Merge branch 'main' into fix/_should_force_answer

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Joe Moura <joao@crewai.com>

docs/concepts/knowledge.mdx

@@ -171,6 +171,58 @@ crewai reset-memories --knowledge
 
 This is useful when you've updated your knowledge sources and want to ensure that the agents are using the most recent information.
 
+## Agent-Specific Knowledge
+
+While knowledge can be provided at the crew level using `crew.knowledge_sources`, individual agents can also have their own knowledge sources using the `knowledge_sources` parameter:
+
+```python Code
+from crewai import Agent, Task, Crew
+from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
+
+# Create agent-specific knowledge about a product
+product_specs = StringKnowledgeSource(
+    content="""The XPS 13 laptop features:
+    - 13.4-inch 4K display
+    - Intel Core i7 processor
+    - 16GB RAM
+    - 512GB SSD storage
+    - 12-hour battery life""",
+    metadata={"category": "product_specs"}
+)
+
+# Create a support agent with product knowledge
+support_agent = Agent(
+    role="Technical Support Specialist",
+    goal="Provide accurate product information and support.",
+    backstory="You are an expert on our laptop products and specifications.",
+    knowledge_sources=[product_specs]  # Agent-specific knowledge
+)
+
+# Create a task that requires product knowledge
+support_task = Task(
+    description="Answer this customer question: {question}",
+    agent=support_agent
+)
+
+# Create and run the crew
+crew = Crew(
+    agents=[support_agent],
+    tasks=[support_task]
+)
+
+# Get answer about the laptop's specifications
+result = crew.kickoff(
+    inputs={"question": "What is the storage capacity of the XPS 13?"}
+)
+```
+
+<Info>
+  Benefits of agent-specific knowledge:
+  - Give agents specialized information for their roles
+  - Maintain separation of concerns between agents
+  - Combine with crew-level knowledge for layered information access
+</Info>
+
 ## Custom Knowledge Sources
 
 CrewAI allows you to create custom knowledge sources for any type of data by extending the `BaseKnowledgeSource` class. Let's create a practical example that fetches and processes space news articles.

src/crewai/agents/agent_builder/base_agent_executor_mixin.py

@@ -26,7 +26,7 @@ class CrewAgentExecutorMixin:
 
     def _should_force_answer(self) -> bool:
         """Determine if a forced answer is required based on iteration count."""
-        return (self.iterations >= self.max_iter) and not self.have_forced_answer
+        return self.iterations >= self.max_iter
 
     def _create_short_term_memory(self, output) -> None:
         """Create and save a short-term memory item if conditions are met."""

src/crewai/knowledge/source/base_file_knowledge_source.py

@@ -26,9 +26,10 @@ class BaseFileKnowledgeSource(BaseKnowledgeSource, ABC):
     safe_file_paths: List[Path] = Field(default_factory=list)
 
     @field_validator("file_path", "file_paths", mode="before")
-    def validate_file_path(cls, v, values):
+    def validate_file_path(cls, v, info):
         """Validate that at least one of file_path or file_paths is provided."""
-        if v is None and ("file_path" not in values or values.get("file_path") is None):
+        # Single check if both are None, O(1) instead of nested conditions
+        if v is None and info.data.get("file_path" if info.field_name == "file_paths" else "file_paths") is None:
             raise ValueError("Either file_path or file_paths must be provided")
         return v
 

tests/knowledge/knowledge_test.py

@@ -584,3 +584,28 @@ def test_docling_source_with_local_file():
     docling_source = CrewDoclingSource(file_paths=[pdf_path])
     assert docling_source.file_paths == [pdf_path]
     assert docling_source.content is not None
+
+
+def test_file_path_validation():
+    """Test file path validation for knowledge sources."""
+    current_dir = Path(__file__).parent
+    pdf_path = current_dir / "crewai_quickstart.pdf"
+
+    # Test valid single file_path
+    source = PDFKnowledgeSource(file_path=pdf_path)
+    assert source.safe_file_paths == [pdf_path]
+
+    # Test valid file_paths list
+    source = PDFKnowledgeSource(file_paths=[pdf_path])
+    assert source.safe_file_paths == [pdf_path]
+
+    # Test both file_path and file_paths provided (should use file_paths)
+    source = PDFKnowledgeSource(file_path=pdf_path, file_paths=[pdf_path])
+    assert source.safe_file_paths == [pdf_path]
+
+    # Test neither file_path nor file_paths provided
+    with pytest.raises(
+        ValueError,
+        match="file_path/file_paths must be a Path, str, or a list of these types"
+    ):
+        PDFKnowledgeSource()