Skip to main content

LLM function calling on steroids using Abstract Syntax Trees.

Project description

🌲 treelang

PyPI - Version PyPI Downloads License: MIT

Abstract Syntax Trees (ASTs) for advanced function calling with Large Language Models (LLMs), i.e. function-calling on steroids!

Why treelang

  • Complex worflows: Primarily treelang was created as a practical way to support arbitrarily complex function composition and conditionals, where the answer to a question may involve multiple steps each with its own multiple dependencies.

  • Cost-Saving and Green: With treelang you avoid the typical function-calling loop whereby the LLM outputs a function call, your program evaluates it and returns the result back to the LLM for this cycle to repeat until the final result is computed. treelang generates the AST for the full solution using a single call to the underlying LLM!

  • Security: treelang deals with ASTs which means it never needs to know the result from any node in the tree, which may be sensitive (e.g. "my patients email addresses"). The developer can focus on the reliability and security of the underlying tools that will be used to evaluate the AST.

  • Portability: treelang "packages" solutions into ASTs which means that solutions can be easily reused, shared, cached and interpreted.

  • Automated solutions generator: coming soon...

Features

  • Abstract Syntax Tree Representation: treelang speaks Trees.
  • MCP Client: treelang is an MCP client out of the box but any other method of tool provision can be used via the ToolProvider abstraction.
  • LLM Integration: Use LLMs (e.g., OpenAI models) to generate ASTs.
  • Tool Selection: Dynamically select tools (functions) available in the system.
  • Asynchronous Execution: Fully asynchronous design for efficient computation.
  • Higher Order Functions: Support for functional patterns using lambda, map, filter and reduce nodes.
  • Tool generation from Trees: Convert treelang ASTs into Tools that can be added dynamically to MCP servers.

Installation

 pip install treelang

Resources

  • Cookbooks: Play with the Jupiter Notebooks in the cookbook directory to learn more about treelang.

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

treelang-0.7.3.tar.gz (15.8 kB view details)

Uploaded Source

Built Distribution

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

treelang-0.7.3-py3-none-any.whl (17.2 kB view details)

Uploaded Python 3

File details

Details for the file treelang-0.7.3.tar.gz.

File metadata

  • Download URL: treelang-0.7.3.tar.gz
  • Upload date:
  • Size: 15.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.3 CPython/3.12.8 Linux/6.6.6-76060606-generic

File hashes

Hashes for treelang-0.7.3.tar.gz
Algorithm Hash digest
SHA256 857c36723e8ca20cf8a8c70ab02c3d5356e78bebfe28aa65fb6b9adea05202d6
MD5 a169edfaf2a0a3ea0934a983b523104d
BLAKE2b-256 5fd5d817f487ddfcd143d1b8cb3cb94818e6d7e524d0334379b51b7637daab63

See more details on using hashes here.

File details

Details for the file treelang-0.7.3-py3-none-any.whl.

File metadata

  • Download URL: treelang-0.7.3-py3-none-any.whl
  • Upload date:
  • Size: 17.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.3 CPython/3.12.8 Linux/6.6.6-76060606-generic

File hashes

Hashes for treelang-0.7.3-py3-none-any.whl
Algorithm Hash digest
SHA256 8909999c274d0269914956d3f4338aeb1e28066f558713a15338b27a7bee3dce
MD5 bdac3c889bfb4f87a13e982d51deb181
BLAKE2b-256 db7d1418562dcaea41f066e65e83585f0a35cacedb91f6641ba52fc291b2a983

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