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Merge pull request #521 from ggozad/feat/monty-0.0.19

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Update to monty 0.0.19
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Yiorgis Gozadinos 2026-07-28 19:25:52 +03:00 committed by GitHub
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8
CHANGELOG.md
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@ -1,9 +1,15 @@
# Changelog
## [Unreleased]
### Added
- Analysis sandbox supports `open()` and `with` blocks for reading document files, including `.read()`, `.readline()`, and `.readlines()`.
### Changed
- Require `pydantic-ai-slim>=2.18,<3`.
- `pydantic-monty` bumped to `>=0.0.19`; sandbox code now runs in a subprocess worker pool. A crashed or timed-out worker fails one call and the next call gets a replacement session.
- The analysis sandbox gives Monty a duration budget of `analysis.code_timeout * analysis.max_executions` for the session, was `analysis.code_timeout`.
- `enable_thinking` maps onto Pydantic AI's unified `thinking` setting for the `anthropic`, `gemini`, `groq` and `bedrock` providers. The Anthropic thinking budget is now Pydantic AI's default of 10000 tokens, was 4096, and `max_tokens` must exceed it on budget-based Claude models; `enable_thinking: false` disables Gemini thinking rather than only hiding thoughts; Groq maps reasoning effort rather than `groq_reasoning_format`; Bedrock Qwen with `enable_thinking: false` no longer sends `reasoning_config`, while Bedrock-served Claude keeps an explicit `thinking: disabled`. The `openai` and `ollama` providers still map to `openai_reasoning_effort`.
- `provider: bedrock` with a proprietary OpenAI model such as `openai.o3-mini-v1:0` raises `UserError`: Bedrock Converse serves only the `gpt-oss` family. Use `provider: bedrock-mantle`.
- Tool failures raise `pydantic_ai.ToolFailed` instead of returning failure text: search and code-execution limits, sandbox execution errors, and `get_document`/`summarize_document` misses.
@ -15,6 +21,8 @@
- `evaluations run` opens the database read-only outside the population phase, so an embedder identity differing from the stored one warns instead of aborting the run.
- `docs/installation.md` documents the `jina`, `s3` and `ingester` extras, names the extras the full package actually pulls, drops the removed MixedBread AI reranker, and no longer lists Anthropic as a built-in provider.
- `docs/tuning.md` no longer points at the removed `claim_timeout_s` setting.
- `analysis.code_timeout` is enforced before each document read, bounding a call that reads in a loop.
- `metadata.json` in the document VFS rejects writes, matching `content.txt`, `items.jsonl` and `toc.json`.
### Removed

4
docs/configuration/qa.md
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@ -50,13 +50,13 @@ analysis:
provider: anthropic
name: claude-sonnet-4-20250514
temperature: 0.0 # Default: 0.0 (deterministic for code generation)
code_timeout: 60.0 # Max seconds for code execution
code_timeout: 60.0 # Max seconds a call may spend reading documents
max_output_chars: 50000 # Truncate output after this many chars
max_executions: 15 # Max execute_code calls per question
```
- **model**: LLM configuration (see [Providers](providers.md#model-settings)). When unset, falls back to `qa.model`.
- **code_timeout**: Maximum seconds for each code execution (default: 60)
- **code_timeout**: Seconds a single `execute_code` call may spend reading documents (default: 60). The sandbox refuses further reads past this point. Code that computes without reading is killed by the worker watchdog at the same limit. `code_timeout * max_executions` is the cumulative ceiling across all calls in one question.
- **max_output_chars**: Truncate code output after this many characters (default: 50000)
- **max_executions**: Maximum `execute_code` calls per question before the capability is told to answer from what it has (default: 15)

2
haiku_rag_slim/haiku/rag/capabilities/analysis.py
View file

@ -66,7 +66,7 @@ class AnalysisCapability(RAGCapabilityBase[AnalysisState]):
async def _close(self) -> None:
if self.sandbox is not None:
self.sandbox.close()
await self.sandbox.close()
self.sandbox = None
await super()._close()

8
haiku_rag_slim/haiku/rag/capabilities/instructions/analysis.md
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@ -17,7 +17,7 @@ Inside the code, these functions are available (use `await`):
- `await list_documents()` → list of dicts with keys: id, title, uri, created_at
Available modules: `json`, `re`, `math`, `pathlib`
Not supported: class definitions, generators/yield, match statements, decorators, `with` statements
Not supported: class inheritance and metaclasses, generators/yield, match statements, decorators, `collections`, iterating a file object (`for line in f`)
### analysis_search
Search the knowledge base directly (outside code execution). Each result has a `Type:` (paragraph, table, code, list_item, picture). When the Type is `picture`, the corresponding figure may also be attached to the tool response as an image alongside the text — use it directly to answer questions about figures, diagrams, charts, screenshots.
@ -48,7 +48,7 @@ All documents are mounted as a virtual filesystem at `/documents/`:
`{document_id}` is an internal identifier, not the user-facing `uri` (filename, URL, etc.). When you only know a document by its URI or title, use `await list_documents()` to enumerate ids and match against `uri` / `title` — that's a single call to the host. Iterating `/documents/` and reading every `metadata.json` works too but is much slower on portal-scale corpora.
### Reading files
Always use `Path.read_text()` — do NOT use `open()` or `with` statements (they are not supported).
Read with `Path.read_text()` or `open()` (including `with` blocks); file objects support `.read()`, `.readline()`, and `.readlines()`. A file object cannot be iterated, so read line-wise with `.readlines()` or `.read().split("\n")` instead of `for line in f`. Files are read-only; writing raises `PermissionError`.
```python
from pathlib import Path
@ -63,7 +63,7 @@ for doc_dir in Path('/documents').iterdir():
content = Path(f'/documents/{doc_id}/content.txt').read_text()
# Read and parse items
for line in Path(f'/documents/{doc_id}/items.jsonl').read_text().strip().split(chr(10)):
for line in Path(f'/documents/{doc_id}/items.jsonl').read_text().strip().split("\n"):
item = json.loads(line)
if item['label'] == 'table':
print(item['text'][:200])
@ -112,6 +112,6 @@ You MUST call `analysis_cite` with at least one chunk ID before producing your f
- Use `print()` to output results — the output is your only feedback
- When you write code, execute it — don't describe what code would do. But not every question needs code; simple lookups are best answered by `analysis_search → analysis_cite`.
- Use `await` for all async functions inside `analysis_execute_code` (`search`, `list_documents`)
- Use `Path.read_text()` to read files — do NOT use `open()`, `with` statements, or `collections` module
- Read files with `Path.read_text()` or `open()`/`with`. For lines use `.readlines()` or `.read().split("\n")`, never `for line in f`. The `collections` module is unavailable.
- Do NOT include chunk IDs or UUIDs in your answer text — your answer should read naturally. Use the `analysis_cite` tool separately to register citations. `cite{...}` markdown-style inline references do nothing; only an actual `analysis_cite` tool call registers a citation.
- **Before you write your final answer, invoke the `analysis_cite` tool with the supporting chunk_ids.** This is the last tool call before answering whenever your answer draws on retrieved evidence.

164
haiku_rag_slim/haiku/rag/sandbox/sandbox.py
View file

@ -2,13 +2,19 @@ import asyncio
import json
import os
from collections.abc import AsyncIterator, Callable, Coroutine
from contextlib import asynccontextmanager
from contextlib import asynccontextmanager, suppress
from dataclasses import dataclass
from pathlib import Path
from typing import TYPE_CHECKING, Any, Literal
import pydantic_monty
from pydantic_monty import CallbackFile, MemoryFile, MontyRepl, OSAccess
from pydantic_monty import (
AsyncMonty,
AsyncMontySession,
CallbackFile,
OSAccess,
ResourceLimits,
)
from haiku.rag.config.models import AppConfig
from haiku.rag.sandbox.dependencies import AnalysisContext
@ -109,24 +115,26 @@ class Sandbox:
"""Execute code in a sandboxed Python interpreter.
Uses pydantic-monty, a minimal secure Python interpreter written in Rust.
External functions (search, list_documents) are called by Monty code
The interpreter runs in a subprocess worker checked out of an ``AsyncMonty``
pool. External functions (search, list_documents) are called by Monty code
using ``await`` and resolved asynchronously on the host. Documents are
exposed via a virtual filesystem at ``/documents/{id}/``.
The interpreter uses a REPL session — variables persist across
``execute()`` calls within the same Sandbox instance.
The session persists across ``execute()`` calls within the same Sandbox
instance — variables carry over. Call ``close()`` to return the worker to
the pool and shut the pool down.
sandbox = Sandbox(db_path, config, context)
result = await sandbox.execute("x = await search('query')")
result = await sandbox.execute("print(x[0]['content'])") # x persists
await sandbox.close()
All database access runs on the event loop that drives ``execute()``. Monty's
file callbacks are synchronous and run on the interpreter's worker thread, so
they bridge back to that loop via ``run_coroutine_threadsafe``; the loop is
free during ``feed_run_async`` (the VM runs on the worker thread), so the
bridge does not deadlock. When a ``rag`` connection is supplied it is used
for every read, so an analysis run drives a single connection on a single
loop; otherwise each read opens an ephemeral read-only connection.
file callbacks are synchronous and run off that loop while ``feed_run`` is
awaited, so they bridge back to it via ``run_coroutine_threadsafe`` without
deadlocking. When a ``rag`` connection is supplied it is used for every read,
so an analysis run drives a single connection on a single loop; otherwise
each read opens an ephemeral read-only connection.
"""
_db_path: Path
@ -139,9 +147,11 @@ class Sandbox:
_doc_chunk_index: dict[str, dict[str, list[str]]]
_items_jsonl_cache: dict[str, str]
_toc_json_cache: dict[str, str]
_repl: MontyRepl | None
_pool: AsyncMonty | None
_session: AsyncMontySession | None
_vfs: OSAccess | None
_loop: asyncio.AbstractEventLoop | None
_deadline: float | None
def __init__(
self,
@ -161,9 +171,11 @@ class Sandbox:
self._doc_chunk_index = {}
self._items_jsonl_cache = {}
self._toc_json_cache = {}
self._repl = None
self._pool = None
self._session = None
self._vfs = None
self._loop = None
self._deadline = None
@asynccontextmanager
async def _connection(self) -> "AsyncIterator[HaikuRAG]":
@ -185,17 +197,49 @@ class Sandbox:
def _run_on_loop(self, coro: Coroutine[Any, Any, Any]) -> Any:
"""Run a coroutine on the execute() loop from a synchronous callback.
Called from Monty's worker thread while ``feed_run_async`` leaves the
loop free, so scheduling onto it and blocking for the result is safe.
Called off the loop while ``feed_run`` is awaited, so scheduling onto it
and blocking for the result is safe.
Blocking here suspends the worker, and Monty checks its duration budget
between interpreter steps, so it cannot check while a read is in flight.
Enforce the budget before starting another read, or code that reads in a
loop overruns it by however long the outstanding reads take. Raising from
inside the callback answers the worker's suspension, which keeps the
session usable — cancelling ``feed_run`` from outside does not, and wedges
the protocol.
"""
assert self._loop is not None, (
"VFS reads happen during execute(); the loop must be captured first."
)
if self._deadline is not None and self._loop.time() > self._deadline:
coro.close()
raise TimeoutError(
"time limit exceeded: no further document reads after "
f"{self._config.analysis.code_timeout}s"
)
return asyncio.run_coroutine_threadsafe(coro, self._loop).result()
def close(self) -> None:
"""Retained for API compatibility; the sandbox owns no resources."""
return
async def _discard_session(self) -> None:
"""Drop a session whose worker is gone.
The session object is unusable once its worker dies: it answers every
later call with ``RuntimeError: this checkout has already been
finished``. Clearing it makes ``_ensure_initialized`` check out a
replacement, at the cost of the variables the dead worker held.
"""
session, self._session = self._session, None
if session is not None:
with suppress(Exception):
await session.__aexit__(None, None, None)
async def close(self) -> None:
"""Return the worker to the pool and shut the pool down. Idempotent."""
if self._session is not None:
await self._session.__aexit__(None, None, None)
self._session = None
if self._pool is not None:
await self._pool.__aexit__(None, None, None)
self._pool = None
def _build_external_functions(self) -> dict[str, Any]:
"""Build async external functions for the Monty interpreter."""
@ -255,12 +299,12 @@ class Sandbox:
"""Build the virtual filesystem with document data.
Mounts per-document directories with:
- metadata.json: MemoryFile (eager, small)
- metadata.json: CallbackFile (eager, small)
- content.txt: CallbackFile (lazy, can be large)
- items.jsonl: CallbackFile (lazy, bulk-cached)
- toc.json: CallbackFile (lazy, bulk-cached)
"""
files: list[MemoryFile | CallbackFile] = []
files: list[CallbackFile] = []
def _deny_write(_path: "PurePosixPath", _content: str | bytes) -> None:
raise PermissionError(f"Document files are read-only: {_path}")
@ -370,7 +414,16 @@ class Sandbox:
},
ensure_ascii=False,
)
files.append(MemoryFile(f"{doc_dir}/metadata.json", metadata))
# MemoryFile has no write hook, so metadata.json goes through the
# same read and deny pair as the rest. Its content is already built.
files.append(
CallbackFile(
f"{doc_dir}/metadata.json",
read=lambda _path, text=metadata: text,
write=_deny_write,
)
)
def _make_content_reader(
did: str,
@ -413,52 +466,79 @@ class Sandbox:
return OSAccess(files)
async def _ensure_initialized(self) -> tuple[MontyRepl, OSAccess]:
"""Initialize the REPL session and VFS on first use."""
if self._repl is None:
def _session_limits(self) -> ResourceLimits:
"""Resource limits for the worker session.
Monty spends ``max_duration_secs`` across the session's whole life, and
the session is reused so variables persist between calls. Budget it for
the run rather than for one call, or the first slow call starves every
later one. ``code_timeout`` is enforced per call elsewhere: the read
deadline in ``_run_on_loop`` bounds a call that reads, and the pool's
``request_timeout`` bounds one that computes.
"""
analysis = self._config.analysis
return {"max_duration_secs": analysis.code_timeout * analysis.max_executions}
async def _ensure_initialized(self) -> tuple[AsyncMontySession, OSAccess]:
"""Check out a worker session and build the VFS on first use."""
if self._vfs is None:
self._vfs = await self._build_vfs()
self._repl = MontyRepl(
limits={
"max_duration_secs": self._config.analysis.code_timeout,
},
)
assert self._repl is not None and self._vfs is not None
return self._repl, self._vfs
if self._pool is None:
# The watchdog counts only time the worker spends running code, so a
# read that blocks the worker never trips it. That leaves the two
# limits disjoint: this one bounds a call that computes, and the read
# deadline bounds a call that reads.
pool = AsyncMonty(request_timeout=self._config.analysis.code_timeout)
await pool.__aenter__()
self._pool = pool
if self._session is None:
session = self._pool.checkout(limits=self._session_limits())
await session.__aenter__()
self._session = session
assert self._session is not None and self._vfs is not None
return self._session, self._vfs
async def execute(self, code: str) -> SandboxResult:
"""Execute Python code in the Monty REPL.
"""Execute Python code in the Monty worker session.
Variables persist across calls within the same Sandbox instance.
"""
# Monty's synchronous file callbacks bridge DB reads back to this loop.
self._loop = asyncio.get_running_loop()
repl, vfs = await self._ensure_initialized()
self._deadline = self._loop.time() + self._config.analysis.code_timeout
session, vfs = await self._ensure_initialized()
external_fns = self._build_external_functions()
stdout_lines: list[str] = []
def print_callback( # pragma: no cover - runs on Monty's Rust thread
_stream: Literal["stdout"], text: str
def print_callback( # pragma: no cover - runs on Monty's worker thread
_stream: Literal["stdout", "stderr"], text: str
) -> None:
stdout_lines.append(text)
max_chars = self._config.analysis.max_output_chars
try:
output = await repl.feed_run_async(
output = await session.feed_run(
code,
external_functions=external_fns,
external_lookup=external_fns,
print_callback=print_callback,
os=vfs,
)
except (
pydantic_monty.MontySyntaxError,
pydantic_monty.MontyRuntimeError,
) as e:
except (pydantic_monty.MontyError, RuntimeError) as e:
stdout = "".join(stdout_lines)
if len(stdout) > max_chars:
stdout = stdout[:max_chars] + "\n... (output truncated)"
return SandboxResult(stdout=stdout, stderr=str(e), success=False)
stderr = str(e)
# A crash kills the worker, and a protocol error leaves it out of
# step. Both poison the session. Bad user code does not.
if isinstance(e, pydantic_monty.MontyCrashedError | RuntimeError):
await self._discard_session()
stderr = (
f"{stderr}\n\nThe interpreter restarted. Variables from "
"earlier calls are gone."
)
return SandboxResult(stdout=stdout, stderr=stderr, success=False)
stdout = "".join(stdout_lines)
if output is not None:

2
haiku_rag_slim/pyproject.toml
View file

@ -30,7 +30,7 @@ dependencies = [
"pathspec>=1.0.4",
"pydantic>=2.12.5",
"pydantic-ai-slim[openai,logfire,ag-ui]>=2.18.0,<3.0.0",
"pydantic-monty>=0.0.17",
"pydantic-monty>=0.0.19",
"pypdfium2>=5.0",
"python-dotenv>=1.2.2",
"pyyaml>=6.0.3",

42
tests/cassettes/test_sandbox/TestSandboxVFS.test_open_read.yaml Normal file
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42
tests/cassettes/test_sandbox/TestSandboxVFS.test_open_readlines.yaml Normal file
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332
tests/sandbox/test_sandbox.py
View file

@ -7,6 +7,7 @@ import pytest
from haiku.rag.client import HaikuRAG
from haiku.rag.config.models import AppConfig
from haiku.rag.sandbox import AnalysisContext, Sandbox, SandboxResult
from haiku.rag.store.models.chunk import Chunk
@pytest.fixture(scope="module")
@ -383,6 +384,175 @@ class TestSandboxVFS:
assert result.success
assert result.stdout.count("True") == 6
@pytest.mark.asyncio
@pytest.mark.vcr()
async def test_open_read(self, temp_db_path):
"""open() and a with-block read document files through the VFS."""
config = AppConfig()
async with HaikuRAG(temp_db_path, create=True) as client:
doc = await client.create_document(
content="Content about foxes and dogs.",
uri="test://doc",
title="Fox Document",
)
context = AnalysisContext()
sb = Sandbox(db_path=temp_db_path, config=config, context=context)
result = await sb.execute(
f"with open('/documents/{doc.id}/content.txt') as f:\n"
" data = f.read()\n"
"print('foxes' in data.lower())"
)
assert result.success
assert "True" in result.stdout
@pytest.mark.asyncio
@pytest.mark.vcr()
async def test_open_readlines(self, temp_db_path):
"""readlines() splits a newline-delimited VFS file into lines."""
config = AppConfig()
async with HaikuRAG(temp_db_path, create=True) as client:
doc = await client.create_document(
content="The quick brown fox jumps over the lazy dog.",
uri="test://animals",
title="Animals",
)
context = AnalysisContext()
sb = Sandbox(db_path=temp_db_path, config=config, context=context)
result = await sb.execute(
f"lines = open('/documents/{doc.id}/items.jsonl').readlines()\n"
"print(len(lines) > 0)\n"
"import json\n"
"print('self_ref' in json.loads(lines[0]))"
)
assert result.success
assert result.stdout.count("True") == 2
@pytest.mark.asyncio
@pytest.mark.parametrize(
"filename", ["content.txt", "items.jsonl", "toc.json", "metadata.json"]
)
async def test_write_denied_for_every_document_file(self, temp_db_path, filename):
"""Every file in the document VFS is read-only, metadata.json included."""
from docling_core.types.doc.document import DoclingDocument
from docling_core.types.doc.labels import DocItemLabel
config = AppConfig()
docling = DoclingDocument(name="d")
docling.add_text(label=DocItemLabel.TEXT, text="Foxes and dogs.")
async with HaikuRAG(temp_db_path, create=True) as client:
doc = await client.import_document(
docling,
[
Chunk(
content="Foxes and dogs.",
embedding=[0.1] * config.embeddings.model.vector_dim,
order=0,
)
],
uri="test://readonly",
)
sb = Sandbox(db_path=temp_db_path, config=config, context=AnalysisContext())
try:
result = await sb.execute(
"from pathlib import Path\n"
"try:\n"
f" Path('/documents/{doc.id}/{filename}').write_text('nope')\n"
" print('WROTE')\n"
"except PermissionError:\n"
" print('DENIED')"
)
assert result.success, result.stderr
assert "DENIED" in result.stdout
assert "WROTE" not in result.stdout
finally:
await sb.close()
@pytest.mark.asyncio
async def test_open_for_writing_is_denied(self, temp_db_path):
"""`open()` in write mode is refused, not only `Path.write_text`."""
from docling_core.types.doc.document import DoclingDocument
from docling_core.types.doc.labels import DocItemLabel
config = AppConfig()
docling = DoclingDocument(name="d")
docling.add_text(label=DocItemLabel.TEXT, text="Foxes and dogs.")
async with HaikuRAG(temp_db_path, create=True) as client:
doc = await client.import_document(
docling,
[
Chunk(
content="Foxes and dogs.",
embedding=[0.1] * config.embeddings.model.vector_dim,
order=0,
)
],
uri="test://openwrite",
)
sb = Sandbox(db_path=temp_db_path, config=config, context=AnalysisContext())
try:
result = await sb.execute(
"try:\n"
f" with open('/documents/{doc.id}/content.txt', 'w') as f:\n"
" f.write('nope')\n"
" print('WROTE')\n"
"except PermissionError:\n"
" print('DENIED')"
)
assert result.success, result.stderr
assert "DENIED" in result.stdout
assert "WROTE" not in result.stdout
finally:
await sb.close()
@pytest.mark.asyncio
async def test_open_file_objects_are_not_iterable(self, temp_db_path):
"""Pins the limitation the instructions warn about: pydantic/monty#490.
A failure here means Monty gained iteration support and the
`for line in f` prohibition in the analysis instructions is now wrong.
"""
from docling_core.types.doc.document import DoclingDocument
from docling_core.types.doc.labels import DocItemLabel
config = AppConfig()
docling = DoclingDocument(name="d")
docling.add_text(label=DocItemLabel.TEXT, text="one\ntwo")
async with HaikuRAG(temp_db_path, create=True) as client:
doc = await client.import_document(
docling,
[
Chunk(
content="one\ntwo",
embedding=[0.1] * config.embeddings.model.vector_dim,
order=0,
)
],
uri="test://lines",
)
sb = Sandbox(db_path=temp_db_path, config=config, context=AnalysisContext())
try:
result = await sb.execute(
f"for line in open('/documents/{doc.id}/content.txt'):\n print(line)"
)
assert result.success is False
assert "not iterable" in result.stderr
# The documented alternatives do work.
result = await sb.execute(
f"print(len(open('/documents/{doc.id}/content.txt').readlines()))"
)
assert result.success, result.stderr
finally:
await sb.close()
@pytest.mark.asyncio
@pytest.mark.vcr()
async def test_context_filter_limits_vfs(self, temp_db_path):
@ -453,7 +623,7 @@ class TestSandboxHeldConnection:
assert int(lines[1]) > 0
assert lines[2] == "True"
finally:
sb.close()
await sb.close()
@pytest.mark.asyncio
@pytest.mark.vcr()
@ -557,7 +727,7 @@ class TestSandboxHeldConnection:
assert first.stdout == second.stdout
assert not any(t.name == "sandbox-vfs" for t in threading.enumerate())
finally:
sb.close()
await sb.close()
@pytest.mark.asyncio
@pytest.mark.vcr()
@ -584,21 +754,21 @@ class TestSandboxHeldConnection:
assert second.success, second.stderr
assert int(second.stdout.strip()) > 0
finally:
sb.close()
await sb.close()
@pytest.mark.asyncio
async def test_close_is_safe_without_vfs_read(self, temp_db_path):
"""close() is a no-op (and safe to call twice) when no VFS read happened."""
"""close() is safe and idempotent before any code has run."""
async with HaikuRAG(temp_db_path, create=True):
config = AppConfig()
sb = Sandbox(db_path=temp_db_path, config=config, context=AnalysisContext())
sb.close()
sb.close()
await sb.close()
await sb.close()
@pytest.mark.asyncio
@pytest.mark.vcr()
async def test_close_is_idempotent_after_vfs_read(self, temp_db_path):
"""close() is a safe no-op after a VFS read; no background thread lingers."""
"""close() tears down the worker and is idempotent; no thread lingers."""
config = AppConfig()
async with HaikuRAG(temp_db_path, create=True) as client:
doc = await client.create_document(
@ -616,5 +786,149 @@ class TestSandboxHeldConnection:
)
assert result.success
assert not any(t.name == "sandbox-vfs" for t in threading.enumerate())
sb.close()
sb.close()
await sb.close()
await sb.close()
class TestSandboxReadDeadline:
"""The VFS bridge suspends the worker for the length of a read, so Monty
cannot check its duration budget while one is in flight. The sandbox
enforces the budget itself, before each read."""
@pytest.mark.asyncio
async def test_read_after_deadline_raises_without_scheduling(self, sandbox):
"""A read attempted past the deadline fails instead of querying."""
scheduled = False
async def _never_runs():
nonlocal scheduled
scheduled = True
sandbox._loop = asyncio.get_running_loop()
sandbox._deadline = sandbox._loop.time() - 1.0
coro = _never_runs()
with pytest.raises(TimeoutError, match="time limit exceeded"):
sandbox._run_on_loop(coro)
coro.close()
assert scheduled is False
def test_session_budget_covers_every_permitted_execution(self, temp_db_path):
"""Monty spends its duration budget across the session's whole life, so a
per-call value would let the first call starve the rest."""
config = AppConfig()
config.analysis.code_timeout = 5.0
config.analysis.max_executions = 3
sb = Sandbox(db_path=temp_db_path, config=config, context=AnalysisContext())
assert sb._session_limits() == {"max_duration_secs": 15.0}
@pytest.mark.asyncio
async def test_refused_read_fails_the_execution(self, temp_db_path, monkeypatch):
"""The refusal surfaces as a failed result, not a raised exception."""
from docling_core.types.doc.document import DoclingDocument
from docling_core.types.doc.labels import DocItemLabel
config = AppConfig()
docling = DoclingDocument(name="d")
docling.add_text(label=DocItemLabel.TEXT, text="Foxes and dogs.")
async with HaikuRAG(temp_db_path, create=True) as client:
doc = await client.import_document(
docling,
[
Chunk(
content="Foxes and dogs.",
embedding=[0.1] * config.embeddings.model.vector_dim,
order=0,
)
],
uri="test://deadline",
)
def _past_deadline(*_args, **_kwargs):
raise TimeoutError(
"time limit exceeded: no further document reads after 60.0s"
)
monkeypatch.setattr(Sandbox, "_run_on_loop", _past_deadline)
sb = Sandbox(db_path=temp_db_path, config=config, context=AnalysisContext())
try:
result = await sb.execute(
"from pathlib import Path\n"
f"print(Path('/documents/{doc.id}/content.txt').read_text())"
)
assert result.success is False
assert "no further document reads" in result.stderr
finally:
await sb.close()
class TestSandboxWorkerCrash:
"""A dead worker must not poison every later call in the run."""
@pytest.mark.asyncio
async def test_crashed_worker_is_replaced(self, temp_db_path):
"""The crash fails one call. The next call gets a fresh session."""
import os
import signal
config = AppConfig()
async with HaikuRAG(temp_db_path, create=True):
pass
sb = Sandbox(db_path=temp_db_path, config=config, context=AnalysisContext())
try:
first = await sb.execute("x = 1\nprint(x)")
assert first.success, first.stderr
assert sb._session is not None
pid = sb._session.worker_pid
assert pid is not None
os.kill(pid, signal.SIGKILL)
crashed = await sb.execute("print(2)")
assert crashed.success is False
assert "restarted" in crashed.stderr
# Without the discard every later call fails on the dead session.
recovered = await sb.execute("print(3)")
assert recovered.success, recovered.stderr
assert "3" in recovered.stdout
# The replacement worker starts empty, which the failure said.
lost = await sb.execute("print(x)")
assert lost.success is False
finally:
await sb.close()
class TestSandboxRequestTimeout:
"""The pool watchdog bounds a call that never reads."""
@pytest.mark.asyncio
async def test_runaway_compute_is_killed_and_the_next_call_recovers(
self, temp_db_path
):
"""Code that never reads escapes the read deadline. The watchdog kills it."""
config = AppConfig()
config.analysis.code_timeout = 1.0
async with HaikuRAG(temp_db_path, create=True):
pass
sb = Sandbox(db_path=temp_db_path, config=config, context=AnalysisContext())
try:
runaway = await sb.execute(
"x = 0\nfor i in range(500000000):\n x += i\nprint(x)"
)
assert runaway.success is False
assert "restarted" in runaway.stderr
recovered = await sb.execute("print('alive')")
assert recovered.success, recovered.stderr
assert "alive" in recovered.stdout
finally:
await sb.close()

17
tests/sandbox/test_sandbox_toc.py
View file

@ -83,6 +83,23 @@ def _flatten(tree: list[dict]) -> list[dict]:
return out
@pytest.mark.asyncio
class TestMetadataJson:
"""metadata.json is served by a reader callback, like the other VFS files."""
async def test_metadata_reader_returns_document_fields(self, temp_db_path):
async with HaikuRAG(temp_db_path, create=True) as client:
doc_id = await _empty_doc(client, uri="test://meta", title="Meta Doc")
sandbox = Sandbox(temp_db_path, AppConfig(), AnalysisContext())
raw = await _read_vfs_text(sandbox, f"/documents/{doc_id}/metadata.json")
meta = json.loads(raw)
assert meta["id"] == doc_id
assert meta["title"] == "Meta Doc"
assert meta["uri"] == "test://meta"
@pytest.mark.asyncio
class TestTocShape:
"""toc.json builds a section tree from heading_level + position."""

123
uv.lock
View file

@ -1770,7 +1770,7 @@ requires-dist = [
{ name = "pydantic-ai-slim", extras = ["mistral"], marker = "extra == 'mistral'" },
{ name = "pydantic-ai-slim", extras = ["openai", "logfire", "ag-ui"], specifier = ">=2.18.0,<3.0.0" },
{ name = "pydantic-ai-slim", extras = ["voyageai"], marker = "extra == 'voyageai'" },
{ name = "pydantic-monty", specifier = ">=0.0.17" },
{ name = "pydantic-monty", specifier = ">=0.0.19" },
{ name = "pypdfium2", specifier = ">=5.0" },
{ name = "python-dotenv", specifier = ">=1.2.2" },
{ name = "pyyaml", specifier = ">=6.0.3" },
@ -3981,49 +3981,94 @@ wheels = [
[[package]]
name = "pydantic-monty"
version = "0.0.17"
version = "0.0.19"
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