integration: langchain-timbr provider documentation

[wpbarco]

Overview

This PR adds Timbr as a new integration provider to the LangChain documentation. Timbr is a semantic SQL knowledge graph platform that enables natural language to SQL query generation using ontology-driven semantic layers.

The documentation covers:

• Timbr provider overview page with installation instructions
• Integration guide showing usage of Timbr's chains and agents
• Complete setup and configuration examples
• Environment-based configuration support
• Multiple usage patterns: pre-built agent, individual chains, and manual connector

Type of change

Type: Add new integration documentation

Related issues/PRs

• Related integration files in langchain-timbr package
• Timbr documentation

Checklist

• I have read the contributing guidelines
• I have tested my changes locally using make lint_md
• All code examples follow LangChain documentation standards
• I have used root relative paths for internal links
• I have updated navigation in src/docs.json if needed (not applicable - added sections to existing pages)
• I have gotten approval from the relevant reviewers
• (Internal team members only / optional) I have created a preview deployment using the Create Preview Branch workflow

Additional notes

Changes made:

1. src/oss/python/integrations/providers/timbr.mdx (new file):

   • Provider overview describing Timbr's semantic SQL capabilities
   • Installation instructions with optional LLM provider selection
   • Import examples for main chains and agent
   • Cross-reference to detailed usage guide

2. src/oss/python/integrations/graphs/timbr.mdx (new file):

   • Comprehensive integration guide with setup instructions

   • Environment-based configuration documentation

   • Examples for main tools:

     • ExecuteTimbrQueryChain for query execution

     • GenerateAnswerChain for response generation

     • TimbrLlmConnector for manual integration

   • LLM configuration examples using both standard LangChain models and Timbr's LlmWrapper

   • Links to additional resources (PyPI, GitHub, official docs)

3. src\oss\python\integrations\providers\all_providers.mdx (updated):

   • Added Timbr card in alphabetical order

     • Description: "Semantic layer for data integration and querying"

     • Link to Timbr provider page

Key features documented:

• Semantic SQL generation: Natural language to SQL using ontology-driven semantic layers
• Environment configuration: Optional environment variables for simplified setup
• Multiple LLM support: Compatible with OpenAI, Anthropic, Google, Azure, Snowflake, Databricks, and Vertex AI
• Flexible usage patterns: Pre-built agent, individual chains, or manual connector
• Usage metadata: Token counting and tracking for LLM interactions

[vercel]

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[Copilot]

Pull Request Overview

This PR introduces comprehensive documentation for the Timbr integration, adding it as a new provider for semantic SQL knowledge graph capabilities in LangChain. The documentation enables users to leverage Timbr's ontology-driven semantic layer for natural language to SQL query generation.

Key changes:

• New provider documentation with installation and setup instructions
• Comprehensive integration guide covering chains, agents, and manual connector usage
• Environment-based configuration support introduced in v2.0.0

Reviewed Changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 4 comments.

File	Description
src/oss/python/integrations/providers/timbr.mdx	New provider overview page introducing Timbr's semantic SQL capabilities with installation instructions and usage imports
src/oss/python/integrations/providers/all_providers.mdx	Added Timbr card to the providers listing in alphabetical order
src/oss/python/integrations/graphs/timbr.mdx	Comprehensive integration guide with configuration examples, chain usage patterns, and connector documentation

[Copilot]

Pull Request Overview

Copilot reviewed 3 out of 3 changed files in this pull request and generated 2 comments.

[Copilot]

Pull Request Overview

Copilot reviewed 3 out of 3 changed files in this pull request and generated 2 comments.