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feat: Add Forge LLM provider support#1090
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## Changes - Added ForgeLlmService subclassing OpenAILlmService in src/vanna/integrations/forge/, added forge optional dependency in pyproject.toml - Environment variable: FORGE_API_KEY - Base URL: https://api.forge.tensorblock.co/v1 - Model format: Provider/model-name (e.g., OpenAI/gpt-4o) - Non-breaking: purely additive, existing providers are untouched ## About Forge Forge (https://github.com/TensorBlock/forge) is an open-source middleware that routes inference across 40+ upstream providers (including OpenAI, Anthropic, Gemini, DeepSeek, and OpenRouter). It is OpenAI API compatible — works with the standard OpenAI SDK by changing base_url and api_key. ## Motivation We have seen growing interest from users who standardize on Forge for their model management and want to use it natively with Vanna. This integration aims to bridge that gap. ## Key Benefits - Self-Hosted & Privacy-First: Forge is open-source and designed to be self-hosted, critical for users who require data sovereignty - Future-Proofing: acts as a decoupling layer — instead of maintaining individual adapters for every new provider, Forge users can access them immediately - Compatibility: supports established aggregators (like OpenRouter) as well as direct provider connections (BYOK) ## References - Repo: https://github.com/TensorBlock/forge - Docs: https://www.tensorblock.co/api-docs/overview - Main Page: https://www.tensorblock.co/
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Changes
About Forge
Forge (https://github.com/TensorBlock/forge) is an open-source middleware that routes inference across 40+ upstream providers (including OpenAI, Anthropic, Gemini, DeepSeek, and OpenRouter). It is OpenAI API compatible — works with the standard OpenAI SDK by changing base_url and api_key.
Motivation
We have seen growing interest from users who standardize on Forge for their model management and want to use it natively with Vanna. This integration aims to bridge that gap.
Key Benefits
References