3506371677test_nudge_tool_calls_wiring.py imported InferenceBackend from core.inference.inference, which pulls in unsloth (and thus unsloth_zoo) at module scope. The dependency-light backend CI matrix job does not install unsloth_zoo, so the import raised at collection time and aborted the whole job (831 tests never ran). Guard that one import and fold the safetensors InferenceBackend checks in only when the unsloth stack is importable; the orchestrator/llama_cpp/safetensors_agentic wiring is still asserted unconditionally, and local/full-stack runs keep the InferenceBackend coverage.
99 lines
4.6 KiB
Python
99 lines
4.6 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
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"""Wiring guard for the plan-without-action ``nudge_tool_calls`` policy.
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Decided policy: the re-prompt is ALWAYS ON for the Studio inference paths
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(safetensors, GGUF/llama_cpp, MLX) and OPT-IN for the API (/v1 OpenAI-compat +
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Anthropic-compat, controlled by the request's ``nudge_tool_calls``, default off).
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Mechanism (verified here without loading a model):
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* every backend tool-loop entry point accepts and forwards ``nudge_tool_calls``
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(safetensors -> ``InferenceBackend``; MLX -> ``InferenceOrchestrator``; both
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call the shared ``run_safetensors_tool_loop``; GGUF -> ``LlamaCppBackend``);
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* the safetensors/MLX loop gates the retry on a truthy flag (new retry ->
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opt-in), while the GGUF loop keeps its pre-existing default-on behaviour
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(``None`` keeps nudging) so an omitted flag never disables GGUF;
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* the API request models default the flag to ``None`` (opt-in / off);
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* the Studio-facing routes forward the request's flag, and the Studio frontend
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sends ``nudge_tool_calls: true`` -- exercised behaviourally in
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``test_safetensors_tool_loop.py`` and ``test_llama_cpp_tool_loop.py``.
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"""
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import inspect
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from core.inference.llama_cpp import LlamaCppBackend
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from core.inference.orchestrator import InferenceOrchestrator
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from core.inference.safetensors_agentic import run_safetensors_tool_loop
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try:
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# core.inference.inference imports unsloth at module scope, which requires
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# unsloth_zoo. The dependency-light backend CI matrix job does not install
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# it, so the safetensors InferenceBackend is folded into the checks below
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# only when the unsloth stack is importable (local runs / full CI); the
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# other entry points are always checked.
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from core.inference.inference import InferenceBackend
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except ImportError:
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InferenceBackend = None
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def _params(fn):
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return inspect.signature(fn).parameters
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def test_shared_loop_accepts_nudge_flag():
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assert "nudge_tool_calls" in _params(run_safetensors_tool_loop)
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def test_backends_accept_the_flag():
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methods = [
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InferenceOrchestrator.generate_chat_completion_with_tools,
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LlamaCppBackend.generate_chat_completion_with_tools,
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]
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if InferenceBackend is not None: # safetensors path; needs the unsloth stack
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methods.append(InferenceBackend.generate_chat_completion_with_tools)
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for method in methods:
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assert "nudge_tool_calls" in _params(method), method.__qualname__
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def test_delegating_backends_forward_the_flag_to_the_shared_loop():
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# safetensors (in-process transformers) and MLX (parent-process orchestrator)
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# both delegate to run_safetensors_tool_loop; GGUF runs its own in-file loop
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# and consumes the flag directly (asserted separately by the gate test).
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methods = [InferenceOrchestrator.generate_chat_completion_with_tools]
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if InferenceBackend is not None: # safetensors path; needs the unsloth stack
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methods.append(InferenceBackend.generate_chat_completion_with_tools)
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for method in methods:
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src = inspect.getsource(method)
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assert "nudge_tool_calls = nudge_tool_calls" in src, method.__qualname__
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def test_safetensors_loop_is_opt_in_while_gguf_stays_default_on():
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# Safetensors/MLX: the retry is new here, so it requires a truthy flag.
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sf_src = inspect.getsource(run_safetensors_tool_loop)
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assert "and nudge_tool_calls" in sf_src
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# GGUF: pre-existing nudge must not be accidentally disabled -- an omitted
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# (None) flag keeps nudging; only an explicit False turns it off.
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gguf_src = inspect.getsource(LlamaCppBackend.generate_chat_completion_with_tools)
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assert "nudge_tool_calls is None or nudge_tool_calls" in gguf_src
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def test_api_request_models_default_the_flag_off():
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from models.inference import AnthropicMessagesRequest, ChatCompletionRequest
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for model in (ChatCompletionRequest, AnthropicMessagesRequest):
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field = model.model_fields["nudge_tool_calls"]
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assert field.default is None, model.__name__
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def test_studio_routes_forward_the_request_flag():
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# The Studio chat frontend posts to /v1/chat/completions and /v1/messages
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# with nudge_tool_calls=true; the route handlers forward the request value
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# (external API clients that omit it fall back to the opt-in default).
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from routes import inference as routes_inference
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for handler in (
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routes_inference.openai_chat_completions,
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routes_inference.anthropic_messages,
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):
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src = inspect.getsource(handler)
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assert "nudge_tool_calls = payload.nudge_tool_calls" in src, handler.__name__
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