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Author SHA1 Message Date
Mustafa Elbehery
b2c7543af7
fix(vectordb): VectorDBInput has no provider_id (#2830)
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# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
This PR add `provider_id` field to `VectorDBInput` class.

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

fixes https://github.com/meta-llama/llama-stack/issues/2819

Signed-off-by: Mustafa Elbehery <melbeher@redhat.com>
 2025-07-21 14:03:40 +02:00
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
Sébastien Han
ac5fd57387
chore: remove nested imports (#2515) 
# What does this PR do?

* Given that our API packages use "import *" in `__init.py__` we don't
need to do `from llama_stack.apis.models.models` but simply from
llama_stack.apis.models. The decision to use `import *` is debatable and
should probably be revisited at one point.

* Remove unneeded Ruff F401 rule
* Consolidate Ruff F403 rule in the pyprojectfrom
llama_stack.apis.models.models

Signed-off-by: Sébastien Han <seb@redhat.com>
 2025-06-26 08:01:05 +05:30
Sébastien Han
bb5fca9521
chore: more API validators (#2165) 
# What does this PR do?

We added:

* make sure docstrings are present with 'params' and 'returns'
* fail if someone sets 'returns: None'
* fix the failing APIs

Signed-off-by: Sébastien Han <seb@redhat.com>
 2025-05-15 11:22:51 -07:00
Sébastien Han
1a529705da
chore: more mypy fixes (#2029) 
# What does this PR do?

Mainly tried to cover the entire llama_stack/apis directory, we only
have one left. Some excludes were just noop.

Signed-off-by: Sébastien Han <seb@redhat.com>
 2025-05-06 09:52:31 -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
Sébastien Han
c029fbcd13
fix: return 4xx for non-existent resources in GET requests (#1635) 
# What does this PR do?

- Removed Optional return types for GET methods
- Raised ValueError when requested resource is not found
- Ensures proper 4xx response for missing resources
- Updated the API generator to check for wrong signatures

```
$ uv run --with ".[dev]" ./docs/openapi_generator/run_openapi_generator.sh
Validating API method return types...

API Method Return Type Validation Errors:

Method ScoringFunctions.get_scoring_function returns Optional type
```

Closes: https://github.com/meta-llama/llama-stack/issues/1630

## Test Plan

Run the server then:

```
curl http://127.0.0.1:8321/v1/models/foo     
{"detail":"Invalid value: Model 'foo' not found"}%  
```

Server log:

```
INFO:     127.0.0.1:52307 - "GET /v1/models/foo HTTP/1.1" 400 Bad Request
09:51:42.654 [END] /v1/models/foo [StatusCode.OK] (134.65ms)
 09:51:42.651 [ERROR] Error executing endpoint route='/v1/models/{model_id:path}' method='get'
Traceback (most recent call last):
  File "/Users/leseb/Documents/AI/llama-stack/llama_stack/distribution/server/server.py", line 193, in endpoint
    return await maybe_await(value)
  File "/Users/leseb/Documents/AI/llama-stack/llama_stack/distribution/server/server.py", line 156, in maybe_await
    return await value
  File "/Users/leseb/Documents/AI/llama-stack/llama_stack/providers/utils/telemetry/trace_protocol.py", line 102, in async_wrapper
    result = await method(self, *args, **kwargs)
  File "/Users/leseb/Documents/AI/llama-stack/llama_stack/distribution/routers/routing_tables.py", line 217, in get_model
    raise ValueError(f"Model '{model_id}' not found")
ValueError: Model 'foo' not found
```

Signed-off-by: Sébastien Han <seb@redhat.com>
 2025-03-18 14:06:53 -07:00
Ashwin Bharambe
314ee09ae3
chore: move all Llama Stack types from llama-models to llama-stack (#1098) 
llama-models should have extremely minimal cruft. Its sole purpose
should be didactic -- show the simplest implementation of the llama
models and document the prompt formats, etc.

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

## Test Plan

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

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

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

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

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

```bash
cd docs/openapi_generator
sh run_openapi_generator.sh
```
 2025-02-14 09:10:59 -08:00
Xi Yan
2fa9e3c941
fix: make backslash work in GET /models/{model_id:path} (#1068) 2025-02-13 08:46:43 -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