10 commits

Author	SHA1	Message	Date
Hardik Shah	985d0b156c	feat: Add suffix to openai_completions (#2449) ... For code completion apps need "fill in the middle" capabilities. Added option of `suffix` to `openai_completion` to enable this. Updated ollama provider to showcase the same. ### Test Plan ``` pytest -sv --stack-config="inference=ollama" tests/integration/inference/test_openai_completion.py --text-model qwen2.5-coder:1.5b -k test_openai_completion_non_streaming_suffix ``` ### OpenAI Sample script ``` from openai import OpenAI client = OpenAI(base_url="http://localhost:8321/v1/openai/v1") response = client.completions.create( model="qwen2.5-coder:1.5b", prompt="The capital of ", suffix="is Paris.", max_tokens=10, ) print(response.choices[0].text) ``` ### Output ``` France is ____. To answer this question, we ```	2025-06-13 16:06:06 -07:00
Ben Browning	ee57e58f29	fix: loosen tool call checks in inference store (#2420) ... # What does this PR do? This loosens up the tool call function name and arguments checks in `tests/integration/inference/test_openai_completion.py::test_inference_store_tool_calls` because the small models we use in CI cannot reliably get the tool call function name or arguments exactly right. Closes #2345 ## Test Plan I ran this flaking test in a loop, let it run many dozens of times, and didn't observe any flakes after the changes. Previously it flaked quite regularly. ``` while uv run pytest -s -v \ 'tests/integration/inference/test_openai_completion.py::test_inference_store_tool_calls[llama_stack_client-txt=3B-False]' \ --stack-config=http://localhost:8321 \ --text-model="meta-llama/Llama-3.2-3B-Instruct" \ --embedding-model=all-MiniLM-L6-v2; do; sleep 0.1; done ``` Signed-off-by: Ben Browning <bbrownin@redhat.com>	2025-06-10 14:45:55 +02:00
ehhuang	2603f10f95	feat: support postgresql inference store (#2310) ... # What does this PR do? * Added support postgresql inference store * Added 'oracle' template that demos how to config postgresql stores (except for telemetry, which is not supported currently) ## Test Plan llama stack build --template oracle --image-type conda --run LLAMA_STACK_CONFIG=http://localhost:8321 pytest -s -v tests/integration/ --text-model accounts/fireworks/models/llama-v3p3-70b-instruct -k 'inference_store'	2025-05-29 14:33:09 -07:00
ehhuang	0b695538af	fix: chat completion with more than one choice (#2288) ... # What does this PR do? Fix a bug in openai_compat where choices are not indexed correctly. ## Test Plan Added a new test. Rerun the failed inference_store tests: llama stack run fireworks --image-type conda pytest -s -v tests/integration/ --stack-config http://localhost:8321 -k 'test_inference_store' --text-model meta-llama/Llama-3.3-70B-Instruct --count 10	2025-05-27 15:39:15 -07:00
Ashwin Bharambe	7504c2f430	test: disable test_inference_store test urrrggg (#2273)	2025-05-26 22:48:41 -07:00
Ashwin Bharambe	66f09f24ed	fix: disable test_responses_store (#2244) ... The test depends on llama's tool calling ability. In the CI, we run with a small ollama model. The fix might be to check for either message or function_call because the model is flaky and we aren't really testing that behavior?	2025-05-24 08:18:06 -07:00
ehhuang	549812f51e	feat: implement get chat completions APIs (#2200) ... # What does this PR do? * Provide sqlite implementation of the APIs introduced in https://github.com/meta-llama/llama-stack/pull/2145. * Introduced a SqlStore API: llama_stack/providers/utils/sqlstore/api.py and the first Sqlite implementation * Pagination support will be added in a future PR. ## Test Plan Unit test on sql store: <img width="1005" alt="image" src="https://github.com/user-attachments/assets/9b8b7ec8-632b-4667-8127-5583426b2e29" /> Integration test: ``` INFERENCE_MODEL="llama3.2:3b-instruct-fp16" llama stack build --template ollama --image-type conda --run ``` ``` LLAMA_STACK_CONFIG=http://localhost:5001 INFERENCE_MODEL="llama3.2:3b-instruct-fp16" python -m pytest -v tests/integration/inference/test_openai_completion.py --text-model "llama3.2:3b-instruct-fp16" -k 'inference_store and openai' ```	2025-05-21 22:21:52 -07:00
Ashwin Bharambe	4fb583b407	fix: check that llama stack client plain can be used as a subst for OpenAI client (#2032) ... With https://github.com/meta-llama/llama-stack-client-python/pull/226, now we have llama-stack-client be able to used as a substitute for OpenAI client (duck-typed) so you don't need to change downstream library code. <img width="1399" alt="image" src="https://github.com/user-attachments/assets/abab6bfd-e6ff-4a7d-a965-fd93e3c105d7" />	2025-04-25 12:23:33 -07:00
Ben Browning	7641a5cd0b	fix: 100% OpenAI API verification for together and fireworks (#1946) ... # What does this PR do? TLDR: Changes needed to get 100% passing tests for OpenAI API verification tests when run against Llama Stack with the `together`, `fireworks`, and `openai` providers. And `groq` is better than before, at 88% passing. This cleans up the OpenAI API support for image message types (specifically `image_url` types) and handling of the `response_format` chat completion parameter. Both of these required a few more Pydantic model definitions in our Inference API, just to move from the not-quite-right stubs I had in place to something fleshed out to match the actual OpenAI API specs. As part of testing this, I also found and fixed a bug in the litellm implementation of openai_completion and openai_chat_completion, so the providers based on those should actually be working now. The method `prepare_openai_completion_params` in `llama_stack/providers/utils/inference/openai_compat.py` was improved to actually recursively clean up input parameters, including handling of lists, dicts, and dumping of Pydantic models to dicts. These changes were required to get to 100% passing tests on the OpenAI API verification against the `openai` provider. With the above, the together.ai provider was passing as well as it is without Llama Stack. But, since we have Llama Stack in the middle, I took the opportunity to clean up the together.ai provider so that it now also passes the OpenAI API spec tests we have at 100%. That means together.ai is now passing our verification test better when using an OpenAI client talking to Llama Stack than it is when hitting together.ai directly, without Llama Stack in the middle. And, another round of work for Fireworks to improve translation of incoming OpenAI chat completion requests to Llama Stack chat completion requests gets the fireworks provider passing at 100%. The server-side fireworks.ai tool calling support with OpenAI chat completions and Llama 4 models isn't great yet, but by pointing the OpenAI clients at Llama Stack's API we can clean things up and get everything working as expected for Llama 4 models. ## Test Plan ### OpenAI API Verification Tests I ran the OpenAI API verification tests as below and 100% of the tests passed. First, start a Llama Stack server that runs the `openai` provider with the `gpt-4o` and `gpt-4o-mini` models deployed. There's not a template setup to do this out of the box, so I added a `tests/verifications/openai-api-verification-run.yaml` to do this. First, ensure you have the necessary API key environment variables set: ``` export TOGETHER_API_KEY="..." export FIREWORKS_API_KEY="..." export OPENAI_API_KEY="..." ``` Then, run a Llama Stack server that serves up all these providers: ``` llama stack run \ --image-type venv \ tests/verifications/openai-api-verification-run.yaml ``` Finally, generate a new verification report against all these providers, both with and without the Llama Stack server in the middle. ``` python tests/verifications/generate_report.py \ --run-tests \ --provider \ together \ fireworks \ groq \ openai \ together-llama-stack \ fireworks-llama-stack \ groq-llama-stack \ openai-llama-stack ``` You'll see that most of the configurations with Llama Stack in the middle now pass at 100%, even though some of them do not pass at 100% when hitting the backend provider's API directly with an OpenAI client. ### OpenAI Completion Integration Tests with vLLM: I also ran the smaller `test_openai_completion.py` test suite (that's not yet merged with the verification tests) on multiple of the providers, since I had to adjust the method signature of openai_chat_completion a bit and thus had to touch lots of these providers to match. Here's the tests I ran there, all passing: ``` VLLM_URL="http://localhost:8000/v1" INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" llama stack build --template remote-vllm --image-type venv --run ``` in another terminal ``` LLAMA_STACK_CONFIG=http://localhost:8321 INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" python -m pytest -v tests/integration/inference/test_openai_completion.py --text-model "meta-llama/Llama-3.2-3B-Instruct" ``` ### OpenAI Completion Integration Tests with ollama ``` INFERENCE_MODEL="llama3.2:3b-instruct-q8_0" llama stack build --template ollama --image-type venv --run ``` in another terminal ``` LLAMA_STACK_CONFIG=http://localhost:8321 INFERENCE_MODEL="llama3.2:3b-instruct-q8_0" python -m pytest -v tests/integration/inference/test_openai_completion.py --text-model "llama3.2:3b-instruct-q8_0" ``` ### OpenAI Completion Integration Tests with together.ai ``` INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct-Turbo" llama stack build --template together --image-type venv --run ``` in another terminal ``` LLAMA_STACK_CONFIG=http://localhost:8321 INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct-Turbo" python -m pytest -v tests/integration/inference/test_openai_completion.py --text-model "meta-llama/Llama-3.2-3B-Instruct-Turbo" ``` ### OpenAI Completion Integration Tests with fireworks.ai ``` INFERENCE_MODEL="meta-llama/Llama-3.1-8B-Instruct" llama stack build --template fireworks --image-type venv --run ``` in another terminal ``` LLAMA_STACK_CONFIG=http://localhost:8321 INFERENCE_MODEL="meta-llama/Llama-3.1-8B-Instruct" python -m pytest -v tests/integration/inference/test_openai_completion.py --text-model "meta-llama/Llama-3.1-8B-Instruct" --------- Signed-off-by: Ben Browning <bbrownin@redhat.com>	2025-04-14 08:56:29 -07:00
Ben Browning	2b2db5fbda	feat: OpenAI-Compatible models, completions, chat/completions (#1894) ... # What does this PR do? This stubs in some OpenAI server-side compatibility with three new endpoints: /v1/openai/v1/models /v1/openai/v1/completions /v1/openai/v1/chat/completions This gives common inference apps using OpenAI clients the ability to talk to Llama Stack using an endpoint like http://localhost:8321/v1/openai/v1 . The two "v1" instances in there isn't awesome, but the thinking is that Llama Stack's API is v1 and then our OpenAI compatibility layer is compatible with OpenAI V1. And, some OpenAI clients implicitly assume the URL ends with "v1", so this gives maximum compatibility. The openai models endpoint is implemented in the routing layer, and just returns all the models Llama Stack knows about. The following providers should be working with the new OpenAI completions and chat/completions API: * remote::anthropic (untested) * remote::cerebras-openai-compat (untested) * remote::fireworks (tested) * remote::fireworks-openai-compat (untested) * remote::gemini (untested) * remote::groq-openai-compat (untested) * remote::nvidia (tested) * remote::ollama (tested) * remote::openai (untested) * remote::passthrough (untested) * remote::sambanova-openai-compat (untested) * remote::together (tested) * remote::together-openai-compat (untested) * remote::vllm (tested) The goal to support this for every inference provider - proxying directly to the provider's OpenAI endpoint for OpenAI-compatible providers. For providers that don't have an OpenAI-compatible API, we'll add a mixin to translate incoming OpenAI requests to Llama Stack inference requests and translate the Llama Stack inference responses to OpenAI responses. This is related to #1817 but is a bit larger in scope than just chat completions, as I have real use-cases that need the older completions API as well. ## Test Plan ### vLLM ``` VLLM_URL="http://localhost:8000/v1" INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" llama stack build --template remote-vllm --image-type venv --run LLAMA_STACK_CONFIG=http://localhost:8321 INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" python -m pytest -v tests/integration/inference/test_openai_completion.py --text-model "meta-llama/Llama-3.2-3B-Instruct" ``` ### ollama ``` INFERENCE_MODEL="llama3.2:3b-instruct-q8_0" llama stack build --template ollama --image-type venv --run LLAMA_STACK_CONFIG=http://localhost:8321 INFERENCE_MODEL="llama3.2:3b-instruct-q8_0" python -m pytest -v tests/integration/inference/test_openai_completion.py --text-model "llama3.2:3b-instruct-q8_0" ``` ## Documentation Run a Llama Stack distribution that uses one of the providers mentioned in the list above. Then, use your favorite OpenAI client to send completion or chat completion requests with the base_url set to http://localhost:8321/v1/openai/v1 . Replace "localhost:8321" with the host and port of your Llama Stack server, if different. --------- Signed-off-by: Ben Browning <bbrownin@redhat.com>	2025-04-11 13:14:17 -07:00