fix: Include agent knowledge in planning process (#1818)

* test: Add test demonstrating knowledge not included in planning process

Issue #1703: Add test to verify that agent knowledge sources are not currently
included in the planning process. This test will help validate the fix once
implemented.

- Creates agent with knowledge sources
- Verifies knowledge context missing from planning
- Checks other expected components are present

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

* fix: Include agent knowledge in planning process

Issue #1703: Integrate agent knowledge sources into planning summaries
- Add agent_knowledge field to task summaries in planning_handler
- Update test to verify knowledge inclusion
- Ensure knowledge context is available during planning phase

The planning agent now has access to agent knowledge when creating
task execution plans, allowing for better informed planning decisions.

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

* style: Fix import sorting in test_knowledge_planning.py

- Reorganize imports according to ruff linting rules
- Fix I001 linting error

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

* test: Update task summary assertions to include knowledge field

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

* fix: Update ChromaDB mock path and fix knowledge string formatting

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

* fix: Improve knowledge integration in planning process with error handling

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

* fix: Update task summary format for empty tools and knowledge

- Change empty tools message to 'agent has no tools'
- Remove agent_knowledge field when empty
- Update test assertions to match new format
- Improve test messages for clarity

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

* fix: Update string formatting for agent tools in task summary

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

* fix: Update string formatting for agent tools in task summary

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

* fix: Update string formatting for agent tools and knowledge in task summary

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

* fix: Update knowledge field formatting in task summary

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

* style: Fix import sorting in test_planning_handler.py

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

* style: Fix import sorting order in test_planning_handler.py

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

* test: Add ChromaDB mocking to test_create_tasks_summary_with_knowledge_and_tools

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

---------

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

tests/utilities/test_knowledge_planning.py

@@ -0,0 +1,84 @@
+"""
+Tests for verifying the integration of knowledge sources in the planning process.
+This module ensures that agent knowledge is properly included during task planning.
+"""
+
+from unittest.mock import patch
+
+import pytest
+
+from crewai.agent import Agent
+from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
+from crewai.task import Task
+from crewai.utilities.planning_handler import CrewPlanner
+
+
+@pytest.fixture
+def mock_knowledge_source():
+    """
+    Create a mock knowledge source with test content.
+    Returns:
+        StringKnowledgeSource:
+            A knowledge source containing AI-related test content
+    """
+    content = """
+    Important context about AI:
+    1. AI systems use machine learning algorithms
+    2. Neural networks are a key component
+    3. Training data is essential for good performance
+    """
+    return StringKnowledgeSource(content=content)
+
+@patch('crewai.knowledge.storage.knowledge_storage.chromadb')
+def test_knowledge_included_in_planning(mock_chroma):
+    """Test that verifies knowledge sources are properly included in planning."""
+    # Mock ChromaDB collection
+    mock_collection = mock_chroma.return_value.get_or_create_collection.return_value
+    mock_collection.add.return_value = None
+    
+    # Create an agent with knowledge
+    agent = Agent(
+        role="AI Researcher",
+        goal="Research and explain AI concepts",
+        backstory="Expert in artificial intelligence",
+        knowledge_sources=[
+            StringKnowledgeSource(
+                content="AI systems require careful training and validation."
+            )
+        ]
+    )
+
+    # Create a task for the agent
+    task = Task(
+        description="Explain the basics of AI systems",
+        expected_output="A clear explanation of AI fundamentals",
+        agent=agent
+    )
+
+    # Create a crew planner
+    planner = CrewPlanner([task], None)
+
+    # Get the task summary
+    task_summary = planner._create_tasks_summary()
+
+    # Verify that knowledge is included in planning when present
+    assert "AI systems require careful training" in task_summary, \
+        "Knowledge content should be present in task summary when knowledge exists"
+    assert '"agent_knowledge"' in task_summary, \
+        "agent_knowledge field should be present in task summary when knowledge exists"
+
+    # Verify that knowledge is properly formatted
+    assert isinstance(task.agent.knowledge_sources, list), \
+        "Knowledge sources should be stored in a list"
+    assert len(task.agent.knowledge_sources) > 0, \
+        "At least one knowledge source should be present"
+    assert task.agent.knowledge_sources[0].content in task_summary, \
+        "Knowledge source content should be included in task summary"
+
+    # Verify that other expected components are still present
+    assert task.description in task_summary, \
+        "Task description should be present in task summary"
+    assert task.expected_output in task_summary, \
+        "Expected output should be present in task summary"
+    assert agent.role in task_summary, \
+        "Agent role should be present in task summary"