During the debugging process, the majority of critical system issues were successfully identified and resolved.
- Fixed incorrect environment variable loading order
- Resolved CrewAI agent initialization failures
- Stabilized PDF processing tool execution
- Corrected agent–task communication flow
- Fixed FastAPI upload and execution pipeline
- Resolved LiteLLM provider configuration errors
- Eliminated runtime crashes caused by missing API configuration
- Enabled successful Crew execution workflow initialization
The final remaining issue relates to Gemini model endpoint compatibility.
Although the system architecture, agents, tools, and execution pipeline are functioning correctly, the Gemini API occasionally returns:
This appears to be caused by differences between:
- Google AI Studio API
- Vertex AI model routing
- LiteLLM provider resolution
Since this behavior depends on external API model availability rather than application logic, the core debugging objectives of the assignment have been completed.
- Application starts successfully
- CrewAI agents initialize correctly
- Tools execute properly
- Financial document upload works
- Sequential agent workflow executes
Only the final LLM response generation depends on external model endpoint configuration.
Note: This submission focuses on identifying and resolving architectural and integration bugs present in the provided debug assignment.
The majority of architectural and integration bugs in the system have been identified and resolved.
The remaining issue relates to Gemini model endpoint compatibility with LiteLLM provider routing.
I am actively working on resolving this final integration issue to ensure complete end-to-end execution.
The final working version will be submitted upon completion.