From 1ada95ce5dd93a1e61ea600d738818a5a72d3bb4 Mon Sep 17 00:00:00 2001 From: Charles Packer Date: Tue, 5 Mar 2024 13:52:54 -0800 Subject: [PATCH] ci: patch embedding issue in tests (#1096) --- memgpt/embeddings.py | 23 ++- poetry.lock | 300 +++++++++++++++++++++++++++++++++++- pyproject.toml | 1 + tests/test_load_archival.py | 20 ++- 4 files changed, 338 insertions(+), 6 deletions(-) diff --git a/memgpt/embeddings.py b/memgpt/embeddings.py index cae4167f..ee7d4b80 100644 --- a/memgpt/embeddings.py +++ b/memgpt/embeddings.py @@ -158,12 +158,25 @@ def embedding_model(config: EmbeddingConfig, user_id: Optional[uuid.UUID] = None credentials = MemGPTCredentials.load() if endpoint_type == "openai": + assert credentials.openai_key is not None from llama_index.embeddings.openai import OpenAIEmbedding additional_kwargs = {"user_id": user_id} if user_id else {} - model = OpenAIEmbedding(api_base=config.embedding_endpoint, api_key=credentials.openai_key, additional_kwargs=additional_kwargs) + model = OpenAIEmbedding( + api_base=config.embedding_endpoint, + api_key=credentials.openai_key, + additional_kwargs=additional_kwargs, + ) return model + elif endpoint_type == "azure": + assert all( + [ + credentials.azure_key is not None, + credentials.azure_embedding_endpoint is not None, + credentials.azure_version is not None, + ] + ) from llama_index.embeddings.azure_openai import AzureOpenAIEmbedding # https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#embeddings @@ -176,7 +189,13 @@ def embedding_model(config: EmbeddingConfig, user_id: Optional[uuid.UUID] = None azure_endpoint=credentials.azure_endpoint, api_version=credentials.azure_version, ) + elif endpoint_type == "hugging-face": - return EmbeddingEndpoint(model=config.embedding_model, base_url=config.embedding_endpoint, user=user_id) + return EmbeddingEndpoint( + model=config.embedding_model, + base_url=config.embedding_endpoint, + user=user_id, + ) + else: return default_embedding_model() diff --git 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Azure Identity Library for Python" +optional = false +python-versions = ">=3.7" +files = [ + {file = "azure-identity-1.15.0.tar.gz", hash = "sha256:4c28fc246b7f9265610eb5261d65931183d019a23d4b0e99357facb2e6c227c8"}, + {file = "azure_identity-1.15.0-py3-none-any.whl", hash = "sha256:a14b1f01c7036f11f148f22cd8c16e05035293d714458d6b44ddf534d93eb912"}, +] + +[package.dependencies] +azure-core = ">=1.23.0,<2.0.0" +cryptography = ">=2.5" +msal = ">=1.24.0,<2.0.0" +msal-extensions = ">=0.3.0,<2.0.0" + [[package]] name = "backoff" version = "2.2.1" @@ -397,6 +433,70 @@ files = [ {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"}, ] +[[package]] +name = "cffi" +version = "1.16.0" +description = "Foreign Function Interface for Python calling C code." +optional = false +python-versions = ">=3.8" +files = [ + {file = "cffi-1.16.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = 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e42200c4..0ef230ae 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -55,6 +55,7 @@ llama-index-embeddings-huggingface = "^0.1.4" python-box = "^7.1.1" pytest-order = {version = "^1.2.0", optional = true} sqlmodel = "^0.0.16" +llama-index-embeddings-azure-openai = "^0.1.6" [tool.poetry.extras] postgres = ["pgvector", "pg8000"] diff --git a/tests/test_load_archival.py b/tests/test_load_archival.py index 786976c3..f89d9139 100644 --- a/tests/test_load_archival.py +++ b/tests/test_load_archival.py @@ -71,6 +71,7 @@ def test_load_directory(metadata_storage_connector, passage_storage_connector, c # embedding config if os.getenv("OPENAI_API_KEY"): + print("Using OpenAI embeddings for testing") credentials = MemGPTCredentials( openai_key=os.getenv("OPENAI_API_KEY"), ) @@ -83,12 +84,25 @@ def test_load_directory(metadata_storage_connector, passage_storage_connector, c ) else: + # print("Using local embedding model for testing") + # embedding_config = EmbeddingConfig( + # embedding_endpoint_type="local", + # embedding_endpoint=None, + # embedding_dim=384, + # ) + + print("Using official hosted embedding model for testing") embedding_config = EmbeddingConfig( - embedding_endpoint_type="local", - embedding_endpoint=None, - embedding_dim=384, + embedding_endpoint_type="hugging-face", + embedding_endpoint="https://embeddings.memgpt.ai", + embedding_model="BAAI/bge-large-en-v1.5", + embedding_dim=1024, ) + # write out the config so that the 'load' command will use it (CLI commands pull from config) + config.default_embedding_config = embedding_config + config.save() + # create user and agent agent = AgentState( user_id=user.id,