doc-convert

name	doc-convert
description	Convert local PDF/DOCX documents to text for analysis
metadata	{"aeloon":{"emoji":"📄","requires":{"bins":["python3"]}}}

Document Conversion

When a user references local documents or directories (e.g., "refer to ~/papers/report.pdf", "according to these files", "use the documents in ~/data/"), convert the referenced documents to text format, then read and analyze them.

Document Detection

Recognize when the user mentions:

• File paths (e.g., ~/papers/report.pdf, /home/user/docs/notes.docx)
• Directories (e.g., ~/papers/, ./docs/)
• "these documents" / "these files" / "use these papers" / "refer to" / "according to"

Conversion Workflow

Step 1: Convert PDF to text

exec(command="python3 -c \"
import fitz, sys, os, pathlib
src = '{source_path}'
out_dir = os.path.expanduser('~/.aeloon/converted_docs')
os.makedirs(out_dir, exist_ok=True)
stem = pathlib.Path(src).stem
out_path = os.path.join(out_dir, stem + '.txt')
doc = fitz.open(src)
text = ''
for page in doc:
    text += page.get_text() + '\n\n'
doc.close()
with open(out_path, 'w', encoding='utf-8') as f:
    f.write(text.strip())
print(f'Converted: {out_path}')
print(f'Pages: {doc.page_count}, Characters: {len(text)}')
\"")

Step 2: Convert DOCX to text

exec(command="python3 -c \"
import docx, os, pathlib
src = '{source_path}'
out_dir = os.path.expanduser('~/.aeloon/converted_docs')
os.makedirs(out_dir, exist_ok=True)
stem = pathlib.Path(src).stem
out_path = os.path.join(out_dir, stem + '.txt')
doc = docx.Document(src)
lines = []
for para in doc.paragraphs:
    if para.style.name.startswith('Heading'):
        level = int(para.style.name.split()[-1]) if para.style.name[-1].isdigit() else 1
        lines.append('#' * level + ' ' + para.text)
    else:
        lines.append(para.text)
text = '\n\n'.join(lines)
with open(out_path, 'w', encoding='utf-8') as f:
    f.write(text.strip())
print(f'Converted: {out_path}')
\"")

Step 3: Read converted text

read_file(path="{converted_path}")

Step 4: Process directory of documents

When the user specifies a directory:

exec(command="python3 -c \"
import fitz, docx, os, pathlib, glob
src_dir = '{directory_path}'
out_dir = os.path.expanduser('~/.aeloon/converted_docs')
os.makedirs(out_dir, exist_ok=True)
supported = {'.pdf', '.docx', '.md', '.txt', '.csv'}
converted = 0
skipped = 0
for f in sorted(pathlib.Path(src_dir).rglob('*')):
    if f.suffix.lower() not in supported:
        continue
    out_path = pathlib.Path(out_dir) / (f.stem + '.txt')
    if f.suffix.lower() == '.pdf':
        doc = fitz.open(str(f))
        text = '\\n\\n'.join(p.get_text() for p in doc)
        doc.close()
    elif f.suffix.lower() == '.docx':
        doc = docx.Document(str(f))
        text = '\\n\\n'.join(p.text for p in doc.paragraphs)
    else:
        text = f.read_text(encoding='utf-8', errors='replace')
    out_path.write_text(text.strip(), encoding='utf-8')
    converted += 1
    print(f'OK: {f.name} -> {out_path.name}')
print(f'\\nTotal: {converted} converted, {skipped} skipped')
\"")

Output Directory

• Converted text files are saved to ~/.aeloon/converted_docs/
• Files are named <original_stem>.txt (e.g., report.txt from report.pdf)
• Never auto-delete converted files — they serve as a local cache for future reference
• If the directory grows too large, the user may manually clean old files

Error Handling

If conversion fails:

1. Report which file failed: "Failed to convert {filename}: {error}"
2. Suggest installing dependencies: pip install PyMuPDF pdfminer.six python-docx
3. Continue with available text-based documents (.md, .txt, .csv)

Important Notes

• Only convert referenced documents — do NOT auto-scan entire file systems
• If a file is already converted (exists in ~/.aeloon/converted_docs/), skip conversion and read the cached version
• Large PDFs may take time — inform the user about processing time
• Always use exec tool for file operations, never call read_file on binary files
• For .md / .txt / .csv files, use read_file directly — no conversion needed