156 commits

Author	SHA1	Message	Date
Ashwin Bharambe	0b08d64ddb	feat(ci): introduce workflow for re-recording inference outputs (#3002)	2025-07-31 17:30:47 -07:00
Francisco Arceo	33cca26154	chore: Enabling Integration tests for Weaviate (#2882) ... # What does this PR do? This PR (1) enables the files API for Weaviate and (2) enables integration tests for Weaviate, which adds a docker container to the github action. This PR also handles a couple of edge cases for in creating the collection and ensuring the tests all pass. ## Test Plan CI enabled --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>	2025-07-31 20:29:50 -04:00
Ashwin Bharambe	d1b300ead9	fix(ci, nvidia): do not use module level pytest skip for now	2025-07-31 12:32:31 -07:00
Ashwin Bharambe	27d866795c	feat(ci): add support for running vision inference tests (#2972) ... This PR significantly refactors the Integration Tests workflow. The main goal behind the PR was to enable recording of vision tests which were never run as part of our CI ever before. During debugging, I ended up making several other changes refactoring and hopefully increasing the robustness of the workflow. After doing the experiments, I have updated the trigger event to be `pull_request_target` so this workflow can get write permissions by default but it will run with source code from the base (main) branch in the source repository only. If you do change the workflow, you'd need to experiment using the `workflow_dispatch` triggers. This should not be news to anyone using Github Actions (except me!) It is likely to be a little rocky though while I learn more about GitHub Actions, etc. Please be patient :) --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>	2025-07-31 11:50:42 -07:00
Nehanth Narendrula	b41d696e4f	fix: Post Training Model change in Tests in order to make it less intensive (#2991) ... # What does this PR do? Changed from` ibm-granite/granite-3.3-2b-instruct` to` HuggingFaceTB/SmolLM2-135M-Instruct` so it as not resource intensive in CI Idea came from - https://github.com/meta-llama/llama-stack/pull/2984#issuecomment-3140400830	2025-07-31 11:22:34 -07:00
Nehanth Narendrula	3a574ef23c	fix: remove unused DPO parameters from schema and tests (#2988) ... # What does this PR do? I removed these DPO parameters from the schema in [this PR](https://github.com/meta-llama/llama-stack/pull/2804), but I may not have done it correctly, since they were reintroduced in [this commit](cb7354a9ce (diff-4e9a8cb358213d6118c4b6ec2a76d0367af06441bf0717e13a775ade75e2061dR15081))—likely due to a pre-commit hook. I've made the changes again, and the pre-commit hook automatically updated the spec sheet.	2025-07-31 09:11:08 -07:00
Charlie Doern	5c33bc1353	fix: post_training ci (#2984)	2025-07-31 08:26:06 -07:00
Nehanth Narendrula	cf73146132	feat: Enable DPO training with HuggingFace inline provider (#2825) ... What does this PR do? This PR adds support for Direct Preference Optimization (DPO) training via the existing HuggingFace inline provider. It introduces a new DPO training recipe, config schema updates, dataset integration, and end-to-end testing to support preference-based fine-tuning with TRL. Test Plan Added integration test: tests/integration/post_training/test_post_training.py::TestPostTraining::test_preference_optimize Ran tests on both CPU and CUDA environments --------- Co-authored-by: Ubuntu <ubuntu@ip-172-31-43-83.ec2.internal> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>	2025-07-30 23:33:36 -07:00
Ashwin Bharambe	2665f00102	chore(rename): move llama_stack.distribution to llama_stack.core (#2975) ... We would like to rename the term `template` to `distribution`. To prepare for that, this is a precursor. cc @leseb	2025-07-30 23:30:53 -07:00
Ashwin Bharambe	b237df8f18	feat(ci): use replay mode, setup ollama if specific label exists on PR (#2955) ... This PR makes setting up Ollama optional for CI. By default, we use `replay` mode for inference requests and use the stored results from the `tests/integration/recordings/` directory. Every so often, users will update tests which will need us to re-record. To do this, we check for the existence of a label `re-record-tests` on the PR. If detected, - ollama is spun up - inference mode is set to record - after the tests are done, if any new changes are detected, they are pushed back to the PR ## Test Plan This is GitHub CI. Gotta test it live.	2025-07-29 16:50:26 -07:00
Ashwin Bharambe	0ac503ec0d	feat(tests): record responses for evals and telemetry tests (#2954) ... Continuing with https://github.com/meta-llama/llama-stack/pull/2952 This also includes a "fix" to inference store related tests so that we pull a large number of inference responses from the DB so as to always find the one we just wrote.	2025-07-29 15:46:21 -07:00
Ashwin Bharambe	81c7d6fa2e	chore(ci): disable post training tests (#2953) ... Post training tests need _much_ better thinking before we can re-enable them to be run on every single PR. Running periodically should be approached only when it is shown that the tests are reliable and as light-weight as can be; otherwise, it is just kicking the can down the road.	2025-07-29 14:20:09 -07:00
Ashwin Bharambe	072d20a124	feat(test): record agents, safety and vector_io integration tests (#2952) ... Continue to build on top of https://github.com/meta-llama/llama-stack/pull/2941 ## Test Plan Run server with `LLAMA_STACK_TEST_INFERENCE_MODE=record` and then run the integration tests with `--stack-config=server:starter`. Then restart the server with `LLAMA_STACK_TEST_INFERENCE_MODE=replay` and re-run the tests. Verify that no request hit Ollama at any point.	2025-07-29 14:02:14 -07:00
Ashwin Bharambe	2e5ca3f15c	chore: move recordings one directory upwards	2025-07-29 12:46:19 -07:00
Ashwin Bharambe	08b4a1deb3	feat(tests): introduce inference record/replay to increase test reliability (#2941) ... Implements a comprehensive recording and replay system for inference API calls that eliminates dependency on online inference providers during testing. The system treats inference as deterministic by recording real API responses and replaying them in subsequent test runs. Applies to OpenAI clients (which should cover many inference requests) as well as Ollama AsyncClient. For storing, we use a hybrid system: Sqlite for fast lookups and JSON files for easy greppability / debuggability. As expected, tests become much much faster (more than 3x in just inference testing.) ```bash LLAMA_STACK_TEST_INFERENCE_MODE=record LLAMA_STACK_TEST_RECORDING_DIR=<...> \ uv run pytest -s -v tests/integration/inference \ --stack-config=starter \ -k "not( builtin_tool or safety_with_image or code_interpreter or test_rag )" \ --text-model="ollama/llama3.2:3b-instruct-fp16" \ --embedding-model=sentence-transformers/all-MiniLM-L6-v2 ``` ```bash LLAMA_STACK_TEST_INFERENCE_MODE=replay LLAMA_STACK_TEST_RECORDING_DIR=<...> \ uv run pytest -s -v tests/integration/inference \ --stack-config=starter \ -k "not( builtin_tool or safety_with_image or code_interpreter or test_rag )" \ --text-model="ollama/llama3.2:3b-instruct-fp16" \ --embedding-model=sentence-transformers/all-MiniLM-L6-v2 ``` - `LLAMA_STACK_TEST_INFERENCE_MODE`: `live` (default), `record`, or `replay` - `LLAMA_STACK_TEST_RECORDING_DIR`: Storage location (must be specified for record or replay modes)	2025-07-29 12:41:31 -07:00
Matthew Farrellee	c7dc0f21b4	fix: error on failed job, do not wait for timeout (#2945) ... # What does this PR do? cause post training integration test to error when job fails. ## Test Plan ci	2025-07-29 11:07:51 -07:00
Nathan Weinberg	870a37ff4b	feat: add base64 encoded PDF support for OpenAI Chat Completions (#2881) ... # What does this PR do? OpenAI Chat Completions supports passing a base64 encoded PDF file to a model, but Llama Stack currently does not allow for this behavior. This PR extends our implementation of the OpenAI API spec to change that. Closes #2129 ## Test Plan A new functional test has been added to test the validity of such a request Signed-off-by: Nathan Weinberg <nweinber@redhat.com>	2025-07-29 06:23:41 -04:00
Derek Higgins	52201612de	feat: implement chunk deletion for vector stores (#2701) ... Add support for deleting individual chunks from vector stores - Add abstract remove_chunk() method to EmbeddingIndex base class - Implement chunk deletion for Faiss provider, SQLite Vec, Milvus, PGVector - Placeholder implementations with NotImplementedError for Chroma/Qdrant/Weaviate - Integrate chunk deletion into OpenAI vector store file deletion flow - removed xfail from test_openai_vector_store_delete_file_removes_from_vector_store Closes: #2477 --------- Signed-off-by: Derek Higgins <derekh@redhat.com> Co-authored-by: Francisco Arceo <arceofrancisco@gmail.com>	2025-07-25 10:30:30 -04:00
Francisco Arceo	9e77be1f72	chore: Fix chroma unit tests (#2896) ... # What does this PR do? Enable Chroma inline unit tests and fix integration tests. <!-- 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.* --> --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>	2025-07-25 10:12:14 -04:00
Derek Higgins	4ea1f2aa9f	test: Add VLLM provider support to integration tests (#2757) ... - Add setup-vllm GitHub action to start VLLM container - Extend integration test matrix to support both ollama and vllm providers - Make test setup conditional based on provider type - Add provider-specific environment variables and configurations - vllm tests setup to run weekly or can be triggered manually (only ollama on PR) TODO: investigate failing tests for vllm provider (safety and post_training) Also need a proper fix for #2713 (tmp fix for this in the first commit in this PR) Closes: #1648 --------- Signed-off-by: Derek Higgins <derekh@redhat.com>	2025-07-24 09:42:26 -07:00
Sarthak Deshpande	cd8715d327	chore: Added openai compatible vector io endpoints for chromadb (#2489) ... # What does this PR do? This PR implements the openai compatible endpoints for chromadb Closes #2462 ## Test Plan Ran ollama llama stack server and ran the command `pytest -sv --stack-config=http://localhost:8321 tests/integration/vector_io/test_openai_vector_stores.py --embedding-model all-MiniLM-L6-v2` 8 failed, 27 passed, 8 skipped, 1 xfailed The failed ones are regarding files api --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com> Co-authored-by: sarthakdeshpande <sarthak.deshpande@engati.com> Co-authored-by: Francisco Javier Arceo <farceo@redhat.com> Co-authored-by: Francisco Arceo <arceofrancisco@gmail.com>	2025-07-23 13:51:58 -07:00
Mustafa Elbehery	9736f096f6	chore(test): fix flaky telemetry tests (#2815) ... # What does this PR do? <!-- Provide a short summary of what this PR does and why. Link to relevant issues if applicable. --> This PR fixes flaky telemetry tests <!-- If resolving an issue, uncomment and update the line below --> <!-- Closes #[issue-number] --> See https://github.com/meta-llama/llama-stack/pull/2814 ## 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.* --> Signed-off-by: Mustafa Elbehery <melbeher@redhat.com>	2025-07-22 12:30:14 -07:00
ehhuang	d0208df286	test: skip flaky telemetry tests (#2814) ... # What does this PR do? example error: 4625086977 ## Test Plan	2025-07-21 10:01:40 -07:00
ehhuang	0a6e588f68	feat: enable auth for LocalFS Files Provider (#2773) ... # What does this PR do? Supports authentication for LocalFS Files provider. closes https://github.com/meta-llama/llama-stack/issues/2760 ## Test Plan CI. added tests.	2025-07-18 19:11:01 -07:00
ehhuang	6d55f2f137	feat: enable ls client for files tests (#2769) ... # What does this PR do? titled ## Test Plan CI	2025-07-18 12:10:30 -07:00
Charlie Doern	d7cc38e934	fix: remove async test markers (fix pre-commit) (#2808) ... # What does this PR do? some async test markers are in the codebase causing pre-commit to fail due to #2744 remove these pytest fixtures ## Test Plan pre-commit passes Signed-off-by: Charlie Doern <cdoern@redhat.com>	2025-07-17 21:35:28 -07:00
ehhuang	3ae4aeb344	test: add some tests for Telemetry API (#2787) ... # What does this PR do? ## Test Plan ENABLE_OLLAMA=ollama LLAMA_STACK_CONFIG=starter uv run pytest tests/integration/telemetry --text-model="ollama/llama3.2:3b-instruct-fp16"	2025-07-17 16:20:51 -07:00
Francisco Arceo	e1755d1ed2	chore: Adding OpenAI Vector Stores Files API compatibility for PGVector (#2755) ... # What does this PR do? Adding OpenAI Vector Stores Files API compatibility for PGVector <!-- If resolving an issue, uncomment and update the line below --> <!-- Closes #[issue-number] --> ## Test Plan Updated CI to include PGVector --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>	2025-07-15 15:46:49 -04:00
Francisco Arceo	31b088978a	fix: Fix /vector-stores/create API when vector store with duplicate name (#2617) ... # What does this PR do? Resolves https://github.com/meta-llama/llama-stack/issues/2735 Currently, if you test against OpenAI's Vector Stores API the `client.vector_stores.search` call fails with an invalid vector_db during routing (see the script referenced in the clickable item under the Test Plan section). This PR ensures that `client.vector_stores.search()` is compatible with OpenAI's Vector Stores API. Two biggest changes: 1. The `name`, which was previously used as the `vector_db_id`, has been changed to be consistent with OpenAI's `vs_{uuid}` format. 2. The vector store ID has to be referenced by the ID, the name is not reliable as every `client.vector_stores.create` results in a new vector store. NOTE: I believe this is a breaking change for end users as they'll need to update their VectorDB identifiers. ## Test Plan Unit tests: ```bash ./scripts/unit-tests.sh tests/unit/providers/vector_io/ -v ``` Integration tests: ```bash ENABLE_MILVUS=milvus llama stack run /Users/farceo/dev/llama-stack/llama_stack/templates/starter/run.yaml --image-type venv LLAMA_STACK_CONFIG=http://localhost:8321 pytest -sv tests/integration/vector_io/test_openai_vector_stores.py --embedding-model=all-MiniLM-L6-v2 -vv ``` Unit tests and test script below 👇 <details> <summary>Click here for script used to test OpenAI and Llama Stack Vector Store implementation</summary> ```python import json import argparse from openai import OpenAI, pagination import logging from colorama import Fore, Style, init import traceback import os # Initialize colorama for color support in terminal init(autoreset=True) # Setup basic logging logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') DEMO_VECTOR_STORE_NAME = "Support FAQ FJA" global DEMO_VECTOR_STORE_ID global DEMO_VECTOR_STORE_ID2 def colored_print(color, text): """Prints text to the console with the specified color.""" print(f"{color}{text}{Style.RESET_ALL}") def log_and_print(color, message, level=logging.INFO): """Logs a message and prints it to the console with the specified color.""" logging.log(level, message) colored_print(color, message) def run_tests(client, prefix="openai"): """ Runs all tests using the provided OpenAI client and saves the output to JSON files with the given prefix. """ # Create the directory if it doesn't exist os.makedirs('openai_testing', exist_ok=True) # Default values in case tests fail global DEMO_VECTOR_STORE_ID, DEMO_VECTOR_STORE_ID2 DEMO_VECTOR_STORE_ID = None DEMO_VECTOR_STORE_ID2 = None def test_idempotent_vector_store_creation(): """ Test that creating a vector store with the same name is idempotent. """ log_and_print(Fore.BLUE, "Starting vector store creation test...") try: vector_store = client.vector_stores.create( name=DEMO_VECTOR_STORE_NAME, ) # Attempt to create the same vector store again vector_store2 = client.vector_stores.create( name=DEMO_VECTOR_STORE_NAME, ) # Check instead of assert if vector_store2.id != vector_store.id: log_and_print(Fore.YELLOW, f"FAILED IDEMPOTENCY: the same VectorStore name for {prefix.upper()} does not return the same ID", level=logging.WARNING) else: log_and_print(Fore.GREEN, f"PASSED IDEMPOTENCY: f{vector_store2.id} == {vector_store.id} the same VectorStore name for {prefix.upper()} returns the same ID") vector_store_data = vector_store.to_dict() log_and_print(Fore.WHITE, f"vector_stores.create = {json.dumps(vector_store_data, indent=2)}") with open(f'openai_testing/{prefix}_vector_store_create.json', 'w') as f: json.dump(vector_store_data, f, indent=2) global DEMO_VECTOR_STORE_ID, DEMO_VECTOR_STORE_ID2 DEMO_VECTOR_STORE_ID = vector_store.id DEMO_VECTOR_STORE_ID2 = vector_store2.id return DEMO_VECTOR_STORE_ID, DEMO_VECTOR_STORE_ID2 except Exception as e: log_and_print(Fore.RED, f"Idempotent vector store creation test failed: {e}", level=logging.ERROR) logging.error(traceback.format_exc()) # Create a fallback vector store ID if needed if 'vector_store' in locals() and vector_store: DEMO_VECTOR_STORE_ID = vector_store.id return DEMO_VECTOR_STORE_ID, DEMO_VECTOR_STORE_ID2 def test_vector_store_list(): """ Test listing vector stores. """ log_and_print(Fore.BLUE, "Starting vector store list test...") try: vector_stores = client.vector_stores.list() # Check instead of assert if not isinstance(vector_stores, pagination.SyncCursorPage): log_and_print(Fore.YELLOW, f"FAILED: Expected a list of vector stores, got {type(vector_stores)}", level=logging.WARNING) else: log_and_print(Fore.GREEN, "Vector store list test passed!") vector_stores_data = vector_stores.to_dict() log_and_print(Fore.WHITE, f"vector_stores.list = {json.dumps(vector_stores_data, indent=2)}") with open(f'openai_testing/{prefix}_vector_store_list.json', 'w') as f: json.dump(vector_stores_data, f, indent=2) except Exception as e: log_and_print(Fore.RED, f"Vector store list test failed: {e}", level=logging.ERROR) logging.error(traceback.format_exc()) def test_retrieve_vector_store(): """ Test retrieving a specific vector store. """ log_and_print(Fore.BLUE, "Starting retrieve vector store test...") if not DEMO_VECTOR_STORE_ID: log_and_print(Fore.YELLOW, "Skipping retrieve vector store test - no vector store ID available", level=logging.WARNING) return try: vector_store = client.vector_stores.retrieve( vector_store_id=DEMO_VECTOR_STORE_ID, ) # Check instead of assert if vector_store.id != DEMO_VECTOR_STORE_ID: log_and_print(Fore.YELLOW, "FAILED: Retrieved vector store ID does not match", level=logging.WARNING) else: log_and_print(Fore.GREEN, "Retrieve vector store test passed!") vector_store_data = vector_store.to_dict() log_and_print(Fore.WHITE, f"vector_stores.retrieve = {json.dumps(vector_store_data, indent=2)}") with open(f'openai_testing/{prefix}_vector_store_retrieve.json', 'w') as f: json.dump(vector_store_data, f, indent=2) except Exception as e: log_and_print(Fore.RED, f"Retrieve vector store test failed: {e}", level=logging.ERROR) logging.error(traceback.format_exc()) def test_modify_vector_store(): """ Test modifying a vector store. """ log_and_print(Fore.BLUE, "Starting modify vector store test...") if not DEMO_VECTOR_STORE_ID: log_and_print(Fore.YELLOW, "Skipping modify vector store test - no vector store ID available", level=logging.WARNING) return try: updated_vector_store = client.vector_stores.update( vector_store_id=DEMO_VECTOR_STORE_ID, name="Updated Support FAQ FJA", ) # Check instead of assert if updated_vector_store.name != "Updated Support FAQ FJA": log_and_print(Fore.YELLOW, "FAILED: Vector store name was not updated correctly", level=logging.WARNING) else: log_and_print(Fore.GREEN, "Modify vector store test passed!") updated_vector_store_data = updated_vector_store.to_dict() log_and_print(Fore.WHITE, f"vector_stores.modify = {json.dumps(updated_vector_store_data, indent=2)}") with open(f'openai_testing/{prefix}_vector_store_modify.json', 'w') as f: json.dump(updated_vector_store_data, f, indent=2) except Exception as e: log_and_print(Fore.RED, f"Modify vector store test failed: {e}", level=logging.ERROR) logging.error(traceback.format_exc()) def test_delete_vector_store(): """ Test deleting a vector store. """ log_and_print(Fore.BLUE, "Starting delete vector store test...") if not DEMO_VECTOR_STORE_ID2: log_and_print(Fore.YELLOW, "Skipping delete vector store test - no second vector store ID available", level=logging.WARNING) return try: response = client.vector_stores.delete( vector_store_id=DEMO_VECTOR_STORE_ID2, ) log_and_print(Fore.GREEN, "Delete vector store test passed!") response_data = response.to_dict() log_and_print(Fore.WHITE, f"Vector store delete response = {json.dumps(response_data, indent=2)}") with open(f'openai_testing/{prefix}_vector_store_delete.json', 'w') as f: json.dump(response_data, f, indent=2) except Exception as e: log_and_print(Fore.RED, f"Delete vector store test failed: {e}", level=logging.ERROR) logging.error(traceback.format_exc()) def test_create_vector_store_file(): log_and_print(Fore.BLUE, "Starting create vector store file test...") if not DEMO_VECTOR_STORE_ID: log_and_print(Fore.YELLOW, "Skipping create vector store file test - no vector store ID available", level=logging.WARNING) return try: # create jsonl of files as an example with open("mydata.jsonl", "w") as f: f.write('{"text": "What is the return policy?", "metadata": {"category": "support"}}\n') f.write('{"text": "How do I reset my password?", "metadata": {"category": "support"}}\n') f.write('{"text": "Where can I find my order history?", "metadata": {"category": "support"}}\n') f.write('{"text": "What are the shipping options?", "metadata": {"category": "support"}}\n') f.write('{"text": "What is your favorite banana?", "metadata": {"category": "support"}}\n') # Create a simple text file if my_data_small.txt doesn't exist if not os.path.exists("my_data_small.txt"): with open("my_data_small.txt", "w") as f: f.write("This is a test file for vector store testing.\n") created_file = client.files.create( file=open("my_data_small.txt", "rb"), purpose="assistants", ) created_file_data = created_file.to_dict() log_and_print(Fore.WHITE, f"Created file {json.dumps(created_file_data, indent=2)}") with open(f'openai_testing/{prefix}_file_create.json', 'w') as f: json.dump(created_file_data, f, indent=2) retrieved_files = client.files.retrieve(created_file.id) retrieved_files_data = retrieved_files.to_dict() log_and_print(Fore.WHITE, f"Retrieved file {json.dumps(retrieved_files_data, indent=2)}") with open(f'openai_testing/{prefix}_file_retrieve.json', 'w') as f: json.dump(retrieved_files_data, f, indent=2) vector_store_file = client.vector_stores.files.create( vector_store_id=DEMO_VECTOR_STORE_ID, file_id=created_file.id, ) log_and_print(Fore.GREEN, "Create vector store file test passed!") except Exception as e: log_and_print(Fore.RED, f"Create vector store file test failed: {e}", level=logging.ERROR) logging.error(traceback.format_exc()) def test_search_vector_store(): """ Test searching a vector store. """ log_and_print(Fore.BLUE, "Starting search vector store test...") if not DEMO_VECTOR_STORE_ID: log_and_print(Fore.YELLOW, "Skipping search vector store test - no vector store ID available", level=logging.WARNING) return try: query = "What is the banana policy?" search_results = client.vector_stores.search( vector_store_id=DEMO_VECTOR_STORE_ID, query=query, max_num_results=10, ranking_options={ 'ranker': 'default-2024-11-15', 'score_threshold': 0.0, }, rewrite_query=False, ) # Check instead of assert if not isinstance(search_results, pagination.SyncPage): log_and_print(Fore.YELLOW, f"FAILED: Expected a list of search results, got {type(search_results)}", level=logging.WARNING) else: log_and_print(Fore.GREEN, "Search vector store test passed!") search_results_dict = search_results.to_dict() log_and_print(Fore.WHITE, f"Search results = {search_results_dict}") with open(f'openai_testing/{prefix}_vector_store_search.json', 'w') as f: json.dump(search_results_dict, f, indent=2) log_and_print(Fore.WHITE, f"vector_stores.search = {search_results.to_json()}") except Exception as e: log_and_print(Fore.RED, f"Search vector store test failed: {e}", level=logging.ERROR) logging.error(traceback.format_exc()) # Run all tests in sequence, even if some fail test_results = [] try: result = test_idempotent_vector_store_creation() if result and len(result) == 2: DEMO_VECTOR_STORE_ID, DEMO_VECTOR_STORE_ID2 = result test_results.append(True) except Exception as e: log_and_print(Fore.RED, f"Vector store creation test failed: {e}", level=logging.ERROR) logging.error(traceback.format_exc()) test_results.append(False) for test_func in [ test_vector_store_list, test_retrieve_vector_store, test_modify_vector_store, test_delete_vector_store, test_create_vector_store_file, test_search_vector_store ]: try: test_func() test_results.append(True) except Exception as e: log_and_print(Fore.RED, f"{test_func.__name__} failed: {e}", level=logging.ERROR) logging.error(traceback.format_exc()) test_results.append(False) if all(test_results): log_and_print(Fore.GREEN, f"All {prefix} tests completed successfully!") else: failed_count = test_results.count(False) log_and_print(Fore.YELLOW, f"{failed_count} {prefix} test(s) failed, but script completed.") if __name__ == "__main__": parser = argparse.ArgumentParser(description="Run OpenAI and/or LlamaStack tests.") parser.add_argument( "--provider", type=str, default="llama", choices=["openai", "llama", "both"], help="Specify which environment to test: openai, llama, or both. Default is both.", ) args = parser.parse_args() try: if args.provider in ("openai", "both"): openai_client = OpenAI() run_tests(openai_client, prefix="openai") if args.provider in ("llama", "both"): llama_client = OpenAI(base_url="http://localhost:8321/v1/openai/v1", api_key="none") run_tests(llama_client, prefix="llama") log_and_print(Fore.GREEN, "All tests completed!") except Exception as e: log_and_print(Fore.RED, f"Tests failed to complete: {e}", level=logging.ERROR) logging.error(traceback.format_exc()) ``` </details> --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>	2025-07-15 11:24:41 -04:00
Hardik Shah	6b8a8c1be9	fix: Safety in starter (#2731) ... - fireworks, together do not support Llama-guard 3 8b model anymore - Need to default to ollama - current safety shields logic was not correct since the shield_id was the provider ( which had duplicates ) - Followed similar logic to models Note: Seems a bit over-engineered but this can now be extended to other providers and fits in the overall mechanism of how env_vars are used to manage starter. ### How to test ``` ENABLE_OLLAMA=ollama ENABLE_FIREWORKS=fireworks SAFETY_MODEL=llama-guard3:1b pytest -s -v tests/integration/ --stack-config starter -k 'not(supervised_fine_tune or builtin_tool_code or safety_with_image or code_interpreter_for or rag_and_code or truncation or register_and_unregister)' --text-model fireworks/meta-llama/Llama-3.3-70B-Instruct --vision-model fireworks/meta-llama/Llama-4-Scout-17B-16E-Instruct --safety-shield llama-guard3:1b --embedding-model all-MiniLM-L6-v2 ``` ### Related but not obvious in this PR In the llama-stack-ops repo, we run tests before publishing packages and docker containers. The actions in that repo were using the fireworks / together distros ( which are non-existent ) So need to update that to run with `starter` and use `ollama` specifically for safety.	2025-07-14 15:07:40 -07:00
Jorge Piedrahita Ortiz	aa2595c7c3	fix: sambanova shields and model validation (#2693) ... # What does this PR do? Update the shield register validation of Sambanova not to raise, but only warn when a model is not available in the base url endpoint used, also added warnings when model is not available in the base url endpoint used <!-- 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.* --> run starter distro with Sambanova enabled	2025-07-11 16:29:15 -04:00
Matthew Farrellee	30b2e6a495	chore: default to pytest asyncio-mode=auto (#2730) ... # What does this PR do? previously, developers who ran `./scripts/unit-tests.sh` would get `asyncio-mode=auto`, which meant `@pytest.mark.asyncio` and `@pytest_asyncio.fixture` were redundent. developers who ran `pytest` directly would get pytest's default (strict mode), would run into errors leading them to add `@pytest.mark.asyncio` / `@pytest_asyncio.fixture` to their code. with this change - - `asyncio_mode=auto` is included in `pyproject.toml` making behavior consistent for all invocations of pytest - removes all redundant `@pytest_asyncio.fixture` and `@pytest.mark.asyncio` - for good measure, requires `pytest>=8.4` and `pytest-asyncio>=1.0` ## Test Plan - `./scripts/unit-tests.sh` - `uv run pytest tests/unit`	2025-07-11 13:00:24 -07:00
ehhuang	d880c2df0e	fix: auth sql store: user is owner policy (#2674) ... # What does this PR do? The current authorized sql store implementation does not respect user.principal (only checks attributes). This PR addresses that. ## Test Plan Added test cases to integration tests.	2025-07-10 14:40:32 -07:00
Sébastien Han	01c222e12f	ci: run all APIs integration tests (#2646) ... # What does this PR do? We are now automatically building the list of integration test to run. In that process, eval and files and being tested now. This is pending https://github.com/meta-llama/llama-stack/pull/2628 Signed-off-by: Sébastien Han <seb@redhat.com>	2025-07-10 15:16:08 +02:00
ehhuang	81109a0f72	test: terminate server process when finished (#2700) ... # What does this PR do? Terminate server process for real. ## Test Plan ```ENABLE_OPENAI=openai LLAMA_STACK_CONFIG=server:starter pytest -v tests/integration/agents/test_openai_responses.py --text-model "gpt-4o-mini" -vv -s -k 'test_list_response_input_items[' && lsof -ti:8321``` observe no process printed anymore	2025-07-09 20:59:37 -07:00
ehhuang	780b4c6eea	fix: llama stack run starter in conda (#2679) ... # What does this PR do? `llama stack run starter` in conda environment fails with ' --config is required for venv and conda environments' because it is passed as --template and start_stack.sh doesn't process template. ## Test Plan `llama stack run starter`	2025-07-09 20:33:45 -07:00
ehhuang	e9926564bd	fix: authorized sql store with postgres (#2641) ... # What does this PR do? postgres has different json extract syntax from sqlite ## Test Plan added integration test	2025-07-07 19:36:34 -07:00
Sébastien Han	5561f1c36d	ci: error when a pipefails (#2635) ... # What does this PR do? The CI was failing but the error was eaten by the pipe. Now we run the task with pipefail. Signed-off-by: Sébastien Han <seb@redhat.com>	2025-07-07 16:47:30 +02:00
Sébastien Han	c4349f532b	feat: consolidate most distros into "starter" (#2516) ... # What does this PR do? * Removes a bunch of distros * Removed distros were added into the "starter" distribution * Doc for "starter" has been added * Partially reverts https://github.com/meta-llama/llama-stack/pull/2482 since inference providers are disabled by default and can be turned on manually via env variable. * Disables safety in starter distro Closes: https://github.com/meta-llama/llama-stack/issues/2502. ~Needs: https://github.com/meta-llama/llama-stack/pull/2482 for Ollama to work properly in the CI.~ TODO: - [ ] We can only update `install.sh` when we get a new release. - [x] Update providers documentation - [ ] Update notebooks to reference starter instead of ollama Signed-off-by: Sébastien Han <seb@redhat.com>	2025-07-04 15:58:03 +02:00
Matthew Farrellee	ef26259209	feat: add llama guard 4 model (#2579) ... add support for Llama Guard 4 model to the llama_guard safety provider test with - 0. NVIDIA_API_KEY=... llama stack build --image-type conda --image-name env-nvidia --providers inference=remote::nvidia,safety=inline::llama-guard --run 1. llama-stack-client models register meta-llama/Llama-Guard-4-12B --provider-model-id meta/llama-guard-4-12b 2. pytest tests/integration/safety/test_llama_guard.py Co-authored-by: raghotham <rsm@meta.com>	2025-07-03 22:29:04 -07:00
Francisco Arceo	4afd619c56	chore: Add support for vector-stores files api for Milvus (#2582) ... # What does this PR do? ### Summary This pull request implements support for the OpenAI Vector Store Files API for the Milvus vector store provider in `llama_stack`. It enables storing, loading, updating, and deleting file metadata and file contents in Milvus collections, allowing OpenAI vector store files to be managed directly within Milvus. ### Main Changes - **Milvus Vector Store Files API Implementation** - Implements all required methods for storing, loading, updating, and deleting vector store file metadata and contents (`_save_openai_vector_store_file`, `_load_openai_vector_store_file`, `_load_openai_vector_store_file_contents`, `_update_openai_vector_store_file`, `_delete_openai_vector_store_file_from_storage`). - Uses two Milvus collections: `openai_vector_store_files` (for metadata) and `openai_vector_store_files_contents` (for chunked file contents). - Collections are created dynamically if they do not exist, with appropriate schema definitions. - **Collection Name Sanitization** - Adds a `sanitize_collection_name` utility to ensure Milvus collection names only contain valid characters (letters, numbers, underscores). - **Testing** - Updates test skip logic to include `"inline::milvus"` for cases where the OpenAI Vector Store Files API is not supported, improving integration test accuracy. - **Other Improvements** - Passes `kvstore` to `MilvusIndex` for consistency. - Removes obsolete NotImplementedErrors and legacy code for file storage. ## Test Plan CI and tested via a test script ## Notes - `VectorDB` currently uses the `name` as the `identifier` in `openai_create_vector_store`. We need to add `name` as a field to `VectorDB` and generate the `identifier` upon creation. OpenAI is not idempotent with respect to the `name` field that they pass (i.e., you can pass the same name multiple times and OpenAI will generate a new identifier). I'll add a follow up PR for this. - The `Files` api needs to use `files-` as a prefix in the identifier. I have updated the Vector Store to use the OpenAI prefix `vs_*`. --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>	2025-07-03 12:15:33 -07:00
Sébastien Han	dae1fcd3c2	ci: let pytest run the distro server (#2586) ... # What does this PR do? * Use #2580 functionality to auto-start the server with the tests * Reduce timeout to 30sec * Print server logs on errors * Pytest logs are collected to a file pytest.log Signed-off-by: Sébastien Han <seb@redhat.com>	2025-07-03 10:51:46 -07:00
ehhuang	fc735a414e	test: Add one-step integration testing with server auto-start (#2580) ... ## Summary Add support for `server:<config>` format in `--stack-config` option to enable seamless one-step integration testing. This eliminates the need to manually start servers in separate terminals before running tests. ## Key Features - **Auto-start server**: Automatically launches `llama stack run <config>` if target port is available - **Smart reuse**: Reuses existing server if port is already occupied - **Health check polling**: Waits up to 2 minutes for server readiness via `/v1/health` endpoint - **Custom port support**: Use `server:<config>:<port>` for non-default ports - **Clean output**: Server runs quietly in background without cluttering test output - **Backward compatibility**: All existing `--stack-config` formats continue to work ## Usage Examples ```bash # Auto-start server with default port 8321 pytest tests/integration/inference/ --stack-config=server:fireworks # Use custom port pytest tests/integration/safety/ --stack-config=server:together:8322 # Run multiple test suites seamlessly pytest tests/integration/inference/ tests/integration/agents/ --stack-config=server:starter ``` ## Implementation Details - Enhanced `llama_stack_client` fixture with server management - Updated documentation with cleaner organization and comprehensive examples - Added utility functions for port checking, server startup, and health verification ## Test Plan - Verified server auto-start when port 8321 is available - Verified server reuse when port 8321 is occupied - Tested health check polling via `/v1/health` endpoint - Confirmed custom port configuration works correctly - Verified backward compatibility with existing config formats ## Before/After Comparison **Before (2 steps):** ```bash # Terminal 1: Start server manually llama stack run fireworks --port 8321 # Terminal 2: Wait for startup, then run tests pytest tests/integration/inference/ --stack-config=http://localhost:8321 ``` **After (1 step):** ```bash # Single command handles everything pytest tests/integration/inference/ --stack-config=server:fireworks ```	2025-07-01 14:48:46 -07:00
Francisco Arceo	0066135944	chore: Enabling VectorIO Integration tests for Milvus (#2546)	2025-06-30 19:49:59 -07:00
Krzysztof Malczuk	be9bf68246	feat: Add webmethod for deleting openai responses (#2160) ... # What does this PR do? This PR creates a webmethod for deleting open AI responses, adds and implementation for it and makes an integration test for the OpenAI delete response method. [//]: # (If resolving an issue, uncomment and update the line below) # (Closes #2077) ## Test Plan Ran the standard tests and the pre-commit hooks and the unit tests. # (## Documentation) For this pr I made the routes and implementation based on the current get and create methods. The unit tests were not able to handle this test due to the mock interface in use, which did not allow for effective CRUD to be tested. I instead created an integration test to match the existing ones in the test_openai_responses.	2025-06-30 11:28:02 +02:00
Francisco Arceo	cc19b56c87	chore: OpenAI compatibility for Milvus (#2470) ... # What does this PR do? Closes https://github.com/meta-llama/llama-stack/issues/2461 ## Test Plan Tested with the `ollama` distriubtion template and updated the vector_io provider to: ```yaml vector_io: - provider_id: milvus provider_type: inline::milvus config: db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/milvus_store.db kvstore: type: sqlite db_name: milvus_registry.db ``` Ran the stack ```bash llama stack run ./llama_stack/templates/ollama/run.yaml --image-type venv --env OLLAMA_URL="http://0.0.0.0:11434" ``` Ran the tests: ``` pytest -sv --stack-config=http://localhost:8321 tests/integration/vector_io/test_openai_vector_stores.py --embedding-model all-MiniLM-L6-v2 ``` Output passed. Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>	2025-06-27 16:00:36 -07:00
ehhuang	1d3f27fe5b	fix: resume responses with tool call output (#2524) ... # What does this PR do? closes #2522 ## Test Plan added integration test LLAMA_STACK_CONFIG=http://localhost:8321 pytest -v tests/integration/agents/test_openai_responses.py --text-model "accounts/fireworks/models/llama-v3p3-70b-instruct" -vv -k 'function_call'	2025-06-25 14:43:37 -07:00
Varsha	cfee63bd0d	feat: Add search_mode support to OpenAI vector store API (#2500) ... # What does this PR do? Add search_mode parameter (vector/keyword/hybrid) to openai_search_vector_store method. Fixes OpenAPI code generation by using str instead of Literal type. Closes: #2459 ## 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.* --> Signed-off-by: Varsha Prasad Narsing <varshaprasad96@gmail.com>	2025-06-24 20:38:47 -04:00
Ben Browning	f394c7f2d9	feat: Add missing Vector Store Files API surface (#2468) ... # What does this PR do? This adds the ability to list, retrieve, update, and delete Vector Store Files. It implements these new APIs for the faiss and sqlite-vec providers, since those are the two that also have the rest of the vector store files implementation. Closes #2445 ## Test Plan ### test_openai_vector_stores Integration Tests There are a number of new integration tests added, which I ran for each provider as outlined below. faiss (from ollama distro): ``` INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" \ llama stack run llama_stack/templates/ollama/run.yaml LLAMA_STACK_CONFIG=http://localhost:8321 \ pytest -sv tests/integration/vector_io/test_openai_vector_stores.py \ --embedding-model=all-MiniLM-L6-v2 ``` sqlite-vec (from starter distro): ``` llama stack run llama_stack/templates/starter/run.yaml LLAMA_STACK_CONFIG=http://localhost:8321 \ pytest -sv tests/integration/vector_io/test_openai_vector_stores.py \ --embedding-model=all-MiniLM-L6-v2 ``` ### file_search verification tests I also ensured the file_search verification tests continue to work, both for faiss and sqlite-vec. faiss (ollama distro): ``` INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" \ llama stack run llama_stack/templates/ollama/run.yaml pytest -sv tests/verifications/openai_api/test_responses.py \ -k'file_search' \ --base-url=http://localhost:8321/v1/openai/v1 \ --model=meta-llama/Llama-3.2-3B-Instruct ``` sqlite-vec (starter distro): ``` llama stack run llama_stack/templates/starter/run.yaml pytest -sv tests/verifications/openai_api/test_responses.py \ -k'file_search' \ --base-url=http://localhost:8321/v1/openai/v1 \ --model=together/meta-llama/Llama-3.2-3B-Instruct-Turbo ``` --------- Signed-off-by: Ben Browning <bbrownin@redhat.com>	2025-06-19 11:08:24 -04:00
Sébastien Han	6039d922c0	fix: allow running vector tests with embedding dimension (#2467) ... # What does this PR do? Do not force 384 for the embedding dimension, use the one provided by the test run. ## Test Plan ``` pytest -s -vvv tests/integration/vector_io/test_vector_io.py --stack-config=http://localhost:8321 \ -k "not(builtin_tool or safety_with_image or code_interpreter or test_rag)" \ --text-model="meta-llama/Llama-3.2-3B-Instruct" \ --embedding-model=granite-embedding-125m --embedding-dimension=768 Uninstalled 1 package in 16ms Installed 1 package in 11ms INFO 2025-06-18 10:52:03,314 tests.integration.conftest:59 tests: Setting DISABLE_CODE_SANDBOX=1 for macOS /Users/leseb/Documents/AI/llama-stack/.venv/lib/python3.10/site-packages/pytest_asyncio/plugin.py:207: PytestDeprecationWarning: The configuration option "asyncio_default_fixture_loop_scope" is unset. The event loop scope for asynchronous fixtures will default to the fixture caching scope. Future versions of pytest-asyncio will default the loop scope for asynchronous fixtures to function scope. Set the default fixture loop scope explicitly in order to avoid unexpected behavior in the future. Valid fixture loop scopes are: "function", "class", "module", "package", "session" warnings.warn(PytestDeprecationWarning(_DEFAULT_FIXTURE_LOOP_SCOPE_UNSET)) ================================================= test session starts ================================================= platform darwin -- Python 3.10.16, pytest-8.3.4, pluggy-1.5.0 -- /Users/leseb/Documents/AI/llama-stack/.venv/bin/python cachedir: .pytest_cache metadata: {'Python': '3.10.16', 'Platform': 'macOS-15.5-arm64-arm-64bit', 'Packages': {'pytest': '8.3.4', 'pluggy': '1.5.0'}, 'Plugins': {'cov': '6.0.0', 'html': '4.1.1', 'json-report': '1.5.0', 'timeout': '2.4.0', 'metadata': '3.1.1', 'asyncio': '0.25.3', 'anyio': '4.8.0', 'nbval': '0.11.0'}} rootdir: /Users/leseb/Documents/AI/llama-stack configfile: pyproject.toml plugins: cov-6.0.0, html-4.1.1, json-report-1.5.0, timeout-2.4.0, metadata-3.1.1, asyncio-0.25.3, anyio-4.8.0, nbval-0.11.0 asyncio: mode=strict, asyncio_default_fixture_loop_scope=None collected 8 items tests/integration/vector_io/test_vector_io.py::test_vector_db_retrieve[emb=granite-embedding-125m:dim=768] PASSED tests/integration/vector_io/test_vector_io.py::test_vector_db_register[emb=granite-embedding-125m:dim=768] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case0] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case1] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case2] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case3] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case4] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks_with_precomputed_embeddings[emb=granite-embedding-125m:dim=768] PASSED ================================================== 8 passed in 5.50s ================================================== ``` Signed-off-by: Sébastien Han <seb@redhat.com>	2025-06-19 13:29:04 +05:30