mirror of
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270 lines
8.7 KiB
Markdown
270 lines
8.7 KiB
Markdown
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<div align="center">
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[](https://pypi.org/project/trustgraph/) 
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[](https://discord.gg/sQMwkRz5GX) [](https://deepwiki.com/trustgraph-ai/trustgraph)
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[**Docs**](https://docs.trustgraph.ai) | [**YouTube**](https://www.youtube.com/@TrustGraphAI?sub_confirmation=1) | [**Configuration Builder**](https://config-ui.demo.trustgraph.ai/) | [**Discord**](https://discord.gg/sQMwkRz5GX) | [**Blog**](https://blog.trustgraph.ai/subscribe)
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<img src="TG-fullname-logo.svg" width=100% />
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</div>
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# AI-Ready Data Infrastructure
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TrustGraph provides an event-driven data-to-AI platform that transforms raw data into AI-ready datasets through automated structuring, knowledge graph construction, and vector embeddings mapping — all deployable privately, on-prem, or in your cloud. Deploy and manage open LLMs within the same platform, ensuring complete data sovereignty while enabling agents that generate real, actionable insights.
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<details>
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<summary>Table of Contents</summary>
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<br>
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- [**Key Features**](#key-features)<br>
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- [**Why TrustGraph?**](#why-trustgraph)<br>
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- [**Agentic MCP Demo**](#agentic-mcp-demo)<br>
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- [**Getting Started**](#getting-started)<br>
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- [**Configuration Builder**](#configuration-builder)<br>
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- [**Knowledge Cores**](#knowledge-cores)<br>
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- [**Integrations**](#integrations)<br>
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- [**Observability & Telemetry**](#observability--telemetry)<br>
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- [**Contributing**](#contributing)<br>
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- [**License**](#license)<br>
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- [**Support & Community**](#support--community)<br>
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</details>
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## Key Features
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TrustGraph is not just another AI framework but a complete, production-ready platform that bridges the gap between raw data and intelligent, adaptable agent deployments.
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- **AI-Ready Data Transformation**
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*Convert unstructured and structured (bring your own schema) data into AI-optimized formats*.
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- **Automated Knowledge Graph Construction**
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*Transform unstructured data into interconnected knowledge graphs that capture relationships, context, and meaning*.
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- **Semantic Retrieval**
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*TrustGraph combines multiple retrieval methods optimized for each data type and use case*.
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- **Event Driven**
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*Built with Apache Pulsar for high-throughput and reliable messaging*.
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- **Datastore Orchestration**
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*Deploy stores like Apache Cassandra, Neo4j, Qdrant, Milvus, Memgraph, or FalkorDB for structured and unstructured data storage*.
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- **Data Sovereignty**
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*Deploy the entire stack—data pipelines, knowledge graphs, vector stores, and LLMs—on-premises, in your VPC, or across hybrid environments*.
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- **Private LLM Inferencing**
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*In addition to support for all major LLM APIs, deploy and manage open models connected to all of the agentic data infrastructure*.
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- **Agentic GraphRAG**
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*Deploy intelligent agents with context awareness. Bring your own ontology for easy integration into interconnected systems*.
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- **Production Ready**
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*Containerized deployment with Docker/Kubernetes support. Built for enterprise scale with monitoring, observability, and management*.
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- **MCP Integration**
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*Native support for MCP enables standardized agent communication with third-party tools and services while maintaining data sovereignty*.
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- **Full Stack Visibility**
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*3D visualization of knowledge graphs. Grafana dashboard for observability*.
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## Why TrustGraph?
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[](https://www.youtube.com/watch?v=Norboj8YP2M)
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## Agentic MCP Demo
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[](https://www.youtube.com/watch?v=mUCL1b1lmbA)
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## Getting Started
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- [**Quickstart Guide**](https://docs.trustgraph.ai/getting-started/)
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- [**Configuration Builder**](#configuration-builder)
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- [**Workbench**](#workbench)
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- [**Developer APIs and CLI**](https://docs.trustgraph.ai/reference/)
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- [**Deployment Guide**](https://docs.trustgraph.ai/deployment/)
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### Watch TrustGraph 101
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[](https://www.youtube.com/watch?v=rWYl_yhKCng)
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## Configuration Builder
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The [**Configuration Builder**](https://config-ui.demo.trustgraph.ai/) assembles all of the selected components and builds them into a deployable package. It has 4 sections:
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- **Version**: Select the version of TrustGraph you'd like to deploy
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- **Component Selection**: Choose from the available deployment platforms, LLMs, graph store, VectorDB, chunking algorithm, chunking parameters, and LLM parameters
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- **Customization**: Enable OCR pipelines and custom embeddings models
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- **Finish Deployment**: Download the launch `YAML` files with deployment instructions
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## Workbench
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The **Workbench** is a UI that provides tools for interacting with all major features of the platform. The **Workbench** is enabled by default in the **Configuration Builder** and is available at port `8888` on deployment. The **Workbench** has the following capabilities:
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- **Agentic, GraphRAG and LLM Chat**: Chat interface for agentic flows, GraphRAG queries, or directly interfacing with a LLM
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- **Semantic Discovery**: Analyze semantic relationships with vector search, knowledge graph relationships, and 3D graph visualization
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- **Data Management**: Load data into the **Librarian** for processing, create and upload **Knowledge Packages**
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- **Flow Management**: Create and delete processing flow patterns
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- **Prompt Management**: Edit all LLM prompts used in the platform during runtime
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- **Agent Tools**: Define tools used by the Agent Flow including MCP tools
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- **MCP Tools**: Connect to MCP servers
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## Knowledge Cores
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A challenge facing RAG architectures is the ability to quickly reuse and remove datasets from pipelines. **TrustGraph** stores the results of the data ingestion process in reusable Knowledge Cores. Knowledge cores can be loaded and removed during runtime. Some sample knowledge cores are [here](https://github.com/trustgraph-ai/catalog/tree/master/v3).
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A Knowledge Core has two components:
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- Knowledge graph triples
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- Vector embeddings mapped to the knowledge graph
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## Integrations
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TrustGraph provides maximum flexibility to avoid vendor lock-in.
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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>VectorDBs</summary>
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<br>
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- Qdrant (default)<br>
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- Pinecone<br>
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- Milvus<br>
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</details>
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<details>
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<summary>Graph Storage</summary>
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<br>
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- Apache Cassandra (default)<br>
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- Neo4j<br>
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- Memgraph<br>
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- FalkorDB<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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</details>
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<details>
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<summary>Control Plane</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/community/developer.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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