feat: Improve content refinement with SystemMessage and prompt updates

This commit refactors the content refinement process to leverage `SystemMessage` for the primary prompt, enhancing clarity and adherence to LLM best practices.

The `pdf_convertor.py` file was updated to:
- Import `SystemMessage` from `langchain_core.messages`.
- Modify the `refine_content` function to use `SystemMessage` for the main prompt, moving the prompt content from `human_message_parts`.
- Adjust `human_message_parts` to only contain the Markdown and image data for the `HumanMessage`.

The `pdf_convertor_prompt.md` file was updated to:
- Reformat the prompt with clearer headings and instructions for each task.
- Improve the clarity and conciseness of the instructions for cleaning up characters, explaining image content, and correcting list formatting.

Additionally, `.gitignore` was updated to include `.vscode/` to prevent IDE-specific files from being committed.

These changes improve the structure of the LLM interaction and make the prompt more readable and maintainable.

pdf_convertor.py

@@ -10,7 +10,7 @@ from docling_core.types.io import DocumentStream
 from docling.datamodel.settings import settings
 from docling.document_converter import DocumentConverter, PdfFormatOption
 from docling_core.types.doc.base import ImageRefMode
-from langchain_core.messages import HumanMessage
+from langchain_core.messages import HumanMessage, SystemMessage
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_ollama import ChatOllama
 from llm import set_api_key, get_model_name, get_temperature
@@ -146,7 +146,7 @@ def refine_content(md: str, images: dict[str, bytes], pdf: bytes) -> str:
         prompt = f.read()
 
     # 添加 Markdown
-    human_message_parts = [{"type": "text", "text": prompt}]
+    human_message_parts = []
     if provider == "gemini":
         human_message_parts.append(
             {
@@ -223,6 +223,7 @@ def refine_content(md: str, images: dict[str, bytes], pdf: bytes) -> str:
         doc.close()
 
     message_content = [
+        SystemMessage(content=prompt),
         HumanMessage(content=human_message_parts),  # type: ignore
     ]