feat(llm): Add Ollama provider and PyMuPDF image extraction

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.

refine.py

@@ -0,0 +1,23 @@
+import argparse  # New import
+from pdf_convertor import load_md_file, save_md_images, refine_content
+from pathlib import Path
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Refine Markdown content from PDF.")
+    parser.add_argument(
+        "--md-path", type=str, required=True, help="Path to the input Markdown file."
+    )
+    args = parser.parse_args()
+
+    md_path = args.md_path
+    pdf_path = Path("input").joinpath(Path(args.md_path).parent.name + ".pdf")
+
+    output = Path(md_path).parent
+    output.mkdir(parents=True, exist_ok=True)
+
+    md, images = load_md_file(md_path)
+    with open(pdf_path, "rb") as pdf_file:
+        pdf = pdf_file.read()
+    md = refine_content(md, images, pdf)
+
+    save_md_images(output, md, images, md_name="index_refined.md")