Enhance error handling and type annotations for optional chromadb dependency

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

README.md

@@ -136,6 +136,14 @@ pip install 'crewai[tools]'
 ```
 The command above installs the basic package and also adds extra components which require more dependencies to function.
 
+For vector storage and RAG capabilities, install with the chromadb extra:
+
+```shell
+pip install 'crewai[chromadb]'
+```
+
+Note: If you're using Alpine Linux or other environments where onnxruntime is not available, you can still use CrewAI without the chromadb dependency, but with limited vector storage functionality.
+
 ### Troubleshooting Dependencies
 
 If you encounter issues during installation or usage, here are some common solutions:

pyproject.toml

@@ -21,7 +21,6 @@ dependencies = [
     "opentelemetry-sdk>=1.22.0",
     "opentelemetry-exporter-otlp-proto-http>=1.22.0",
     # Data Handling
-    "chromadb>=0.5.23",
     "openpyxl>=3.1.5",
     "pyvis>=0.3.2",
     # Authentication and Security
@@ -64,6 +63,9 @@ mem0 = ["mem0ai>=0.1.29"]
 docling = [
     "docling>=2.12.0",
 ]
+chromadb = [
+    "chromadb>=0.5.23",
+]
 
 [tool.uv]
 dev-dependencies = [

src/crewai/knowledge/storage/knowledge_storage.py

@@ -6,11 +6,18 @@ import os
 import shutil
 from typing import Any, Dict, List, Optional, Union, cast
 
-import chromadb
+try:
-import chromadb.errors
+    import chromadb
-from chromadb.api import ClientAPI
+    import chromadb.errors
-from chromadb.api.types import OneOrMany
+    from chromadb.api import ClientAPI
-from chromadb.config import Settings
+    from chromadb.api.types import OneOrMany
+    from chromadb.config import Settings
+    CHROMADB_AVAILABLE = True
+except ImportError:
+    CHROMADB_AVAILABLE = False
+    # Define placeholder types for type checking
+    ClientAPI = Any
+    OneOrMany = Any
 
 from crewai.knowledge.storage.base_knowledge_storage import BaseKnowledgeStorage
 from crewai.utilities import EmbeddingConfigurator
@@ -42,9 +49,10 @@ class KnowledgeStorage(BaseKnowledgeStorage):
     search efficiency.
     """
 
-    collection: Optional[chromadb.Collection] = None
+    collection: Optional[Any] = None  # Will be chromadb.Collection when available
     collection_name: Optional[str] = "knowledge"
-    app: Optional[ClientAPI] = None
+    app: Optional[Any] = None  # Will be ClientAPI when available
+    embedder: Optional[Any] = None
 
     def __init__(
         self,
@@ -61,63 +69,98 @@ class KnowledgeStorage(BaseKnowledgeStorage):
         filter: Optional[dict] = None,
         score_threshold: float = 0.35,
     ) -> List[Dict[str, Any]]:
-        with suppress_logging():
+        if not CHROMADB_AVAILABLE:
-            if self.collection:
+            logging.warning(
-                fetched = self.collection.query(
+                "ChromaDB is not installed. Search functionality limited. "
-                    query_texts=query,
+                "Install with 'pip install crewai[chromadb]' to enable full functionality."
-                    n_results=limit,
+            )
-                    where=filter,
+            return []
-                )
+            
-                results = []
+        try:
-                for i in range(len(fetched["ids"][0])):  # type: ignore
+            with suppress_logging():
-                    result = {
+                if self.collection:
-                        "id": fetched["ids"][0][i],  # type: ignore
+                    fetched = self.collection.query(
-                        "metadata": fetched["metadatas"][0][i],  # type: ignore
+                        query_texts=query,
-                        "context": fetched["documents"][0][i],  # type: ignore
+                        n_results=limit,
-                        "score": fetched["distances"][0][i],  # type: ignore
+                        where=filter,
-                    }
+                    )
-                    if result["score"] >= score_threshold:
+                    results = []
-                        results.append(result)
+                    for i in range(len(fetched["ids"][0])):  # type: ignore
-                return results
+                        result = {
-            else:
+                            "id": fetched["ids"][0][i],  # type: ignore
-                raise Exception("Collection not initialized")
+                            "metadata": fetched["metadatas"][0][i],  # type: ignore
+                            "context": fetched["documents"][0][i],  # type: ignore
+                            "score": fetched["distances"][0][i],  # type: ignore
+                        }
+                        if result["score"] >= score_threshold:
+                            results.append(result)
+                    return results
+                else:
+                    return []
+        except (ImportError, NameError, AttributeError, Exception) as e:
+            logging.error(f"Error during knowledge search operation: {str(e)}")
+            return []
 
     def initialize_knowledge_storage(self):
-        base_path = os.path.join(db_storage_path(), "knowledge")
+        if not CHROMADB_AVAILABLE:
-        chroma_client = chromadb.PersistentClient(
+            import logging
-            path=base_path,
+            logging.warning(
-            settings=Settings(allow_reset=True),
+                "ChromaDB is not installed. Knowledge storage functionality will be limited. "
-        )
+                "Install with 'pip install crewai[chromadb]' to enable full functionality."
-
-        self.app = chroma_client
-
-        try:
-            collection_name = (
-                f"knowledge_{self.collection_name}"
-                if self.collection_name
-                else "knowledge"
             )
-            if self.app:
+            self.app = None
-                self.collection = self.app.get_or_create_collection(
+            self.collection = None
-                    name=collection_name, embedding_function=self.embedder
+            return
-                )
+            
-            else:
+        try:
-                raise Exception("Vector Database Client not initialized")
+            base_path = os.path.join(db_storage_path(), "knowledge")
-        except Exception:
+            chroma_client = chromadb.PersistentClient(
-            raise Exception("Failed to create or get collection")
-
-    def reset(self):
-        base_path = os.path.join(db_storage_path(), KNOWLEDGE_DIRECTORY)
-        if not self.app:
-            self.app = chromadb.PersistentClient(
                 path=base_path,
                 settings=Settings(allow_reset=True),
             )
 
-        self.app.reset()
+            self.app = chroma_client
-        shutil.rmtree(base_path)
+
-        self.app = None
+            try:
-        self.collection = None
+                collection_name = (
+                    f"knowledge_{self.collection_name}"
+                    if self.collection_name
+                    else "knowledge"
+                )
+                if self.app:
+                    self.collection = self.app.get_or_create_collection(
+                        name=collection_name, embedding_function=self.embedder
+                    )
+                else:
+                    raise Exception("Vector Database Client not initialized")
+            except Exception:
+                raise Exception("Failed to create or get collection")
+        except Exception:
+            logging.warning(
+                "Error initializing ChromaDB. Knowledge storage functionality will be limited."
+            )
+            self.app = None
+            self.collection = None
+
+    def reset(self):
+        base_path = os.path.join(db_storage_path(), KNOWLEDGE_DIRECTORY)
+        try:
+            if not self.app:
+                self.app = chromadb.PersistentClient(
+                    path=base_path,
+                    settings=Settings(allow_reset=True),
+                )
+
+            self.app.reset()
+            shutil.rmtree(base_path)
+            self.app = None
+            self.collection = None
+        except (ImportError, NameError, AttributeError):
+            # Handle case when chromadb is not available
+            if os.path.exists(base_path):
+                shutil.rmtree(base_path)
+            self.app = None
+            self.collection = None
 
     def save(
         self,
@@ -125,7 +168,8 @@ class KnowledgeStorage(BaseKnowledgeStorage):
         metadata: Optional[Union[Dict[str, Any], List[Dict[str, Any]]]] = None,
     ):
         if not self.collection:
-            raise Exception("Collection not initialized")
+            # Just return silently if chromadb is not available
+            return
 
         try:
             # Create a dictionary to store unique documents
@@ -154,7 +198,7 @@ class KnowledgeStorage(BaseKnowledgeStorage):
                 filtered_ids.append(doc_id)
 
             # If we have no metadata at all, set it to None
-            final_metadata: Optional[OneOrMany[chromadb.Metadata]] = (
+            final_metadata = (
                 None if all(m is None for m in filtered_metadata) else filtered_metadata
             )
 
@@ -163,29 +207,40 @@ class KnowledgeStorage(BaseKnowledgeStorage):
                 metadatas=final_metadata,
                 ids=filtered_ids,
             )
-        except chromadb.errors.InvalidDimensionException as e:
+        except (ImportError, NameError, AttributeError) as e:
-            Logger(verbose=True).log(
+            # Handle case when chromadb is not available
-                "error",
+            return
-                "Embedding dimension mismatch. This usually happens when mixing different embedding models. Try resetting the collection using `crewai reset-memories -a`",
-                "red",
-            )
-            raise ValueError(
-                "Embedding dimension mismatch. Make sure you're using the same embedding model "
-                "across all operations with this collection."
-                "Try resetting the collection using `crewai reset-memories -a`"
-            ) from e
         except Exception as e:
+            if "chromadb" in str(e.__class__):
+                # Handle chromadb-specific errors silently when chromadb might not be fully available
+                return
             Logger(verbose=True).log("error", f"Failed to upsert documents: {e}", "red")
-            raise
+            # Don't raise the exception, just log it and continue
+            return
 
     def _create_default_embedding_function(self):
-        from chromadb.utils.embedding_functions.openai_embedding_function import (
+        try:
-            OpenAIEmbeddingFunction,
+            from chromadb.utils.embedding_functions.openai_embedding_function import (
-        )
+                OpenAIEmbeddingFunction,
+            )
 
-        return OpenAIEmbeddingFunction(
+            api_key = os.getenv("OPENAI_API_KEY")
-            api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"
+            if not api_key:
-        )
+                logging.warning(
+                    "OPENAI_API_KEY not found. Vector operations will be limited."
+                )
+                return None
+                
+            return OpenAIEmbeddingFunction(
+                api_key=api_key, model_name="text-embedding-3-small"
+            )
+        except ImportError:
+            import logging
+            logging.warning(
+                "ChromaDB is not installed. Cannot create default embedding function. "
+                "Install with 'pip install crewai[chromadb]' to enable full functionality."
+            )
+            return None
 
     def _set_embedder_config(self, embedder: Optional[Dict[str, Any]] = None) -> None:
         """Set the embedding configuration for the knowledge storage.
@@ -194,8 +249,12 @@ class KnowledgeStorage(BaseKnowledgeStorage):
             embedder_config (Optional[Dict[str, Any]]): Configuration dictionary for the embedder.
                 If None or empty, defaults to the default embedding function.
         """
-        self.embedder = (
+        try:
-            EmbeddingConfigurator().configure_embedder(embedder)
+            self.embedder = (
-            if embedder
+                EmbeddingConfigurator().configure_embedder(embedder)
-            else self._create_default_embedding_function()
+                if embedder
-        )
+                else self._create_default_embedding_function()
+            )
+        except (ImportError, NameError, AttributeError):
+            # Handle case when chromadb is not available
+            self.embedder = None

src/crewai/memory/storage/rag_storage.py

@@ -4,9 +4,15 @@ import logging
 import os
 import shutil
 import uuid
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, cast
 
-from chromadb.api import ClientAPI
+try:
+    from chromadb.api import ClientAPI
+    CHROMADB_AVAILABLE = True
+except ImportError:
+    CHROMADB_AVAILABLE = False
+    # Define placeholder type for type checking
+    ClientAPI = Any
 
 from crewai.memory.storage.base_rag_storage import BaseRAGStorage
 from crewai.utilities import EmbeddingConfigurator
@@ -37,7 +43,7 @@ class RAGStorage(BaseRAGStorage):
     search efficiency.
     """
 
-    app: ClientAPI | None = None
+    app = None  # Type will be ClientAPI when available
 
     def __init__(
         self, type, allow_reset=True, embedder_config=None, crew=None, path=None
@@ -60,26 +66,41 @@ class RAGStorage(BaseRAGStorage):
         self.embedder_config = configurator.configure_embedder(self.embedder_config)
 
     def _initialize_app(self):
-        import chromadb
+        if not CHROMADB_AVAILABLE:
-        from chromadb.config import Settings
+            logging.warning(
-
+                "ChromaDB is not installed. RAG storage functionality will be limited. "
-        self._set_embedder_config()
+                "Install with 'pip install crewai[chromadb]' to enable full functionality."
-        chroma_client = chromadb.PersistentClient(
+            )
-            path=self.path if self.path else self.storage_file_name,
+            self.app = None
-            settings=Settings(allow_reset=self.allow_reset),
+            self.collection = None
-        )
+            return
-
+            
-        self.app = chroma_client
-
         try:
-            self.collection = self.app.get_collection(
+            import chromadb
-                name=self.type, embedding_function=self.embedder_config
+            from chromadb.config import Settings
-            )
+
-        except Exception:
+            self._set_embedder_config()
-            self.collection = self.app.create_collection(
+            chroma_client = chromadb.PersistentClient(
-                name=self.type, embedding_function=self.embedder_config
+                path=self.path if self.path else self.storage_file_name,
+                settings=Settings(allow_reset=self.allow_reset),
             )
 
+            self.app = chroma_client
+
+            try:
+                self.collection = self.app.get_collection(
+                    name=self.type, embedding_function=self.embedder_config
+                )
+            except Exception as e:
+                logging.info(f"Collection not found, creating new one: {str(e)}")
+                self.collection = self.app.create_collection(
+                    name=self.type, embedding_function=self.embedder_config
+                )
+        except Exception as e:
+            logging.error(f"Failed to initialize ChromaDB: {str(e)}")
+            self.app = None
+            self.collection = None
+
     def _sanitize_role(self, role: str) -> str:
         """
         Sanitizes agent roles to ensure valid directory names.
@@ -103,6 +124,10 @@ class RAGStorage(BaseRAGStorage):
     def save(self, value: Any, metadata: Dict[str, Any]) -> None:
         if not hasattr(self, "app") or not hasattr(self, "collection"):
             self._initialize_app()
+            
+        if not self.collection:
+            return
+            
         try:
             self._generate_embedding(value, metadata)
         except Exception as e:
@@ -115,8 +140,18 @@ class RAGStorage(BaseRAGStorage):
         filter: Optional[dict] = None,
         score_threshold: float = 0.35,
     ) -> List[Any]:
+        if not CHROMADB_AVAILABLE:
+            logging.warning(
+                "ChromaDB is not installed. Search functionality limited. "
+                "Install with 'pip install crewai[chromadb]' to enable full functionality."
+            )
+            return []
+            
         if not hasattr(self, "app"):
             self._initialize_app()
+            
+        if not self.collection:
+            return []
 
         try:
             with suppress_logging():
@@ -141,6 +176,9 @@ class RAGStorage(BaseRAGStorage):
     def _generate_embedding(self, text: str, metadata: Dict[str, Any]) -> None:  # type: ignore
         if not hasattr(self, "app") or not hasattr(self, "collection"):
             self._initialize_app()
+            
+        if not self.collection:
+            return
 
         self.collection.add(
             documents=[text],
@@ -149,26 +187,44 @@ class RAGStorage(BaseRAGStorage):
         )
 
     def reset(self) -> None:
+        if not self.app:
+            return
+            
         try:
-            if self.app:
+            self.app.reset()
-                self.app.reset()
+            path = f"{db_storage_path()}/{self.type}"
-                shutil.rmtree(f"{db_storage_path()}/{self.type}")
+            if os.path.exists(path):
-                self.app = None
+                shutil.rmtree(path)
-                self.collection = None
+            self.app = None
+            self.collection = None
         except Exception as e:
             if "attempt to write a readonly database" in str(e):
                 # Ignore this specific error
                 pass
             else:
-                raise Exception(
+                logging.error(f"Error during {self.type} reset: {str(e)}")
-                    f"An error occurred while resetting the {self.type} memory: {e}"
+                # Don't raise the exception, just log it
-                )
 
     def _create_default_embedding_function(self):
-        from chromadb.utils.embedding_functions.openai_embedding_function import (
+        try:
-            OpenAIEmbeddingFunction,
+            from chromadb.utils.embedding_functions.openai_embedding_function import (
-        )
+                OpenAIEmbeddingFunction,
+            )
 
-        return OpenAIEmbeddingFunction(
+            api_key = os.getenv("OPENAI_API_KEY")
-            api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"
+            if not api_key:
-        )
+                logging.warning(
+                    "OPENAI_API_KEY not found. Vector operations will be limited."
+                )
+                return None
+                
+            return OpenAIEmbeddingFunction(
+                api_key=api_key, model_name="text-embedding-3-small"
+            )
+        except ImportError:
+            import logging
+            logging.warning(
+                "ChromaDB is not installed. Cannot create default embedding function. "
+                "Install with 'pip install crewai[chromadb]' to enable full functionality."
+            )
+            return None

src/crewai/utilities/embedding_configurator.py

@@ -1,8 +1,17 @@
 import os
 from typing import Any, Dict, Optional, cast
 
-from chromadb import Documents, EmbeddingFunction, Embeddings
+try:
-from chromadb.api.types import validate_embedding_function
+    from chromadb import Documents, EmbeddingFunction, Embeddings
+    from chromadb.api.types import validate_embedding_function
+    CHROMADB_AVAILABLE = True
+except ImportError:
+    CHROMADB_AVAILABLE = False
+    # Define placeholder types for type checking
+    Documents = Any
+    EmbeddingFunction = Any
+    Embeddings = Any
+    def validate_embedding_function(func): return func
 
 
 class EmbeddingConfigurator:
@@ -47,6 +56,14 @@ class EmbeddingConfigurator:
 
     @staticmethod
     def _create_default_embedding_function():
+        if not CHROMADB_AVAILABLE:
+            import logging
+            logging.warning(
+                "ChromaDB is not installed. Cannot create default embedding function. "
+                "Install with 'pip install crewai[chromadb]' to enable full functionality."
+            )
+            return None
+            
         from chromadb.utils.embedding_functions.openai_embedding_function import (
             OpenAIEmbeddingFunction,
         )

tests/test_optional_dependencies.py

@@ -0,0 +1,52 @@
+import importlib
+import sys
+from unittest import mock
+
+import pytest
+
+
+def test_rag_storage_without_chromadb():
+    # Mock the import to simulate chromadb not being installed
+    with mock.patch.dict(sys.modules, {'chromadb': None}):
+        # Force reload to ensure our mock takes effect
+        if 'crewai.memory.storage.rag_storage' in sys.modules:
+            importlib.reload(sys.modules['crewai.memory.storage.rag_storage'])
+        
+        # Now import and test
+        from crewai.memory.storage.rag_storage import RAGStorage
+        
+        # Should not raise an exception
+        storage = RAGStorage(type="test", allow_reset=True)
+        
+        # Methods should handle the case when chromadb is not available
+        assert storage.app is None
+        assert storage.collection is None
+        
+        # These methods should not raise exceptions
+        storage.save("test", {})
+        results = storage.search("test")
+        assert results == []
+        storage.reset()
+
+def test_knowledge_storage_without_chromadb():
+    # Mock the import to simulate chromadb not being installed
+    with mock.patch.dict(sys.modules, {'chromadb': None}):
+        # Force reload to ensure our mock takes effect
+        if 'crewai.knowledge.storage.knowledge_storage' in sys.modules:
+            importlib.reload(sys.modules['crewai.knowledge.storage.knowledge_storage'])
+        
+        # Now import and test
+        from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
+        
+        # Should not raise an exception
+        storage = KnowledgeStorage()
+        
+        # Methods should handle the case when chromadb is not available
+        assert storage.app is None
+        assert storage.collection is None
+        
+        # These methods should not raise exceptions
+        storage.initialize_knowledge_storage()
+        results = storage.search(["test"])
+        assert results == []
+        storage.reset()

uv.lock

@@ -1,42 +1,19 @@
 version = 1
 requires-python = ">=3.10, <3.13"
 resolution-markers = [
-    "python_full_version < '3.11' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version < '3.11' and sys_platform == 'darwin'",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "python_version < '0'",
-    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and sys_platform == 'linux'",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version < '3.11' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and sys_platform == 'darwin'",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and sys_platform == 'linux'",
-    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform == 'darwin'",
-    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
-    "python_full_version == '3.11.*' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12.4' and sys_platform == 'darwin'",
-    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
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-    "python_full_version >= '3.12.4' and platform_system == 'Darwin' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'darwin'",
-    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Darwin' and sys_platform == 'linux'",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
-    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
-    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
 ]
 
 [[package]]
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 version = "1.2.2.post1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "colorama", marker = "os_name == 'nt'" },
+    { name = "colorama", marker = "(os_name == 'nt' and platform_machine != 'aarch64' and sys_platform == 'linux') or (os_name == 'nt' and sys_platform != 'darwin' and sys_platform != 'linux')" },
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@@ -568,7 +545,7 @@ name = "click"
 version = "8.1.8"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "colorama", marker = "platform_system == 'Windows'" },
+    { name = "colorama", marker = "sys_platform == 'win32'" },
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 sdist = { url = "https://files.pythonhosted.org/packages/b9/2e/0090cbf739cee7d23781ad4b89a9894a41538e4fcf4c31dcdd705b78eb8b/click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a", size = 226593 }
 wheels = [
@@ -625,7 +602,6 @@ dependencies = [
     { name = "appdirs" },
     { name = "auth0-python" },
     { name = "blinker" },
-    { name = "chromadb" },
     { name = "click" },
     { name = "instructor" },
     { name = "json-repair" },
@@ -651,6 +627,9 @@ dependencies = [
 agentops = [
     { name = "agentops" },
 ]
+chromadb = [
+    { name = "chromadb" },
+]
 docling = [
     { name = "docling" },
 ]
@@ -701,7 +680,7 @@ requires-dist = [
     { name = "appdirs", specifier = ">=1.4.4" },
     { name = "auth0-python", specifier = ">=4.7.1" },
     { name = "blinker", specifier = ">=1.9.0" },
-    { name = "chromadb", specifier = ">=0.5.23" },
+    { name = "chromadb", marker = "extra == 'chromadb'", specifier = ">=0.5.23" },
     { name = "click", specifier = ">=8.1.7" },
     { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.37.0" },
     { name = "docling", marker = "extra == 'docling'", specifier = ">=2.12.0" },
@@ -2500,7 +2479,7 @@ version = "1.6.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "click" },
-    { name = "colorama", marker = "platform_system == 'Windows'" },
+    { name = "colorama", marker = "sys_platform == 'win32'" },
     { name = "ghp-import" },
     { name = "jinja2" },
     { name = "markdown" },
@@ -2681,7 +2660,7 @@ version = "2.10.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "pygments" },
-    { name = "pywin32", marker = "platform_system == 'Windows'" },
+    { name = "pywin32", marker = "sys_platform == 'win32'" },
     { name = "tqdm" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/3a/93/80ac75c20ce54c785648b4ed363c88f148bf22637e10c9863db4fbe73e74/mpire-2.10.2.tar.gz", hash = "sha256:f66a321e93fadff34585a4bfa05e95bd946cf714b442f51c529038eb45773d97", size = 271270 }
@@ -2928,7 +2907,7 @@ name = "nvidia-cudnn-cu12"
 version = "9.1.0.70"
 source = { registry = "https://pypi.org/simple" }
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+    { name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
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 wheels = [
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@@ -2955,9 +2934,9 @@ name = "nvidia-cusolver-cu12"
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+    { name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
-    { name = "nvidia-cusparse-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
+    { name = "nvidia-cusparse-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
-    { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
+    { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
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 wheels = [
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@@ -2968,7 +2947,7 @@ name = "nvidia-cusparse-cu12"
 version = "12.1.0.106"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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+    { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
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 wheels = [
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@@ -3506,7 +3485,7 @@ name = "portalocker"
 version = "2.10.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "pywin32", marker = "platform_system == 'Windows'" },
+    { name = "pywin32", marker = "sys_platform == 'win32'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/ed/d3/c6c64067759e87af98cc668c1cc75171347d0f1577fab7ca3749134e3cd4/portalocker-2.10.1.tar.gz", hash = "sha256:ef1bf844e878ab08aee7e40184156e1151f228f103aa5c6bd0724cc330960f8f", size = 40891 }
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@@ -5019,19 +4998,19 @@ dependencies = [
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     { name = "jinja2" },
     { name = "networkx" },
-    { name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cuda-runtime-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cuda-runtime-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cufft-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cufft-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-curand-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-curand-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cusolver-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cusolver-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cusparse-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cusparse-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
     { name = "sympy" },
-    { name = "triton", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
     { name = "typing-extensions" },
 ]
 wheels = [
@@ -5078,7 +5057,7 @@ name = "tqdm"
 version = "4.66.5"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "colorama", marker = "platform_system == 'Windows'" },
+    { name = "colorama", marker = "sys_platform == 'win32'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/58/83/6ba9844a41128c62e810fddddd72473201f3eacde02046066142a2d96cc5/tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad", size = 169504 }
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-    { name = "filelock", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
+    { name = "filelock", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
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