25 commits

Author	SHA1	Message	Date
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
Ben Browning	0883944bc3	fix: Some missed env variable changes from PR 2490 (#2538) ... # What does this PR do? Some templates were still using the old environment variable substition syntax instead of the new one and were not getting substituted properly. Also, some places didn't handle the new None vs old empty string ("") values that come from the conditional environment variable substitution. This gets the starter and remote-vllm distributions starting again, and I tested various permutations of the starter as chroma and pgvector needed some adjustments to their config classes to handle the new possible `None` values. And, I had to tweak our `Provider` class to also handle `None` values, for cases where we disable providers in the starter config via environment variables. This may not have caught everything that was missed, but I did grep around quite a bit to try and find anything lingering. ## Test Plan The following permutations now all run (or attempt to run to the point of complaining that they can't connect to chroma, vllm, etc) when before they failed immediately on startup because of bad environment variable substitions: ``` uv run llama stack run llama_stack/templates/starter/run.yaml ENABLE_SQLITE_VEC=true uv run llama stack run llama_stack/templates/starter/run.yaml ENABLE_PGVECTOR=true uv run llama stack run llama_stack/templates/starter/run.yaml ENABLE_CHROMADB=true uv run llama stack run llama_stack/templates/starter/run.yaml uv run llama stack run llama_stack/templates/remote-vllm/run.yaml ``` <!-- 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: Ben Browning <bbrownin@redhat.com> Co-authored-by: raghotham <rsm@meta.com>	2025-06-26 17:59:15 -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
Ashwin Bharambe	73c18feac4	fix: update the signature of openai_list_files_in_vector_store in all VectorIO impls (#2503)	2025-06-24 18:55:56 +05:30
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
ehhuang	db2cd9e8f3	feat: support filters in file search (#2472) ... # What does this PR do? Move to use vector_stores.search for file search tool in Responses, which supports filters. closes #2435 ## Test Plan Added e2e test with fitlers. myenv ❯ llama stack run llama_stack/templates/fireworks/run.yaml pytest -sv tests/verifications/openai_api/test_responses.py \ -k 'file_search and filters' \ --base-url=http://localhost:8321/v1/openai/v1 \ --model=meta-llama/Llama-3.3-70B-Instruct	2025-06-18 21:50:55 -07:00
Varsha	2e8054bede	feat: Implement hybrid search in SQLite-vec (#2312) ... # What does this PR do? Add support for hybrid search mode in SQLite-vec provider, which combines keyword and vector search for better results. The implementation: - Adds hybrid search mode as a new option alongside vector and keyword search - Implements query_hybrid method in SQLiteVecIndex that: - First performs keyword search to get candidate matches - Then applies vector similarity search on those candidates - Updates documentation to reflect the new search mode This change improves search quality by leveraging both semantic similarity and keyword matching, while maintaining backward compatibility with existing vector and keyword search modes. ## Test Plan ``` pytest tests/unit/providers/vector_io/test_sqlite_vec.py -v -s --tb=short /Users/vnarsing/miniconda3/envs/stack-client/lib/python3.10/site-packages/pytest_asyncio/plugin.py:217: 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-8.3.5, pluggy-1.5.0 -- /Users/vnarsing/miniconda3/envs/stack-client/bin/python cachedir: .pytest_cache metadata: {'Python': '3.10.16', 'Platform': 'macOS-14.7.6-arm64-arm-64bit', 'Packages': {'pytest': '8.3.5', 'pluggy': '1.5.0'}, 'Plugins': {'html': '4.1.1', 'json-report': '1.5.0', 'timeout': '2.4.0', 'metadata': '3.1.1', 'anyio': '4.8.0', 'asyncio': '0.26.0', 'nbval': '0.11.0', 'cov': '6.1.1'}} rootdir: /Users/vnarsing/go/src/github/meta-llama/llama-stack configfile: pyproject.toml plugins: html-4.1.1, json-report-1.5.0, timeout-2.4.0, metadata-3.1.1, anyio-4.8.0, asyncio-0.26.0, nbval-0.11.0, cov-6.1.1 asyncio: mode=strict, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function collected 10 items tests/unit/providers/vector_io/test_sqlite_vec.py::test_add_chunks PASSED tests/unit/providers/vector_io/test_sqlite_vec.py::test_query_chunks_vector PASSED tests/unit/providers/vector_io/test_sqlite_vec.py::test_query_chunks_full_text_search PASSED tests/unit/providers/vector_io/test_sqlite_vec.py::test_query_chunks_hybrid PASSED tests/unit/providers/vector_io/test_sqlite_vec.py::test_query_chunks_full_text_search_k_greater_than_results PASSED tests/unit/providers/vector_io/test_sqlite_vec.py::test_chunk_id_conflict PASSED tests/unit/providers/vector_io/test_sqlite_vec.py::test_generate_chunk_id PASSED tests/unit/providers/vector_io/test_sqlite_vec.py::test_query_chunks_hybrid_no_keyword_matches PASSED tests/unit/providers/vector_io/test_sqlite_vec.py::test_query_chunks_hybrid_score_threshold PASSED tests/unit/providers/vector_io/test_sqlite_vec.py::test_query_chunks_hybrid_different_embedding PASSED ``` --------- Signed-off-by: Varsha Prasad Narsing <varshaprasad96@gmail.com>	2025-06-13 15:54:06 -04:00
Ben Browning	941f505eb0	feat: File search tool for Responses API (#2426) ... # What does this PR do? This is an initial working prototype of wiring up the `file_search` builtin tool for the Responses API to our existing rag knowledge search tool. This is me seeing what I could pull together on top of the bits we already have merged. This may not be the ideal way to implement this, and things like how I shuffle the vector store ids from the original response API tool request to the actual tool execution feel a bit hacky (grep for `tool_kwargs["vector_db_ids"]` in `_execute_tool_call` to see what I mean). ## Test Plan I stubbed in some new tests to exercise this using text and pdf documents. Note that this is currently under tests/verification only because it sometimes flakes with tool calling of the small Llama-3.2-3B model we run in CI (and that I use as an example below). We'd want to make the test a bit more robust in some way if we moved this over to tests/integration and ran it in CI. ### OpenAI SaaS (to verify test correctness) ``` pytest -sv tests/verifications/openai_api/test_responses.py \ -k 'file_search' \ --base-url=https://api.openai.com/v1 \ --model=gpt-4o ``` ### Fireworks with faiss vector store ``` llama stack run llama_stack/templates/fireworks/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-3.3-70B-Instruct ``` ### Ollama with faiss vector store This sometimes flakes on Ollama because the quantized small model doesn't always choose to call the tool to answer the user's question. But, it often works. ``` ollama run llama3.2:3b INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" \ llama stack run ./llama_stack/templates/ollama/run.yaml \ --image-type venv \ --env OLLAMA_URL="http://0.0.0.0:11434" 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 ``` ### OpenAI provider with sqlite-vec vector store ``` llama stack run ./llama_stack/templates/starter/run.yaml --image-type venv pytest -sv tests/verifications/openai_api/test_responses.py \ -k 'file_search' \ --base-url=http://localhost:8321/v1/openai/v1 \ --model=openai/gpt-4o-mini ``` ### Ensure existing vector store integration tests still pass ``` ollama run llama3.2:3b INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" \ llama stack run ./llama_stack/templates/ollama/run.yaml \ --image-type venv \ --env OLLAMA_URL="http://0.0.0.0:11434" LLAMA_STACK_CONFIG=http://localhost:8321 \ pytest -sv tests/integration/vector_io \ --text-model "meta-llama/Llama-3.2-3B-Instruct" \ --embedding-model=all-MiniLM-L6-v2 ``` --------- Signed-off-by: Ben Browning <bbrownin@redhat.com>	2025-06-13 14:32:48 -04:00
Hardik Shah	0bc1747ed8	feat: update search for vector_stores (#2441) ... Updated the `search` functionality return response to match openai. ## Test Plan ``` pytest -sv --stack-config=http://localhost:8321 tests/integration/vector_io/test_openai_vector_stores.py --embedding-model all-MiniLM-L6-v2 ```	2025-06-12 15:34:22 -07:00
Hardik Shah	de37a04c3e	fix: set appropriate defaults for params (#2434) ... Setting defaults to be `| None` else they get marked as required params in open-api spec.	2025-06-11 17:30:34 -07:00
Hardik Shah	d55100d9b7	feat: OpenAIVectorIOMixin for vector_stores common logic (#2427) ... Extracts common OpenAI vector-store code into its own mixin so that all providers can share the same core logic. This also makes it easy for Llama Stack to support both vector-stores and Llama Stack APIs in the interim so that both share the same underlying vector-dbs. Each provider contains storage specific logic to `create / edit / delete / list` vector dbs while the plumbing logic is standardized in the common code. Ensured that this works well with both faiss and sqllite-vec. ### Test Plan ``` llama stack run starter pytest -sv --stack-config http://localhost:8321 tests/integration/vector_io/test_openai_vector_stores.py --embedding-model all-MiniLM-L6-v2 ```	2025-06-11 15:40:57 -07:00
Hardik Shah	5ac43268e8	feat: Add OpenAI compat /v1/vector_store APIs (#2423) ... Adding OpenAI compat `/v1/vector-store` apis. This PR implements the `faiss` provider with followup PRs coming up for other providers. Added routes to create, update, delete, list vector stores. Also added route to search a vector store Inserting into vector stores is missing and will be a follow up diff. ### Test Plan - Added new integration test for testing the faiss provider ``` pytest -sv --stack-config http://localhost:8321 tests/integration/vector_io/test_openai_vector_stores.py --embedding-model all-MiniLM-L6-v2 ```	2025-06-10 13:07:39 -07:00
Hardik Shah	1f48577a02	fix: ChromaDB provider (#2413) ... fixes the remote::chromaDB provider for vector_io by updating the method definition appropriately. Fixed impl to use score_threshold properly. ### Test Plan ``` # Start Chroma Docker docker run --rm \ --name chromadb \ -p 8800:8000 \ -v ~/chroma:/chroma/chroma \ -e IS_PERSISTENT=TRUE \ -e ANONYMIZED_TELEMETRY=FALSE \ chromadb/chroma:latest # run pytest CHROMADB_URL="http://localhost:8800" pytest -sv tests/integration/vector_io/test_vector_io.py --stack-config vector_io=remote::chromadb,inference=fireworks --embedding-model nomic-ai/nomic-embed-text-v1.5 ```	2025-06-06 11:25:58 -07:00
Varsha	e92301f2d7	feat(sqlite-vec): enable keyword search for sqlite-vec (#1439) ... # What does this PR do? This PR introduces support for keyword based FTS5 search with BM25 relevance scoring. It makes changes to the existing EmbeddingIndex base class in order to support a search_mode and query_str parameter, that can be used for keyword based search implementations. [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan run ``` pytest llama_stack/providers/tests/vector_io/test_sqlite_vec.py -v -s --tb=short --disable-warnings --asyncio-mode=auto ``` Output: ``` pytest llama_stack/providers/tests/vector_io/test_sqlite_vec.py -v -s --tb=short --disable-warnings --asyncio-mode=auto /Users/vnarsing/miniconda3/envs/stack-client/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/vnarsing/miniconda3/envs/stack-client/bin/python cachedir: .pytest_cache metadata: {'Python': '3.10.16', 'Platform': 'macOS-14.7.4-arm64-arm-64bit', 'Packages': {'pytest': '8.3.4', 'pluggy': '1.5.0'}, 'Plugins': {'html': '4.1.1', 'metadata': '3.1.1', 'asyncio': '0.25.3', 'anyio': '4.8.0'}} rootdir: /Users/vnarsing/go/src/github/meta-llama/llama-stack configfile: pyproject.toml plugins: html-4.1.1, metadata-3.1.1, asyncio-0.25.3, anyio-4.8.0 asyncio: mode=auto, asyncio_default_fixture_loop_scope=None collected 7 items llama_stack/providers/tests/vector_io/test_sqlite_vec.py::test_add_chunks PASSED llama_stack/providers/tests/vector_io/test_sqlite_vec.py::test_query_chunks_vector PASSED llama_stack/providers/tests/vector_io/test_sqlite_vec.py::test_query_chunks_fts PASSED llama_stack/providers/tests/vector_io/test_sqlite_vec.py::test_chunk_id_conflict PASSED llama_stack/providers/tests/vector_io/test_sqlite_vec.py::test_register_vector_db PASSED llama_stack/providers/tests/vector_io/test_sqlite_vec.py::test_unregister_vector_db PASSED llama_stack/providers/tests/vector_io/test_sqlite_vec.py::test_generate_chunk_id PASSED ``` For reference, with the implementation, the fts table looks like below: ``` Chunk ID: 9fbc39ce-c729-64a2-260f-c5ec9bb2a33e, Content: Sentence 0 from document 0 Chunk ID: 94062914-3e23-44cf-1e50-9e25821ba882, Content: Sentence 1 from document 0 Chunk ID: e6cfd559-4641-33ba-6ce1-7038226495eb, Content: Sentence 2 from document 0 Chunk ID: 1383af9b-f1f0-f417-4de5-65fe9456cc20, Content: Sentence 3 from document 0 Chunk ID: 2db19b1a-de14-353b-f4e1-085e8463361c, Content: Sentence 4 from document 0 Chunk ID: 9faf986a-f028-7714-068a-1c795e8f2598, Content: Sentence 5 from document 0 Chunk ID: ef593ead-5a4a-392f-7ad8-471a50f033e8, Content: Sentence 6 from document 0 Chunk ID: e161950f-021f-7300-4d05-3166738b94cf, Content: Sentence 7 from document 0 Chunk ID: 90610fc4-67c1-e740-f043-709c5978867a, Content: Sentence 8 from document 0 Chunk ID: 97712879-6fff-98ad-0558-e9f42e6b81d3, Content: Sentence 9 from document 0 Chunk ID: aea70411-51df-61ba-d2f0-cb2b5972c210, Content: Sentence 0 from document 1 Chunk ID: b678a463-7b84-92b8-abb2-27e9a1977e3c, Content: Sentence 1 from document 1 Chunk ID: 27bd63da-909c-1606-a109-75bdb9479882, Content: Sentence 2 from document 1 Chunk ID: a2ad49ad-f9be-5372-e0c7-7b0221d0b53e, Content: Sentence 3 from document 1 Chunk ID: cac53bcd-1965-082a-c0f4-ceee7323fc70, Content: Sentence 4 from document 1 ``` Query results: Result 1: Sentence 5 from document 0 Result 2: Sentence 5 from document 1 Result 3: Sentence 5 from document 2 [//]: # (## Documentation) --------- Signed-off-by: Varsha Prasad Narsing <varshaprasad96@gmail.com>	2025-05-21 15:24:24 -04:00
Matthew Farrellee	9a6e91cd93	fix: chromadb type hint (#2136) ... ``` $ INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \ CHROMADB_URL=http://localhost:8000 \ llama stack build --image-type conda --image-name llama \ --providers vector_io=remote::chromadb,inference=remote::ollama \ --run ... File ".../llama_stack/providers/remote/vector_io/chroma/chroma.py", line 31, in <module> ChromaClientType = chromadb.AsyncHttpClient | chromadb.PersistentClient TypeError: unsupported operand type(s) for |: 'function' and 'function' ``` issue: AsyncHttpClient and PersistentClient are functions that return AsyncClientAPI and ClientAPI types, respectively. | cannot be used to construct a type from functions. previously the code was Union[AsyncHttpClient, PersistentClient], which did not trigger an error # What does this PR do? Closes #2135	2025-05-12 06:27:01 -07:00
Ihar Hrachyshka	9e6561a1ec	chore: enable pyupgrade fixes (#1806) ... # What does this PR do? The goal of this PR is code base modernization. Schema reflection code needed a minor adjustment to handle UnionTypes and collections.abc.AsyncIterator. (Both are preferred for latest Python releases.) Note to reviewers: almost all changes here are automatically generated by pyupgrade. Some additional unused imports were cleaned up. The only change worth of note can be found under `docs/openapi_generator` and `llama_stack/strong_typing/schema.py` where reflection code was updated to deal with "newer" types. Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>	2025-05-01 14:23:50 -07:00
Ashwin Bharambe	6609d4ada4	feat: allow conditionally enabling providers in run.yaml (#1321) ... # What does this PR do? We want to bundle a bunch of (typically remote) providers in a distro template and be able to configure them "on the fly" via environment variables. So far, we have been able to do this with simple env var replacements. However, sometimes you want to only conditionally enable providers (because the relevant remote services may not be alive, or relevant.) This was not possible until now. To aid this, we add a simple (bash-like) env var replacement enhancement: `${env.FOO+bar}` evaluates to `bar` if the variable is SET and evaluates to empty string if it is not. On top of that, we update our main resolver to ignore any provider whose ID is null. This allows using the distro like this: ```bash llama stack run dev --env CHROMADB_URL=http://localhost:6001 --env ENABLE_CHROMADB=1 ``` when only Chroma is UP. This disables the other `pgvector` provider in the run configuration. ## Test Plan Hard code `chromadb` as the vector io provider inside `test_vector_io.py` and run: ```bash LLAMA_STACK_BASE_URL=http://localhost:8321 pytest -s -v tests/client-sdk/vector_io/ --embedding-model all-MiniLM-L6-v2 ```	2025-03-01 11:19:14 -08:00
Sébastien Han	c0ee512980	build: configure ruff from pyproject.toml (#1100) ... # What does this PR do? - Remove hardcoded configurations from pre-commit. - Allow configuration to be set via pyproject.toml. - Merge .ruff.toml settings into pyproject.toml. - Ensure the linter and formatter use the defined configuration instead of being overridden by pre-commit. 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) Signed-off-by: Sébastien Han <seb@redhat.com>	2025-02-14 09:01:57 -08:00
Yuan Tang	5858777ff0	fix: Update VectorIO config classes in registry (#1079) ... This was missed in https://github.com/meta-llama/llama-stack/pull/1023. ``` Traceback (most recent call last): File "/home/yutang/.conda/envs/distribution-myenv/lib/python3.10/runpy.py", line 196, in _run_module_as_main return _run_code(code, main_globals, None, File "/home/yutang/.conda/envs/distribution-myenv/lib/python3.10/runpy.py", line 86, in _run_code exec(code, run_globals) File "/home/yutang/repos/llama-stack/llama_stack/distribution/server/server.py", line 488, in <module> main() File "/home/yutang/repos/llama-stack/llama_stack/distribution/server/server.py", line 389, in main impls = asyncio.run(construct_stack(config)) File "/home/yutang/.conda/envs/distribution-myenv/lib/python3.10/asyncio/runners.py", line 44, in run return loop.run_until_complete(main) File "/home/yutang/.conda/envs/distribution-myenv/lib/python3.10/asyncio/base_events.py", line 649, in run_until_complete return future.result() File "/home/yutang/repos/llama-stack/llama_stack/distribution/stack.py", line 202, in construct_stack impls = await resolve_impls(run_config, provider_registry or get_provider_registry(), dist_registry) File "/home/yutang/repos/llama-stack/llama_stack/distribution/resolver.py", line 230, in resolve_impls impl = await instantiate_provider( File "/home/yutang/repos/llama-stack/llama_stack/distribution/resolver.py", line 312, in instantiate_provider config_type = instantiate_class_type(provider_spec.config_class) File "/home/yutang/repos/llama-stack/llama_stack/distribution/utils/dynamic.py", line 13, in instantiate_class_type return getattr(module, class_name) AttributeError: module 'llama_stack.providers.inline.vector_io.faiss' has no attribute 'FaissImplConfig' ``` --------- Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>	2025-02-13 15:39:13 -08:00
Yuan Tang	8ff27b58fa	chore: Consistent naming for VectorIO providers (#1023) ... # What does this PR do? This changes all VectorIO providers classes to follow the pattern `<ProviderName>VectorIOConfig` and `<ProviderName>VectorIOAdapter`. All API endpoints for VectorIOs are currently consistent with `/vector-io`. Note that API endpoint for VectorDB stay unchanged as `/vector-dbs`. ## Test Plan I don't have a way to test all providers. This is a simple renaming so things should work as expected. --------- Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>	2025-02-13 13:15:49 -05:00
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
Ashwin Bharambe	f2feb7d15c	Fix Chroma adapter (#893) ... Chroma method had the wrong signature. ## Test Plan Start Chroma: `chroma run --path /tmp/foo/chroma2 --host localhost --port 6001` Modify run.yaml to include Chroma server pointing to localhost:6001 and run `llama stack run` Then: ```bash LLAMA_STACK_BASE_URL=http://localhost:8321 pytest -s -v agents/test_agents.py -k rag ``` passes	2025-01-28 13:19:47 -08:00
Ashwin Bharambe	c9e5578151	[memory refactor][5/n] Migrate all vector_io providers (#835) ... See https://github.com/meta-llama/llama-stack/issues/827 for the broader design. This PR finishes off all the stragglers and migrates everything to the new naming.	2025-01-22 10:17:59 -08:00
Ashwin Bharambe	3ae8585b65	[memory refactor][1/n] Rename Memory -> VectorIO, MemoryBanks -> VectorDBs (#828) ... See https://github.com/meta-llama/llama-stack/issues/827 for the broader design. This is the first part: - delete other kinds of memory banks (keyvalue, keyword, graph) for now; we will introduce a keyvalue store API as part of this design but not use it in the RAG tool yet. - renaming of the APIs	2025-01-22 09:59:30 -08:00