6027ba6bb5
DispatcherManager caches one ServiceRequestor per (flow_id, kind) in
self.dispatchers, lazily created on first use. stop_flow dropped the
flow from self.flows but never touched the cached dispatchers, so
their publisher/subscriber connections persisted — bound to the
per-flow exchanges that flow-svc tears down when the flow stops.
If the same flow id was later re-created, flow-svc re-declared fresh
per-flow exchanges, but the gateway's cached dispatcher still held a
subscription queue bound to the now-gone old response exchange.
Requests went out fine (publishers target exchanges by name and the
new exchange has the right name), but responses landed on an exchange
with no binding to the dispatcher's queue and were silently dropped.
The calling CLI or websocket session hung waiting for a reply that
would never arrive.
Reproduction before fix:
tg-start-flow -i test-flow-1 ...
# any query on test-flow-1 works
tg-stop-flow -i test-flow-1
tg-start-flow -i test-flow-1 ...
tg-show-graph -f test-flow-1 -C <collection> # hangs
Flows that were never stopped (e.g. "default" in a typical session)
were unaffected — their cached dispatcher still pointed at live
plumbing. That's why the bug appeared flow-name-specific at first
glance; it's actually lifecycle-specific.
Fix: in stop_flow, evict and cleanly stop() every cached dispatcher
keyed on the stopped flow id. Next request after restart constructs
a fresh dispatcher against the freshly-declared exchanges. Tuple
shape check preserves global dispatchers, which use (None, kind) as
their key and must survive flow churn.
Uses pop(id, None) instead of del in case stop_flow is invoked
defensively for a flow the gateway never saw.
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|---|---|---|
| .github/workflows | ||
| containers | ||
| dev-tools | ||
| docs | ||
| specs | ||
| test-api | ||
| tests | ||
| tests.manual | ||
| trustgraph | ||
| trustgraph-base | ||
| trustgraph-bedrock | ||
| trustgraph-cli | ||
| trustgraph-embeddings-hf | ||
| trustgraph-flow | ||
| trustgraph-mcp | ||
| trustgraph-ocr | ||
| trustgraph-unstructured | ||
| trustgraph-vertexai | ||
| .coveragerc | ||
| .gitignore | ||
| check_imports.py | ||
| context7.json | ||
| DEVELOPER_GUIDE.md | ||
| install_packages.sh | ||
| LICENSE | ||
| Makefile | ||
| ontology-prompt.md | ||
| product-platform-diagram.svg | ||
| prompt.txt | ||
| README.md | ||
| requirements.txt | ||
| run_tests.sh | ||
| schema.ttl | ||
| SECURITY.md | ||
| TEST_CASES.md | ||
| TEST_SETUP.md | ||
| TEST_STRATEGY.md | ||
| TESTS.md | ||
| TG-fullname-logo.svg | ||
| TG-hero-diagram.svg | ||
Building applications that need to know things requires more than a database. TrustGraph is the context development platform: graph-native infrastructure for storing, enriching, and retrieving structured knowledge at any scale. Think like Supabase but built around context graphs: multi-model storage, semantic retrieval pipelines, portable 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:
- Multi-model and multimodal database system
- Tabular/relational, key-value
- Document, graph, and vectors
- Images, video, and audio
- Automated data ingest and loading
- Quick ingest with semantic similarity retrieval
- Ontology structuring for precision retrieval
- Out-of-the-box RAG pipelines
- DocumentRAG
- GraphRAG
- OntologyRAG
- 3D GraphViz for exploring context
- Fully Agentic System
- Single Agent
- Multi Agent
- MCP integration
- Run anywhere
- Deploy locally with Docker
- Deploy in cloud with Kubernetes
- Support for all major LLMs
- API support for Anthropic, Cohere, Gemini, Mistral, OpenAI, and others
- Model inferencing with vLLM, Ollama, TGI, LM Studio, and Llamafiles
- Developer friendly
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.
- Managed Multi-model storage in Cassandra
- Managed Vector embedding storage in Qdrant
- Managed File and Object storage in Garage (S3 compatible)
- Managed High-speed Pub/Sub messaging fabric with Pulsar
- Complete LLM inferencing stack for open LLMs with vLLM, TGI, Ollama, LM Studio, and Llamafiles
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 an app config that can be run locally with Docker, Podman, or Minikube. The process will output:
deploy.zipwith either adocker-compose.yamlfile for a Docker/Podman orresources.yamlfor Kubernetes- Deployment instructions as
INSTALLATION.md
For a browser based configuration, try the Configuration Terminal.
Watch What is a Context Graph?
Watch Context Graphs in Action
Getting Started with TrustGraph
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.
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
License
TrustGraph is licensed under Apache 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.