mirror of
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275 lines
10 KiB
Markdown
275 lines
10 KiB
Markdown
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<div align="center">
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<img src="TG-fullname-logo.svg" width=100% />
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[](https://pypi.org/project/trustgraph/) [](LICENSE) 
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[](https://discord.gg/sQMwkRz5GX) [](https://deepwiki.com/trustgraph-ai/trustgraph)
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[**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)
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<a href="https://trendshift.io/repositories/17291" target="_blank"><img src="https://trendshift.io/api/badge/repositories/17291" alt="trustgraph-ai%2Ftrustgraph | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
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# The context development platform
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</div>
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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.
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The platform:
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- [x] Multi-model and multimodal database system
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- [x] Tabular/relational, key-value
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- [x] Document, graph, and vectors
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- [x] Images, video, and audio
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- [x] Automated data ingest and loading
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- [x] Quick ingest with semantic similarity retrieval
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- [x] Ontology structuring for precision retrieval
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- [x] Out-of-the-box RAG pipelines
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- [x] DocumentRAG
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- [x] GraphRAG
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- [x] OntologyRAG
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- [x] 3D GraphViz for exploring context
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- [x] Fully Agentic System
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- [x] Single Agent
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- [x] Multi Agent
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- [x] MCP integration
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- [x] Run anywhere
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- [x] Deploy locally with Docker
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- [x] Deploy in cloud with Kubernetes
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- [x] Support for all major LLMs
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- [x] API support for Anthropic, Cohere, Gemini, Mistral, OpenAI, and others
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- [x] Model inferencing with vLLM, Ollama, TGI, LM Studio, and Llamafiles
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- [x] Developer friendly
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- [x] REST API [Docs](https://docs.trustgraph.ai/reference/apis/rest.html)
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- [x] Websocket API [Docs](https://docs.trustgraph.ai/reference/apis/websocket.html)
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- [x] Python API [Docs](https://docs.trustgraph.ai/reference/apis/python)
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- [x] CLI [Docs](https://docs.trustgraph.ai/reference/cli/)
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## No API Keys Required
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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:
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- 3rd party LLM services like Anthropic, Cohere, Gemini, Mistral, OpenAI, etc.
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- 3rd party OCR like Mistral OCR
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- The API key *you set* for the TrustGraph API gateway
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Everything else is included.
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- [x] Managed Multi-model storage in [Cassandra](https://cassandra.apache.org/_/index.html)
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- [x] Managed Vector embedding storage in [Qdrant](https://github.com/qdrant/qdrant)
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- [x] Managed File and Object storage in [Garage](https://github.com/deuxfleurs-org/garage) (S3 compatible)
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- [x] Managed High-speed Pub/Sub messaging fabric with [Pulsar](https://github.com/apache/pulsar)
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- [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)
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## Quickstart
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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:
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```
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npx @trustgraph/config
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```
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The config process will generate an app config that can be run locally with Docker, Podman, or Minikube. The process will output:
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- `deploy.zip` with either a `docker-compose.yaml` file for a Docker/Podman or `resources.yaml` for Kubernetes
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- Deployment instructions as `INSTALLATION.md`
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<p align="center">
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<video src="https://github.com/user-attachments/assets/2978a6aa-4c9c-4d7c-ad02-8f3d01a1c602"
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width="80%" controls></video>
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</p>
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For a browser based configuration, try the [Configuration Terminal](https://config-ui.demo.trustgraph.ai/).
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## Watch What is a Context Graph?
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[](https://www.youtube.com/watch?v=gZjlt5WcWB4)
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## Watch Context Graphs in Action
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[](https://www.youtube.com/watch?v=sWc7mkhITIo)
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## Getting Started with TrustGraph
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- [**Getting Started Guides**](https://docs.trustgraph.ai/getting-started)
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- [**Using the Workbench**](#workbench)
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- [**Developer APIs and CLI**](https://docs.trustgraph.ai/reference)
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- [**Deployment Guides**](https://docs.trustgraph.ai/deployment)
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## Workbench
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The **Workbench** provides tools for all major features of TrustGraph. The **Workbench** is on port `8888` by default.
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- **Vector Search**: Search the installed knowledge bases
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- **Agentic, GraphRAG and LLM Chat**: Chat interface for agents, GraphRAG queries, or direct to LLMs
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- **Relationships**: Analyze deep relationships in the installed knowledge bases
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- **Graph Visualizer**: 3D GraphViz of the installed knowledge bases
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- **Library**: Staging area for installing knowledge bases
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- **Flow Classes**: Workflow preset configurations
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- **Flows**: Create custom workflows and adjust LLM parameters during runtime
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- **Knowledge Cores**: Manage resuable knowledge bases
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- **Prompts**: Manage and adjust prompts during runtime
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- **Schemas**: Define custom schemas for structured data knowledge bases
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- **Ontologies**: Define custom ontologies for unstructured data knowledge bases
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- **Agent Tools**: Define tools with collections, knowledge cores, MCP connections, and tool groups
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- **MCP Tools**: Connect to MCP servers
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## TypeScript Library for UIs
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There are 3 libraries for quick UI integration of TrustGraph services.
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- [@trustgraph/client](https://www.npmjs.com/package/@trustgraph/client)
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- [@trustgraph/react-state](https://www.npmjs.com/package/@trustgraph/react-state)
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- [@trustgraph/react-provider](https://www.npmjs.com/package/@trustgraph/react-provider)
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## Context Cores
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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.
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### What’s inside a Context Core
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A Context Core typically includes:
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- Ontology (your domain schema) and mappings
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- Context Graph (entities, relationships, supporting evidence)
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- Embeddings / vector indexes for fast semantic entry-point lookup
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- Source manifests + provenance (where facts came from, when, and how they were derived)
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- Retrieval policies (traversal rules, freshness, authority ranking)
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## Tech Stack
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TrustGraph provides component flexibility to optimize agent workflows.
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<details>
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<summary>LLM APIs</summary>
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<br>
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- Anthropic<br>
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- AWS Bedrock<br>
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- AzureAI<br>
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- AzureOpenAI<br>
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- Cohere<br>
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- Google AI Studio<br>
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- Google VertexAI<br>
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- Mistral<br>
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- OpenAI<br>
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</details>
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<details>
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<summary>LLM Orchestration</summary>
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<br>
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- LM Studio<br>
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- Llamafiles<br>
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- Ollama<br>
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- TGI<br>
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- vLLM<br>
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</details>
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<details>
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<summary>Multi-model storage</summary>
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<br>
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- Apache Cassandra<br>
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</details>
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<details>
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<summary>VectorDB</summary>
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<br>
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- Qdrant<br>
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</details>
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<details>
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<summary>File and Object Storage</summary>
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<br>
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- Garage<br>
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</details>
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<details>
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<summary>Observability</summary>
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<br>
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- Prometheus<br>
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- Grafana<br>
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- Loki<br>
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</details>
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<details>
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<summary>Data Streaming</summary>
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<br>
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- Apache Pulsar<br>
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</details>
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<details>
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<summary>Clouds</summary>
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<br>
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- AWS<br>
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- Azure<br>
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- Google Cloud<br>
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- OVHcloud<br>
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- Scaleway<br>
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</details>
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## Observability & Telemetry
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Once the platform is running, access the Grafana dashboard at:
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```
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http://localhost:3000
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```
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Default credentials are:
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```
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user: admin
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password: admin
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```
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The default Grafana dashboard tracks the following:
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<details>
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<summary>Telemetry</summary>
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<br>
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- LLM Latency<br>
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- Error Rate<br>
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- Service Request Rates<br>
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- Queue Backlogs<br>
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- Chunking Histogram<br>
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- Error Source by Service<br>
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- Rate Limit Events<br>
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- CPU usage by Service<br>
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- Memory usage by Service<br>
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- Models Deployed<br>
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- Token Throughput (Tokens/second)<br>
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- Cost Throughput (Cost/second)<br>
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</details>
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## Contributing
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[Developer's Guide](https://docs.trustgraph.ai/guides/building/introduction.html)
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## License
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**TrustGraph** is licensed under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0).
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Copyright 2024-2025 TrustGraph
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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## Support & Community
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- Bug Reports & Feature Requests: [Discord](https://discord.gg/sQMwkRz5GX)
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- Discussions & Questions: [Discord](https://discord.gg/sQMwkRz5GX)
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- Documentation: [Docs](https://docs.trustgraph.ai/)
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