Improve types and better support for file paths

tests/agent_test.py

@@ -10,10 +10,11 @@ from crewai import Agent, Crew, Task
 from crewai.agents.cache import CacheHandler
 from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.agents.parser import AgentAction, CrewAgentParser, OutputParserException
+from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
 from crewai.llm import LLM
+from crewai.tools import tool
 from crewai.tools.tool_calling import InstructorToolCalling
 from crewai.tools.tool_usage import ToolUsage
-from crewai.tools import tool
 from crewai.tools.tool_usage_events import ToolUsageFinished
 from crewai.utilities import RPMController
 from crewai.utilities.events import Emitter
@@ -1574,3 +1575,32 @@ def test_agent_execute_task_with_ollama():
     result = agent.execute_task(task)
     assert len(result.split(".")) == 2
     assert "AI" in result or "artificial intelligence" in result.lower()
+
+
+# @pytest.mark.vcr(filter_headers=["authorization"])
+def test_agent_with_knowledge_sources():
+    # Create a knowledge source with some content
+    content = "Brandon's favorite color is blue and he likes Mexican food."
+    string_source = StringKnowledgeSource(content=content)
+
+    # Create an agent with the knowledge source
+    agent = Agent(
+        role="Information Agent",
+        goal="Provide information based on knowledge sources",
+        backstory="You have access to specific knowledge sources.",
+        llm=LLM(model="gpt-3.5-turbo"),
+        knowledge_sources=[string_source],
+    )
+
+    # Create a task that requires the agent to use the knowledge
+    task = Task(
+        description="What is Brandon's favorite color?",
+        expected_output="Brandon's favorite color.",
+        agent=agent,
+    )
+
+    # Execute the task
+    result = agent.execute_task(task)
+
+    # Assert that the agent provides the correct information
+    assert "blue" in result.lower()

tests/knowledge/knowledge_test.py

@@ -1,6 +1,6 @@
 """Test Knowledge creation and querying functionality."""
 
-import os
+from pathlib import Path
 
 from crewai.knowledge.knowledge import Knowledge
 from crewai.knowledge.source.pdf_knowledge_source import PDFKnowledgeSource
@@ -141,11 +141,11 @@ def test_multiple_2k_character_strings():
 def test_single_short_file(tmpdir):
     # Create a single short text file
     content = "Brandon's favorite sport is basketball."
-    file_path = tmpdir.join("short_file.txt")
+    file_path = Path(tmpdir.join("short_file.txt"))
     with open(file_path, "w") as f:
         f.write(content)
 
-    file_source = TextFileKnowledgeSource(file_path=str(file_path))
+    file_source = TextFileKnowledgeSource(file_path=file_path)
     knowledge_base = Knowledge(sources=[file_source])
 
     # Perform a query
@@ -180,11 +180,11 @@ def test_single_2k_character_file(tmpdir):
         "Brandon's favorite sport is basketball, and he often plays with his friends on weekends. "
         "He is also a fan of the Golden State Warriors and enjoys watching their games. "
     ) * 2  # Repeat to ensure it's 2k characters
-    file_path = tmpdir.join("long_file.txt")
+    file_path = Path(tmpdir.join("long_file.txt"))
     with open(file_path, "w") as f:
         f.write(content)
 
-    file_source = TextFileKnowledgeSource(file_path=str(file_path))
+    file_source = TextFileKnowledgeSource(file_path=file_path)
     knowledge_base = Knowledge(sources=[file_source])
 
     # Perform a query
@@ -204,10 +204,10 @@ def test_multiple_short_files(tmpdir):
     ]
     file_paths = []
     for i, content in enumerate(contents):
-        file_path = tmpdir.join(f"file_{i}.txt")
+        file_path = Path(tmpdir.join(f"file_{i}.txt"))
         with open(file_path, "w") as f:
             f.write(content)
-        file_paths.append(str(file_path))
+        file_paths.append(file_path)
 
     file_sources = [TextFileKnowledgeSource(file_path=path) for path in file_paths]
     knowledge_base = Knowledge(sources=file_sources)
@@ -272,10 +272,10 @@ def test_multiple_2k_character_files(tmpdir):
     ]
     file_paths = []
     for i, content in enumerate(contents):
-        file_path = tmpdir.join(f"long_file_{i}.txt")
+        file_path = Path(tmpdir.join(f"long_file_{i}.txt"))
         with open(file_path, "w") as f:
             f.write(content)
-        file_paths.append(str(file_path))
+        file_paths.append(file_path)
 
     file_sources = [TextFileKnowledgeSource(file_path=path) for path in file_paths]
     knowledge_base = Knowledge(sources=file_sources)
@@ -307,10 +307,10 @@ def test_hybrid_string_and_files(tmpdir):
     ]
     file_paths = []
     for i, content in enumerate(file_contents):
-        file_path = tmpdir.join(f"file_{i}.txt")
+        file_path = Path(tmpdir.join(f"file_{i}.txt"))
         with open(file_path, "w") as f:
             f.write(content)
-        file_paths.append(str(file_path))
+        file_paths.append(file_path)
 
     file_sources = [TextFileKnowledgeSource(file_path=path) for path in file_paths]
 
@@ -327,9 +327,9 @@ def test_hybrid_string_and_files(tmpdir):
 
 def test_pdf_knowledge_source():
     # Get the directory of the current file
-    current_dir = os.path.dirname(__file__)
+    current_dir = Path(__file__).parent
     # Construct the path to the PDF file
-    pdf_path = os.path.join(current_dir, "crewai_quickstart.pdf")
+    pdf_path = current_dir / "crewai_quickstart.pdf"
 
     # Create a PDFKnowledgeSource
     pdf_source = PDFKnowledgeSource(file_path=pdf_path)