* Bump setup.py versions for 1.1
* PoC MCP server (#419)
* Very initial MCP server PoC for TrustGraph
* Put service on port 8000
* Add MCP container and packages to buildout
* Update docs for API/CLI changes in 1.0 (#421)
* Update some API basics for the 0.23/1.0 API change
* Add MCP container push (#425)
* Add command args to the MCP server (#426)
* Host and port parameters
* Added websocket arg
* More docs
* MCP client support (#427)
- MCP client service
- Tool request/response schema
- API gateway support for mcp-tool
- Message translation for tool request & response
- Make mcp-tool using configuration service for information
about where the MCP services are.
* Feature/react call mcp (#428)
Key Features
- MCP Tool Integration: Added core MCP tool support with ToolClientSpec and ToolClient classes
- API Enhancement: New mcp_tool method for flow-specific tool invocation
- CLI Tooling: New tg-invoke-mcp-tool command for testing MCP integration
- React Agent Enhancement: Fixed and improved multi-tool invocation capabilities
- Tool Management: Enhanced CLI for tool configuration and management
Changes
- Added MCP tool invocation to API with flow-specific integration
- Implemented ToolClientSpec and ToolClient for tool call handling
- Updated agent-manager-react to invoke MCP tools with configurable types
- Enhanced CLI with new commands and improved help text
- Added comprehensive documentation for new CLI commands
- Improved tool configuration management
Testing
- Added tg-invoke-mcp-tool CLI command for isolated MCP integration testing
- Enhanced agent capability to invoke multiple tools simultaneously
* Test suite executed from CI pipeline (#433)
* Test strategy & test cases
* Unit tests
* Integration tests
* Extending test coverage (#434)
* Contract tests
* Testing embeedings
* Agent unit tests
* Knowledge pipeline tests
* Turn on contract tests
* Increase storage test coverage (#435)
* Fixing storage and adding tests
* PR pipeline only runs quick tests
* Empty configuration is returned as empty list, previously was not in response (#436)
* Update config util to take files as well as command-line text (#437)
* Updated CLI invocation and config model for tools and mcp (#438)
* Updated CLI invocation and config model for tools and mcp
* CLI anomalies
* Tweaked the MCP tool implementation for new model
* Update agent implementation to match the new model
* Fix agent tools, now all tested
* Fixed integration tests
* Fix MCP delete tool params
* Update Python deps to 1.2
* Update to enable knowledge extraction using the agent framework (#439)
* Implement KG extraction agent (kg-extract-agent)
* Using ReAct framework (agent-manager-react)
* ReAct manager had an issue when emitting JSON, which conflicts which ReAct manager's own JSON messages, so refactored ReAct manager to use traditional ReAct messages, non-JSON structure.
* Minor refactor to take the prompt template client out of prompt-template so it can be more readily used by other modules. kg-extract-agent uses this framework.
* Migrate from setup.py to pyproject.toml (#440)
* Converted setup.py to pyproject.toml
* Modern package infrastructure as recommended by py docs
* Install missing build deps (#441)
* Install missing build deps (#442)
* Implement logging strategy (#444)
* Logging strategy and convert all prints() to logging invocations
* Fix/startup failure (#445)
* Fix loggin startup problems
* Fix logging startup problems (#446)
* Fix logging startup problems (#447)
* Fixed Mistral OCR to use current API (#448)
* Fixed Mistral OCR to use current API
* Added PDF decoder tests
* Fix Mistral OCR ident to be standard pdf-decoder (#450)
* Fix Mistral OCR ident to be standard pdf-decoder
* Correct test
* Schema structure refactor (#451)
* Write schema refactor spec
* Implemented schema refactor spec
* Structure data mvp (#452)
* Structured data tech spec
* Architecture principles
* New schemas
* Updated schemas and specs
* Object extractor
* Add .coveragerc
* New tests
* Cassandra object storage
* Trying to object extraction working, issues exist
* Validate librarian collection (#453)
* Fix token chunker, broken API invocation (#454)
* Fix token chunker, broken API invocation (#455)
* Knowledge load utility CLI (#456)
* Knowledge loader
* More tests
- Keeps processing in different flows separate so that data can go to different stores / collections etc.
- Potentially supports different processing flows
- Tidies the processing API with common base-classes for e.g. LLMs, and automatic configuration of 'clients' to use the right queue names in a flow
* - Fixed error reporting in config
- Updated tg-init-pulsar to be able to load initial config to config-svc
- Tweaked API naming and added more config calls
* Tools to dump out prompts and agent tools
* - Locked 0.11 packages to 0.11 deps
- Added 'trustgraph' uber-package which installs the rest
- Added dependency to set package versions before building packages
* Bump version
* Some basic structure for workflows
* Add PyPI publication for 0.12
* Bump version
* Test bundle generation
* Install jsonnet
* Use release action to automate release creation
* Renaming what will become the core package
* Tweaking to get package build working
* Fix metering merge
* Rename to core directory
* Bump version. Use namespace searching for packaging trustgraph-core
* Change references to trustgraph-core
* Forming embeddings-hf package
* Reference modules in core package.
* Build both packages to one container, bump version
* Update YAMLs
* Separate Prom metrics, different processors as different jobs
* Create producers before consumers, may streamline startup.
* Bump version
* Add Pulsar init command, will replace pulsar-admin invocations.
* Integrate tg-init-pulsar with YAMLs
* Update YAMLs
* Add a Prom metric to consumers & consumer/producers to track the running
state.
* New script, gets processor state using prometheus
* Bump version, add tg-processor-state to package
* Update templates
* Added a config to create Minikube k8s, uses hostpath volumes
* Reworked templater to produce docker compose and minikube output
* Fix config templates
Added templates which produce K8s resources. With the provided GCP wrapper, it works on GCP K8s cluster. This isn't stable enough for other folks to use so will need more piloting before it can be documented and released.
