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hugpy-tools

hugpy_tools is a standalone set of tools for autonomous agents. Its core uses only the standard library. Optional backends add document extraction, model-specific token counting, rendering, media, image, desktop and VM tools. It does not import Toolserver, and it needs no running service, database or fleet.

Distribution hugpy-tools 0.2.11, import hugpy_tools. It has no runtime dependencies.

Status: LIVE. It is installed as a library in the Core, Agent and Harness environments, and in the Toolserver host venv at /opt/abstract-toolserver/venv-0.0.99. Toolserver uses the staged 0.2.11 source for its media tools. It runs no service of its own. Its consumers:

  • abstract_toolserver 0.0.98 and later: the tool registry
  • hugpy-agent
  • hugpy-harness: hugpy_harness.tools.portable
  • the media, video and agent toolsets: hugpy_tools.schema.build_parameters, imported lazily

The live 7004_toolserver service runs abstract_toolserver 0.0.99. See docs/packages.md.

Standalone use

pip install hugpy-tools
hugpy-tools list [--optional]         # every tool: name, description, inputSchema (JSON)
hugpy-tools call text_estimate_tokens --arguments '{"text":"hello world"}'
# The same CLI is available as python -m hugpy_tools.
from hugpy_tools import call_tool, get_toolset, list_tools

result = call_tool("fs_read_lines", {"path": "/tmp/example.txt", "start": 1, "end": 20})
schemas = list_tools()  # name, description, inputSchema
tools = get_toolset()  # category -> route -> callable; fresh mappings per call

Direct module functions remain available. include_optional=True adds backend tools to each registry API, or use --optional with the CLI. Discovery imports no optional backend; an unavailable dependency fails when that tool is called. Install only the extras needed: files, text, web, legacy (all three), render, images, vision, media, or desktop. Rendering also needs a Playwright browser installation; VM operations require host libvirt/LXD tools.

Toolserver integration

The dependency runs one way: abstract_toolserver imports hugpy_tools.

The optional media tools call the authoritative hugpy-media API through backends.media_proxy (default http://127.0.0.1:7340/api, overridable with HUGPY_MEDIA_API_URL). Toolserver and /media therefore share the same Media routes for Whisper, vision, extraction, summaries and the other inference operations; model placement and task selection stay in Hugpy Media/Core.

This package owns Toolserver adds
Portable implementations, backend adapters, registry, and input schemas HTTP/MCP transport, authentication, and discovery
Local screenshot rendering, image operations, grid math, and aiming helpers Hosted screenshot URLs, cleanup, and fleet vision routing
Explicit local execution Command allowlist, node delegation, and session context

Boards, handoffs, credentials, database records, and managed browser/VM sessions remain Toolserver services. process.run_command(argv) is available directly; Toolserver exposes it through its allowlist-gated sys_run_cmd adapter.

compat.py preserves established Toolserver arguments and backend results where the native helpers have different contracts. For example, text_estimate_tokens is approximate and dependency-free; optional text_count_tokens retains the model_name argument and model-specific backend. fs_read_text returns metadata and text; fs_read_file retains the text-only result. Old Toolserver visual imports alias the portable modules, so there is one implementation to maintain.

The imports/ layer

hugpy_tools/imports/ is the reference for the workspace-wide imports/ layout (docs/packages.md). Importing it performs no I/O and loads no optional backend:

module contents
constants.py static defaults: DEFAULT_COMMAND_TIMEOUT, DEFAULT_VM_URI, DEFAULT_RENDER_TIMEOUT_MS
functions.py lazy("module:attr") (import on first call, so a missing backend raises ToolError instead of breaking startup), first_lazy(*paths), strip_remote_kwargs(kwargs)
classes.py ToolError
init_imports.py one-stop: json, logging, os, re, sys, time, C (the constants) and the shared names
from hugpy_tools.imports import constants as C
from hugpy_tools.imports.functions import lazy
from hugpy_tools.imports.classes import ToolError
from hugpy_tools.imports.init_imports import *   # the house one-stop surface

Other shared modules: schema.build_parameters(func) builds a JSON-schema inputSchema from a function signature, and toolset.get_toolset(), list_tools() and call_tool() are the registry.

Built-in tools

Every fs function takes an already-confined absolute path — call paths.confine(root, path) first to enforce a workspace jail (rejects .., absolute-outside, and symlink escapes in one check).

Module Function What it does
paths confine(root, path, for_write=False) Resolve a path under root; raise PathEscape on any escape.
paths file_parts(path) Decompose into dir/base/name/ext + two enclosing dir levels.
paths sanitize_filename(name) Reduce to one safe path component, length-bounded.
fs read_text(path, max_bytes=None) Read with encoding detection (BOM → utf-8 → cp1252).
fs read_lines(path, start, end, number=False) 1-based inclusive line-range read.
fs atomic_write(path, content, append=False) Durable write (temp file + os.replace); append supported.
fs edit_replace(path, old, new, count=None) Exact string replace with an occurrence-count contract; atomic.
fs file_info(path, hash_files=False) Size, mtime, type, symlink flag, optional sha256.
fs list_dir(path, glob=None, ...) Immediate entries (dirs first), optional fnmatch.
fs tree(path, max_depth=3, max_entries=500) Bounded recursive tree text (never follows dir symlinks).
hashkit sha256_text / sha256_file / quick_hash Content hashing (files streamed in 1 MiB windows).
text count_tokens(text) Dependency-free approximate BPE token count.
text chunk_by_lines / chunk_by_tokens Chunk on line or token budgets (paragraph-aware).
text unified_diff(before, after) Unified diff between two texts.
data read_data(path, fmt=None) Parse JSON always, TOML via stdlib tomllib, YAML if PyYAML present.
data write_json(path, obj) / safe_json_dumps(obj) Atomic JSON write / non-exploding dumps.
timekit now_iso / now_epoch / epoch_to_iso / iso_to_epoch UTC time conversions.
web assess_webpage(url, ...) assessManager-parity structured page assessment over urllib + html.parser.
web prescreen_webpage(url, ...) Cheap title + description + lede relevance pre-screen.

Web assessment

assess_webpage returns the same dict shape as abstract_webtools.assessManager.assess_webpage ({url, title, description, text, metadata, jsonld, links, truncated, render}) plus additive keys final_url, status, canonical, lang, headings, and error. The fetch is http(s)-only, refuses redirects to other schemes, disables file:// / ftp://, caps the body, times out, handles gzip/deflate, and detects charset (Content-Type → BOM → <meta charset> → utf-8 → cp1252).

JS rendering is opt-in and lazy: force_render=True (or an automatic fall-back when the cheap fetch yields almost no text) drives a headless browser only if Playwright or Selenium is installed, and raises a clear "install X" error otherwise. The default path never needs a browser.

Layer

Foundation. Core imports use only the standard library. Optional integrations are loaded on use from compat, backends, and visual; they must not import abstract_toolserver. The host owns authorization and resource lifecycle.

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