langchain-timbr 2.1.0

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

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.

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 (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:

• Timbr LangChain Documentation
• Timbr LangGraph Documentation

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