mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-01-08 15:48:29 +00:00
fix: Resolve all remaining lint issues (S101, RUF005, N806)
- Replace remaining assert statements with conditional checks - Fix list concatenation to use iterable unpacking - Change variable names from UPPER_CASE to lower_case - All lint checks now pass locally Co-Authored-By: João <joao@crewai.com>
This commit is contained in:
Devin AI
@@ -600,15 +600,15 @@ class LLM(BaseLLM):
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full_response += chunk_content
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# Emit the chunk event
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assert hasattr(crewai_event_bus, "emit")
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crewai_event_bus.emit(
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self,
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event=LLMStreamChunkEvent(
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chunk=chunk_content,
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from_task=from_task,
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from_agent=from_agent,
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),
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)
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if hasattr(crewai_event_bus, "emit"):
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crewai_event_bus.emit(
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self,
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event=LLMStreamChunkEvent(
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chunk=chunk_content,
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from_task=from_task,
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from_agent=from_agent,
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),
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)
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# --- 4) Fallback to non-streaming if no content received
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if not full_response.strip() and chunk_count == 0:
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logging.warning(
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@@ -755,13 +755,13 @@ class LLM(BaseLLM):
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return full_response
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# Emit failed event and re-raise the exception
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assert hasattr(crewai_event_bus, "emit")
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crewai_event_bus.emit(
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self,
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event=LLMCallFailedEvent(
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error=str(e), from_task=from_task, from_agent=from_agent
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),
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)
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if hasattr(crewai_event_bus, "emit"):
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crewai_event_bus.emit(
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self,
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event=LLMCallFailedEvent(
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error=str(e), from_task=from_task, from_agent=from_agent
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),
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)
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raise Exception(f"Failed to get streaming response: {e!s}")
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def _handle_streaming_tool_calls(
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@@ -975,9 +975,9 @@ class LLM(BaseLLM):
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fn = available_functions[function_name]
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# --- 3.2) Execute function
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assert hasattr(crewai_event_bus, "emit")
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started_at = datetime.now()
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crewai_event_bus.emit(
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if hasattr(crewai_event_bus, "emit"):
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started_at = datetime.now()
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crewai_event_bus.emit(
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self,
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event=ToolUsageStartedEvent(
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tool_name=function_name,
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@@ -1015,8 +1015,8 @@ class LLM(BaseLLM):
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function_name, lambda: None
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) # Ensure fn is always a callable
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logging.error(f"Error executing function '{function_name}': {e}")
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assert hasattr(crewai_event_bus, "emit")
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crewai_event_bus.emit(
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if hasattr(crewai_event_bus, "emit"):
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crewai_event_bus.emit(
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self,
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event=LLMCallFailedEvent(error=f"Tool execution error: {e!s}"),
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)
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@@ -1067,8 +1067,8 @@ class LLM(BaseLLM):
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LLMContextLengthExceededException: If input exceeds model's context limit
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"""
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# --- 1) Emit call started event
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assert hasattr(crewai_event_bus, "emit")
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crewai_event_bus.emit(
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if hasattr(crewai_event_bus, "emit"):
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crewai_event_bus.emit(
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self,
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event=LLMCallStartedEvent(
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messages=messages,
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@@ -1140,13 +1140,13 @@ class LLM(BaseLLM):
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from_agent=from_agent,
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)
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assert hasattr(crewai_event_bus, "emit")
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crewai_event_bus.emit(
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self,
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event=LLMCallFailedEvent(
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error=str(e), from_task=from_task, from_agent=from_agent
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),
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)
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if hasattr(crewai_event_bus, "emit"):
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crewai_event_bus.emit(
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self,
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event=LLMCallFailedEvent(
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error=str(e), from_task=from_task, from_agent=from_agent
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),
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)
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raise
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def _handle_emit_call_events(
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@@ -1166,18 +1166,18 @@ class LLM(BaseLLM):
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from_agent: Optional agent object
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messages: Optional messages object
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"""
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assert hasattr(crewai_event_bus, "emit")
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crewai_event_bus.emit(
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self,
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event=LLMCallCompletedEvent(
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messages=messages,
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response=response,
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call_type=call_type,
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from_task=from_task,
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from_agent=from_agent,
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model=self.model,
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),
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)
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if hasattr(crewai_event_bus, "emit"):
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crewai_event_bus.emit(
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self,
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event=LLMCallCompletedEvent(
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messages=messages,
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response=response,
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call_type=call_type,
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from_task=from_task,
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from_agent=from_agent,
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model=self.model,
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),
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)
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def _format_messages_for_provider(
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self, messages: list[dict[str, str]]
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@@ -1222,7 +1222,7 @@ class LLM(BaseLLM):
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if "mistral" in self.model.lower():
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# Check if the last message has a role of 'assistant'
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if messages and messages[-1]["role"] == "assistant":
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return messages + [{"role": "user", "content": "Please continue."}]
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return [*messages, {"role": "user", "content": "Please continue."}]
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return messages
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# TODO: Remove this code after merging PR https://github.com/BerriAI/litellm/pull/10917
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@@ -1232,7 +1232,7 @@ class LLM(BaseLLM):
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and messages
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and messages[-1]["role"] == "assistant"
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):
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return messages + [{"role": "user", "content": ""}]
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return [*messages, {"role": "user", "content": ""}]
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# Handle Anthropic models
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if self.is_anthropic:
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@@ -1306,14 +1306,14 @@ class LLM(BaseLLM):
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if self.context_window_size != 0:
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return self.context_window_size
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MIN_CONTEXT = 1024
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MAX_CONTEXT = 2097152 # Current max from gemini-1.5-pro
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min_context = 1024
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max_context = 2097152 # Current max from gemini-1.5-pro
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# Validate all context window sizes
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for key, value in LLM_CONTEXT_WINDOW_SIZES.items():
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if value < MIN_CONTEXT or value > MAX_CONTEXT:
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if value < min_context or value > max_context:
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raise ValueError(
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f"Context window for {key} must be between {MIN_CONTEXT} and {MAX_CONTEXT}"
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f"Context window for {key} must be between {min_context} and {max_context}"
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)
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self.context_window_size = int(
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