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Release/v1.2 (#457)
* 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
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162
tests/unit/test_storage/conftest.py
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tests/unit/test_storage/conftest.py
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"""
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Shared fixtures for storage tests
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"""
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import pytest
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from unittest.mock import AsyncMock, MagicMock
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@pytest.fixture
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def base_storage_config():
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"""Base configuration for storage processors"""
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return {
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'taskgroup': AsyncMock(),
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'id': 'test-storage-processor'
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}
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@pytest.fixture
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def qdrant_storage_config(base_storage_config):
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"""Configuration for Qdrant storage processors"""
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return base_storage_config | {
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'store_uri': 'http://localhost:6333',
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'api_key': 'test-api-key'
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}
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@pytest.fixture
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def mock_qdrant_client():
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"""Mock Qdrant client"""
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mock_client = MagicMock()
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mock_client.collection_exists.return_value = True
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mock_client.create_collection.return_value = None
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mock_client.upsert.return_value = None
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return mock_client
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@pytest.fixture
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def mock_uuid():
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"""Mock UUID generation"""
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mock_uuid = MagicMock()
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mock_uuid.uuid4.return_value = MagicMock()
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mock_uuid.uuid4.return_value.__str__ = MagicMock(return_value='test-uuid-123')
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return mock_uuid
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# Document embeddings fixtures
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@pytest.fixture
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def mock_document_embeddings_message():
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"""Mock document embeddings message"""
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mock_message = MagicMock()
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mock_message.metadata.user = 'test_user'
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mock_message.metadata.collection = 'test_collection'
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mock_chunk = MagicMock()
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mock_chunk.chunk.decode.return_value = 'test document chunk'
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mock_chunk.vectors = [[0.1, 0.2, 0.3]]
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mock_message.chunks = [mock_chunk]
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return mock_message
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@pytest.fixture
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def mock_document_embeddings_multiple_chunks():
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"""Mock document embeddings message with multiple chunks"""
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mock_message = MagicMock()
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mock_message.metadata.user = 'multi_user'
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mock_message.metadata.collection = 'multi_collection'
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mock_chunk1 = MagicMock()
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mock_chunk1.chunk.decode.return_value = 'first document chunk'
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mock_chunk1.vectors = [[0.1, 0.2]]
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mock_chunk2 = MagicMock()
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mock_chunk2.chunk.decode.return_value = 'second document chunk'
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mock_chunk2.vectors = [[0.3, 0.4]]
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mock_message.chunks = [mock_chunk1, mock_chunk2]
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return mock_message
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@pytest.fixture
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def mock_document_embeddings_multiple_vectors():
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"""Mock document embeddings message with multiple vectors per chunk"""
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mock_message = MagicMock()
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mock_message.metadata.user = 'vector_user'
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mock_message.metadata.collection = 'vector_collection'
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mock_chunk = MagicMock()
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mock_chunk.chunk.decode.return_value = 'multi-vector document chunk'
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mock_chunk.vectors = [
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[0.1, 0.2, 0.3],
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[0.4, 0.5, 0.6],
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[0.7, 0.8, 0.9]
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]
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mock_message.chunks = [mock_chunk]
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return mock_message
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@pytest.fixture
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def mock_document_embeddings_empty_chunk():
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"""Mock document embeddings message with empty chunk"""
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mock_message = MagicMock()
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mock_message.metadata.user = 'empty_user'
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mock_message.metadata.collection = 'empty_collection'
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mock_chunk = MagicMock()
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mock_chunk.chunk.decode.return_value = "" # Empty string
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mock_chunk.vectors = [[0.1, 0.2]]
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mock_message.chunks = [mock_chunk]
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return mock_message
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# Graph embeddings fixtures
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@pytest.fixture
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def mock_graph_embeddings_message():
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"""Mock graph embeddings message"""
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mock_message = MagicMock()
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mock_message.metadata.user = 'test_user'
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mock_message.metadata.collection = 'test_collection'
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mock_entity = MagicMock()
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mock_entity.entity.value = 'test_entity'
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mock_entity.vectors = [[0.1, 0.2, 0.3]]
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mock_message.entities = [mock_entity]
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return mock_message
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@pytest.fixture
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def mock_graph_embeddings_multiple_entities():
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"""Mock graph embeddings message with multiple entities"""
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mock_message = MagicMock()
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mock_message.metadata.user = 'multi_user'
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mock_message.metadata.collection = 'multi_collection'
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mock_entity1 = MagicMock()
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mock_entity1.entity.value = 'entity_one'
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mock_entity1.vectors = [[0.1, 0.2]]
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mock_entity2 = MagicMock()
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mock_entity2.entity.value = 'entity_two'
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mock_entity2.vectors = [[0.3, 0.4]]
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mock_message.entities = [mock_entity1, mock_entity2]
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return mock_message
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@pytest.fixture
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def mock_graph_embeddings_empty_entity():
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"""Mock graph embeddings message with empty entity"""
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mock_message = MagicMock()
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mock_message.metadata.user = 'empty_user'
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mock_message.metadata.collection = 'empty_collection'
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mock_entity = MagicMock()
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mock_entity.entity.value = "" # Empty string
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mock_entity.vectors = [[0.1, 0.2]]
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mock_message.entities = [mock_entity]
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return mock_message
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