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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

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