trustgraph
Basic Information
Trustgraph is a project intended to help teams and developers take control of model context and orchestrate large language models across different deployment targets. The repository is described as enabling orchestration of LLMs through third-party APIs or private, self-hosted deployments while automating how contextual data is provided to models. It is aimed at situations where you need to manage and route context from your own data to language models, maintain control over deployment location, and run the orchestration components in diverse environments. The README and repo summary emphasize context automation, flexible deployment options, and portability rather than a single end-user application.
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App Details
Features
The repository highlights orchestration of LLMs through external APIs and private deployments. It emphasizes context automation so that user or organizational data can be used to supply context to models. The project is described as portable and able to run anywhere, implying support for different infrastructure targets. It focuses on giving users control over context flow and deployment choice. The README text suggests an emphasis on privacy and deployment flexibility by enabling private deployments, and on integration capabilities that let teams adapt context handling to their own data sources and operational requirements.
Use Cases
Trustgraph helps organizations centralize and automate how contextual information is supplied to language models, enabling consistent model inputs across APIs and private deployments. By orchestrating where and how models are called, it reduces the need to reimplement context handling in each application. The support for private deployments can help teams retain data control and meet infrastructure constraints. Portability and the ability to run components in different environments make it easier to integrate LLM-based functionality into existing systems and pipelines. The project is positioned as a developer-focused tool for managing model context and deployment choices.