From 3dc02310b62c473c0764f10f08aef678291e9aaf Mon Sep 17 00:00:00 2001 From: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com> Date: Thu, 14 Nov 2024 14:13:12 -0800 Subject: [PATCH] upgrade chroma and adjust embedder function generator (#1607) * upgrade chroma and adjust embedder function generator * >= version * linted --- pyproject.toml | 2 +- src/crewai/memory/entity/entity_memory.py | 2 +- src/crewai/memory/storage/rag_storage.py | 88 ++++++++++++++--------- uv.lock | 84 +++++++++------------- 4 files changed, 87 insertions(+), 89 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 66adfee3e7..57868636ff 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -27,8 +27,8 @@ dependencies = [ "pyvis>=0.3.2", "uv>=0.4.25", "tomli-w>=1.1.0", - "chromadb>=0.4.24", "tomli>=2.0.2", + "chromadb>=0.5.18", ] [project.urls] diff --git a/src/crewai/memory/entity/entity_memory.py b/src/crewai/memory/entity/entity_memory.py index 134e19bfad..88d33c09a2 100644 --- a/src/crewai/memory/entity/entity_memory.py +++ b/src/crewai/memory/entity/entity_memory.py @@ -30,7 +30,7 @@ def __init__(self, crew=None, embedder_config=None, storage=None): if storage else RAGStorage( type="entities", - allow_reset=False, + allow_reset=True, embedder_config=embedder_config, crew=crew, ) diff --git a/src/crewai/memory/storage/rag_storage.py b/src/crewai/memory/storage/rag_storage.py index d0f1cfc645..7af5fb5544 100644 --- a/src/crewai/memory/storage/rag_storage.py +++ b/src/crewai/memory/storage/rag_storage.py @@ -51,8 +51,6 @@ def __init__(self, type, allow_reset=True, embedder_config=None, crew=None): self._initialize_app() def _set_embedder_config(self): - import chromadb.utils.embedding_functions as embedding_functions - if self.embedder_config is None: self.embedder_config = self._create_default_embedding_function() @@ -61,12 +59,20 @@ def _set_embedder_config(self): config = self.embedder_config.get("config", {}) model_name = config.get("model") if provider == "openai": - self.embedder_config = embedding_functions.OpenAIEmbeddingFunction( + from chromadb.utils.embedding_functions.openai_embedding_function import ( + OpenAIEmbeddingFunction, + ) + + self.embedder_config = OpenAIEmbeddingFunction( api_key=config.get("api_key") or os.getenv("OPENAI_API_KEY"), model_name=model_name, ) elif provider == "azure": - self.embedder_config = embedding_functions.OpenAIEmbeddingFunction( + from chromadb.utils.embedding_functions.openai_embedding_function import ( + OpenAIEmbeddingFunction, + ) + + self.embedder_config = OpenAIEmbeddingFunction( api_key=config.get("api_key"), api_base=config.get("api_base"), api_type=config.get("api_type", "azure"), @@ -74,45 +80,55 @@ def _set_embedder_config(self): model_name=model_name, ) elif provider == "ollama": - from openai import OpenAI - - class OllamaEmbeddingFunction(EmbeddingFunction): - def __call__(self, input: Documents) -> Embeddings: - client = OpenAI( - base_url="http://localhost:11434/v1", - api_key=config.get("api_key", "ollama"), - ) - try: - response = client.embeddings.create( - input=input, model=model_name - ) - embeddings = [item.embedding for item in response.data] - return cast(Embeddings, embeddings) - except Exception as e: - raise e + from chromadb.utils.embedding_functions.ollama_embedding_function import ( + OllamaEmbeddingFunction, + ) - self.embedder_config = OllamaEmbeddingFunction() + self.embedder_config = OllamaEmbeddingFunction( + url=config.get("url", "http://localhost:11434/api/embeddings"), + model_name=model_name, + ) elif provider == "vertexai": - self.embedder_config = ( - embedding_functions.GoogleVertexEmbeddingFunction( - model_name=model_name, - api_key=config.get("api_key"), - ) + from chromadb.utils.embedding_functions.google_embedding_function import ( + GoogleVertexEmbeddingFunction, + ) + + self.embedder_config = GoogleVertexEmbeddingFunction( + model_name=model_name, + api_key=config.get("api_key"), ) elif provider == "google": - self.embedder_config = ( - embedding_functions.GoogleGenerativeAiEmbeddingFunction( - model_name=model_name, - api_key=config.get("api_key"), - ) + from chromadb.utils.embedding_functions.google_embedding_function import ( + GoogleGenerativeAiEmbeddingFunction, + ) + + self.embedder_config = GoogleGenerativeAiEmbeddingFunction( + model_name=model_name, + api_key=config.get("api_key"), ) elif provider == "cohere": - self.embedder_config = embedding_functions.CohereEmbeddingFunction( + from chromadb.utils.embedding_functions.cohere_embedding_function import ( + CohereEmbeddingFunction, + ) + + self.embedder_config = CohereEmbeddingFunction( model_name=model_name, api_key=config.get("api_key"), ) + elif provider == "bedrock": + from chromadb.utils.embedding_functions.amazon_bedrock_embedding_function import ( + AmazonBedrockEmbeddingFunction, + ) + + self.embedder_config = AmazonBedrockEmbeddingFunction( + session=config.get("session"), + ) elif provider == "huggingface": - self.embedder_config = embedding_functions.HuggingFaceEmbeddingServer( + from chromadb.utils.embedding_functions.huggingface_embedding_function import ( + HuggingFaceEmbeddingServer, + ) + + self.embedder_config = HuggingFaceEmbeddingServer( url=config.get("api_url"), ) elif provider == "watson": @@ -253,8 +269,10 @@ def reset(self) -> None: ) def _create_default_embedding_function(self): - import chromadb.utils.embedding_functions as embedding_functions + from chromadb.utils.embedding_functions.openai_embedding_function import ( + OpenAIEmbeddingFunction, + ) - 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