trustgraph/tests.manual/report-chunk-sizes
cybermaggedon 89be656990
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
2025-08-18 20:56:09 +01:00

100 lines
2.2 KiB
Python
Executable file

#!/usr/bin/env python3
"""
Accepts entity/vector pairs and writes them to a Milvus store.
"""
from trustgraph.schema import Chunk
from trustgraph.schema import chunk_ingest_queue
from trustgraph.log_level import LogLevel
from trustgraph.base import Consumer
from threading import Thread, Lock
import time
module = "test-chunk-size"
default_input_queue = chunk_ingest_queue
default_subscriber = module
default_store_uri = 'http://localhost:19530'
class Processor(Consumer):
def __init__(self, **params):
input_queue = params.get("input_queue", default_input_queue)
subscriber = params.get("subscriber", default_subscriber)
width = params.get("width", 200)
super(Processor, self).__init__(
**params | {
"input_queue": input_queue,
"subscriber": subscriber,
"input_schema": Chunk,
}
)
self.sizes = {}
self.width = width
self.lock = Lock()
Thread(target=self.report).start()
def report(self):
while True:
time.sleep(1)
print()
with self.lock:
tot = 0
for i in range(0, 20000, self.width):
k = (i, i + self.width)
if k in self.sizes:
print(f"{i:5d} ..{i+self.width:5d}: {self.sizes[k]}")
tot += self.sizes[k]
print(f"{'Total':13s}: {tot}")
def handle(self, msg):
v = msg.value()
chunk = v.chunk.decode("utf-8")
l = len(chunk)
low = int(l / self.width) * self.width
high = low + self.width
key = (low, high)
with self.lock:
if key not in self.sizes:
self.sizes[key] = 0
self.sizes[key] += 1
@staticmethod
def add_args(parser):
Consumer.add_args(
parser, default_input_queue, default_subscriber,
)
parser.add_argument(
'--width',
type=int,
default=200,
help=f'Histogram width (default: 200)',
)
def run():
Processor.start(module, __doc__)
run()