Skip to main content

LangChain & LangGraph extensions that parse LLM prompts into Timbr semantic SQL and execute them.

Project description

Timbr logo description

FOSSA Status FOSSA Status

Python 3.10 Python 3.11 Python 3.12

Timbr LangChain LLM SDK

Timbr LangChain LLM SDK is a Python SDK that extends LangChain and LangGraph with custom agents, chains, and nodes for seamless integration with the Timbr semantic layer. It enables converting natural language prompts into optimized semantic-SQL queries and executing them directly against your data.

Timbr LangGraph pipeline

Dependencies

  • Access to a timbr-server
  • Python 3.10 or newer

Installation

Using pip

python -m pip install langchain-timbr

Install with selected LLM providers

One of: openai, anthropic, google, azure_openai, snowflake, databricks, vertex_ai, bedrock (or 'all')

python -m pip install 'langchain-timbr[<your selected providers, separated by comma w/o space>]'

Using pip from github

pip install git+https://github.com/WPSemantix/langchain-timbr

Documentation

For comprehensive documentation and usage examples, please visit:

Configuration

The SDK uses environment variables for configuration. All configurations are optional - when set, they serve as default values for langchain-timbr provided tools. Below are all available configuration options:

Configuration Options

Timbr Connection Settings

  • TIMBR_URL - The URL of your Timbr server
  • TIMBR_TOKEN - Authentication token for accessing the Timbr server
  • TIMBR_ONTOLOGY - The ontology to use (also accepts ONTOLOGY as an alias)
  • IS_JWT - Whether the token is a JWT token (true/false)
  • JWT_TENANT_ID - Tenant ID for JWT authentication

Cache and Data Processing

  • CACHE_TIMEOUT - Timeout for caching operations in seconds
  • IGNORE_TAGS - Comma-separated list of tags to ignore during processing
  • IGNORE_TAGS_PREFIX - Comma-separated list of tag prefixes to ignore during processing

LLM Configuration

  • LLM_TYPE - The type of LLM provider to use
  • LLM_MODEL - The specific model to use with the LLM provider
  • LLM_API_KEY - API key or client secret for the LLM provider
  • LLM_TEMPERATURE - Temperature setting for LLM responses (controls randomness)
  • LLM_ADDITIONAL_PARAMS - Additional parameters to pass to the LLM
  • LLM_TIMEOUT - Timeout for LLM requests in seconds
  • LLM_TENANT_ID - LLM provider tenant/directory ID (Used for Service Principal authentication)
  • LLM_CLIENT_ID - LLM provider client ID (Used for Service Principal authentication)
  • LLM_CLIENT_SECRET - LLM provider client secret (Used for Service Principal authentication)
  • LLM_ENDPOINT - LLM provider OpenAI endpoint URL
  • LLM_API_VERSION - LLM provider API version
  • LLM_SCOPE - LLM provider authentication scope

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

langchain_timbr-2.1.14.tar.gz (61.1 kB view details)

Uploaded Source

Built Distribution

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

langchain_timbr-2.1.14-py3-none-any.whl (63.1 kB view details)

Uploaded Python 3

File details

Details for the file langchain_timbr-2.1.14.tar.gz.

File metadata

  • Download URL: langchain_timbr-2.1.14.tar.gz
  • Upload date:
  • Size: 61.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for langchain_timbr-2.1.14.tar.gz
Algorithm Hash digest
SHA256 13f063696b7454ac649d25a08dd5bc9881d8e1162569aabd69c0a8690c378d25
MD5 6472ffaf746f02b05347c573203a5706
BLAKE2b-256 07166a5fa97344efd2db1f13d79e5bc4049334b6798149c58c961436fe33998e

See more details on using hashes here.

File details

Details for the file langchain_timbr-2.1.14-py3-none-any.whl.

File metadata

File hashes

Hashes for langchain_timbr-2.1.14-py3-none-any.whl
Algorithm Hash digest
SHA256 c213e13acf31d67fe6b686ba46a54605d39226fee316cadf947a44ea84f9987f
MD5 31bf5f99bc66c66ee8f08581d4cb1dcc
BLAKE2b-256 cf57a309a569e89bde4250aeed5844a6198055ea6058b080b29f8a25687ba818

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