Implement OAuth2 authentication support for custom LiteLLM providers

- Add OAuth2Config and OAuth2ConfigLoader for litellm_config.json configuration
- Add OAuth2TokenManager for token acquisition, caching, and refresh
- Extend LLM class to support OAuth2 authentication with custom providers
- Add comprehensive tests covering OAuth2 flow and error handling
- Add documentation and usage examples
- Support Client Credentials OAuth2 flow for server-to-server authentication
- Maintain backward compatibility with existing LLM providers

Fixes #3114

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

examples/oauth2_llm_example.py

@@ -0,0 +1,64 @@
+"""
+Example demonstrating OAuth2 authentication with custom LLM providers in CrewAI.
+
+This example shows how to configure and use OAuth2-authenticated LLM providers.
+"""
+
+import json
+from pathlib import Path
+from crewai import Agent, Task, Crew, LLM
+
+def create_example_config():
+    """Create an example OAuth2 configuration file."""
+    config = {
+        "oauth2_providers": {
+            "my_custom_provider": {
+                "client_id": "your_client_id_here",
+                "client_secret": "your_client_secret_here",
+                "token_url": "https://your-provider.com/oauth/token",
+                "scope": "llm.read llm.write"
+            }
+        }
+    }
+    
+    config_path = Path("example_oauth2_config.json")
+    with open(config_path, 'w') as f:
+        json.dump(config, f, indent=2)
+    
+    print(f"Created example config at {config_path}")
+    return config_path
+
+def main():
+    config_path = create_example_config()
+    
+    try:
+        llm = LLM(
+            model="my_custom_provider/my-model",
+            oauth2_config_path=str(config_path)
+        )
+        
+        agent = Agent(
+            role="Research Assistant",
+            goal="Provide helpful research insights",
+            backstory="An AI assistant specialized in research and analysis",
+            llm=llm
+        )
+        
+        task = Task(
+            description="Research the benefits of OAuth2 authentication in AI systems",
+            agent=agent,
+            expected_output="A comprehensive summary of OAuth2 benefits"
+        )
+        
+        crew = Crew(agents=[agent], tasks=[task])
+        
+        print("Running crew with OAuth2-authenticated LLM...")
+        result = crew.kickoff()
+        print(f"Result: {result}")
+        
+    finally:
+        if config_path.exists():
+            config_path.unlink()
+
+if __name__ == "__main__":
+    main()