Guard-3-8B
```

**memory**
```
pytest -v -s llama_stack/providers/tests/memory/test_memory.py -m "sentence_transformers" --env EMBEDDING_DIMENSION=384
```

**scoring**
```
pytest -v -s -m llm_as_judge_scoring_together_inference llama_stack/providers/tests/scoring/test_scoring.py --judge-model meta-llama/Llama-3.2-3B-Instruct
pytest -v -s -m basic_scoring_together_inference llama_stack/providers/tests/scoring/test_scoring.py
pytest -v -s -m braintrust_scoring_together_inference llama_stack/providers/tests/scoring/test_scoring.py
```


**datasetio**
```
pytest -v -s -m localfs llama_stack/providers/tests/datasetio/test_datasetio.py
pytest -v -s -m huggingface llama_stack/providers/tests/datasetio/test_datasetio.py
```


**eval**
```
pytest -v -s -m meta_reference_eval_together_inference llama_stack/providers/tests/eval/test_eval.py
pytest -v -s -m meta_reference_eval_together_inference_huggingface_datasetio llama_stack/providers/tests/eval/test_eval.py
```

### Client-SDK Tests
```
LLAMA_STACK_BASE_URL=http://localhost:5000 pytest -v ./tests/client-sdk
```

### llama-stack-apps
```
PORT=5000
LOCALHOST=localhost

python -m examples.agents.hello $LOCALHOST $PORT
python -m examples.agents.inflation $LOCALHOST $PORT
python -m examples.agents.podcast_transcript $LOCALHOST $PORT
python -m examples.agents.rag_as_attachments $LOCALHOST $PORT
python -m examples.agents.rag_with_memory_bank $LOCALHOST $PORT
python -m examples.safety.llama_guard_demo_mm $LOCALHOST $PORT
python -m examples.agents.e2e_loop_with_custom_tools $LOCALHOST $PORT

# Vision model
python -m examples.interior_design_assistant.app
python -m examples.agent_store.app $LOCALHOST $PORT
```

### CLI
```
which llama
llama model prompt-format -m Llama3.2-11B-Vision-Instruct
llama model list
llama stack list-apis
llama stack list-providers inference

llama stack build --template ollama --image-type conda
```

### Distributions Tests
**ollama**
```
llama stack build --template ollama --image-type conda
ollama run llama3.2:1b-instruct-fp16
llama stack run ./llama_stack/templates/ollama/run.yaml --env INFERENCE_MODEL=meta-llama/Llama-3.2-1B-Instruct
```

**fireworks**
```
llama stack build --template fireworks --image-type conda
llama stack run ./llama_stack/templates/fireworks/run.yaml
```

**together**
```
llama stack build --template together --image-type conda
llama stack run ./llama_stack/templates/together/run.yaml
```

**tgi**
```
llama stack run ./llama_stack/templates/tgi/run.yaml --env TGI_URL=http://0.0.0.0:5009 --env INFERENCE_MODEL=meta-llama/Llama-3.1-8B-Instruct
```

## Sources

Please link relevant resources if necessary.


## Before submitting

- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Ran pre-commit to handle lint / formatting issues.
- [ ] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
      Pull Request section?
- [ ] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.
2024-12-27 15:45:44 -08:00
Ashwin Bharambe
2e5bfcd42a
Update Telemetry API so OpenAPI generation can work (#640)
We cannot use recursive types because not only does our OpenAPI
generator not like them, even if it did, it is not easy for all client
languages to automatically construct proper APIs (especially considering
garbage collection) around them. For now, we can return a `Dict[str,
SpanWithStatus]` instead of `SpanWithChildren` and rely on the client to
reconstruct the tree.

Also fixed a super subtle issue with the OpenAPI generation process
(monkey-patching of json_schema_type wasn't working because of import
reordering.)
2024-12-16 13:00:14 -08:00
Dinesh Yeduguru
e128f2547a
add tracing back to the lib cli (#595)
Adds back all the tracing logic removed from library client. also adds
back the logging to agent_instance.
2024-12-11 08:44:20 -08:00
Dinesh Yeduguru
2e3d3a62a5 Revert "add tracing to library client (#591)"
This reverts commit bc1fddf1df.
2024-12-10 08:50:20 -08:00
Dinesh Yeduguru
bc1fddf1df
add tracing to library client (#591) 2024-12-09 15:46:26 -08:00
Ashwin Bharambe
e951852848 Miscellaneous fixes around telemetry, library client and run yaml autogen
Also add a `venv` image-type for llama stack build
2024-12-08 20:40:22 -08:00
Ashwin Bharambe
224e62290f kill unnecessarily large imports from telemetry init 2024-12-08 16:57:16 -08:00
Dinesh Yeduguru
c543bc0745
Console span processor improvements (#577)
Makes the console span processor output spans in less prominent way and
highlight the logs based on severity.


![Screenshot 2024-12-06 at 11 26
46 AM](https://github.com/user-attachments/assets/c3a1b051-85db-4b71-b7a5-7bab5a26f072)
2024-12-06 11:46:16 -08:00
Ashwin Bharambe
084ec337af Small cleanup of console logs 2024-12-06 10:29:24 -08:00
Adrian Cole
27a27152cd
Renames otel config from jaeger to otel (#569)
# What does this PR do?

#525 introduced a telemetry configuration named jaeger, but what it
really is pointing to is an OTLP HTTP endpoint which is supported by
most servers in the ecosystem, including raw opentelemetry collectors,
several APMs, and even https://github.com/ymtdzzz/otel-tui

I chose to rename this to "otel" as it will bring in more people to the
ecosystem vs feeling it only works with jaeger. Later, we can use the
[standard
ENV](https://opentelemetry.io/docs/specs/otel/protocol/exporter/) to
configure this if we like so that you can override things with variables
people might expect.

Note: I also added to the README that you have to install conda.
Depending on experience level of the user, and especially with miniforge
vs other ways, I felt this helps.

## Test Plan

I would like to test this, but actually got a little lost. The previous
PRs referenced yaml which doesn't seem published anywhere. It would be
nice to have a pre-canned setup that uses ollama and turns on otel, but
would also appreciate a hand on instructions meanwhile.

## Sources

https://github.com/meta-llama/llama-stack/pull/525

## Before submitting

- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] Ran pre-commit to handle lint / formatting issues.
- [x] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
      Pull Request section?
- [ ] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.

---------

Signed-off-by: Adrian Cole <adrian.cole@elastic.co>
2024-12-06 10:16:42 -08:00
Ashwin Bharambe
392be5f6dc Reduce log volume a bit, needs more work 2024-12-05 21:40:21 -08:00
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