unidoc-agent 0.2.1

Universal Document Agent for extracting and analyzing various documents with Ollama support.

UniversalDocAgent (unidoc_agent) UniversalDocAgent is a Python package designed to intelligently detect document types and automatically extract or summarize their contents using a set of specialized tools. It supports a wide range of file types such as PDFs, Word documents, emails, source code, Excel files, XML, OCR-recognizable images, and plain text. You can optionally integrate with an LLM backend like Ollama to generate summaries and maintain conversation history across sessions.

🚧 Installation pip install .

Run this from the root directory of your cloned project or package.

📂 Supported Document Types

File Type

Handled By

.pdf

PDFTool

.docx

WordTool

.txt

TextTool

.py/.js/etc.

CodeTool

.eml

EmailTool

.xlsx

ExcelTool

.jpg/.png/etc.

OCRTool

.xml

XMLTool

🚀 Usage Examples

1. Extracting Content from unidoc_agent.agent import read_document

file_path = "sample.pdf" content = read_document(file_path) print(content)

2. Summarizing Content summary = read_document("example.docx", summarize=True) print(summary)

🧠 Advanced: Use Ollama LLM Backend Custom LLM model or session from unidoc_agent.agent import UniversalDocAgent from unidoc_agent.agent import tools

agent = UniversalDocAgent(tools=tools, llm_backend="ollama") summary = agent.summarize_content("report.txt") print(summary)

💬 Conversation History with OllamaClient The OllamaClient class is used internally to manage conversation context for summarization.

Caching: Stores conversation history locally in ~/.unidoc_ollama_cache/{model}_{session_id}.json

Session Management: Custom session IDs let you manage multiple user contexts

Clearing History from unidoc_agent.ollama_client import OllamaClient

client = OllamaClient(session_id="user123") client.clear_history()

🔧 API Reference read_document(file_path, summarize=False)

file_path: Path to the input document

summarize: If True, returns a summary via LLM; else returns extracted content

UniversalDocAgent

extract_content(file_path): Extracts raw content

summarize_content(file_path): Summarizes content using the selected tool + LLM

🔮 Tests Make sure you have pytest or unittest installed:

pytest

Or:

python -m unittest discover tests/

📄 License This project is licensed under the MIT License. See the LICENSE file for details.

📊 Use Cases ✉️ Email Parsing Automatically extract the body of .eml files and summarize them.

📄 Document Summary Get concise summaries of long reports, manuals, or meeting notes.

📈 Spreadsheet Reader Read .xlsx Excel files and extract tables or data grids.

🔧 OCR Scanning Use OCRTool to read text from images (e.g., scanned receipts).

📁 Source Code Insight Extract and analyze comments or logic from .py or .js files.

📖 Multi-format Aggregation Use the same interface (read_document) for any supported format.

🚀 Contributing Pull requests are welcome. Please open issues for bugs or feature requests.

✨ Acknowledgements Thanks to OpenAI, Ollama, and the open-source contributors whose tools helped build this module.