fix linting

src/crewai/agent.py

@@ -1,18 +1,19 @@
 import os
 from inspect import signature
 from typing import Any, List, Optional, Union
+
 from pydantic import Field, InstanceOf, PrivateAttr, model_validator
 
 from crewai.agents import CacheHandler
-from crewai.utilities import Converter, Prompts
-from crewai.tools.agent_tools import AgentTools
-from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.agents.agent_builder.base_agent import BaseAgent
-from crewai.memory.contextual.contextual_memory import ContextualMemory
-from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_FILE
-from crewai.utilities.training_handler import CrewTrainingHandler
-from crewai.utilities.token_counter_callback import TokenCalcHandler
+from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.llm import LLM
+from crewai.memory.contextual.contextual_memory import ContextualMemory
+from crewai.tools.agent_tools import AgentTools
+from crewai.utilities import Converter, Prompts
+from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_FILE
+from crewai.utilities.token_counter_callback import TokenCalcHandler
+from crewai.utilities.training_handler import CrewTrainingHandler
 
 
 def mock_agent_ops_provider():
@@ -292,9 +293,9 @@ class Agent(BaseAgent):
             step_callback=self.step_callback,
             function_calling_llm=self.function_calling_llm,
             respect_context_window=self.respect_context_window,
-            request_within_rpm_limit=self._rpm_controller.check_or_wait
-            if self._rpm_controller
-            else None,
+            request_within_rpm_limit=(
+                self._rpm_controller.check_or_wait if self._rpm_controller else None
+            ),
             callbacks=[TokenCalcHandler(self._token_process)],
         )
 

src/crewai/memory/storage/rag_storage.py

@@ -5,11 +5,6 @@ import os
 import shutil
 from typing import Any, Dict, List, Optional
 
-from embedchain import App
-from embedchain.llm.base import BaseLlm
-from embedchain.models.data_type import DataType
-from embedchain.vectordb.chroma import InvalidDimensionException
-
 from crewai.memory.storage.interface import Storage
 from crewai.utilities.paths import db_storage_path
 
@@ -29,10 +24,6 @@ def suppress_logging(
     logger.setLevel(original_level)
 
 
-class FakeLLM(BaseLlm):
-    pass
-
-
 class RAGStorage(Storage):
     """
     Extends Storage to handle embeddings for memory entries, improving
@@ -74,9 +65,19 @@ class RAGStorage(Storage):
         if embedder_config:
             config["embedder"] = embedder_config
         self.type = type
-        self.app = App.from_config(config=config)
+        self.config = config
+        self.allow_reset = allow_reset
+
+    def _initialize_app(self):
+        from embedchain import App
+        from embedchain.llm.base import BaseLlm
+
+        class FakeLLM(BaseLlm):
+            pass
+
+        self.app = App.from_config(config=self.config)
         self.app.llm = FakeLLM()
-        if allow_reset:
+        if self.allow_reset:
             self.app.reset()
 
     def _sanitize_role(self, role: str) -> str:
@@ -86,6 +87,8 @@ class RAGStorage(Storage):
         return role.replace("\n", "").replace(" ", "_").replace("/", "_")
 
     def save(self, value: Any, metadata: Dict[str, Any]) -> None:
+        if not hasattr(self, "app"):
+            self._initialize_app()
         self._generate_embedding(value, metadata)
 
     def search(  # type: ignore # BUG?: Signature of "search" incompatible with supertype "Storage"
@@ -95,6 +98,10 @@ class RAGStorage(Storage):
         filter: Optional[dict] = None,
         score_threshold: float = 0.35,
     ) -> List[Any]:
+        if not hasattr(self, "app"):
+            self._initialize_app()
+        from embedchain.vectordb.chroma import InvalidDimensionException
+
         with suppress_logging():
             try:
                 results = (
@@ -108,6 +115,10 @@ class RAGStorage(Storage):
         return [r for r in results if r["metadata"]["score"] >= score_threshold]
 
     def _generate_embedding(self, text: str, metadata: Dict[str, Any]) -> Any:
+        if not hasattr(self, "app"):
+            self._initialize_app()
+        from embedchain.models.data_type import DataType
+
         self.app.add(text, data_type=DataType.TEXT, metadata=metadata)
 
     def reset(self) -> None:

src/crewai/telemetry/telemetry.py

@@ -21,9 +21,7 @@ with suppress_warnings():
 
 
 from opentelemetry import trace  # noqa: E402
-from opentelemetry.exporter.otlp.proto.http.trace_exporter import (
-    OTLPSpanExporter,  # noqa: E402
-)
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter  # noqa: E402
 from opentelemetry.sdk.resources import SERVICE_NAME, Resource  # noqa: E402
 from opentelemetry.sdk.trace import TracerProvider  # noqa: E402
 from opentelemetry.sdk.trace.export import BatchSpanProcessor  # noqa: E402

src/crewai/tools/agent_tools.py

@@ -1,4 +1,3 @@
-from langchain.tools import StructuredTool
 from crewai.agents.agent_builder.utilities.base_agent_tool import BaseAgentTools
 
 
@@ -6,6 +5,8 @@ class AgentTools(BaseAgentTools):
     """Default tools around agent delegation"""
 
     def tools(self):
+        from langchain.tools import StructuredTool
+
         coworkers = ", ".join([f"{agent.role}" for agent in self.agents])
         tools = [
             StructuredTool.from_function(

src/crewai/tools/cache_tools.py

@@ -1,4 +1,3 @@
-from langchain.tools import StructuredTool
 from pydantic import BaseModel, Field
 
 from crewai.agents.cache import CacheHandler
@@ -14,6 +13,8 @@ class CacheTools(BaseModel):
     )
 
     def tool(self):
+        from langchain.tools import StructuredTool
+
         return StructuredTool.from_function(
             func=self.hit_cache,
             name=self.name,

src/crewai/utilities/internal_instructor.py

@@ -1,8 +1,5 @@
 from typing import Any, Optional, Type
 
-import instructor
-from litellm import completion
-
 
 class InternalInstructor:
     """Class that wraps an agent llm with instructor."""
@@ -28,6 +25,10 @@ class InternalInstructor:
         if self.agent and not self.llm:
             self.llm = self.agent.function_calling_llm or self.agent.llm
 
+        # Lazy import
+        import instructor
+        from litellm import completion
+
         self._client = instructor.from_litellm(
             completion,
             mode=instructor.Mode.TOOLS,

src/crewai/utilities/token_counter_callback.py

@@ -1,4 +1,5 @@
 from litellm.integrations.custom_logger import CustomLogger
+
 from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess