apunkt/trustgraph
1
0
Fork 0
mirror of https://github.com/trustgraph-ai/trustgraph.git synced 2026-04-26 00:46:22 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions 1

Release/v1.2 (#457)

Browse source 
* 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
This commit is contained in:
cybermaggedon 2025-08-18 20:56:09 +01:00 • committed by GitHub
parent c85ba197be
commit 89be656990
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
509 changed files with 49632 additions and 5159 deletions
Download patch file Download diff file Expand all files Collapse all files

139
docs/tech-specs/STRUCTURED_DATA_SCHEMAS.md Normal file
View file

@ -0,0 +1,139 @@
# Structured Data Pulsar Schema Changes
## Overview
Based on the STRUCTURED_DATA.md specification, this document proposes the necessary Pulsar schema additions and modifications to support structured data capabilities in TrustGraph.
## Required Schema Changes
### 1. Core Schema Enhancements
#### Enhanced Field Definition
The existing `Field` class in `core/primitives.py` needs additional properties:
```python
class Field(Record):
name = String()
type = String() # int, string, long, bool, float, double, timestamp
size = Integer()
primary = Boolean()
description = String()
# NEW FIELDS:
required = Boolean() # Whether field is required
enum_values = Array(String()) # For enum type fields
indexed = Boolean() # Whether field should be indexed
```
### 2. New Knowledge Schemas
#### 2.1 Structured Data Submission
New file: `knowledge/structured.py`
```python
from pulsar.schema import Record, String, Bytes, Map
from ..core.metadata import Metadata
class StructuredDataSubmission(Record):
metadata = Metadata()
format = String() # "json", "csv", "xml"
schema_name = String() # Reference to schema in config
data = Bytes() # Raw data to ingest
options = Map(String()) # Format-specific options
```
### 3. New Service Schemas
#### 3.1 NLP to Structured Query Service
New file: `services/nlp_query.py`
```python
from pulsar.schema import Record, String, Array, Map, Integer, Double
from ..core.primitives import Error
class NLPToStructuredQueryRequest(Record):
natural_language_query = String()
max_results = Integer()
context_hints = Map(String()) # Optional context for query generation
class NLPToStructuredQueryResponse(Record):
error = Error()
graphql_query = String() # Generated GraphQL query
variables = Map(String()) # GraphQL variables if any
detected_schemas = Array(String()) # Which schemas the query targets
confidence = Double()
```
#### 3.2 Structured Query Service
New file: `services/structured_query.py`
```python
from pulsar.schema import Record, String, Map, Array
from ..core.primitives import Error
class StructuredQueryRequest(Record):
query = String() # GraphQL query
variables = Map(String()) # GraphQL variables
operation_name = String() # Optional operation name for multi-operation documents
class StructuredQueryResponse(Record):
error = Error()
data = String() # JSON-encoded GraphQL response data
errors = Array(String()) # GraphQL errors if any
```
#### 2.2 Object Extraction Output
New file: `knowledge/object.py`
```python
from pulsar.schema import Record, String, Map, Double
from ..core.metadata import Metadata
class ExtractedObject(Record):
metadata = Metadata()
schema_name = String() # Which schema this object belongs to
values = Map(String()) # Field name -> value
confidence = Double()
source_span = String() # Text span where object was found
```
### 4. Enhanced Knowledge Schemas
#### 4.1 Object Embeddings Enhancement
Update `knowledge/embeddings.py` to support structured object embeddings better:
```python
class StructuredObjectEmbedding(Record):
metadata = Metadata()
vectors = Array(Array(Double()))
schema_name = String()
object_id = String() # Primary key value
field_embeddings = Map(Array(Double())) # Per-field embeddings
```
## Integration Points
### Flow Integration
The schemas will be used by new flow modules:
- `trustgraph-flow/trustgraph/decoding/structured` - Uses StructuredDataSubmission
- `trustgraph-flow/trustgraph/query/nlp_query/cassandra` - Uses NLP query schemas
- `trustgraph-flow/trustgraph/query/objects/cassandra` - Uses structured query schemas
- `trustgraph-flow/trustgraph/extract/object/row/` - Consumes Chunk, produces ExtractedObject
- `trustgraph-flow/trustgraph/storage/objects/cassandra` - Uses Rows schema
- `trustgraph-flow/trustgraph/embeddings/object_embeddings/qdrant` - Uses object embedding schemas
## Implementation Notes
1. **Schema Versioning**: Consider adding a `version` field to RowSchema for future migration support
2. **Type System**: The `Field.type` should support all Cassandra native types
3. **Batch Operations**: Most services should support both single and batch operations
4. **Error Handling**: Consistent error reporting across all new services
5. **Backwards Compatibility**: Existing schemas remain unchanged except for minor Field enhancements
## Next Steps
1. Implement schema files in the new structure
2. Update existing services to recognize new schema types
3. Implement flow modules that use these schemas
4. Add gateway/rev-gateway endpoints for new services
5. Create unit tests for schema validation