This commit introduces support for Ollama as an alternative Large Language Model (LLM) provider and enhances PDF image extraction capabilities.
- **Ollama Integration:**
- Implemented `set_ollama_config` to configure Ollama's base URL from `config.ini`.
- Modified `llm.py` to dynamically select and configure the LLM (Gemini or Ollama) based on the `PROVIDER` setting.
- Updated `get_model_name` to return provider-specific default model names.
- `pdf_convertor.py` now conditionally initializes `ChatGoogleGenerativeAI` or `ChatOllama` based on the configured provider.
- **PyMuPDF Image Extraction:**
- Added a new `extract_images_from_pdf` function using PyMuPDF (`fitz`) for direct image extraction from PDF files.
- Introduced `get_extract_images_from_pdf_flag` to control this feature via `config.ini`.
- `convert_pdf_to_markdown` and `refine_content` functions were updated to utilize this new image extraction method when enabled.
- **Refinement Flow:**
- Adjusted the order of `save_md_images` in `main.py` and added an option to save the refined markdown with a specific filename (`index_refined.md`).
- **Dependencies:**
- Updated `pyproject.lock` to include new dependencies for Ollama integration (`langchain-ollama`) and PyMuPDF (`PyMuPDF`), along with platform-specific markers for NVIDIA dependencies.
The main.py script was becoming monolithic, containing all the logic for PDF conversion, image path simplification, and content refinement. This change extracts these core functionalities into a new `pdf_convertor` module.
This refactoring improves the project structure by:
- Enhancing modularity and separation of concerns.
- Making the main.py script a cleaner, high-level orchestrator.
- Improving code readability and maintainability.
The functions `convert_pdf_to_markdown`, `save_md_images`, and `refine_content` are now imported from the `pdf_convertor` module and called from the main execution block.
