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-0.7.2.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-0.7.2-py3-none-any.whl (17.1 kB view details)

Uploaded Python 3

File details

Details for the file treelang-0.7.2.tar.gz.

File metadata

  • Download URL: treelang-0.7.2.tar.gz
  • Upload date:
  • Size: 15.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.1 CPython/3.12.8 Linux/6.9.3-76060903-generic

File hashes

Hashes for treelang-0.7.2.tar.gz
Algorithm Hash digest
SHA256 86a7ec6e4bbe49aa309b2eab0ee566f5726e12293886c7123d15ffe34c3db6b8
MD5 c9c33d395c85dae18c2ada536c005ee5
BLAKE2b-256 704e162c6aa0ecd405976cb7fcd806a6447f1982c748844100dff583e0cf195c

See more details on using hashes here.

File details

Details for the file treelang-0.7.2-py3-none-any.whl.

File metadata

  • Download URL: treelang-0.7.2-py3-none-any.whl
  • Upload date:
  • Size: 17.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.1 CPython/3.12.8 Linux/6.9.3-76060903-generic

File hashes

Hashes for treelang-0.7.2-py3-none-any.whl
Algorithm Hash digest
SHA256 ed3321393930286cd7a98657884925b1203496930082a2c9a09469797ec2dd9a
MD5 43229c08f0edd23c5687718693c09260
BLAKE2b-256 9d3aacd40f789963e0929506216d6037b55a89d68262c179ab92fdb04e60a256

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