Enhance knowledge management in CrewAI (#2637)

* Enhance knowledge management in CrewAI

- Added `KnowledgeConfig` class to configure knowledge retrieval parameters such as `limit` and `score_threshold`.
- Updated `Agent` and `Crew` classes to utilize the new knowledge configuration for querying knowledge sources.
- Enhanced documentation to clarify the addition of knowledge sources at both agent and crew levels.
- Introduced new tips in documentation to guide users on knowledge source management and configuration.

* Refactor knowledge configuration parameters in CrewAI

- Renamed `limit` to `results_limit` in `KnowledgeConfig`, `query_knowledge`, and `query` methods for consistency and clarity.
- Updated related documentation to reflect the new parameter name, ensuring users understand the configuration options for knowledge retrieval.

* Refactor agent tests to utilize mock knowledge storage

- Updated test cases in `agent_test.py` to use `KnowledgeStorage` for mocking knowledge sources, enhancing test reliability and clarity.
- Renamed `limit` to `results_limit` in `KnowledgeConfig` for consistency with recent changes.
- Ensured that knowledge queries are properly mocked to return expected results during tests.

* Add VCR support for agent tests with query limits and score thresholds

- Introduced `@pytest.mark.vcr` decorator in `agent_test.py` for tests involving knowledge sources, ensuring consistent recording of HTTP interactions.
- Added new YAML cassette files for `test_agent_with_knowledge_sources_with_query_limit_and_score_threshold` and `test_agent_with_knowledge_sources_with_query_limit_and_score_threshold_default`, capturing the expected API responses for these tests.
- Enhanced test reliability by utilizing VCR to manage external API calls during testing.

* Update documentation to format parameter names in code style

- Changed the formatting of `results_limit` and `score_threshold` in the documentation to use code style for better clarity and emphasis.
- Ensured consistency in documentation presentation to enhance user understanding of configuration options.

* Enhance KnowledgeConfig with field descriptions

- Updated `results_limit` and `score_threshold` in `KnowledgeConfig` to use Pydantic's `Field` for improved documentation and clarity.
- Added descriptions to both parameters to provide better context for their usage in knowledge retrieval configuration.

* docstrings added

src/crewai/knowledge/knowledge_config.py

@@ -0,0 +1,16 @@
+from pydantic import BaseModel, Field
+
+
+class KnowledgeConfig(BaseModel):
+    """Configuration for knowledge retrieval.
+
+    Args:
+        results_limit (int): The number of relevant documents to return.
+        score_threshold (float): The minimum score for a document to be considered relevant.
+    """
+
+    results_limit: int = Field(default=3, description="The number of results to return")
+    score_threshold: float = Field(
+        default=0.35,
+        description="The minimum score for a result to be considered relevant",
+    )