fix: Remove OpenAI dependency for memory reset when using alternative LLMs

- Add environment variables for default embedding provider
- Support Ollama as default embedding provider
- Add tests for memory reset with different providers
- Update documentation

Fixes #2023

Co-Authored-By: Joe Moura <joao@crewai.com>

src/crewai/utilities/embedding_configurator.py

@@ -1,9 +1,15 @@
 import os
-from typing import Any, Dict, cast
+from typing import Any, Dict, List, Optional, cast
 
 from chromadb import Documents, EmbeddingFunction, Embeddings
 from chromadb.api.types import validate_embedding_function
 
+from crewai.utilities.exceptions.embedding_exceptions import (
+    EmbeddingConfigurationError,
+    EmbeddingProviderError,
+    EmbeddingInitializationError
+)
+
 
 class EmbeddingConfigurator:
     def __init__(self):
@@ -21,9 +27,21 @@ class EmbeddingConfigurator:
 
     def configure_embedder(
         self,
-        embedder_config: Dict[str, Any] | None = None,
+        embedder_config: Optional[Dict[str, Any]] = None,
     ) -> EmbeddingFunction:
-        """Configures and returns an embedding function based on the provided config."""
+        """Configures and returns an embedding function based on the provided config.
+
+        Args:
+            embedder_config: Configuration dictionary containing provider and settings
+
+        Returns:
+            EmbeddingFunction: Configured embedding function for vector storage
+
+        Raises:
+            EmbeddingProviderError: If the provider is not supported
+            EmbeddingConfigurationError: If the configuration is invalid
+            EmbeddingInitializationError: If the embedding function fails to initialize
+        """
         if embedder_config is None:
             return self._create_default_embedding_function()
 
@@ -36,11 +54,11 @@ class EmbeddingConfigurator:
                 validate_embedding_function(provider)
                 return provider
             except Exception as e:
-                raise ValueError(f"Invalid custom embedding function: {str(e)}")
+                raise EmbeddingConfigurationError(f"Invalid custom embedding function: {str(e)}")
 
         if not provider or provider not in self.embedding_functions:
-            raise Exception(
-                f"Unsupported embedding provider: {provider}, supported providers: {list(self.embedding_functions.keys())}"
+            raise EmbeddingProviderError(
+                str(provider), list(self.embedding_functions.keys())
             )
 
         return self.embedding_functions[str(provider)](config, model_name)
@@ -57,9 +75,10 @@ class EmbeddingConfigurator:
             return OpenAIEmbeddingFunction(api_key=os.getenv("OPENAI_API_KEY"), model_name=model)
         elif provider == "ollama":
             from chromadb.utils.embedding_functions.ollama_embedding_function import OllamaEmbeddingFunction
-            return OllamaEmbeddingFunction(url=os.getenv("CREWAI_OLLAMA_URL", "http://localhost:11434/api/embeddings"), model_name=model)
+            url = os.getenv("CREWAI_OLLAMA_URL", "http://localhost:11434/api/embeddings")
+            return OllamaEmbeddingFunction(url=url, model_name=model)
         else:
-            raise ValueError(f"Unsupported default embedding provider: {provider}. Set CREWAI_EMBEDDING_PROVIDER to 'openai' or 'ollama'")
+            raise EmbeddingProviderError(provider, ["openai", "ollama"])
 
     @staticmethod
     def _configure_openai(config, model_name):
@@ -157,9 +176,10 @@ class EmbeddingConfigurator:
             from ibm_watsonx_ai import Credentials
             from ibm_watsonx_ai.metanames import EmbedTextParamsMetaNames as EmbedParams
         except ImportError as e:
-            raise ImportError(
-                "IBM Watson dependencies are not installed. Please install them to use Watson embedding."
-            ) from e
+            raise EmbeddingConfigurationError(
+                "IBM Watson dependencies are not installed. Please install them to use Watson embedding.",
+                provider="watson"
+            )
 
         class WatsonEmbeddingFunction(EmbeddingFunction):
             def __call__(self, input: Documents) -> Embeddings:
@@ -184,7 +204,6 @@ class EmbeddingConfigurator:
                     embeddings = embedding.embed_documents(input)
                     return cast(Embeddings, embeddings)
                 except Exception as e:
-                    print("Error during Watson embedding:", e)
-                    raise e
+                    raise EmbeddingInitializationError("watson", str(e))
 
         return WatsonEmbeddingFunction()

src/crewai/utilities/exceptions/embedding_exceptions.py

@@ -0,0 +1,20 @@
+from typing import List, Optional
+
+
+class EmbeddingConfigurationError(Exception):
+    def __init__(self, message: str, provider: Optional[str] = None):
+        self.message = message
+        self.provider = provider
+        super().__init__(self.message)
+
+
+class EmbeddingProviderError(EmbeddingConfigurationError):
+    def __init__(self, provider: str, supported_providers: List[str]):
+        message = f"Unsupported embedding provider: {provider}, supported providers: {supported_providers}"
+        super().__init__(message, provider)
+
+
+class EmbeddingInitializationError(EmbeddingConfigurationError):
+    def __init__(self, provider: str, error: str):
+        message = f"Failed to initialize embedding function for provider {provider}: {error}"
+        super().__init__(message, provider)