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title Python packages
nav_order 4
parent Reference
review_date 2026-06-01

Python Packages

TrustGraph is distributed as a collection of Python packages available on PyPI. Each package provides specific functionality while maintaining minimal dependencies to avoid large installation footprints.

Installation

All packages are available on PyPI and can be installed using pip:

pip install trustgraph-base
pip install trustgraph-flow
pip install trustgraph-cli
# ... and so on

Note that all packages depend on trustgraph-base as a dependency so there is no need to install it unless you are using that package in isolation.

Version strategy

The TrustGraph release process creates containers and packages with the same version number. For best results, match the container and package version numbers.

Package Structure

Package Description Major Dependencies Scripts
trustgraph-base Minimal base classes and API support pulsar-client, prometheus-client None
trustgraph-flow Core AI processing pipeline capabilities anthropic, openai, langchain, neo4j, milvus, pinecone, qdrant, fastembed, ollama, cohere, mistralai 60+ processing scripts
trustgraph-cli Command-line interface for client-side operations requests, aiohttp, rdflib, tabulate, websockets 49 tg-* CLI commands
trustgraph-embeddings-hf HuggingFace embeddings support torch, transformers, sentence-transformers, huggingface-hub embeddings-hf
trustgraph-bedrock AWS Bedrock integration boto3 text-completion-bedrock
trustgraph-vertexai Google Vertex AI integration google-cloud-aiplatform text-completion-vertexai
trustgraph-unstructured Universal multi-format document decoder unstructured[csv,docx,epub,md,odt,pdf,pptx,rst,rtf,tsv,xlsx], python-magic universal-decoder
trustgraph-ocr OCR processing capabilities boto3, pdf2image, pytesseract pdf-ocr
trustgraph-mcp Model Context Protocol server mcp, websockets mcp-server

Package Dependencies

Core Dependencies

  • trustgraph-base: Minimal foundation with messaging and metrics
  • trustgraph-flow: Full AI pipeline with extensive ML/AI library support
  • trustgraph-cli: Client tools with web and RDF support

Specialized Dependencies

  • embeddings-hf: PyTorch and HuggingFace ecosystem
  • bedrock/vertexai: Cloud provider SDKs
  • ocr: Image processing and OCR libraries
  • mcp: Model Context Protocol implementation

Python Requirements

All packages require Python {{site.data.software.python-min-version}} or higher and are licensed under GPLv3+.

Architecture

The modular design allows users to install only the components they need:

  • Install trustgraph-base for basic API integration
  • Add trustgraph-flow for full AI processing capabilities
  • Include trustgraph-cli for command-line management
  • Add specialized packages (embeddings, cloud providers, OCR) as needed