feat: enhance LLMClient with structured output capabilities

feat: enhance app.py with session state management and extraction strategy selection

feat: enhance architecture and developer documentation for clarity and detail

feat: enhance field and unique indices descriptions handling in app and agents

feat: update unique indices combinator to return array of objects

Add extraction strategy selection and unique indices handling in app.py and FieldMapperAgent. Enhance Planner to accommodate new parameters for execution plans. Update AzureDIService to process tables and save extracted content in both markdown and JSON formats for improved traceability.

Add cost tracking functionality across various components, including Executor, Planner, and FieldMapperAgent. Integrate CostTracker to monitor LLM and document intelligence costs, enhancing logging for cost-related metrics and providing detailed cost breakdowns in the user interface.

Revise documentation in app.py for Deep‑Research PDF Field Extractor, enhancing clarity on system architecture, core components, processing pipeline, and key features. Update usage instructions and support resources for better user guidance.

Update Dockerfile to use new app entry point and enhance requirements.txt with additional dependencies. Remove obsolete streamlit_app.py file.