Commit graph

22 commits

Author SHA1 Message Date
Ashwin Bharambe
81ce39a607
feat(api): Add options for supporting various embedding models (#1192)
We need to support:
- asymmetric embedding models (#934)
- truncation policies (#933)
- varying dimensional output (#932) 

## Test Plan

```bash
$ cd llama_stack/providers/tests/inference
$ pytest -s -v -k fireworks test_embeddings.py \
   --inference-model nomic-ai/nomic-embed-text-v1.5 --env EMBEDDING_DIMENSION=784
$  pytest -s -v -k together test_embeddings.py \
   --inference-model togethercomputer/m2-bert-80M-8k-retrieval --env EMBEDDING_DIMENSION=784
$ pytest -s -v -k ollama test_embeddings.py \
   --inference-model all-minilm:latest --env EMBEDDING_DIMENSION=784
```
2025-02-20 22:27:12 -08:00
Ashwin Bharambe
6f9d622340
fix(api): update embeddings signature so inputs and outputs list align (#1161)
See Issue #922 

The change is slightly backwards incompatible but no callsite (in our
client codebases or stack-apps) every passes a depth-2
`List[List[InterleavedContentItem]]` (which is now disallowed.)

## Test Plan

```bash
$ cd llama_stack/providers/tests/inference
$ pytest -s -v -k fireworks test_embeddings.py \
   --inference-model nomic-ai/nomic-embed-text-v1.5 --env EMBEDDING_DIMENSION=784
$  pytest -s -v -k together test_embeddings.py \
   --inference-model togethercomputer/m2-bert-80M-8k-retrieval --env EMBEDDING_DIMENSION=784
$ pytest -s -v -k ollama test_embeddings.py \
   --inference-model all-minilm:latest --env EMBEDDING_DIMENSION=784
```

Also ran `tests/client-sdk/inference/test_embeddings.py`
2025-02-20 21:43:13 -08:00
Ashwin Bharambe
07ccf908f7 ModelAlias -> ProviderModelEntry 2025-02-20 14:02:36 -08:00
Ashwin Bharambe
cdcbeb005b
chore: remove llama_models.llama3.api imports from providers (#1107)
There should be a choke-point for llama3.api imports -- this is the
prompt adapter. Creating a ChatFormat() object on demand is inexpensive.
The underlying Tokenizer is a singleton anyway.
2025-02-19 19:01:29 -08:00
Ben Browning
e9b8259cf9
fix: Get distro_codegen.py working with default deps and enabled in pre-commit hooks (#1123)
# What does this PR do?

Before this change, `distro_codegen.py` would only work if the user
manually installed multiple provider-specific dependencies (see #1122).
Now, users can run `distro_codegen.py` without any provider-specific
dependencies because we avoid importing the entire provider
implementations just to get the config needed to build the provider
template.

Concretely, this mostly means moving the
MODEL_ALIASES (and related variants) definitions to a new models.py
class within the provider implementation for those providers that
require additional dependencies. It also meant moving a couple of
imports from top-level imports to inside `get_adapter_impl` for some
providers, which follows the pattern used by multiple existing
providers.

To ensure we don't regress and accidentally add new imports that cause
distro_codegen.py to fail, the stubbed-in pre-commit hook for
distro_codegen.py was uncommented and slightly tweaked to run via `uv
run python ...` to ensure it runs with only the project's default
dependencies and to run automatically instead of manually.

Lastly, this updates distro_codegen.py itself to keep track of paths it
might have changed and to only `git diff` those specific paths when
checking for changed files instead of doing a diff on the entire working
tree. The latter was overly broad and would require a user have no other
unstaged changes in their working tree, even if those unstaged changes
were unrelated to generated code. Now it only flags uncommitted changes
for paths distro_codegen.py actually writes to.

Our generated code was also out-of-date, presumably because of these
issues, so this commit also has some updates to the generated code
purely because it was out of sync, and the pre-commit hook now enforces
things to be updated.

(Closes #1122)

## Test Plan

I manually tested distro_codegen.py and the pre-commit hook to verify
those work as expected, flagging any uncommited changes and catching any
imports that attempt to pull in provider-specific dependencies.

However, I do not have valid api keys to the impacted provider
implementations, and am unable to easily run the inference tests against
each changed provider. There are no functional changes to the provider
implementations here, but I'd appreciate a second set of eyes on the
changed import statements and moving of MODEL_ALIASES type code to a
separate models.py to ensure I didn't make any obvious errors.

---------

Signed-off-by: Ben Browning <bbrownin@redhat.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
2025-02-19 18:39:20 -08:00
Ashwin Bharambe
314ee09ae3
chore: move all Llama Stack types from llama-models to llama-stack (#1098)
llama-models should have extremely minimal cruft. Its sole purpose
should be didactic -- show the simplest implementation of the llama
models and document the prompt formats, etc.

This PR is the complement to
https://github.com/meta-llama/llama-models/pull/279

## Test Plan

Ensure all `llama` CLI `model` sub-commands work:

```bash
llama model list
llama model download --model-id ...
llama model prompt-format -m ...
```

Ran tests:
```bash
cd tests/client-sdk
LLAMA_STACK_CONFIG=fireworks pytest -s -v inference/
LLAMA_STACK_CONFIG=fireworks pytest -s -v vector_io/
LLAMA_STACK_CONFIG=fireworks pytest -s -v agents/
```

Create a fresh venv `uv venv && source .venv/bin/activate` and run
`llama stack build --template fireworks --image-type venv` followed by
`llama stack run together --image-type venv` <-- the server runs

Also checked that the OpenAPI generator can run and there is no change
in the generated files as a result.

```bash
cd docs/openapi_generator
sh run_openapi_generator.sh
```
2025-02-14 09:10:59 -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
Xi Yan
66d7e15c93
perf: ensure ToolCall in ChatCompletionResponse is subset of ChatCompletionRequest.tools (#1041)
# What does this PR do?

**Problem**
- Using script:
https://gist.github.com/thoraxe/6163b2145ce7b1c24c6026b64cf90085

- This hits an issue on server with `code_interpreter` not found, as we
do not pass "builtin::code_interpreter" in AgentConfig's `toolgroups`.

This is a general issue where model always tries to output
`code_interpreter` in `ToolCall` even when we do not have
`code_interpreter` available for execution.

**Reproduce Deeper Problem in chat-completion**
- Use script:
https://gist.github.com/yanxi0830/163a9ad7b5db10556043fbfc7ecd7603

1. We currently always populate `code_interpreter` in `ToolCall` in
ChatCompletionResponse if the model's response begins with
`<|python_tag|>`. See
c5f5958498/models/llama3/api/chat_format.py (L200-L213)

<img width="913" alt="image"
src="https://github.com/user-attachments/assets/328d313d-0a0b-495c-8715-61cca9ccc4a6"
/>

2. This happens even if we do not pass the `code_interpreter` as a
`tools` in ChatCompletionRequest.

**This PR**

Explicitly make sure that the tools returned in
`ChatCompletionResponse.tool_calls` is always a tool requested by
`ChatCompletionRequest.tools`.

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

## Test Plan

**Before**
<img width="913" alt="image"
src="https://github.com/user-attachments/assets/328d313d-0a0b-495c-8715-61cca9ccc4a6"
/>
<img width="997" alt="image"
src="https://github.com/user-attachments/assets/d3e82b62-b142-4939-954c-62843bec7110"
/>


**After**
<img width="856" alt="image"
src="https://github.com/user-attachments/assets/2c70ce55-c8d0-45ea-b10f-f70adc50d3d9"
/>
<img width="1000" alt="image"
src="https://github.com/user-attachments/assets/b5e81826-c35b-4052-bf81-7afff93ce2ef"
/>



**Unit Test**
```
LLAMA_STACK_BASE_URL=http://localhost:8321 pytest -v tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_tool_calling_tools_not_in_request --inference-model "meta-llama/Llama-3.3-70B-Instruct"
```

```
LLAMA_STACK_BASE_URL=http://localhost:8321 pytest -v tests/client-sdk/agents/
```
<img width="1002" alt="image"
src="https://github.com/user-attachments/assets/04808517-eded-4122-97f5-7e5142de9779"
/>



**Streaming**
- Chat Completion
<img width="902" alt="image"
src="https://github.com/user-attachments/assets/f477bc86-bd38-4729-b49e-a0a6ed3f835a"
/>

- Agent
<img width="916" alt="image"
src="https://github.com/user-attachments/assets/f4cc3417-23cd-46b1-953d-3a2271e79bbb"
/>


[//]: # (## Documentation)
[//]: # (- [ ] Added a Changelog entry if the change is significant)
2025-02-11 18:31:35 -08:00
ehhuang
c9ab72fa82
Support sys_prompt behavior in inference (#937)
# What does this PR do?

The current default system prompt for llama3.2 tends to overindex on
tool calling and doesn't work well when the prompt does not require tool
calling.

This PR adds an option to override the default system prompt, and
organizes tool-related configs into a new config object.

- [ ] Addresses issue (#issue)


## Test Plan

python -m unittest
llama_stack.providers.tests.inference.test_prompt_adapter


## 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.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with
[ReviewStack](https://reviewstack.dev/meta-llama/llama-stack/pull/937).
* #938
* __->__ #937
2025-02-03 23:35:16 -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
Hardik Shah
a51c8b4efc
Convert SamplingParams.strategy to a union (#767)
# What does this PR do?

Cleans up how we provide sampling params. Earlier, strategy was an enum
and all params (top_p, temperature, top_k) across all strategies were
grouped. We now have a strategy union object with each strategy (greedy,
top_p, top_k) having its corresponding params.
Earlier, 
```
class SamplingParams: 
    strategy: enum ()
    top_p, temperature, top_k and other params
```
However, the `strategy` field was not being used in any providers making
it confusing to know the exact sampling behavior purely based on the
params since you could pass temperature, top_p, top_k and how the
provider would interpret those would not be clear.

Hence we introduced -- a union where the strategy and relevant params
are all clubbed together to avoid this confusion.

Have updated all providers, tests, notebooks, readme and otehr places
where sampling params was being used to use the new format.
   

## Test Plan
`pytest llama_stack/providers/tests/inference/groq/test_groq_utils.py`
// inference on ollama, fireworks and together 
`with-proxy pytest -v -s -k "ollama"
--inference-model="meta-llama/Llama-3.1-8B-Instruct"
llama_stack/providers/tests/inference/test_text_inference.py `
// agents on fireworks 
`pytest -v -s -k 'fireworks and create_agent'
--inference-model="meta-llama/Llama-3.1-8B-Instruct"
llama_stack/providers/tests/agents/test_agents.py
--safety-shield="meta-llama/Llama-Guard-3-8B"`

## 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?
- [X] Updated relevant documentation.
- [X] Wrote necessary unit or integration tests.

---------

Co-authored-by: Hardik Shah <hjshah@fb.com>
2025-01-15 05:38:51 -08:00
Dinesh Yeduguru
8af6951106
remove conflicting default for tool prompt format in chat completion (#742)
# What does this PR do?
We are setting a default value of json for tool prompt format, which
conflicts with llama 3.2/3.3 models since they use python list. This PR
changes the defaults to None and in the code, we infer default based on
the model.

Addresses: #695 

Tests:
❯ LLAMA_STACK_BASE_URL=http://localhost:5000 pytest -v
tests/client-sdk/inference/test_inference.py -k
"test_text_chat_completion"

 pytest llama_stack/providers/tests/inference/test_prompt_adapter.py
2025-01-10 10:41:53 -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
ceadaf1840 Dont include 3B / 1B models for bedrock since they arent ondemand 2024-12-18 06:30:02 -08:00
Ashwin Bharambe
c39a3777b5 Make bedrock "just" work 2024-12-18 06:22:33 -08:00
Ashwin Bharambe
8de8eb03c8
Update the "InterleavedTextMedia" type (#635)
## What does this PR do?

This is a long-pending change and particularly important to get done
now.

Specifically:
- we cannot "localize" (aka download) any URLs from media attachments
anywhere near our modeling code. it must be done within llama-stack.
- `PIL.Image` is infesting all our APIs via `ImageMedia ->
InterleavedTextMedia` and that cannot be right at all. Anything in the
API surface must be "naturally serializable". We need a standard `{
type: "image", image_url: "<...>" }` which is more extensible
- `UserMessage`, `SystemMessage`, etc. are moved completely to
llama-stack from the llama-models repository.

See https://github.com/meta-llama/llama-models/pull/244 for the
corresponding PR in llama-models.

## Test Plan

```bash
cd llama_stack/providers/tests

pytest -s -v -k "fireworks or ollama or together" inference/test_vision_inference.py
pytest -s -v -k "(fireworks or ollama or together) and llama_3b" inference/test_text_inference.py
pytest -s -v -k chroma memory/test_memory.py \
  --env EMBEDDING_DIMENSION=384 --env CHROMA_DB_PATH=/tmp/foobar

pytest -s -v -k fireworks agents/test_agents.py  \
   --safety-shield=meta-llama/Llama-Guard-3-8B \
   --inference-model=meta-llama/Llama-3.1-8B-Instruct
```

Updated the client sdk (see PR ...), installed the SDK in the same
environment and then ran the SDK tests:

```bash
cd tests/client-sdk
LLAMA_STACK_CONFIG=together pytest -s -v agents/test_agents.py
LLAMA_STACK_CONFIG=ollama pytest -s -v memory/test_memory.py

# this one needed a bit of hacking in the run.yaml to ensure I could register the vision model correctly
INFERENCE_MODEL=llama3.2-vision:latest LLAMA_STACK_CONFIG=ollama pytest -s -v inference/test_inference.py
```
2024-12-17 11:18:31 -08:00
Xi Yan
99f331f5c8
[bugfix] no shield_call when there's no shields configured (#642)
# What does this PR do?

**Why**
- When AgentConfig has no `input_shields` / `output_shields` defined, we
still outputs a shield_call step with violation=None. This is impossible
to distinguish the case b/w (1) no violation from running shields v.s.
(2) no shields call

**What**
- We should not have a shield_call step when no `input_shields` /
`output_shields` are defined.

- Also removes a never reached try/catch code block in agent loop.
`run_multiple_shields` is never called in the try block (verified by
stacktrace print)

**Side Note**
- pre-commit fix

## Test Plan

Tested w/ DirectClient via:
https://gist.github.com/yanxi0830/b48f2a53b6f5391b9ff1e39992bc05b3

**No Shields**
<img width="858" alt="image"
src="https://github.com/user-attachments/assets/67319370-329f-4954-bd16-d21ce54c6ebf"
/>

**With Input + Output Shields**
<img width="854" alt="image"
src="https://github.com/user-attachments/assets/75ab1bee-3ba9-4549-ab51-23210be83da7"
/>

**Input Shields Only**
<img width="858" alt="image"
src="https://github.com/user-attachments/assets/1897206b-13dd-4ea5-92c2-b39bf68e9286"
/>


E2E pytest
```
LLAMA_STACK_BASE_URL=http://localhost:5000 pytest -v ./tests/client-sdk/agents/test_agents.py
```

## 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.
2024-12-17 11:10:19 -08:00
Ashwin Bharambe
c2f7905fa4 Fix bedrock inference impl 2024-12-16 14:22:34 -08:00
Dinesh Yeduguru
96e158eaac
Make embedding generation go through inference (#606)
This PR does the following:
1) adds the ability to generate embeddings in all supported inference
providers.
2) Moves all the memory providers to use the inference API and improved
the memory tests to setup the inference stack correctly and use the
embedding models

This is a merge from #589 and #598
2024-12-12 11:47:50 -08:00
Dinesh Yeduguru
fdff24e77a
Inference to use provider resource id to register and validate (#428)
This PR changes the way model id gets translated to the final model name
that gets passed through the provider.
Major changes include:
1) Providers are responsible for registering an object and as part of
the registration returning the object with the correct provider specific
name of the model provider_resource_id
2) To help with the common look ups different names a new ModelLookup
class is created.



Tested all inference providers including together, fireworks, vllm,
ollama, meta reference and bedrock
2024-11-12 20:02:00 -08:00
Dinesh Yeduguru
d800a16acd
Resource oriented design for shields (#399)
* init

* working bedrock tests

* bedrock test for inference fixes

* use env vars for bedrock guardrail vars

* add register in meta reference

* use correct shield impl in meta ref

* dont add together fixture

* right naming

* minor updates

* improved registration flow

* address feedback

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Co-authored-by: Dinesh Yeduguru <dineshyv@fb.com>
2024-11-08 12:16:11 -08:00
Ashwin Bharambe
994732e2e0
impls -> inline, adapters -> remote (#381) 2024-11-06 14:54:05 -08:00
Renamed from llama_stack/providers/adapters/inference/bedrock/bedrock.py (Browse further)