[![PyPI version](https://img.shields.io/pypi/v/trustgraph.svg)](https://pypi.org/project/trustgraph/) [![License](https://img.shields.io/github/license/trustgraph-ai/trustgraph?color=blue)](LICENSE) ![E2E Tests](https://github.com/trustgraph-ai/trustgraph/actions/workflows/release.yaml/badge.svg) [![Discord](https://img.shields.io/discord/1251652173201149994 )](https://discord.gg/sQMwkRz5GX) [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/trustgraph-ai/trustgraph) [**Website**](https://trustgraph.ai) | [**Docs**](https://docs.trustgraph.ai) | [**YouTube**](https://www.youtube.com/@TrustGraphAI?sub_confirmation=1) | [**Configuration Terminal**](https://config-ui.demo.trustgraph.ai/) | [**Discord**](https://discord.gg/sQMwkRz5GX) | [**Blog**](https://blog.trustgraph.ai/subscribe) trustgraph-ai%2Ftrustgraph | Trendshift # The context development platform
Building applications that need to know things requires more than a database. [TrustGraph](https://trustgraph.ai) is the context development platform: graph-native infrastructure for storing, enriching, and retrieving structured knowledge at any scale. Think like [Supabase](https://github.com/supabase/supabase) but built around context graphs: multi-model storage, semantic retrieval pipelines, portable [context cores](#context-cores), and a full developer toolkit out of the box. Deploy locally or in the cloud. No unnecessary API keys. Just context, engineered. The platform: - [x] Multi-model and multimodal database system - [x] Tabular/relational, key-value - [x] Document, graph, and vectors - [x] Images, video, and audio - [x] Automated data ingest and loading - [x] Quick ingest with semantic similarity retrieval - [x] Ontology structuring for precision retrieval - [x] Out-of-the-box RAG pipelines - [x] DocumentRAG - [x] GraphRAG - [x] OntologyRAG - [x] 3D GraphViz for exploring context - [x] Fully Agentic System - [x] Single Agent - [x] Multi Agent - [x] MCP integration - [x] Run anywhere - [x] Deploy locally with Docker - [x] Deploy in cloud with Kubernetes - [x] Support for all major LLMs - [x] API support for Anthropic, Cohere, Gemini, Mistral, OpenAI, and others - [x] Model inferencing with vLLM, Ollama, TGI, LM Studio, and Llamafiles - [x] Developer friendly - [x] REST API [Docs](https://docs.trustgraph.ai/reference/apis/rest.html) - [x] Websocket API [Docs](https://docs.trustgraph.ai/reference/apis/websocket.html) - [x] Python API [Docs](https://docs.trustgraph.ai/reference/apis/python) - [x] CLI [Docs](https://docs.trustgraph.ai/reference/cli/) ## No API Keys Required How many times have you cloned a repo and opened the `.env.example` to see the dozens of API keys for 3rd party dependencies needed to make the services work? There are only 3 things in TrustGraph that might need an API key: - 3rd party LLM services like Anthropic, Cohere, Gemini, Mistral, OpenAI, etc. - 3rd party OCR like Mistral OCR - The API key *you set* for the TrustGraph API gateway Everything else is included. - [x] Managed Multi-model storage in [Cassandra](https://cassandra.apache.org/_/index.html) - [x] Managed Vector embedding storage in [Qdrant](https://github.com/qdrant/qdrant) - [x] Managed File and Object storage in [Garage](https://github.com/deuxfleurs-org/garage) (S3 compatible) - [x] Managed High-speed Pub/Sub messaging fabric with [Pulsar](https://github.com/apache/pulsar) - [x] Complete LLM inferencing stack for open LLMs with [vLLM](https://github.com/vllm-project/vllm), [TGI](https://github.com/huggingface/text-generation-inference), [Ollama](https://github.com/ollama/ollama), [LM Studio](https://github.com/lmstudio-ai), and [Llamafiles](https://github.com/mozilla-ai/llamafile) ## Quickstart There's no need to clone this repo, unless you want to build from source. TrustGraph is a fully containerized app that deploys as a set of Docker containers. To configure TrustGraph on the command line: ``` npx @trustgraph/config ``` The config process will generate app config that can be run locally with Docker, Podman, or Minikube. The process will output: - `deploy.zip` with either a `docker-compose.yaml` file for a Docker/Podman or `resources.yaml` for Kubernetes - Deployment instructions as `INSTALLATION.md`

For a browser based configuration, try the [Configuration Terminal](https://config-ui.demo.trustgraph.ai/).
Table of Contents
- [**What is a Context Graph?**](#watch-what-is-a-context-graph)
- [**Context Graphs in Action**](#watch-context-graphs-in-action)
- [**Getting Started**](#getting-started-with-trustgraph)
- [**Context Cores**](#context-cores)
- [**Tech Stack**](#tech-stack)
- [**Observability & Telemetry**](#observability--telemetry)
- [**Contributing**](#contributing)
- [**License**](#license)
- [**Support & Community**](#support--community)
## Watch What is a Context Graph? [![What is a Context Graph?](https://img.youtube.com/vi/gZjlt5WcWB4/maxresdefault.jpg)](https://www.youtube.com/watch?v=gZjlt5WcWB4) ## Watch Context Graphs in Action [![Context Graphs in Action with TrustGraph](https://img.youtube.com/vi/sWc7mkhITIo/maxresdefault.jpg)](https://www.youtube.com/watch?v=sWc7mkhITIo) ## Getting Started with TrustGraph - [**Getting Started Guides**](https://docs.trustgraph.ai/getting-started) - [**Using the Workbench**](#workbench) - [**Developer APIs and CLI**](https://docs.trustgraph.ai/reference) - [**Deployment Guides**](https://docs.trustgraph.ai/deployment) ## Workbench The **Workbench** provides tools for all major features of TrustGraph. The **Workbench** is on port `8888` by default. - **Vector Search**: Search the installed knowledge bases - **Agentic, GraphRAG and LLM Chat**: Chat interface for agents, GraphRAG queries, or direct to LLMs - **Relationships**: Analyze deep relationships in the installed knowledge bases - **Graph Visualizer**: 3D GraphViz of the installed knowledge bases - **Library**: Staging area for installing knowledge bases - **Flow Classes**: Workflow preset configurations - **Flows**: Create custom workflows and adjust LLM parameters during runtime - **Knowledge Cores**: Manage resuable knowledge bases - **Prompts**: Manage and adjust prompts during runtime - **Schemas**: Define custom schemas for structured data knowledge bases - **Ontologies**: Define custom ontologies for unstructured data knowledge bases - **Agent Tools**: Define tools with collections, knowledge cores, MCP connections, and tool groups - **MCP Tools**: Connect to MCP servers ## TypeScript Library for UIs There are 3 libraries for quick UI integration of TrustGraph services. - [@trustgraph/client](https://www.npmjs.com/package/@trustgraph/client) - [@trustgraph/react-state](https://www.npmjs.com/package/@trustgraph/react-state) - [@trustgraph/react-provider](https://www.npmjs.com/package/@trustgraph/react-provider) ## Context Cores A Context Core is a **portable, versioned bundle of context** that you can ship between projects and environments, pin in production, and reuse across agents. It packages the “stuff agents need to know” (structured knowledge + embeddings + evidence + policies) into a single artifact, so you can treat context like code: build it, test it, version it, promote it, and roll it back. TrustGraph is built to support this kind of end-to-end context engineering and orchestration workflow. ### What’s inside a Context Core A Context Core typically includes: - Ontology (your domain schema) and mappings - Context Graph (entities, relationships, supporting evidence) - Embeddings / vector indexes for fast semantic entry-point lookup - Source manifests + provenance (where facts came from, when, and how they were derived) - Retrieval policies (traversal rules, freshness, authority ranking) ## Tech Stack TrustGraph provides component flexibility to optimize agent workflows.
LLM APIs
- Anthropic
- AWS Bedrock
- AzureAI
- AzureOpenAI
- Cohere
- Google AI Studio
- Google VertexAI
- Mistral
- OpenAI
LLM Orchestration
- LM Studio
- Llamafiles
- Ollama
- TGI
- vLLM
Multi-model storage
- Apache Cassandra
VectorDB
- Qdrant
File and Object Storage
- Garage
Observability
- Prometheus
- Grafana
- Loki
Data Streaming
- Apache Pulsar
Clouds
- AWS
- Azure
- Google Cloud
- OVHcloud
- Scaleway
## Observability & Telemetry Once the platform is running, access the Grafana dashboard at: ``` http://localhost:3000 ``` Default credentials are: ``` user: admin password: admin ``` The default Grafana dashboard tracks the following:
Telemetry
- LLM Latency
- Error Rate
- Service Request Rates
- Queue Backlogs
- Chunking Histogram
- Error Source by Service
- Rate Limit Events
- CPU usage by Service
- Memory usage by Service
- Models Deployed
- Token Throughput (Tokens/second)
- Cost Throughput (Cost/second)
## Contributing [Developer's Guide](https://docs.trustgraph.ai/guides/building/introduction.html) ## License **TrustGraph** is licensed under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0). Copyright 2024-2025 TrustGraph Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ## Support & Community - Bug Reports & Feature Requests: [Discord](https://discord.gg/sQMwkRz5GX) - Discussions & Questions: [Discord](https://discord.gg/sQMwkRz5GX) - Documentation: [Docs](https://docs.trustgraph.ai/)