fix: Update embedding configuration and fix type errors

- Add configurable embedding provider support
- Remove OpenAI dependency for memory reset
- Add tests for different embedding providers
- Fix type hints and improve docstrings

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

src/crewai/crew.py

@@ -1,10 +1,11 @@
 import asyncio
 import json
+import re
 import uuid
 import warnings
 from concurrent.futures import Future
 from hashlib import md5
-from typing import Any, Callable, Dict, List, Optional, Tuple, Union
+from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union
 
 from pydantic import (
     UUID4,

src/crewai/memory/storage/rag_storage.py

@@ -163,12 +163,3 @@ class RAGStorage(BaseRAGStorage):
                 raise Exception(
                     f"An error occurred while resetting the {self.type} memory: {e}"
                 )
-
-    def _create_default_embedding_function(self):
-        from chromadb.utils.embedding_functions.openai_embedding_function import (
-            OpenAIEmbeddingFunction,
-        )
-
-        return OpenAIEmbeddingFunction(
-            api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"
-        )

src/crewai/utilities/embedding_configurator.py

@@ -1,5 +1,5 @@
 import os
-from typing import Any, Dict, cast
+from typing import Any, Dict, Optional, cast
 
 from chromadb import Documents, EmbeddingFunction, Embeddings
 from chromadb.api.types import validate_embedding_function
@@ -21,9 +21,36 @@ 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."""
+        """Configure and return an embedding function based on the provided config.
+        
+        Args:
+            embedder_config: Optional configuration dictionary containing:
+                - provider: Name of the embedding provider or EmbeddingFunction instance
+                - config: Provider-specific configuration dictionary with options like:
+                    - api_key: API key for the provider
+                    - model: Model name to use for embeddings
+                    - url: API endpoint URL (for some providers)
+                    - session: Session object (for some providers)
+        
+        Returns:
+            EmbeddingFunction: Configured embedding function for the specified provider
+            
+        Raises:
+            ValueError: If custom embedding function is invalid
+            Exception: If provider is not supported or configuration is invalid
+            
+        Examples:
+            >>> config = {
+            ...     "provider": "openai",
+            ...     "config": {
+            ...         "api_key": "your-api-key",
+            ...         "model": "text-embedding-3-small"
+            ...     }
+            ... }
+            >>> embedder = EmbeddingConfigurator().configure_embedder(config)
+        """
         if embedder_config is None:
             return self._create_default_embedding_function()
 
@@ -47,12 +74,23 @@ class EmbeddingConfigurator:
 
     @staticmethod
     def _create_default_embedding_function():
-        from chromadb.utils.embedding_functions.openai_embedding_function import (
-            OpenAIEmbeddingFunction,
-        )
-
-        return OpenAIEmbeddingFunction(
-            api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"
+        """Create a default embedding function based on environment variables.
+        
+        Environment Variables:
+            CREWAI_EMBEDDING_PROVIDER: The embedding provider to use (default: "openai")
+            CREWAI_EMBEDDING_MODEL: The model to use for embeddings
+            OPENAI_API_KEY: API key for OpenAI (required if using OpenAI provider)
+        
+        Returns:
+            EmbeddingFunction: Configured embedding function
+        """
+        provider = os.getenv("CREWAI_EMBEDDING_PROVIDER", "openai")
+        config = {
+            "api_key": os.getenv("OPENAI_API_KEY"),
+            "model": os.getenv("CREWAI_EMBEDDING_MODEL", "text-embedding-3-small")
+        }
+        return EmbeddingConfigurator().configure_embedder(
+            {"provider": provider, "config": config}
         )
 
     @staticmethod