mirror of
https://github.com/trustgraph-ai/trustgraph.git
synced 2026-04-25 00:16:23 +02:00
* 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
51 lines
1.8 KiB
Python
Executable file
51 lines
1.8 KiB
Python
Executable file
#!/usr/bin/env python3
|
|
|
|
import json
|
|
from trustgraph.clients.prompt_client import PromptClient
|
|
|
|
p = PromptClient(
|
|
pulsar_host="pulsar://localhost:6650",
|
|
input_queue="non-persistent://tg/request/prompt:default",
|
|
output_queue="non-persistent://tg/response/prompt:default",
|
|
subscriber="test1",
|
|
)
|
|
|
|
chunk="""
|
|
The Space Shuttle was a reusable spacecraft that transported astronauts and cargo to and from Earth's orbit. It was designed to launch like a rocket, maneuver in orbit like a spacecraft, and land like an airplane. The Space Shuttle was NASA's space transportation system and was used for many purposes, including:
|
|
|
|
Carrying astronauts
|
|
The Space Shuttle could carry up to seven astronauts at a time.
|
|
|
|
Launching, recovering, and repairing satellites
|
|
The Space Shuttle could launch satellites into orbit, recover them, and repair them.
|
|
Building the International Space Station
|
|
The Space Shuttle carried large parts into space to build the International Space Station.
|
|
Conducting research
|
|
Astronauts conducted experiments in the Space Shuttle, which was like a science lab in space.
|
|
|
|
The Space Shuttle was retired in 2011 after the Columbia accident in 2003. The Columbia Accident Investigation Board report found that the Space Shuttle was unsafe and expensive to make safe.
|
|
Here are some other facts about the Space Shuttle:
|
|
|
|
The Space Shuttle was 184 ft tall and had a diameter of 29 ft.
|
|
|
|
The Space Shuttle had a mass of 4,480,000 lb.
|
|
The Space Shuttle's first flight was on April 12, 1981.
|
|
The Space Shuttle's last mission was in 2011.
|
|
"""
|
|
|
|
q = "Tell me some facts in the knowledge graph"
|
|
|
|
resp = p.request(
|
|
id="extract-definitions",
|
|
variables = {
|
|
"text": chunk,
|
|
}
|
|
)
|
|
|
|
print(resp)
|
|
|
|
for fact in resp:
|
|
print(fact["entity"], "::")
|
|
print(fact["definition"])
|
|
print()
|
|
|