Skip to main content

Universal document assistant using popular AI models (PDF, Word, Excel)

Project description

📁 Malama FileParse

Malama FileParse is a flexible and extensible framework for querying content from PDF, DOCX, and Excel files using any large language model (LLM) such as OpenAI, Gemini, Claude, Mistral, DeepSeek, and more.

🔍 Upload a file → Load context (optionally with page/range control) → Ask intelligent questions → Get accurate LLM-powered responses.


✨ Features

  • ✅ Extracts content from PDF, DOCX, and XLSX files
  • 📄 Supports full-document or partial (page-based) extraction for applicable formats
  • 🤖 Works with any LLM by passing the desired model name
  • 🔌 Easily extendable to new AI providers or formats
  • 🧠 Unified prompt structure and clean response interface
  • ⚙️ Minimal dependencies and easy integration

📂 Supported File Types

File Type Description
PDF Supports full and paginated text extraction
DOCX Extracts paragraphs and tables in document order
XLSX Reads sheet names and cell contents in readable format

🤖 Supported LLMs

Malama FileParse accepts any valid model name for the provider you configure.
Here are some examples you can use out of the box:

Provider Example Models (not restricted)
OpenAI gpt-3.5-turbo, gpt-4
Gemini gemini-1.5-pro, gemini-1.0
Anthropic claude-3-sonnet, claude-3-opus
Groq llama3-70b-8192, mixtral-8x7b
Mistral mistral-medium, mistral-tiny
Cohere command-r, command-r-plus
DeepSeek deepseek-coder, deepseek-r1
Together.ai Qwen2-72B, Falcon-180B (via API key)
Amazon Titan (Coming Soon via Boto3 integration)

You can pass any model name recognized by your chosen provider—no hardcoded restrictions. Prefer your own model name to work around different models of LLM provider.


📦 Installation

pip install malama

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

malama-0.1.6.tar.gz (9.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

malama-0.1.6-py3-none-any.whl (14.1 kB view details)

Uploaded Python 3

File details

Details for the file malama-0.1.6.tar.gz.

File metadata

  • Download URL: malama-0.1.6.tar.gz
  • Upload date:
  • Size: 9.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.2

File hashes

Hashes for malama-0.1.6.tar.gz
Algorithm Hash digest
SHA256 54e48846e89a959d887e740b9ebf82f0bc1e42640c9aa68eef05aefdcd7df4ab
MD5 ac5298b72108426483a66cd6049f9147
BLAKE2b-256 7415751ae3a96fd53037ad2fa29ec0430ef4d939e858f3ed8ca3ea9e164060b1

See more details on using hashes here.

File details

Details for the file malama-0.1.6-py3-none-any.whl.

File metadata

  • Download URL: malama-0.1.6-py3-none-any.whl
  • Upload date:
  • Size: 14.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.2

File hashes

Hashes for malama-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 99f5d125ffa7a4fa140555e1b32f7a861ece99e66f222440c2a38404df85302f
MD5 b929bf0ccbb7eabacbdeb58ebf362516
BLAKE2b-256 4e09df5f0d06374066d637620a4b0970fb998359b0604586323e72a8e3a34d92

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page