f109e7f0e6* Studio: parse Mistral [TOOL_CALLS] and rehearsal tool-call shapes
Extends the rescue parsers in core/tool_healing.py and
core/inference/tool_call_parser.py to recognise two extra serialisations
local models commonly emit when bypassing native function calling:
* [TOOL_CALLS]name{json_args} (Devstral-Small-2, Mistral-Small-3.x).
* name[ARGS]{json_args} (reasoning-model rehearsal).
Both extractors use a brace-balance scan that honours escapes and
quoted strings so nested JSON args stay intact.
Also pre-strips <think>...</think> and [THINK]...[/THINK] blocks before
matching so calls emitted after a reasoning preamble are recognised
regardless of position.
Streaming gates (TOOL_XML_SIGNALS, llama_cpp.py _TOOL_XML_SIGNALS) and
the SSE strip regex (routes/inference.py _TOOL_XML_RE) gain the new
sentinels so the parser is actually invoked and the raw markup never
leaks to the UI.
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* Strip unclosed think blocks and catch rehearsal [ARGS] mid-buffer
The pre-existing ``_THINK_TAG_RE`` only matched closed thinking
blocks (``<think>...</think>`` or ``[THINK]...[/THINK]``). During
streaming the model is still inside the open block when the parser
runs, so any tool-shaped markup the model is REHEARSING inside that
block survived the strip and could be executed as a real call.
Switch both copies of the regex (parser + healing) to accept the
trailing block being terminated by end-of-string in addition to
the explicit closer.
The ``_TOOL_XML_SIGNALS`` list on the llama_cpp streaming buffer
included ``[ARGS]`` to catch rehearsal syntax, but the gate used a
``startswith`` check against the buffer head -- rehearsal is shaped
``name[ARGS]{json}``, so the buffer never STARTS with ``[ARGS]``
and the signal had no effect. Add a substring fallback for the
bracket-style signals so the BUFFERING window can still divert the
stream into DRAINING when rehearsal markup arrives mid-buffer.
Adds three regression tests covering rehearsal inside unclosed
``<think>`` / ``[THINK]`` blocks (must yield no calls) and the
positive case after a closed think block (still parsed).
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* Studio: harden bracket-tag tool-call parsing and streaming strip
Address review findings on the Mistral [TOOL_CALLS] / rehearsal [ARGS] paths:
- Accept hyphenated tool names in the bracket parsers and strip patterns.
_MISTRAL_BRACKET_RE and _REHEARSAL_RE used \w+, which dropped or truncated
MCP function names containing dashes (mcp__srv__list-issues). Use [\w-]+ to
match the XML and Gemma parsers.
- Strip a partial bracket marker streamed before its opening brace. The
trailing-unclosed patterns required the {, so a [TOOL_CALLS]web_search or
python[ARGS] split across deltas leaked the raw marker to the UI. Match the
bare marker to end-of-text, mirroring how the bare open tags are stripped.
Closed pairs are unchanged so in-progress markup stays buffered until parsed.
- Strip a truncated bracket tail in the route-level display regex. _TOOL_XML_RE
required a balanced JSON object; a tool call truncated by EOS now strips up
to \Z, like the orphan-opening XML shapes. Complete calls still strip only
their balanced JSON so following prose survives.
Add regression tests for hyphenated names, the streaming partial-marker strip,
and the unclosed-tail route strip.
* Studio: preserve XML parameter indentation in tool_healing
The chat template emits <parameter=k>\nVALUE\n</parameter>; the parameter-start
regex consumed the wrapping newline AND the value's first-line indentation via a
trailing \s*, then str.strip() removed the rest, corrupting code/diff arguments.
Narrow the trailing class to horizontal whitespace and trim exactly one wrapping
newline (_trim_param_value), preserving indentation. Matches SGLang's qwen3_coder
detector and the same fix on the multi-format parser. Add a regression test.
* Studio: tighten Mistral/rehearsal tool-call comments
Compress the comments in the Mistral [TOOL_CALLS] / rehearsal [ARGS] healing shim
and its callers to one or two lines, keeping the bracket-tag stripping rationale,
the thinking-block handling note, and the forge attribution intact.
Comment-only: no code or behavior change (verified with comment_tools.py check
--strip-docstrings; tests green).
* Studio: fix think-strip arg corruption and nested bracket-JSON strip
Review follow-up for the Mistral/rehearsal healing shim:
- The <think>/[THINK] strip ran unconditionally over the whole content before
parsing, so a real tool argument that legitimately contained a <think> /
[THINK] literal was silently corrupted. Don't delete the blocks: compute the
reasoning-block spans and skip any tool-call candidate that STARTS inside one,
across all parse paths (JSON, Gemma, XML, bracket, rehearsal). A rehearsed call
inside reasoning is still ignored; a real call after </think> still parses.
- The bracket-tag display strip used a fixed one-level-nesting regex, so a call
with two-level-nested JSON args either leaked raw markup or, in final mode, let
the catch-all eat the trailing prose. Add a balanced-brace
_strip_bracket_tag_calls pass (any nesting depth) used by strip_tool_call_markup
and the route display strip.
Add regressions: <think>/[THINK] literal inside a real argument, rehearsal-inside-
think with a real call after, and two-level-nested bracket/rehearsal strip keeping
trailing prose.
* Studio: correct think-block comments to match span-skip behavior
The think-strip fix replaced the unconditional think-block strip with a
span-skip (the block is kept and any tool-call candidate starting inside it is
ignored), but two comments still described the old strip-first behavior. Update
the _THINK_TAG_RE comment and the parse_tool_calls_from_text docstring.
* Studio: parse Mistral arrays and call-ids, unify bracket parse/strip, keep it linear
- Parse the canonical Mistral array form (TOOL_CALLS followed by a JSON list of
calls) and emit every call; parse the v11 shape that carries an opaque CALL_ID
token between the name and ARGS (the function name is the token after
TOOL_CALLS, never the call-id); and parse a Mistral call plus a rehearsal call
in one message (the second was dropped yet still stripped from display).
- One shared balanced forward scan (_iter_bracket_spans) backs both the parser
and the strip path, so they no longer diverge. It is linear: each regex is
re-searched only once its cached match falls behind the cursor, replacing the
per-match full-tail re-scan that was O(n^2) (O(n^3) over a stream). A length cap
before the scan is a backstop.
- strip_tool_call_markup preserves think/reasoning blocks verbatim (the parser
skips tool markup inside them), stripping only the visible text around them.
- _in_think uses bisect over the sorted think spans (was a linear scan per
candidate).
- GGUF streaming strip runs the balanced bracket pre-pass before the regex
patterns so nested-arg calls do not leak or eat trailing prose, and the
BUFFERING ARGS detector requires the rehearsal name-ARGS shape.
- Tests: canonical array, array string-args, array strip keeps prose, Mistral
plus rehearsal multi-call, v11 call-id name, think-rehearsal strip
preservation, and bracket-strip linearity.
* Studio: preserve reasoning blocks in the route and streaming strip paths too
Addresses Gemini/Codex review: making strip_tool_call_markup preserve think
blocks left the route display strip and the GGUF streaming strip inconsistent,
so a rehearsed call inside a reasoning block was still deleted from the visible
text on those paths.
- Extract the think-block segmentation into one shared helper (strip_outside_think)
and route all three strip paths through it: strip_tool_call_markup,
_strip_tool_xml_for_display, and the GGUF _strip_tool_markup_streaming closure.
- Add a route-strip regression test that a rehearsal inside a reasoning block is
preserved while a real call outside it is still stripped.
* Studio: fix bracket-tag strip/buffer review findings
Address the live code-review findings on the Mistral bracket-tag / rehearsal
tool-call rescue path:
- tool_healing: a literal think block inside a tool-call argument is no longer
treated as a reasoning block. strip_outside_think now excludes think spans
that sit inside a complete tool-call span, so the call is stripped whole
instead of the split hiding its open/close pair and leaking the raw call.
- tool_healing: the rehearsal trailing-strip pattern requires a following brace
or end-of-text, so prose that merely mentions name[ARGS] is not truncated as
a phantom call. The bracket strip patterns are aligned with the parser
regexes (whitespace, v11 [CALL_ID]/[ARGS] metadata, and the [CALL_ID]
lookbehind).
- routes: strip a truncated canonical Mistral array ([TOOL_CALLS] [{... with no
closing bracket) that the balanced scan cannot remove, align the display
regex with the parser regexes, and apply the same rehearsal-prose guard.
- safetensors loop: mirror the GGUF [ARGS] rehearsal-substring check during
BUFFERING so a rehearsal name does not stream before its [ARGS] arrives.
Adds regression tests for each; existing parser suite stays green.
* Studio: hold split rehearsal tool-name prefix in both streaming loops
A reasoning-model rehearsal call can stream the tool name and its [ARGS] arm in
separate chunks (web_search then [ARGS]{...}). The buffering detector only
recognised the rehearsal once [ARGS] was present, so the bare tool name was
emitted as visible content before the call drained and executed.
Add _is_rehearsal_prefix (mirrored in the safetensors loop and the GGUF loop):
when a no-signal buffer is a bare active-tool name -- or a partial prefix of
NAME[ARGS] -- hold it as a prefix instead of streaming it, so the next chunk's
[ARGS] flips it to a drain. A whitespace in the buffer means prose, not a split
call, so ordinary text still streams.
Adds regression tests for the split rehearsal in both loops and a guard that a
plain non-tool word still streams.
* Studio: route Anthropic tool-call cleanup through the protected display strip
The Anthropic stream, non-stream, and passthrough paths cleaned content with raw
_TOOL_XML_RE.sub instead of _strip_tool_xml_for_display, so a rehearsal call
inside <think> was deleted from the reasoning and a nested [TOOL_CALLS] call
dropped its trailing prose (the OpenAI-compatible paths already use the helper).
Route all four sites (prior-assistant cleanup, streaming content events,
non-stream aggregation, passthrough conversion) through the protected helper, and
add a source-level guard test so raw _TOOL_XML_RE.sub stays confined to the
helper itself.
* Studio: stop split rehearsal tool names leaking once streaming, uncapped, or unrestricted
The split-rehearsal guard (NAME in one chunk, [ARGS]{...} in the next) only held
the name in the initial BUFFERING state. Three gaps remained where the bare tool
name still streamed as visible content before the call drained:
- STREAMING: after prose had already streamed, both loops emitted a trailing
active-tool-name token (and the GGUF/safetensors [ARGS] boundary was not pulled
back over the name). Hold the trailing rehearsal token and release it on the
next chunk, with an end-of-stream flush so a plain answer that merely ends on a
tool-name word is never dropped.
- Buffer cap: a realistic MCP name longer than the 32-char _MAX_BUFFER_CHARS cap
defeated the BUFFERING hold. A rehearsal prefix is self-bounding (it stops
matching once it grows past NAME[ARGS]), so the generic cap no longer applies to
it.
- Unrestricted mode (tools=[]): with no declared tool list, any bare identifier
may be a NAME[ARGS] rehearsal, so the prefix check now recognises one instead of
leaking the name and mis-parsing the call.
Regression tests cover the streaming, long-name, and unrestricted cases plus the
plain-prose paths that must not be held or corrupted.
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* Studio tools: protect think blocks in safetensors streaming, hold split rehearsal on initial flush, advertise Mistral tools
Pass-3 review follow-ups on the Mistral [TOOL_CALLS] / rehearsal [ARGS] work:
- Safetensors streaming display strip now preserves think / [THINK] reasoning
verbatim (routes through strip_outside_think like the GGUF path). A call
rehearsed inside a reasoning block was stripped mid-stream and then restored by
the final strip, a non-monotonic shrink/grow that corrupted append-by-length
stream consumers and the visible reasoning.
- The first flush out of BUFFERING (safetensors and GGUF) now applies the same
trailing-name hold the STREAMING branch uses, so a split rehearsal (prose plus a
trailing active tool name in one chunk, [ARGS]{...} in the next) no longer leaks
the bare name before the call drains.
- Safetensors capability gate no longer suppresses tools for Mistral [TOOL_CALLS]
templates, which the shared bracket-tag parser now handles end to end. Llama
python_tag stays suppressed (still unparseable).
- Route display strip applies the open-ended / bare-marker tail arms only on the
segment after the last reasoning block (closed-only regex before it), matching
strip_tool_call_markup, so a bare foo[ARGS] before a reasoning block is preserved
while complete calls are still removed in every segment.
Adds regression tests for each and updates the now-stale Mistral capability test.
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* Fix tool-call think-marker and bracket-wrapper edge cases
Round-1 review follow-ups on the Mistral/rehearsal tool-call healing:
- tool_healing: a reasoning marker that opens INSIDE a tool call's
arguments is argument data, not a reasoning block. Add
_think_spans_outside_tool_markup (start-inside test) and use it in
both parse_tool_calls_from_text and strip_outside_think so a literal
marker in one call's args no longer hides a later call (parse) or
leaks the raw markup (strip) when the greedy match runs past the
call's closer.
- tool_healing: strip the orphan Mistral v11 [/TOOL_CALLS] closer left
behind after the balanced scan removes the call body. Add a route arm
for the same closer in _TOOL_XML_RE / _TOOL_XML_CLOSED_RE.
- safetensors + llama_cpp streaming strip: run the open-ended (EOS
anchored) tail patterns only on the last segment; segments before a
reasoning block use the closed-only patterns, matching the final
strip and the route strip. A bare foo[ARGS] before a reasoning block
is prose, not a truncated call.
- safetensors streaming detector: validate each [ARGS] hit before
draining. A bare foo[ARGS] in prose (no active tool name in front)
no longer drains the rest of the turn; a later real NAME[ARGS] call
is still found and the prose in between is preserved.
Regression tests added for each case across the parser, strip helpers,
and both streaming loops.
* Strip incomplete-XML tool markup with literal think tags; widen render-html detector
Round-2 review follow-ups.
- tool_healing: an UNCLOSED <tool_call> / <function= call that the parser still
executes via allow_incomplete leaked its markup when an argument contained a
literal think marker. _tool_call_markup_spans only covered closed calls, so the
literal was treated as a reasoning block to preserve. Extend it to the
open-ended XML tail forms (shared as _TOOL_OPEN_XML_TAIL_PATS) so a think marker
inside an unclosed call is argument data and the call's markup is stripped. A
complete call's opener stays bounded to its closed span, and a real reasoning
block with no tool call is still preserved.
- safetensors render-html provisional card: _detect_render_html_tool_start was
XML-only, so a Mistral [TOOL_CALLS]render_html or rehearsal render_html[ARGS]
call executed but skipped the early card. Detect the earliest tool-call marker
across every serialization the loop executes and fire when it is render_html.
Regression tests added for both.
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* Studio tools: gate [ARGS] on active tools and skip think-block render_html rehearsal
Round 3 review fixes for the Mistral / rehearsal tool-call parsing path. Both are
asymmetric-fix bugs where one code path applied a guard the analogous paths did not.
- [ARGS] active-tool gating: the streaming state already validates a rehearsal
NAME[ARGS] against the active tool list before draining, but the BUFFERING
detection and the end-of-stream safety-net checks (safetensors and GGUF) treated
any word[ARGS] substring as a tool boundary. An answer containing a literal
foo[ARGS]{...} in prose, where foo is not an enabled tool, was drained, parsed into
a disabled foo no-op, and forced an extra generation turn. Gate those checks on the
active tool name too (unrestricted mode still accepts any name), so inactive-name
prose is neither drained nor parsed. Adds a shared _has_genuine_tool_signal helper
(safetensors) and _gguf_rehearsal_signal_pos / _gguf_has_genuine_tool_signal (GGUF).
- render_html provisional card vs think blocks: the parser skips tool candidates that
start inside a <think>/[THINK] reasoning block, but the provisional render_html
detector scanned raw content. A render_html rehearsed inside <think> followed by a
real non-render_html call emitted a provisional render_html tool_start (reusing the
later call's id) that the loop never executed. Drop candidates that start inside a
think span and use the first marker of each shape outside the blocks. Also resolve
the [TOOL_CALLS] [{...}] array shape through the parser so a nested "name" argument
key no longer fires a false provisional card ahead of the real top-level tool name.
Adds regression tests for both loops: inactive-name foo[ARGS]{...} is not drained into
a disabled no-op or a retry turn, a think-block render_html rehearsal emits no
provisional card, and the array top-level name is read correctly.
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* Gate ambiguous bare-rehearsal parse and strip on the active tool list
A bare NAME[ARGS]{json} is a genuine rehearsal call only when NAME is an
active tool; otherwise it is prose. The earlier round gated only detection
(so an inactive foo[ARGS] no longer drained the buffer or forced a retry
turn), but the parse and strip stayed unrestricted, which produced two
regressions:
1. An inactive foo[ARGS]{...} placed immediately before a real
web_search[ARGS]{...} in the same content span made the real call fail
to execute (parse consumed the phantom foo call).
2. An inactive foo[ARGS]{...} in a prose answer had its markup stripped
from the visible text, corrupting the sentence to " is just syntax."
Thread enabled_tool_names through the shared parser/strip so parse and
strip apply the SAME active-tool gate as detection:
- core/tool_healing.py: _iter_bracket_spans skips an inactive rehearsal
span; parse_tool_calls_from_text, _strip_bracket_tag_calls,
_strip_markup_segment and strip_tool_call_markup accept and thread the
gate; apply_tool_strip_patterns keeps an inactive rehearsal match.
- core/inference/tool_call_parser.py: wrappers forward the gate.
- core/inference/safetensors_agentic.py and core/inference/llama_cpp.py:
compute the gate from the active tool list (None when unrestricted, to
keep the legacy strip-all behavior) and thread it into every parse and
streaming/final strip site.
- routes/inference.py: _strip_tool_xml_for_display accepts the gate and
keeps an inactive rehearsal via a capture group on its rehearsal arm, so
the display cleanup does not re-strip the already-correct loop output.
The [TOOL_CALLS] control-token arms still strip unconditionally. Wire
the current turn's active tool names into the GGUF and safetensors
content-display sites.
Tests: parse and strip gate coverage in test_tool_call_parser_strict.py,
test_tool_xml_strip.py and test_safetensors_tool_loop.py; end-to-end GGUF
coverage for the real-call-after-inactive-rehearsal case and a
strengthened assertion that the inactive rehearsal prose survives intact.
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* Studio: render the reasoning block for safetensors and MLX like GGUF
enable_thinking chat templates (Qwen3/Qwen3.5/GLM) prefill an unclosed <think>
into the generation prompt, so the model emits only the closing </think> then
the answer. The safetensors/MLX chat stream emitted that as plain content, so
the reasoning showed inline with no collapsible thinking block, while GGUF
(which surfaces reasoning via reasoning_content) rendered one. This brings
safetensors and MLX to parity.
- _ResponsesReasoningExtractor gains a reasoning_prefilled mode that starts
inside the reasoning block and splits on the first </think>; default False
keeps GGUF and every existing caller byte-identical. It suppresses a stray
re-emitted <think> and holds partial markers back across chunk boundaries.
- _sf_reasoning_prefill_mode gates the mode on reasoning being enabled for the
request, an enable_thinking or enable_thinking_effort style, and the template
actually using the standard <think>/</think> markers. Models with a bespoke
reasoning channel (e.g. gemma's <|think|>/<|channel>) are excluded so their
answer is never swallowed; gpt-oss (Harmony) and thinking-off requests are
excluded too.
- sf_tool_stream and stream_chunks (the latter also serves MLX) feed text
through the extractor, emitting reasoning_content then content deltas, with a
per-turn reset in the tool loop and a flush before each tool_start; only the
visible delta reaches the monitor reply. The two non-streaming drains split
reasoning_content the same way.
- Tests: extractor prefilled mode (streaming and edge cases), the gate matrix
including the gemma-style exclusion, and a route-replay of the tool-loop
reasoning stream.
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* studio: skip tool calls rehearsed in prefilled reasoning
Reasoning models (Qwen3.5 enable_thinking) open <think> in the prompt, so the
generated text starts inside the thought and emits only a closing </think> with
no opener. _think_spans_outside_tool_markup only found spans with an explicit
opener, so a NAME[ARGS]{...} or [TOOL_CALLS] call rehearsed in that leading
thought was parsed and executed as a real call.
Add a leading think span (offset 0 through the first close marker) when the
content opens with a bare close, so the rehearsed call is skipped and the
reasoning is preserved by strip_outside_think. Guarded by the existing call-span
check: a literal </think> inside a real call's arguments does not trigger the
span, so a genuine leading call still fires. Tests for both cases.
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* studio: do not start prefilled reasoning mode when reasoning_effort is none
enable_thinking_effort models (e.g. GLM-5.2) express thinking-off via
reasoning_effort="none" rather than enable_thinking=False, but
_sf_reasoning_prefill_mode only looked at enable_thinking, so such a request
started the extractor in prefilled mode. With thinking off the model never emits
</think>, so the whole answer was captured as reasoning_content and the visible
content/stream came back empty. Thread reasoning_effort through and return False
when it is "none". Tests for none vs a real effort level.
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* studio: only treat a leading bare </think> as prefilled reasoning when a real call follows
The prefilled-reasoning virtual span fired on any unmatched leading close marker,
so a non-prefilled turn that emits a real call before a stray </think> (for
example "Now web_search[ARGS]{...}</think> answer") had the call swallowed by the
span and dropped. Require that a real tool call also appear after the close (the
actual turn that follows the thought) before adding the span, so a stray close in
a normal answer no longer suppresses a genuine leading call. The rehearse-then-
call case still skips the rehearsal. Test for the stray-close case.
* Studio: trim redundant comments (comment-only, AST-verified)
* studio: keep tool_healing importable on Python 3.9
_balanced_json_span was annotated -> int | None. With no
from __future__ import annotations, that PEP 604 union is evaluated at
import time, so on Python 3.9 (which the package still supports,
requires-python >=3.9, and where external inference servers import this
module standalone) the def raises TypeError and the whole module fails
to import before any parsing runs.
Add from __future__ import annotations so annotations stay lazy strings,
matching the prevailing convention across studio/backend. No behavior
change: the module has no runtime annotation introspection.
* Studio: gate the Anthropic tool-stream display strip on declared tools
The Anthropic streaming and non-streaming tool paths called
_strip_tool_xml_for_display without enabled_tool_names, so with the default
strip-all behavior a final answer that literally contains an inactive-name
NAME[ARGS]{json} (prose, not a call) lost those bytes in the delivered text.
The GGUF and safetensors paths already pass _display_tool_name_gate(tools);
these two sites were missed when that gate was threaded through.
Compute the gate from the declared tools and pass it at both sites (threading
openai_tools into _anthropic_tool_non_streaming and its caller), so an
inactive-name rehearsal survives while an active-name one is still stripped.
Add a regression test.
* Studio: hold a split unrestricted rehearsal prefix at the bracket
In unrestricted tool mode (tools=[]) the rehearsal-prefix regex required
[A after the bracket, so a chunk boundary landing right after NAME[ (e.g.
web_search[ then ARGS]{...}) failed the prefix check and streamed the
partial tool markup web_search[ to the client before the call drained.
Restricted mode already holds this via a startswith check. Make the bracket
and each ARGS letter individually optional so NAME[ is held too, matching
the documented intent. Add a regression test.
* Studio: gate rehearsal detection and history strip on the original tool set
Two display/loop gate fixes so a spent one-shot tool is handled consistently:
- Rehearsal DETECTION (safetensors and GGUF loops) now uses the ORIGINAL tool
list, matching the strip gate, instead of the post-removal active_tools. After a
one-shot tool (render_html) runs it is dropped from active_tools; a repeat
render_html[ARGS]{...} while another tool is still active was stripped from
display yet never detected, so it was not routed to the render_html_repeat no-op
and the turn ended as a blank continuation. Detection now fires for it.
- The GGUF assistant-history sanitiser forwards the enabled-tool-name gate (like
the live-response strip), so a prior turn documenting an inactive foo[ARGS]{...}
shape is preserved in the replayed prompt context instead of being deleted.
Add regression tests for both loops and the history strip.
* Studio: thread the tool-name gate through the remaining rehearsal/history sites
Follow-up to the rehearsal-detection and history-strip gate fixes, covering the
sibling sites that were missed:
- GGUF loop: the rehearsal-prefix and trailing-name hold checks now use the
original tool list (_detect_tools) like the detection path, so a spent one-shot's
split repeat (bare render_html then [ARGS]{...}) is held instead of flushed as
visible text.
- The safetensors and Anthropic assistant-history sanitisers and the Anthropic
non-streaming passthrough now forward the enabled-tool-name gate to
_strip_tool_xml_for_display, matching the GGUF history sanitiser and the live
strips, so a prior turn documenting an inactive foo[ARGS]{...} example is
preserved in the replayed prompt / final text instead of deleted.
Add regression tests.
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* Tile bracket-call spans per array item and include the v11 closer
Two with_spans fixes for the Mistral bracket parser, both hit through the
client-tool passthrough healers:
- A multi-call [TOOL_CALLS] array carried its whole markup span on the first
call and zero-width spans after, so a consumer that filters promotions by
the declared tool set either re-emitted the full raw array as text next to
the promoted call or silently dropped a filtered call's bytes. The region is
now tiled across the call-producing items (each call's span covers its own
JSON object plus the separator bytes before it; the last span runs to the
region end), so promoted markup strips exactly once and a skipped call's
bytes stay visible.
- The v11 wrapper closer [/TOOL_CALLS] sat outside the reported span and
leaked as stray text after promotion; the region now extends over an
immediately-following closer.
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* Address review: decouple healer signals from the loop signal set
The passthrough healer buffered on every TOOL_XML_SIGNALS entry, so the bare
[ARGS] rehearsal marker this branch adds for the loops (where it is gated on
active tool names) put legitimate prose like 'Use foo[ARGS] in templates'
into the holding state and stalled the stream until finalization. The healer
can never promote a bare rehearsal call, so it now buffers only on formats
its parser promotes: <tool_call>, <|tool_call>, <function=, [TOOL_CALLS].
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* Condense comments in the Mistral tool-call rescue to contract essentials
* verify_import_hoist: exempt __future__ imports and same-diff relocations
Two false positives fired on this PR's refactor. A from __future__ import
is a compiler directive whose name never appears as a runtime load, so
HOISTED-IMPORT-UNUSED can never see it used, yet the file requires it for
PEP 604 annotations on Python 3.9. TARGET-CHANGED flagged the deliberate
move of the strip-pattern constants into core.inference.tool_call_parser
as a silent re-point even though the old module-level target was removed
and the new one added in the same diff. Both get narrow exemptions; a
re-point to a pre-existing target is still caught, and the self-test
negative controls all pass unchanged.
* Drain the whole Mistral [TOOL_CALLS] array in streaming passthrough healing
StreamToolCallHealer._drain promoted only the first parsed call per pass and
dropped the rest of the buffer past that one span. For a well-formed Mistral
parallel-tool-call array streamed through client-tool passthrough
([TOOL_CALLS][{...},{...}]), the per-item spans are contiguous, so after the
first call was promoted the residue began with ,{...}] (no leading signal) and
was flushed as raw text: every call after the first was lost.
_drain now walks the contiguous run of parsed calls (adjacent tiled spans =
one array), promoting each declared call and relaying undeclared ones as data,
and stops at the first gap (prose) or incomplete trailing block so separate
blocks still stream incrementally in document order. This mirrors the
non-streaming heal_openai_message / finalize promote-or-flush loop and the
server-side safetensors loop, which already handled multi-call arrays.
Added regression tests: 2-call array in one feed and char-by-char, an
undeclared middle call kept as text, and an array followed by trailing prose.
* Drain comma-less Mistral tool-call arrays and normalize null arguments
The array branch fed the whole body to a single json.loads, which rejects the
comma-less multi-call form the repo's own Mistral/Ollama templates render (the
range loop in ollama_template_mappers.py emits the objects with no separator) and
so dropped every call. Decode elements individually with the existing
comma-tolerant raw_decode helper, now _decode_array_items, which also returns the
objects, so all calls are recovered while the span tiling is unchanged.
Also normalize a non-object array argument such as arguments null to an empty
object, matching the wrapped tool_call path, instead of serializing None to the
string "null" that auto-heal would turn into a bogus query of "null".
* Gate safetensors reasoning prefill on the rendered generation prompt
reasoning_always_on fires on any paired <think></think> in the template,
including markup that only renders PAST assistant history (Kimi-K2-Thinking)
while the generation prompt opens no <think>. Starting the reasoning extractor
in prefilled mode there captured a normal answer entirely as reasoning_content
and returned blank visible content. Prefill only when rendering the generation
prompt actually leaves <think> open (DeepSeek-R1 / QwQ / Qwen3-Thinking);
history-only templates start the extractor in normal mode and parse the model's
own <think>...</think>. Adds a Kimi-shape regression test.
* Keep bare scalar Mistral array arguments raw instead of double-encoding
A scalar string argument in the canonical Mistral [TOOL_CALLS] array
(for example [TOOL_CALLS][{"name":"web_search","arguments":"weather"}])
was run through json.dumps, turning weather into the JSON string
"weather". The downstream argument healer then wrapped that quoted
form, so a single-string tool like web_search searched for the literal
"weather" with quotes. The <tool_call> path already keeps a scalar
argument raw; mirror it here so only a dict is serialized. Add a
regression test asserting both paths yield the same healed arguments.
* Tighten tool-call rescue and reasoning-prefill comments
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
4552 lines
189 KiB
Python
4552 lines
189 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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"""Tests for the safetensors agentic tool loop.
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Covers the ``tool_call_parser`` helpers and the cumulative-text state machine in
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``run_safetensors_tool_loop``, run against fake single-turn generators (no model
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load). Edge cases: plain answers, JSON and XML tool-call forms, truncated/unclosed
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calls, tool-result feedback, bad-JSON heal, duplicate-call short-circuit,
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``__IMAGES__`` sentinel stripping, executor errors, cancel, and the iteration cap.
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"""
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import json
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import threading
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from typing import cast
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import pytest
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from core.inference import safetensors_agentic
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from core.inference.safetensors_agentic import (
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_coerce_arguments,
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_detect_render_html_tool_start,
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run_safetensors_tool_loop,
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strip_tool_markup_streaming,
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)
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from core.inference.tool_call_parser import (
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RAG_MAX_SEARCHES_PER_TURN,
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has_tool_signal,
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parse_tool_calls_from_text,
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strip_tool_markup,
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)
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from state import tool_approvals
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from state.tool_approvals import resolve_tool_decision
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from utils.datasets import is_gpt_oss_model_name
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# ────────────────────────────────────────────────────────────────────
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# parse_tool_calls_from_text
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# ────────────────────────────────────────────────────────────────────
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class TestParser:
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def test_json_tool_call(self):
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text = '<tool_call>{"name":"web_search","arguments":{"query":"hello"}}</tool_call>'
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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tc = result[0]
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assert tc["type"] == "function"
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assert tc["function"]["name"] == "web_search"
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# Arguments must always be a JSON string.
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assert isinstance(tc["function"]["arguments"], str)
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assert "hello" in tc["function"]["arguments"]
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def test_json_tool_call_unclosed(self):
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# No </tool_call>; balanced-brace extractor must still close it.
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text = '<tool_call>{"name":"python","arguments":{"code":"print(1)"}}'
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert result[0]["function"]["name"] == "python"
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def test_json_tool_call_unclosed_requires_healing(self):
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text = '<tool_call>{"name":"python","arguments":{"code":"print(1)"}}'
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assert parse_tool_calls_from_text(text)[0]["function"]["name"] == "python"
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assert parse_tool_calls_from_text(text, allow_incomplete = False) == []
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def test_gemma_native_tool_call(self):
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text = '<|tool_call>call:terminal{command:"ls -la",workdir:"."}<tool_call|>'
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert result[0]["function"]["name"] == "terminal"
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args = json.loads(result[0]["function"]["arguments"])
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assert args == {"command": "ls -la", "workdir": "."}
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def test_gemma_native_tool_call_template_quotes(self):
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text = '<|tool_call>call:web_search{query:<|"|>openai news<|"|>}<tool_call|>'
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert result[0]["function"]["name"] == "web_search"
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assert json.loads(result[0]["function"]["arguments"]) == {"query": "openai news"}
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def test_gemma_native_tool_call_template_quotes_escape_backslashes(self):
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text = r'<|tool_call>call:ls{path:<|"|>C:\Users\wasim\repo<|"|>}<tool_call|>'
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert result[0]["function"]["name"] == "ls"
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assert json.loads(result[0]["function"]["arguments"]) == {"path": r"C:\Users\wasim\repo"}
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def test_gemma_native_tool_call_hyphenated_argument_name(self):
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text = '<|tool_call>call:mcp__srv__create-issue{issue-title:"Bug report"}<tool_call|>'
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert result[0]["function"]["name"] == "mcp__srv__create-issue"
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assert json.loads(result[0]["function"]["arguments"]) == {"issue-title": "Bug report"}
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def test_gemma_native_tool_call_keeps_braces_inside_string_value(self):
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text = '<|tool_call>call:terminal{command:"echo {foo:bar}"}<tool_call|>'
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert result[0]["function"]["name"] == "terminal"
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assert json.loads(result[0]["function"]["arguments"]) == {"command": "echo {foo:bar}"}
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def test_gemma_native_tool_call_bare_string_values(self):
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text = "<|tool_call>call:get_weather{location:Tokyo,unit:celsius}<tool_call|>"
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert json.loads(result[0]["function"]["arguments"]) == {
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"location": "Tokyo",
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"unit": "celsius",
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}
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def test_xml_function_call(self):
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text = "<function=python><parameter=code>print('hi')</parameter></function>"
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert result[0]["function"]["name"] == "python"
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assert "print('hi')" in result[0]["function"]["arguments"]
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def test_xml_param_preserves_leading_indentation(self):
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import json
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# Only the wrapping newline is trimmed; code-argument indentation survives.
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text = (
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"<function=python><parameter=code>\n"
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" indented = 1\n"
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" more\n"
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"</parameter></function>"
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)
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert json.loads(result[0]["function"]["arguments"]) == {
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"code": " indented = 1\n more"
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}
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def test_xml_unclosed(self):
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# Closing tags omitted; parser must still extract the value.
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text = "<function=terminal><parameter=command>ls -la"
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert result[0]["function"]["name"] == "terminal"
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assert "ls -la" in result[0]["function"]["arguments"]
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def test_xml_unclosed_requires_healing(self):
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text = "<function=terminal><parameter=command>ls -la"
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assert parse_tool_calls_from_text(text)[0]["function"]["name"] == "terminal"
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assert parse_tool_calls_from_text(text, allow_incomplete = False) == []
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def test_code_with_embedded_xml(self):
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# A code parameter with a literal </parameter> must not truncate: the
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# parser uses end-of-body as the only boundary for single-param calls.
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text = (
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"<function=python><parameter=code>html = '<a></a>'\nprint('hi')</parameter></function>"
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)
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert "print('hi')" in result[0]["function"]["arguments"]
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def test_xml_param_preserves_leading_indentation(self):
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# Only the wrapping newline is trimmed, so code-argument indentation survives (str.strip() destroyed it).
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text = (
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"<function=python><parameter=code>\n"
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" indented = 1\n"
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" more\n"
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"</parameter></function>"
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)
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert json.loads(result[0]["function"]["arguments"]) == {
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"code": " indented = 1\n more"
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}
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def test_function_signal_inside_parameter_is_literal(self):
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text = (
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"<function=python>"
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"<parameter=code>print('<function=render_html>')</parameter>"
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"</function>"
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)
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result = parse_tool_calls_from_text(text)
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assert len(result) == 1
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assert result[0]["function"]["name"] == "python"
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assert "<function=render_html>" in result[0]["function"]["arguments"]
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def test_multiple_calls(self):
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text = (
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'<tool_call>{"name":"web_search","arguments":{"query":"a"}}</tool_call>'
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'<tool_call>{"name":"web_search","arguments":{"query":"b"}}</tool_call>'
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)
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result = parse_tool_calls_from_text(text)
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assert len(result) == 2
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assert result[0]["function"]["name"] == "web_search"
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assert result[1]["function"]["name"] == "web_search"
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def test_bad_json_does_not_raise(self):
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text = "<tool_call>{not valid json}</tool_call>"
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result = parse_tool_calls_from_text(text)
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# Bad JSON is dropped silently; caller can fall back to text.
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assert result == []
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def test_has_tool_signal(self):
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assert has_tool_signal("blah <tool_call> x")
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assert has_tool_signal("blah <|tool_call>call:terminal")
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assert has_tool_signal("hi <function=foo>...")
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assert has_tool_signal("ok [TOOL_CALLS]web_search{...")
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assert has_tool_signal("fine python[ARGS]{...")
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assert not has_tool_signal("hello world")
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def test_render_html_start_detector_uses_first_tool(self):
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assert _detect_render_html_tool_start("<function=render_html>")
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assert _detect_render_html_tool_start(
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'<tool_call>{"name":"render_html","arguments":{"code":"<html>"}'
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)
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assert not _detect_render_html_tool_start(
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"<function=python><parameter=code>'<function=render_html>'"
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)
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assert not _detect_render_html_tool_start(
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'<tool_call>{"name":"python","arguments":{"code":"<function=render_html>"}}'
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)
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def test_render_html_start_detector_covers_mistral_and_rehearsal_forms(self):
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# The provisional render-html card must fire for bracket-tag forms too, not only XML.
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assert _detect_render_html_tool_start('[TOOL_CALLS]render_html{"code":"<html>"}')
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assert _detect_render_html_tool_start('[TOOL_CALLS]render_html[ARGS]{"code":"x"}')
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assert _detect_render_html_tool_start(
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'[TOOL_CALLS] [{"name":"render_html","arguments":{}}]'
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)
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assert _detect_render_html_tool_start('render_html[ARGS]{"code":"<html>"}')
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# A different first tool (or a prose mention with no JSON body) must not fire.
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assert not _detect_render_html_tool_start('[TOOL_CALLS]web_search{"q":"x"}')
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assert not _detect_render_html_tool_start('web_search[ARGS]{"q":"x"}')
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assert not _detect_render_html_tool_start('python[ARGS]{"code":"render_html[ARGS]{}"}')
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assert not _detect_render_html_tool_start("use render_html[ARGS] to render")
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||
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def test_render_html_start_detector_skips_think_block_rehearsal(self):
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# A render_html rehearsed inside think must not fire the card; the outside-think call decides.
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assert not _detect_render_html_tool_start(
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'<think>draft render_html[ARGS]{"code":"x"}</think>python[ARGS]{"code":"print(1)"}'
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)
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assert not _detect_render_html_tool_start(
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'[THINK]render_html[ARGS]{"code":"x"}[/THINK]web_search[ARGS]{"q":"y"}'
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)
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# A real render_html AFTER a rehearsed non-render_html inside think still fires.
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||
assert _detect_render_html_tool_start(
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'<think>web_search[ARGS]{"q":"x"}</think>render_html[ARGS]{"code":"<html>"}'
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)
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# A render_html rehearsed inside think with no real call after does not fire.
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assert not _detect_render_html_tool_start('<think>render_html[ARGS]{"code":"x"}</think>')
|
||
|
||
def test_render_html_start_detector_reads_top_level_array_name(self):
|
||
# Array form: the name is the object's top-level ``"name"``, not an argument key.
|
||
assert not _detect_render_html_tool_start(
|
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'[TOOL_CALLS] [{"arguments":{"name":"render_html"},"name":"python"}]'
|
||
)
|
||
assert _detect_render_html_tool_start(
|
||
'[TOOL_CALLS] [{"arguments":{"name":"python"},"name":"render_html"}]'
|
||
)
|
||
|
||
def test_strip_markup_closed(self):
|
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text = "before <tool_call>{}</tool_call> after"
|
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assert strip_tool_markup(text) == "before after"
|
||
text = 'before <|tool_call>call:terminal{command:"ls"}<tool_call|> after'
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assert strip_tool_markup(text) == "before after"
|
||
|
||
def test_strip_named_mistral_call_consumes_trailing_eos(self):
|
||
# The named ``[TOOL_CALLS]name{json}`` shape must eat the optional
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||
# trailing ``</s>`` like the array shape, so the EOS marker is not left
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||
# behind as visible content.
|
||
text = '[TOOL_CALLS]web_search{"query":"cats"}</s>'
|
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assert strip_tool_markup(text) == ""
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text = '[TOOL_CALLS]web_search{"query":"cats"}</s> and then'
|
||
assert strip_tool_markup(text) == " and then"
|
||
|
||
def test_strip_markup_unclosed_final(self):
|
||
text = "before <tool_call>{partial"
|
||
# final=True drops the trailing run.
|
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assert strip_tool_markup(text, final = True) == "before"
|
||
# Without final=True the unclosed run is preserved.
|
||
assert "partial" in strip_tool_markup(text)
|
||
assert strip_tool_markup("before <|tool_call>call:terminal{", final = True) == "before"
|
||
|
||
def test_streaming_strip_respects_disabled_healing(self):
|
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raw = 'before <tool_call>{"name":"web_search"'
|
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assert strip_tool_markup_streaming(raw, auto_heal_tool_calls = False) == raw
|
||
assert strip_tool_markup_streaming(raw) == "before "
|
||
|
||
def test_streaming_strip_respects_disabled_healing_without_tool_protocol(self):
|
||
raw = 'before <tool_call>{"name":"web_search"'
|
||
assert strip_tool_markup_streaming(raw, auto_heal_tool_calls = False) == raw
|
||
assert (
|
||
strip_tool_markup_streaming(
|
||
raw,
|
||
auto_heal_tool_calls = False,
|
||
tool_protocol_active = True,
|
||
)
|
||
== "before "
|
||
)
|
||
|
||
# Mistral [TOOL_CALLS] bracket-tag.
|
||
|
||
def test_mistral_bracket_basic(self):
|
||
# Devstral / Mistral-Small fallback when bypassing native FC.
|
||
text = '[TOOL_CALLS]web_search{"query":"weather"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
assert isinstance(result[0]["function"]["arguments"], str)
|
||
assert "weather" in result[0]["function"]["arguments"]
|
||
|
||
def test_rehearsal_inside_unclosed_think_is_ignored(self):
|
||
"""Rehearsal-shaped markup inside an unclosed <think> block must
|
||
not be executed as a real tool call. Mid-stream the </think>
|
||
tag has not arrived yet, so the strip regex has to accept
|
||
end-of-string as a terminator. Regression for the Gemini
|
||
high-severity flag on this PR."""
|
||
text = (
|
||
"<think>I should call web_search[ARGS]" '{"query":"weather"} next to find the answer.'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
# Inside an unclosed think block no calls are yielded.
|
||
assert result == []
|
||
|
||
def test_rehearsal_inside_unclosed_bracket_think_is_ignored(self):
|
||
text = "[THINK]planning to use python[ARGS]" '{"code":"print(1)"} but not yet.'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert result == []
|
||
|
||
def test_rehearsal_after_closed_think_still_parsed(self):
|
||
text = "<think>planning</think>" 'python[ARGS]{"code":"print(1)"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "python"
|
||
|
||
def test_rehearsal_inside_prefilled_think_is_ignored(self):
|
||
"""Reasoning models (Qwen3.5 enable_thinking) open <think> in the PROMPT,
|
||
so generated content starts inside the thought and carries only a closing
|
||
</think>. A call rehearsed in that leading thought must be skipped, while a
|
||
real call after the close still fires."""
|
||
text = 'planning web_search[ARGS]{"query":"draft"}</think>python[ARGS]{"code":"print(1)"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "python"
|
||
|
||
def test_literal_close_think_in_leading_argument_not_prefill(self):
|
||
"""A </think> literal inside a real leading call's arguments must not be
|
||
read as a prefilled-reasoning close (which would skip the call)."""
|
||
text = 'web_search[ARGS]{"query":"what is </think>"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
|
||
def test_stray_close_after_real_call_not_treated_as_prefill(self):
|
||
"""A real leading call followed by a stray </think> and no further call is
|
||
a normal answer, not prefilled reasoning; the call must still fire (the
|
||
virtual span only applies when a real call follows the close)."""
|
||
text = 'Now web_search[ARGS]{"query":"x"}</think> answer'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
|
||
def test_mistral_bracket_with_whitespace(self):
|
||
# Optional whitespace (incl. newlines) between the name and the opening brace.
|
||
text = '[TOOL_CALLS]python \n {"code":"print(1)"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "python"
|
||
assert "print(1)" in result[0]["function"]["arguments"]
|
||
|
||
def test_mistral_bracket_nested_json(self):
|
||
# Brace-balance scan handles nested objects and braces inside string literals.
|
||
text = "[TOOL_CALLS]web_search" '{"query":"a {nested} brace","opts":{"limit":5}}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
import json as _json
|
||
|
||
args = _json.loads(result[0]["function"]["arguments"])
|
||
assert args["query"] == "a {nested} brace"
|
||
assert args["opts"] == {"limit": 5}
|
||
|
||
def test_mistral_bracket_with_prose(self):
|
||
# Bracket-tag surrounded by prose is still recognised.
|
||
text = (
|
||
"Sure, I will look that up.\n"
|
||
'[TOOL_CALLS]web_search{"query":"weather"}\n'
|
||
"Calling now."
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
|
||
def test_mistral_bracket_bad_json_dropped(self):
|
||
text = "[TOOL_CALLS]web_search{not valid}"
|
||
result = parse_tool_calls_from_text(text)
|
||
# No usable tool call; callers fall back to text.
|
||
assert result == []
|
||
|
||
def test_mistral_bracket_object_with_array_value(self):
|
||
# Args must be a JSON object; a dict wrapping an array value is accepted.
|
||
text = '[TOOL_CALLS]web_search{"opts":[1,2,3]}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
|
||
# Rehearsal syntax name[ARGS]{json}.
|
||
|
||
def test_rehearsal_basic(self):
|
||
text = 'python[ARGS]{"code":"print(1)"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "python"
|
||
assert "print(1)" in result[0]["function"]["arguments"]
|
||
|
||
def test_rehearsal_with_prose(self):
|
||
text = "I should call the python tool. Like this: " 'python[ARGS]{"code":"x = 1"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "python"
|
||
|
||
def test_rehearsal_bad_json_dropped(self):
|
||
text = "python[ARGS]{not valid json}"
|
||
result = parse_tool_calls_from_text(text)
|
||
assert result == []
|
||
|
||
def test_mistral_bracket_hyphenated_mcp_name(self):
|
||
# Dashed MCP names must be captured whole, not truncated at the first dash.
|
||
text = '[TOOL_CALLS]mcp__srv__list-issues{"q":"x"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "mcp__srv__list-issues"
|
||
|
||
def test_rehearsal_hyphenated_mcp_name(self):
|
||
text = 'mcp__srv__list-issues[ARGS]{"q":"x"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "mcp__srv__list-issues"
|
||
|
||
def test_streaming_strip_removes_partial_bracket_marker(self):
|
||
# A bracket tag streamed before its opening brace must strip on the final pass, not leak.
|
||
assert strip_tool_markup("answer [TOOL_CALLS]web_search", final = True) == "answer"
|
||
assert strip_tool_markup("text python[ARGS]", final = True) == "text"
|
||
# Non-final must keep the in-progress tag buffered (not yet stripped).
|
||
partial = "answer [TOOL_CALLS]web_search"
|
||
assert strip_tool_markup(partial, final = False) == partial
|
||
|
||
def test_strip_removes_two_level_nested_bracket_call_keeps_prose(self):
|
||
# Two-level-nested args must be removed whole; the balanced scan handles any depth.
|
||
text = 'before [TOOL_CALLS]search{"f":{"g":{"h":1}}} after'
|
||
assert strip_tool_markup(text, final = False) == "before after"
|
||
assert strip_tool_markup(text, final = True) == "before after"
|
||
|
||
def test_strip_removes_call_with_literal_think_in_argument(self):
|
||
# A literal think block inside arguments strips with the call, not as a reasoning block.
|
||
text = (
|
||
'<tool_call>{"name":"write","arguments":'
|
||
'{"text":"compare <think> and </think> tags"}}</tool_call>'
|
||
)
|
||
assert strip_tool_markup(text, final = True) == ""
|
||
|
||
def test_strip_preserves_real_think_but_strips_call_with_literal_think(self):
|
||
text = (
|
||
"<think>planning</think> ok "
|
||
'<tool_call>{"name":"w","arguments":{"t":"<think>x</think>"}}</tool_call> done'
|
||
)
|
||
out = strip_tool_markup(text, final = True)
|
||
assert "<think>planning</think>" in out
|
||
assert "<tool_call>" not in out and '"name"' not in out
|
||
assert "ok" in out and "done" in out
|
||
|
||
def test_prose_mentioning_args_marker_is_not_truncated(self):
|
||
# ``foo[ARGS] to the template`` is prose; the catch-all must not delete the sentence.
|
||
text = "Please pass foo[ARGS] to the template and continue reading."
|
||
assert strip_tool_markup(text, final = True) == text
|
||
|
||
def test_streaming_strip_handles_mistral_v11_call_id_args(self):
|
||
# The streaming strip uses the regex patterns directly, so they must cover the v11
|
||
# [CALL_ID]/[ARGS] metadata (aligned with the parser).
|
||
raw = 'before [TOOL_CALLS]web_search[CALL_ID]abc123[ARGS]{"q":"x"} after'
|
||
out = strip_tool_markup_streaming(raw)
|
||
assert "[TOOL_CALLS]" not in out and "[CALL_ID]" not in out and "[ARGS]" not in out
|
||
assert "before" in out and "after" in out
|
||
|
||
# <think> pre-strip.
|
||
|
||
def test_think_block_stripped_before_xml(self):
|
||
# The think block is stripped before matching so the post-thinking call is recognised.
|
||
text = (
|
||
"<think>I will use web_search to find the weather.</think>"
|
||
'<tool_call>{"name":"web_search","arguments":{"query":"sf"}}</tool_call>'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
|
||
def test_think_block_stripped_before_bracket_tag(self):
|
||
text = (
|
||
"<think>Let me search for that.</think>\n" '[TOOL_CALLS]web_search{"query":"weather"}'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
|
||
def test_uppercase_think_tag_stripped(self):
|
||
# Some templates use [THINK]...[/THINK] instead of <think>.
|
||
text = "[THINK]planning my next call[/THINK]" '[TOOL_CALLS]python{"code":"print(1)"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "python"
|
||
|
||
def test_think_block_hides_inner_tool_call(self):
|
||
# A call mentioned inside think is a rehearsal; the wrapper strip removes the inner markup.
|
||
text = (
|
||
"<think>I might call "
|
||
'<tool_call>{"name":"web_search","arguments":{}}</tool_call> '
|
||
"but I am not sure</think>\n"
|
||
"Let me just answer directly."
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert result == []
|
||
|
||
def test_think_literal_inside_real_tool_argument_is_preserved(self):
|
||
# A real call whose argument contains a literal think tag must not be corrupted.
|
||
text = (
|
||
'<tool_call>{"name":"write","arguments":'
|
||
'{"text":"compare <think> and </think> tags"}}</tool_call>'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert json.loads(result[0]["function"]["arguments"])["text"] == (
|
||
"compare <think> and </think> tags"
|
||
)
|
||
|
||
def test_bracket_tag_argument_with_think_literal_is_preserved(self):
|
||
text = '[TOOL_CALLS]search{"q":"explain [THINK] blocks"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert json.loads(result[0]["function"]["arguments"])["q"] == "explain [THINK] blocks"
|
||
|
||
def test_real_call_after_think_with_rehearsal_inside(self):
|
||
# A rehearsal inside <think> is skipped, but the real call after the close tag parses.
|
||
text = '<think>plan: search[ARGS]{"q":"x"}</think>search[ARGS]{"q":"real"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert json.loads(result[0]["function"]["arguments"])["q"] == "real"
|
||
|
||
# XML takes precedence over bracket-tag.
|
||
|
||
def test_xml_wins_over_bracket(self):
|
||
# When a model emits both forms in one message, the XML form is canonical and wins.
|
||
text = (
|
||
'<tool_call>{"name":"primary","arguments":{}}</tool_call>'
|
||
'[TOOL_CALLS]secondary{"k":"v"}'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "primary"
|
||
|
||
# Strip patterns include bracket-tag and rehearsal.
|
||
|
||
def test_strip_bracket_tag_closed(self):
|
||
text = 'before [TOOL_CALLS]web_search{"q":"hi"} after'
|
||
assert "[TOOL_CALLS]" not in strip_tool_markup(text)
|
||
assert "before" in strip_tool_markup(text)
|
||
assert "after" in strip_tool_markup(text)
|
||
|
||
def test_strip_rehearsal_closed(self):
|
||
text = 'prose python[ARGS]{"code":"x"} more prose'
|
||
cleaned = strip_tool_markup(text)
|
||
assert "[ARGS]" not in cleaned
|
||
assert "prose" in cleaned
|
||
assert "more prose" in cleaned
|
||
|
||
def test_strip_bracket_tag_unclosed_final(self):
|
||
text = 'before [TOOL_CALLS]web_search{"q":"part'
|
||
# Final-mode strip drops the trailing unclosed run.
|
||
cleaned = strip_tool_markup(text, final = True)
|
||
assert "TOOL_CALLS" not in cleaned
|
||
assert cleaned == "before"
|
||
|
||
# Canonical Mistral array, v11 [CALL_ID], unified multi-call (PR review fixes).
|
||
|
||
def test_mistral_canonical_array_is_parsed(self):
|
||
# Canonical multi-call array: every call must parse (was dropped then deleted to EOS).
|
||
text = '[TOOL_CALLS] [{"name":"a","arguments":{"x":1}},{"name":"b","arguments":{"y":2}}]'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert [c["function"]["name"] for c in result] == ["a", "b"]
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"x": 1}
|
||
assert json.loads(result[1]["function"]["arguments"]) == {"y": 2}
|
||
|
||
def test_mistral_array_string_arguments_are_decoded(self):
|
||
# OpenAI-spec arguments arrive as a JSON string; decode to an object.
|
||
text = '[TOOL_CALLS] [{"name":"a","arguments":"{\\"x\\":1}"}]'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"x": 1}
|
||
|
||
def test_mistral_array_scalar_string_argument_not_double_encoded(self):
|
||
# A bare scalar string argument in the Mistral array form must be kept
|
||
# raw, exactly like the <tool_call> path, so the downstream argument
|
||
# healer wraps ``weather`` into the single-string tool's key -- not
|
||
# ``"weather"`` with literal quotes from a redundant json.dumps.
|
||
array = parse_tool_calls_from_text(
|
||
'[TOOL_CALLS][{"name":"web_search","arguments":"weather"}]'
|
||
)
|
||
xml = parse_tool_calls_from_text(
|
||
'<tool_call>{"name":"web_search","arguments":"weather"}</tool_call>'
|
||
)
|
||
assert array[0]["function"]["arguments"] == xml[0]["function"]["arguments"] == "weather"
|
||
healed = _coerce_arguments(
|
||
array[0]["function"]["arguments"], heal = True, tool_name = "web_search"
|
||
)
|
||
assert healed == {"query": "weather"}
|
||
|
||
def test_mistral_array_strip_keeps_trailing_prose(self):
|
||
# The array form must be removed whole, not deleted to end-of-string.
|
||
text = 'answer [TOOL_CALLS] [{"name":"a","arguments":{}}] tail'
|
||
assert strip_tool_markup(text, final = True) == "answer tail"
|
||
|
||
def test_mistral_and_rehearsal_in_one_message_both_parse(self):
|
||
# A Mistral call and a rehearsal call together: both must parse.
|
||
text = '[TOOL_CALLS]a{"x":1} then b[ARGS]{"y":2}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert [c["function"]["name"] for c in result] == ["a", "b"]
|
||
|
||
def test_mistral_v11_call_id_is_not_the_function_name(self):
|
||
# v11 shape: the function name is ``name``, never the opaque call-id token.
|
||
result = parse_tool_calls_from_text('[TOOL_CALLS]get_weather[CALL_ID]abc123[ARGS]{"q":"x"}')
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "get_weather"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"q": "x"}
|
||
# v11 without a call-id parses the same name.
|
||
r2 = parse_tool_calls_from_text('[TOOL_CALLS]get_weather[ARGS]{"q":"y"}')
|
||
assert r2[0]["function"]["name"] == "get_weather"
|
||
|
||
def test_strip_preserves_rehearsal_inside_think(self):
|
||
# A rehearsal inside <think> is reasoning; strip keeps it verbatim.
|
||
text = '<think>plan: search[ARGS]{"q":"x"}</think> A'
|
||
out = strip_tool_markup(text, final = True)
|
||
assert out == text
|
||
assert "search[ARGS]" in out
|
||
|
||
def test_streaming_strip_preserves_rehearsal_inside_think(self):
|
||
# The streaming strip must also preserve a think rehearsal: a mid-stream strip shrinks
|
||
# then regrows the cumulative text (corrupts append-by-length consumers). Matches GGUF.
|
||
text = '<think>plan: search[ARGS]{"q":"x"}</think> A'
|
||
assert strip_tool_markup_streaming(text) == text
|
||
assert strip_tool_markup_streaming(text, tool_protocol_active = True) == text
|
||
# An unclosed block during streaming is preserved too (the parser keeps it).
|
||
partial = '<think>plan: search[ARGS]{"q":"x"}'
|
||
assert strip_tool_markup_streaming(partial, tool_protocol_active = True) == partial
|
||
|
||
def test_streaming_strip_still_removes_real_call_outside_think(self):
|
||
# The think guard must not stop the streaming strip removing a call outside the block.
|
||
text = '<think>reason</think> web_search[ARGS]{"q":"x"}'
|
||
out = strip_tool_markup_streaming(text, tool_protocol_active = True)
|
||
assert "web_search[ARGS]" not in out
|
||
assert "<think>reason</think>" in out
|
||
|
||
def test_strip_bracket_calls_is_linear(self):
|
||
# Many complete bracket calls must strip in ~linear time (was O(n^2) per match).
|
||
import time
|
||
|
||
text = '[TOOL_CALLS]f{"a":1}' * 4000 # ~80KB, 4000 complete calls
|
||
t0 = time.perf_counter()
|
||
out = strip_tool_markup(text, final = True)
|
||
elapsed = time.perf_counter() - t0
|
||
assert "[TOOL_CALLS]" not in out
|
||
assert elapsed < 1.0, f"strip took {elapsed * 1000:.0f}ms on 4000 bracket calls"
|
||
|
||
def test_streaming_strip_handles_nested_mistral_json(self):
|
||
# The non-greedy [TOOL_CALLS]name{...} pattern truncates nested JSON at the first }; the
|
||
# balanced helper must remove the whole call so no trailing brace leaks to the streaming ...
|
||
raw = 'ok [TOOL_CALLS]foo{"a":{"b":1}} tail'
|
||
out = strip_tool_markup_streaming(raw)
|
||
assert "[TOOL_CALLS]" not in out
|
||
assert "}" not in out
|
||
assert "ok " in out and "tail" in out
|
||
|
||
def test_streaming_strip_handles_nested_wrapperless_gemma(self):
|
||
# Same class of bug for the wrapper-less Gemma call:NAME{...} form with a
|
||
# nested object argument.
|
||
raw = "ok call:f{loc:{city:NYC},n:3} tail"
|
||
out = strip_tool_markup_streaming(raw)
|
||
assert "call:f" not in out
|
||
assert "}" not in out
|
||
assert "ok " in out and "tail" in out
|
||
|
||
def test_streaming_strip_keeps_prose_after_function_xml_with_literal_marker(self):
|
||
# A literal ``<function=...>`` in a value is data: the strip must close at the REAL
|
||
# ``</function>`` and keep trailing prose (the open-ended regex ate to EOF).
|
||
raw = (
|
||
"pref <function=python><parameter=code>"
|
||
'print("<function=x>")</parameter></function> tail'
|
||
)
|
||
assert strip_tool_markup_streaming(raw) == "pref tail"
|
||
# Streaming and final strip agree on the visible text (final also trims).
|
||
assert strip_tool_markup_streaming(raw) == strip_tool_markup(raw, final = True)
|
||
|
||
def test_streaming_strip_drops_leading_magistral_reasoning(self):
|
||
# Magistral emits reasoning as a leading ``[THINK]...[/THINK]`` bracket block
|
||
# (not the ``<think>`` the reasoning channel renders). The streaming display
|
||
# strip must drop it so the raw chain-of-thought does not leak into the
|
||
# safetensors content; GGUF routes it to reasoning_content natively.
|
||
closed = "[THINK]Let me think. 2+2 is 4.[/THINK]The answer is 4."
|
||
assert strip_tool_markup_streaming(closed) == "The answer is 4."
|
||
assert strip_tool_markup_streaming(closed) == strip_tool_markup(closed, final = True)
|
||
# Unclosed mid-stream reasoning is held from the marker on (nothing leaks, and
|
||
# the cleaned text only grows as the answer streams in after ``[/THINK]``).
|
||
assert strip_tool_markup_streaming("[THINK]still thinking") == ""
|
||
assert strip_tool_markup_streaming("[THINK]r[/THINK]The") == "The"
|
||
assert strip_tool_markup_streaming("[THINK]r[/THINK]The answer") == "The answer"
|
||
# A non-leading ``[THINK]`` is ordinary prose and is left untouched.
|
||
assert strip_tool_markup_streaming("hi [THINK] later") == "hi [THINK] later"
|
||
|
||
|
||
class TestParserMultiFormat:
|
||
"""Shared-parser coverage: every family's emission maps to the same OpenAI shape."""
|
||
|
||
# Llama-3
|
||
|
||
def test_llama3_python_tag_dot_call(self):
|
||
# Llama-3 built-in tools: <|python_tag|>NAME.call(k="v", ...).
|
||
import json
|
||
|
||
text = '<|python_tag|>brave_search.call(query="weather in Tokyo")'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "brave_search"
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"query": "weather in Tokyo"}
|
||
|
||
def test_llama3_python_tag_dot_call_multi_arg(self):
|
||
import json
|
||
|
||
text = "<|python_tag|>get_weather.call(" 'location="Tokyo", units="celsius", days=5)'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"location": "Tokyo", "units": "celsius", "days": 5}
|
||
|
||
def test_llama3_python_tag_json_form(self):
|
||
import json
|
||
|
||
text = '<|python_tag|>{"name":"web_search","parameters":{"query":"hi","n":5}}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"query": "hi", "n": 5}
|
||
|
||
def test_llama3_python_tag_json_form_with_eom(self):
|
||
# Llama-3 emits ``<|eom_id|>`` after the JSON; must not break parsing.
|
||
import json
|
||
|
||
text = '<|python_tag|>{"name":"python","parameters":{"code":"print(2+2)"}}<|eom_id|>'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"code": "print(2+2)"}
|
||
|
||
def test_llama3_strip_markup_final(self):
|
||
text = '<|python_tag|>brave_search.call(query="x")'
|
||
assert strip_tool_markup(text, final = True) == ""
|
||
|
||
def test_llama3_python_tag_json_form_non_scalar_args_skipped(self):
|
||
# Should NOT fabricate ``{"value": args}`` when the JSON form
|
||
# has a non-dict / non-string ``arguments`` value.
|
||
for bad in (
|
||
'<|python_tag|>{"name":"foo","arguments":42}',
|
||
'<|python_tag|>{"name":"foo","arguments":[1,2,3]}',
|
||
'<|python_tag|>{"name":"foo","arguments":null}',
|
||
'<|python_tag|>{"name":"foo","arguments":true}',
|
||
):
|
||
assert parse_tool_calls_from_text(bad) == [], bad
|
||
|
||
# ── Llama-3.2 bare JSON ``custom_tools`` ─────────────────────
|
||
|
||
def test_llama3_2_bare_json_parameters(self):
|
||
# Llama-3.2-Instruct emits bare JSON directly as content; no
|
||
# <|python_tag|> prefix per its training template.
|
||
import json
|
||
|
||
text = '{"name":"web_search","parameters":{"query":"Tokyo weather"}}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"query": "Tokyo weather"}
|
||
|
||
def test_llama3_2_bare_json_arguments_key(self):
|
||
import json
|
||
|
||
text = '{"name":"add","arguments":{"a":1,"b":2}}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"a": 1, "b": 2}
|
||
|
||
def test_llama3_2_bare_json_multi_call(self):
|
||
# Llama-3 may chain calls with ``; `` per training template.
|
||
text = '{"name":"a","parameters":{}}; {"name":"b","parameters":{}}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 2
|
||
assert result[0]["function"]["name"] == "a"
|
||
assert result[1]["function"]["name"] == "b"
|
||
|
||
def test_llama3_2_bare_json_with_eom_sentinel(self):
|
||
text = '{"name":"x","parameters":{"y":1}}<|eom_id|>'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "x"
|
||
|
||
def test_llama3_2_bare_json_leading_sentinel_skipped(self):
|
||
# Sometimes prior <|eot_id|> leaks into the next turn.
|
||
text = '<|eot_id|>{"name":"x","parameters":{}}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "x"
|
||
|
||
def test_llama3_2_bare_json_plain_prose_does_not_fire(self):
|
||
# Defensive: must NOT fire on plain assistant prose.
|
||
text = "Hello world, how are you today?"
|
||
assert parse_tool_calls_from_text(text) == []
|
||
|
||
def test_llama3_2_bare_json_embedded_in_prose_does_not_fire(self):
|
||
# Defensive: JSON embedded in prose must NOT fire (parser is
|
||
# strict about content STARTING with `{`).
|
||
text = 'The tool result was: {"name":"foo"}'
|
||
assert parse_tool_calls_from_text(text) == []
|
||
|
||
def test_llama3_2_bare_json_missing_name_does_not_fire(self):
|
||
text = '{"result":"ok","data":[1,2,3]}'
|
||
assert parse_tool_calls_from_text(text) == []
|
||
|
||
def test_llama3_2_bare_json_missing_args_does_not_fire(self):
|
||
text = '{"name":"x"}'
|
||
assert parse_tool_calls_from_text(text) == []
|
||
|
||
def test_llama3_2_bare_json_args_not_dict_does_not_fire(self):
|
||
text = '{"name":"x","parameters":42}'
|
||
assert parse_tool_calls_from_text(text) == []
|
||
|
||
def test_llama3_2_bare_json_string_parameters_does_not_fire(self):
|
||
# Llama-3 spec: parameters must be a dict. Prose like
|
||
# ``{"name":"foo","parameters":"a sentence"}`` must NOT trigger.
|
||
text = '{"name":"foo","parameters":"this is a sentence"}'
|
||
assert parse_tool_calls_from_text(text) == []
|
||
|
||
def test_llama3_2_bare_json_string_arguments_not_json_does_not_fire(self):
|
||
# OpenAI ``arguments`` may be a JSON-string of a dict, but a
|
||
# plain non-JSON string must not pass the guard.
|
||
text = '{"name":"foo","arguments":"not json"}'
|
||
assert parse_tool_calls_from_text(text) == []
|
||
|
||
def test_llama3_2_bare_json_string_arguments_json_dict_fires(self):
|
||
# OpenAI shape: arguments is a JSON-encoded string of a dict.
|
||
text = '{"name":"foo","arguments":"{\\"q\\":\\"x\\"}"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "foo"
|
||
# arguments stays as the original JSON-string.
|
||
assert result[0]["function"]["arguments"] == '{"q":"x"}'
|
||
|
||
def test_llama3_2_bare_json_string_arguments_json_non_dict_does_not_fire(self):
|
||
# JSON-string that parses to a list / scalar / null must NOT fire.
|
||
for bad in (
|
||
'{"name":"foo","arguments":"[1,2,3]"}',
|
||
'{"name":"foo","arguments":"\\"plain\\""}',
|
||
'{"name":"foo","arguments":"null"}',
|
||
'{"name":"foo","arguments":"42"}',
|
||
):
|
||
assert parse_tool_calls_from_text(bad) == [], bad
|
||
|
||
# Mistral pre-v11
|
||
|
||
def test_mistral_pre_v11_array(self):
|
||
import json
|
||
|
||
text = '[TOOL_CALLS] [{"name":"web_search","arguments":{"query":"hello"},"id":"abc"}]'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
# Mistral provides its own id; preserve it.
|
||
assert result[0]["id"] == "abc"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"query": "hello"}
|
||
|
||
def test_mistral_array_parameters_key_alias(self):
|
||
import json
|
||
|
||
# Array object keyed on ``parameters`` (not ``arguments``) must keep its
|
||
# payload, matching the JSON/XML paths and SGLang's base detector.
|
||
text = '[TOOL_CALLS] [{"name":"get_weather","parameters":{"city":"Paris"}}]'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "get_weather"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"city": "Paris"}
|
||
|
||
def test_mistral_pre_v11_array_multi(self):
|
||
text = (
|
||
'[TOOL_CALLS] [{"name":"a","arguments":{"x":1},"id":"id1"},'
|
||
'{"name":"b","arguments":{"y":2},"id":"id2"}]'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 2
|
||
assert result[0]["function"]["name"] == "a"
|
||
assert result[1]["function"]["name"] == "b"
|
||
|
||
def test_mistral_pre_v11_unclosed_array(self):
|
||
# Closing ``]`` truncated -- parser must heal off individual objects.
|
||
text = '[TOOL_CALLS] [{"name":"web_search","arguments":{"q":"x"},"id":"id"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
|
||
# Mistral v11+
|
||
|
||
def test_mistral_v11_single(self):
|
||
# Magistral / Mistral Small 3.1: bare ``name{json}`` after trigger.
|
||
import json
|
||
|
||
text = '[TOOL_CALLS]add{"a":3.5,"b":4}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "add"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"a": 3.5, "b": 4}
|
||
|
||
def test_mistral_v11_parallel(self):
|
||
# v11+ parallel: ``[TOOL_CALLS]a{...}[TOOL_CALLS]b{...}``.
|
||
text = '[TOOL_CALLS]add{"a":1}[TOOL_CALLS]sub{"b":2}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 2
|
||
assert result[0]["function"]["name"] == "add"
|
||
assert result[1]["function"]["name"] == "sub"
|
||
|
||
def test_mistral_v11_with_args_marker(self):
|
||
# Ministral / Mistral Large 3: ``[TOOL_CALLS]name[ARGS]{json}``.
|
||
import json
|
||
|
||
text = '[TOOL_CALLS]add[ARGS]{"a":1,"b":2}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "add"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"a": 1, "b": 2}
|
||
|
||
def test_mistral_strip_markup_v11(self):
|
||
text = '[TOOL_CALLS]add{"a":1}'
|
||
assert strip_tool_markup(text, final = True) == ""
|
||
|
||
def test_mistral_call_id_form(self):
|
||
# Mistral Small 3.2: ``[TOOL_CALLS]name[CALL_ID]<id>[ARGS]{json}``.
|
||
# The ``[CALL_ID]`` segment must be skipped, not treated as a stop
|
||
# (llama.cpp test-chat.cpp:4785 parses this to one call).
|
||
import json
|
||
|
||
text = '[TOOL_CALLS]special_function[CALL_ID]123456789[ARGS]{"arg1": 1}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "special_function"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"arg1": 1}
|
||
|
||
def test_mistral_call_id_form_parallel(self):
|
||
text = (
|
||
'[TOOL_CALLS]special_function[CALL_ID]000000001[ARGS]{"arg1": 1}'
|
||
"[TOOL_CALLS]special_function_with_opt[CALL_ID]000000002"
|
||
'[ARGS]{"arg1": 1, "arg2": 2}'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 2
|
||
assert result[0]["function"]["name"] == "special_function"
|
||
assert result[1]["function"]["name"] == "special_function_with_opt"
|
||
|
||
def test_mistral_call_id_form_stripped(self):
|
||
text = '[TOOL_CALLS]special_function[CALL_ID]123456789[ARGS]{"arg1": 1}'
|
||
assert strip_tool_markup(text, final = True) == ""
|
||
|
||
def test_mistral_think_reasoning_ignored(self):
|
||
# Magistral wraps reasoning in ``[THINK]...[/THINK]``. A ``[TOOL_CALLS]``
|
||
# inside the reasoning is chain-of-thought, not a real call; only the
|
||
# call after ``[/THINK]`` counts (llama.cpp test-chat.cpp:2285).
|
||
import json
|
||
|
||
text = (
|
||
'[THINK]Let me think about [TOOL_CALLS]fake[ARGS]{"x":1} '
|
||
'and more[/THINK][TOOL_CALLS]real_fn[ARGS]{"y":2}'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "real_fn"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"y": 2}
|
||
|
||
def test_mistral_think_reasoning_no_real_call(self):
|
||
# Reasoning that merely mentions a tool call but does not emit one
|
||
# after ``[/THINK]`` yields no calls.
|
||
text = '[THINK]I might call [TOOL_CALLS]fake[ARGS]{"x":1}[/THINK]Done.'
|
||
assert parse_tool_calls_from_text(text) == []
|
||
|
||
def test_mistral_think_literal_in_argument_preserved(self):
|
||
# A literal ``[THINK]`` inside a real tool argument (after the call)
|
||
# must not be stripped or corrupt the parse.
|
||
import json
|
||
|
||
text = '[TOOL_CALLS]search[ARGS]{"q":"explain the [THINK] token"}'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"q": "explain the [THINK] token"}
|
||
|
||
# Gemma 4
|
||
|
||
def test_gemma4_simple_call(self):
|
||
import json
|
||
|
||
text = (
|
||
"<|tool_call>call:get_weather{"
|
||
'location:<|"|>Tokyo<|"|>,units:<|"|>celsius<|"|>}<tool_call|>'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "get_weather"
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"location": "Tokyo", "units": "celsius"}
|
||
|
||
def test_gemma4_with_primitives(self):
|
||
import json
|
||
|
||
text = (
|
||
"<|tool_call>call:set_pref{"
|
||
"enabled:true,attempts:5,threshold:1.5,nickname:null}<tool_call|>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"enabled": True, "attempts": 5, "threshold": 1.5, "nickname": None}
|
||
|
||
def test_gemma4_nested_args(self):
|
||
# Gemma 4 nests dicts / lists with bare keys and ``<|"|>`` strings.
|
||
import json
|
||
|
||
text = (
|
||
"<|tool_call>call:search{"
|
||
'query:<|"|>foo<|"|>,filters:{site:<|"|>example.com<|"|>,recent:true},'
|
||
'tags:[<|"|>a<|"|>,<|"|>b<|"|>]}<tool_call|>'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args["query"] == "foo"
|
||
assert args["filters"] == {"site": "example.com", "recent": True}
|
||
assert args["tags"] == ["a", "b"]
|
||
|
||
def test_gemma4_multi_call(self):
|
||
text = "<|tool_call>call:a{x:1}<tool_call|><|tool_call>call:b{y:2}<tool_call|>"
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 2
|
||
assert result[0]["function"]["name"] == "a"
|
||
assert result[1]["function"]["name"] == "b"
|
||
|
||
def test_gemma4_unclosed_does_not_raise(self):
|
||
# Truncated mid-stream; must not raise.
|
||
text = '<|tool_call>call:foo{x:<|"|>bar<|"|>'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert isinstance(result, list)
|
||
|
||
def test_gemma4_strip_markup_final(self):
|
||
text = "<|tool_call>call:foo{x:1}<tool_call|>"
|
||
assert strip_tool_markup(text, final = True) == ""
|
||
|
||
# ── Gemma 4 wrapper-less (skip_special_tokens stripped) ───────────
|
||
|
||
def test_gemma4_bare_stripped_call(self):
|
||
# skip_special_tokens removes <|tool_call>/<tool_call|> and <|"|>,
|
||
# leaving a bare call:NAME{...} with an unquoted value.
|
||
import json
|
||
|
||
text = "call:web_search{query:weather in San Francisco right now}"
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"query": "weather in San Francisco right now"}
|
||
|
||
def test_gemma4_bare_code_with_commas(self):
|
||
# A code value with commas must not truncate at the first comma.
|
||
import json
|
||
|
||
text = (
|
||
"call:python{code:def f(n):\n a, b = 0, 1\n"
|
||
" for _ in range(2, n+1):\n a, b = b, a + b\n"
|
||
" return b\n\nprint(f(30))}"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert result[0]["function"]["name"] == "python"
|
||
code = json.loads(result[0]["function"]["arguments"])["code"]
|
||
assert "a, b = 0, 1" in code and "print(f(30))" in code
|
||
|
||
def test_gemma4_bare_quotes_normalized(self):
|
||
# The same value quoted vs unquoted must parse identically so the
|
||
# agentic loop can collapse a looping model's repeated calls.
|
||
import json
|
||
|
||
a = parse_tool_calls_from_text('call:web_search{query:"foo bar"}')
|
||
b = parse_tool_calls_from_text("call:web_search{query:foo bar}")
|
||
assert json.loads(a[0]["function"]["arguments"]) == {"query": "foo bar"}
|
||
assert json.loads(a[0]["function"]["arguments"]) == json.loads(
|
||
b[0]["function"]["arguments"]
|
||
)
|
||
|
||
def test_gemma4_bare_multi_arg(self):
|
||
import json
|
||
|
||
text = "call:web_search{query:pytorch latest, url:https://pytorch.org}"
|
||
result = parse_tool_calls_from_text(text)
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"query": "pytorch latest", "url": "https://pytorch.org"}
|
||
|
||
def test_gemma4_bare_not_matched_in_prose(self):
|
||
# A word ending in "call:" must not trigger a bare tool call.
|
||
text = "I will recall:that the function{ } is helpful."
|
||
result = parse_tool_calls_from_text(text)
|
||
assert result == []
|
||
|
||
def test_gemma4_bare_strip_markup_final(self):
|
||
text = "Here you go: call:web_search{query:weather today}"
|
||
assert "call:web_search" not in strip_tool_markup(text, final = True)
|
||
|
||
# ── Cross-format sentinels ────────────────────────────────────
|
||
|
||
def test_all_markers_in_tool_xml_signals(self):
|
||
# Streaming buffer wakes up on every emission marker.
|
||
from core.inference.tool_call_parser import TOOL_XML_SIGNALS
|
||
for marker in (
|
||
"<tool_call>",
|
||
"<function=",
|
||
"<|python_tag|>",
|
||
"[TOOL_CALLS]",
|
||
"<|tool_call>",
|
||
):
|
||
assert marker in TOOL_XML_SIGNALS, f"streaming loop would not wake on {marker!r}"
|
||
|
||
def test_has_tool_signal_for_all_formats(self):
|
||
assert has_tool_signal('<|python_tag|>brave_search.call(q="x")')
|
||
assert has_tool_signal('[TOOL_CALLS] [{"name":"x"}]')
|
||
assert has_tool_signal('[TOOL_CALLS]add{"a":1}')
|
||
assert has_tool_signal("<|tool_call>call:foo{}<tool_call|>")
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────────
|
||
# run_safetensors_tool_loop
|
||
# ────────────────────────────────────────────────────────────────────
|
||
|
||
|
||
def _fake_stream(chunks):
|
||
"""Build a single-turn generator that yields cumulative snapshots."""
|
||
|
||
def _gen(_messages):
|
||
acc = ""
|
||
for c in chunks:
|
||
acc += c
|
||
yield acc
|
||
|
||
return _gen
|
||
|
||
|
||
def _const_stream(text):
|
||
"""A single-turn generator that yields one cumulative snapshot."""
|
||
|
||
def _gen(_messages):
|
||
yield text
|
||
|
||
return _gen
|
||
|
||
|
||
class FakeExecuteTool:
|
||
"""Stand-in for ``core.inference.tools.execute_tool``."""
|
||
|
||
def __init__(self, results):
|
||
# ``results`` is a list of strings or RuntimeError instances.
|
||
self.results = list(results)
|
||
self.calls: list[tuple[str, dict]] = []
|
||
|
||
def __call__(
|
||
self,
|
||
name,
|
||
arguments,
|
||
*,
|
||
cancel_event = None,
|
||
timeout = None,
|
||
session_id = None,
|
||
rag_scope = None,
|
||
disable_sandbox = False,
|
||
):
|
||
self.calls.append((name, arguments))
|
||
result = self.results.pop(0) if self.results else "OK"
|
||
if isinstance(result, Exception):
|
||
raise result
|
||
return result
|
||
|
||
|
||
def _collect_events(generator, max_events = 200):
|
||
events = []
|
||
for ev in generator:
|
||
events.append(ev)
|
||
if len(events) >= max_events:
|
||
break
|
||
return events
|
||
|
||
|
||
def _make_loop(
|
||
*,
|
||
turns,
|
||
exec_results = None,
|
||
**kwargs,
|
||
):
|
||
"""Build a configured loop with a multi-turn fake generator.
|
||
|
||
``turns`` is a list of chunk-lists; iteration N yields chunks from ``turns[N]``.
|
||
"""
|
||
turn_iter = iter(turns)
|
||
|
||
def _gen(_messages):
|
||
try:
|
||
chunks = next(turn_iter)
|
||
except StopIteration:
|
||
return
|
||
acc = ""
|
||
for c in chunks:
|
||
acc += c
|
||
yield acc
|
||
|
||
exec_fn = FakeExecuteTool(exec_results or [])
|
||
return run_safetensors_tool_loop(
|
||
single_turn = _gen,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [
|
||
{"type": "function", "function": {"name": "web_search"}},
|
||
{"type": "function", "function": {"name": "python"}},
|
||
{"type": "function", "function": {"name": "terminal"}},
|
||
],
|
||
execute_tool = exec_fn,
|
||
**kwargs,
|
||
), exec_fn
|
||
|
||
|
||
class TestParserDeepSeek:
|
||
"""DeepSeek R1 / V3 / V3.1 coverage. Markers use full-width pipes
|
||
(U+FF5C) and lower-one-eighth-block (U+2581). R1 wraps args in a
|
||
Markdown ``` ```json ``` ``` fence; V3 / V3.1 emit bare JSON."""
|
||
|
||
def test_r1_simple_call_with_code_fence(self):
|
||
import json as _json
|
||
|
||
text = (
|
||
"<｜tool▁calls▁begin｜>"
|
||
"<｜tool▁call▁begin｜>function"
|
||
"<｜tool▁sep｜>special_function\n"
|
||
"```json\n"
|
||
'{"arg1": 1}\n'
|
||
"```"
|
||
"<｜tool▁call▁end｜>"
|
||
"<｜tool▁calls▁end｜>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "special_function"
|
||
assert _json.loads(result[0]["function"]["arguments"]) == {"arg1": 1}
|
||
|
||
def test_r1_short_form_outer_marker(self):
|
||
# llama.cpp accepts ``<｜tool▁calls｜>`` as the short-form opener.
|
||
import json as _json
|
||
|
||
text = (
|
||
"<｜tool▁calls｜>function"
|
||
"<｜tool▁sep｜>get_time\n"
|
||
"```json\n"
|
||
'{"city": "Paris"}\n'
|
||
"```"
|
||
"<｜tool▁call▁end｜>"
|
||
"<｜tool▁calls▁end｜>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "get_time"
|
||
|
||
def test_v3_1_bare_json(self):
|
||
# V3 / V3.1 omit the ``function`` prefix and the code fence.
|
||
import json as _json
|
||
|
||
text = (
|
||
"<｜tool▁calls▁begin｜>"
|
||
"<｜tool▁call▁begin｜>get_time"
|
||
"<｜tool▁sep｜>"
|
||
'{"city": "Tokyo"}'
|
||
"<｜tool▁call▁end｜>"
|
||
"<｜tool▁calls▁end｜>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "get_time"
|
||
assert _json.loads(result[0]["function"]["arguments"]) == {"city": "Tokyo"}
|
||
|
||
def test_v3_1_multi_call_shares_envelope(self):
|
||
# Parallel calls share one outer envelope; each inner call has
|
||
# its own ``<｜tool▁call▁begin｜>...<｜tool▁call▁end｜>``.
|
||
text = (
|
||
"<｜tool▁calls▁begin｜>"
|
||
"<｜tool▁call▁begin｜>get_time"
|
||
"<｜tool▁sep｜>"
|
||
'{"city": "Paris"}'
|
||
"<｜tool▁call▁end｜>"
|
||
"<｜tool▁call▁begin｜>get_weather"
|
||
"<｜tool▁sep｜>"
|
||
'{"city": "Paris"}'
|
||
"<｜tool▁call▁end｜>"
|
||
"<｜tool▁calls▁end｜>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 2
|
||
assert result[0]["function"]["name"] == "get_time"
|
||
assert result[1]["function"]["name"] == "get_weather"
|
||
|
||
def test_v3_1_with_reasoning(self):
|
||
# Reasoning <think>...</think> precedes the tool block.
|
||
text = (
|
||
"<think>I'm thinking</think>\n"
|
||
"<｜tool▁calls▁begin｜>"
|
||
"<｜tool▁call▁begin｜>get_time"
|
||
"<｜tool▁sep｜>"
|
||
'{"city": "Tokyo"}'
|
||
"<｜tool▁call▁end｜>"
|
||
"<｜tool▁calls▁end｜>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "get_time"
|
||
|
||
def test_v3_1_strict_rejects_unclosed_envelope(self):
|
||
# Envelope truncated mid-stream (no <｜tool▁calls▁end｜>): healed by
|
||
# default, rejected with Auto-Heal off.
|
||
text = (
|
||
"<｜tool▁calls▁begin｜>"
|
||
"<｜tool▁call▁begin｜>get_time"
|
||
"<｜tool▁sep｜>"
|
||
'{"city": "Tokyo"}'
|
||
)
|
||
assert len(parse_tool_calls_from_text(text)) == 1
|
||
assert parse_tool_calls_from_text(text, allow_incomplete = False) == []
|
||
|
||
def test_v3_1_multi_call_recovers_when_first_end_marker_missing(self):
|
||
# First inner call omits its <｜tool▁call▁end｜>; the second must still be parsed.
|
||
text = (
|
||
"<｜tool▁calls▁begin｜>"
|
||
"<｜tool▁call▁begin｜>get_time"
|
||
"<｜tool▁sep｜>"
|
||
'{"city": "Paris"}'
|
||
"<｜tool▁call▁begin｜>get_weather"
|
||
"<｜tool▁sep｜>"
|
||
'{"city": "Paris"}'
|
||
"<｜tool▁call▁end｜>"
|
||
"<｜tool▁calls▁end｜>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert [c["function"]["name"] for c in result] == ["get_time", "get_weather"]
|
||
|
||
def test_v3_1_strict_recovers_after_missing_call_end(self):
|
||
# Strict mode (Auto-Heal off): the FIRST inner call is missing its <｜tool▁call▁end｜>
|
||
# terminator, so it is skipped -- but the parser must keep scanning and still return the ...
|
||
text = (
|
||
"<｜tool▁calls▁begin｜>"
|
||
"<｜tool▁call▁begin｜>get_weather"
|
||
"<｜tool▁sep｜>"
|
||
'{"city": "SF"}'
|
||
"<｜tool▁call▁begin｜>get_time"
|
||
"<｜tool▁sep｜>"
|
||
'{"tz": "PST"}'
|
||
"<｜tool▁call▁end｜>"
|
||
"<｜tool▁calls▁end｜>"
|
||
)
|
||
# Auto-Heal keeps both; strict skips the truncated first, keeps the second.
|
||
assert [c["function"]["name"] for c in parse_tool_calls_from_text(text)] == [
|
||
"get_weather",
|
||
"get_time",
|
||
]
|
||
strict = parse_tool_calls_from_text(text, allow_incomplete = False)
|
||
assert [c["function"]["name"] for c in strict] == ["get_time"]
|
||
|
||
def test_r1_strict_recovers_after_missing_close_fence(self):
|
||
# R1 form.
|
||
text = (
|
||
"<｜tool▁calls▁begin｜>"
|
||
"function<｜tool▁sep｜>get_weather\n```json\n"
|
||
'{"city": "SF"}'
|
||
"function<｜tool▁sep｜>get_time\n```json\n"
|
||
'{"tz": "PST"}'
|
||
"\n```<｜tool▁call▁end｜>"
|
||
"<｜tool▁calls▁end｜>"
|
||
)
|
||
strict = parse_tool_calls_from_text(text, allow_incomplete = False)
|
||
assert [c["function"]["name"] for c in strict] == ["get_time"]
|
||
|
||
def test_deepseek_strip_markup(self):
|
||
text = (
|
||
"before "
|
||
"<｜tool▁calls▁begin｜>"
|
||
"<｜tool▁call▁begin｜>foo"
|
||
"<｜tool▁sep｜>"
|
||
"{}"
|
||
"<｜tool▁call▁end｜>"
|
||
"<｜tool▁calls▁end｜>"
|
||
" after"
|
||
)
|
||
assert strip_tool_markup(text, final = True) == "before after"
|
||
|
||
def test_deepseek_signal_wakes_streaming(self):
|
||
# The streaming buffer state machine must wake on the DeepSeek opener so the rest of the
|
||
# section is drained instead of leaked.
|
||
text = "<｜tool▁calls▁begin｜>..."
|
||
assert has_tool_signal(text)
|
||
|
||
def test_deepseek_short_opener_is_stripped(self):
|
||
# The short ``<｜tool▁calls｜>`` opener is parsed, so its markup must also be stripped (the
|
||
# strip patterns used to require ...calls_begin and left the short-opener markup leaking to ...
|
||
text = (
|
||
"before "
|
||
"<｜tool▁calls｜>"
|
||
"<｜tool▁call▁begin｜>foo"
|
||
"<｜tool▁sep｜>"
|
||
"{}"
|
||
"<｜tool▁call▁end｜>"
|
||
"<｜tool▁calls▁end｜>"
|
||
" after"
|
||
)
|
||
assert strip_tool_markup(text, final = True) == "before after"
|
||
|
||
|
||
class TestParserGLM:
|
||
"""GLM 4.5 / 4.6 / 4.7 coverage. Marker collides with Qwen's
|
||
``<tool_call>`` but the body shape is XML kv pairs instead of JSON,
|
||
so the dispatch order keeps both formats working."""
|
||
|
||
def test_glm_simple_call(self):
|
||
import json as _json
|
||
|
||
text = (
|
||
"<tool_call>web_search\n"
|
||
"<arg_key>query</arg_key>\n"
|
||
"<arg_value>weather Tokyo</arg_value>\n"
|
||
"</tool_call>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
args = _json.loads(result[0]["function"]["arguments"])
|
||
# Strings come through raw; the parser does not double-quote.
|
||
assert args == {"query": "weather Tokyo"}
|
||
|
||
def test_glm_mixed_types_decode_correctly(self):
|
||
# Per the chat_template.jinja, strings are emitted raw and non-strings are JSON-encoded.
|
||
import json as _json
|
||
|
||
text = (
|
||
"<tool_call>complex_function\n"
|
||
"<arg_key>name</arg_key>\n<arg_value>John Doe</arg_value>\n"
|
||
"<arg_key>age</arg_key>\n<arg_value>30</arg_value>\n"
|
||
"<arg_key>active</arg_key>\n<arg_value>true</arg_value>\n"
|
||
"<arg_key>score</arg_key>\n<arg_value>95.5</arg_value>\n"
|
||
"</tool_call>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
args = _json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"name": "John Doe", "age": 30, "active": True, "score": 95.5}
|
||
|
||
def test_glm_multi_call_back_to_back(self):
|
||
# GLM emits parallel calls as consecutive ``<tool_call>...
|
||
# </tool_call>`` blocks with no outer envelope.
|
||
text = (
|
||
"<tool_call>a\n<arg_key>x</arg_key>\n<arg_value>1</arg_value>\n</tool_call>"
|
||
"<tool_call>b\n<arg_key>y</arg_key>\n<arg_value>2</arg_value>\n</tool_call>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 2
|
||
assert result[0]["function"]["name"] == "a"
|
||
assert result[1]["function"]["name"] == "b"
|
||
|
||
def test_glm_unclosed_tool_call_does_not_lose_value(self):
|
||
# Truncated mid-stream (no </tool_call>) -- the parser must
|
||
# still surface what it found rather than dropping the call.
|
||
text = "<tool_call>web_search\n<arg_key>query</arg_key>\n<arg_value>partial</arg_value>"
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
|
||
def test_glm_does_not_break_qwen_path(self):
|
||
# Real Qwen emission must still be parsed by the Qwen branch,
|
||
# not silently misrouted to GLM (the marker is shared).
|
||
text = '<tool_call>{"name":"web_search","arguments":{"q":"x"}}</tool_call>'
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
|
||
def test_glm_strip_markup(self):
|
||
text = (
|
||
"before "
|
||
"<tool_call>a\n<arg_key>x</arg_key>\n<arg_value>1</arg_value>\n</tool_call>"
|
||
" after"
|
||
)
|
||
assert strip_tool_markup(text, final = True) == "before after"
|
||
|
||
def test_glm_zero_arg_inline_call(self):
|
||
# GLM 4.7 emits a no-argument call inline as ``<tool_call>name</tool_call>`` (name followed
|
||
# straight by the close tag, no \n / <arg_key>).
|
||
import json as _json
|
||
|
||
text = "<tool_call>get_current_date</tool_call>"
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "get_current_date"
|
||
assert _json.loads(result[0]["function"]["arguments"]) == {}
|
||
|
||
def test_glm_zero_arg_call_in_parallel_batch(self):
|
||
# A no-arg call alongside a normal one must not make either vanish.
|
||
text = (
|
||
"<tool_call>get_current_date</tool_call>"
|
||
"<tool_call>get_weather\n<arg_key>city</arg_key>\n"
|
||
"<arg_value>Tokyo</arg_value></tool_call>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 2
|
||
assert result[0]["function"]["name"] == "get_current_date"
|
||
assert result[1]["function"]["name"] == "get_weather"
|
||
|
||
def test_glm_string_value_whitespace_preserved(self):
|
||
# The template emits string args verbatim, so significant leading / trailing whitespace
|
||
# (code, diffs) must survive.
|
||
import json as _json
|
||
|
||
text = (
|
||
"<tool_call>run\n<arg_key>code</arg_key>\n"
|
||
"<arg_value> indented code </arg_value></tool_call>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
args = _json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"code": " indented code "}
|
||
|
||
|
||
class TestParserKimi:
|
||
"""Kimi K2 / Moonshot coverage. ASCII pipes only (NOT full-width).
|
||
Name arrives as ``functions.NAME:IDX``; the parser strips the
|
||
prefix and the index to recover the bare callable name while
|
||
preserving the full id for round-trip rendering."""
|
||
|
||
def test_kimi_simple_call(self):
|
||
import json as _json
|
||
|
||
text = (
|
||
"<|tool_calls_section_begin|>"
|
||
"<|tool_call_begin|>functions.special_function:0"
|
||
"<|tool_call_argument_begin|>"
|
||
'{"arg1": 1}'
|
||
"<|tool_call_end|>"
|
||
"<|tool_calls_section_end|>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
# Bare name recovered; full id preserved verbatim.
|
||
assert result[0]["function"]["name"] == "special_function"
|
||
assert result[0]["id"] == "functions.special_function:0"
|
||
assert _json.loads(result[0]["function"]["arguments"]) == {"arg1": 1}
|
||
|
||
def test_outer_tool_call_with_embedded_kimi_marker_parses_outer(self):
|
||
# A Qwen/Hermes <tool_call> whose argument contains literal Kimi markup (a user asking
|
||
# about that syntax) must execute the OUTER call, not the embedded marker via the ...
|
||
text = (
|
||
'<tool_call>{"name":"web_search","arguments":{"query":'
|
||
'"explain <|tool_call_begin|>functions.evil:0'
|
||
'<|tool_call_argument_begin|>{}<|tool_call_end|>"}}'
|
||
"</tool_call>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
|
||
def test_genuine_kimi_call_without_envelope_still_parses(self):
|
||
# Control: a real Kimi call with no leading <tool_call> envelope must
|
||
# still go through the pre-pass.
|
||
text = (
|
||
"<|tool_calls_section_begin|>"
|
||
"<|tool_call_begin|>functions.web_search:0"
|
||
'<|tool_call_argument_begin|>{"query":"x"}<|tool_call_end|>'
|
||
"<|tool_calls_section_end|>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "web_search"
|
||
|
||
def test_kimi_multi_call_with_index(self):
|
||
# Multiple consecutive calls inside a single section, each
|
||
# with its own monotonically incrementing ``:IDX``.
|
||
text = (
|
||
"<|tool_calls_section_begin|>"
|
||
"<|tool_call_begin|>functions.read_file:0"
|
||
"<|tool_call_argument_begin|>"
|
||
'{"path":"a"}'
|
||
"<|tool_call_end|>"
|
||
"<|tool_call_begin|>functions.web_search:1"
|
||
"<|tool_call_argument_begin|>"
|
||
'{"query":"x"}'
|
||
"<|tool_call_end|>"
|
||
"<|tool_calls_section_end|>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 2
|
||
assert result[0]["function"]["name"] == "read_file"
|
||
assert result[0]["id"].endswith(":0")
|
||
assert result[1]["function"]["name"] == "web_search"
|
||
assert result[1]["id"].endswith(":1")
|
||
|
||
def test_kimi_dotted_name_keeps_full_dotted_name(self):
|
||
# A dotted Kimi id keeps its FULL name after stripping only the ``functions.`` prefix and
|
||
# ``:idx`` suffix -- matching current vLLM ...
|
||
text = (
|
||
"<|tool_calls_section_begin|>"
|
||
"<|tool_call_begin|>a.b.c:2"
|
||
"<|tool_call_argument_begin|>"
|
||
"{}"
|
||
"<|tool_call_end|>"
|
||
"<|tool_calls_section_end|>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "a.b.c"
|
||
|
||
def test_kimi_dotted_mcp_name_with_functions_prefix(self):
|
||
# ``functions.mcp.server-list:0`` must resolve to ``mcp.server-list``
|
||
# (only the ``functions.`` prefix and ``:idx`` are removed).
|
||
text = (
|
||
"<|tool_calls_section_begin|>"
|
||
"<|tool_call_begin|>functions.mcp.server-list:0"
|
||
"<|tool_call_argument_begin|>"
|
||
"{}"
|
||
"<|tool_call_end|>"
|
||
"<|tool_calls_section_end|>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "mcp.server-list"
|
||
|
||
def test_kimi_multi_call_recovers_when_first_end_marker_missing(self):
|
||
# First call omits its <|tool_call_end|>; the second must still parse.
|
||
text = (
|
||
"<|tool_calls_section_begin|>"
|
||
"<|tool_call_begin|>functions.read_file:0"
|
||
"<|tool_call_argument_begin|>"
|
||
'{"path":"a"}'
|
||
"<|tool_call_begin|>functions.web_search:1"
|
||
"<|tool_call_argument_begin|>"
|
||
'{"query":"x"}'
|
||
"<|tool_call_end|>"
|
||
"<|tool_calls_section_end|>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert [c["function"]["name"] for c in result] == ["read_file", "web_search"]
|
||
|
||
def test_kimi_handles_unclosed_section(self):
|
||
# End marker missing -- the parser must still extract the call.
|
||
text = (
|
||
"<|tool_calls_section_begin|>"
|
||
"<|tool_call_begin|>functions.foo:0"
|
||
"<|tool_call_argument_begin|>"
|
||
'{"a":1}'
|
||
"<|tool_call_end|>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "foo"
|
||
|
||
def test_kimi_strip_markup(self):
|
||
text = (
|
||
"before "
|
||
"<|tool_calls_section_begin|>"
|
||
"<|tool_call_begin|>functions.x:0"
|
||
"<|tool_call_argument_begin|>"
|
||
"{}"
|
||
"<|tool_call_end|>"
|
||
"<|tool_calls_section_end|>"
|
||
" after"
|
||
)
|
||
assert strip_tool_markup(text, final = True) == "before after"
|
||
|
||
def test_kimi_signal_wakes_streaming(self):
|
||
text = "<|tool_calls_section_begin|>..."
|
||
assert has_tool_signal(text)
|
||
|
||
def test_kimi_call_without_section_wrapper(self):
|
||
# llama.cpp makes the ``<|tool_calls_section_begin|>`` wrapper optional -- Kimi K2 can emit
|
||
# a bare ``<|tool_call_begin|>`` call.
|
||
import json as _json
|
||
|
||
text = (
|
||
"<|tool_call_begin|>functions.execute_command:0"
|
||
"<|tool_call_argument_begin|>"
|
||
'{"cmd":"ls"}'
|
||
"<|tool_call_end|>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "execute_command"
|
||
assert _json.loads(result[0]["function"]["arguments"]) == {"cmd": "ls"}
|
||
|
||
def test_kimi_malformed_json_recovers_later_calls(self):
|
||
# A call with malformed / truncated JSON must not drop the valid calls that follow it in
|
||
# the same section (the bad call is skipped, the good one is recovered).
|
||
import json as _json
|
||
|
||
text = (
|
||
"<|tool_calls_section_begin|>"
|
||
"<|tool_call_begin|>functions.a:0"
|
||
'<|tool_call_argument_begin|>{"city":"Beijing"' # missing closing brace
|
||
"<|tool_call_end|>"
|
||
"<|tool_call_begin|>functions.b:1"
|
||
'<|tool_call_argument_begin|>{"city":"Shanghai"}'
|
||
"<|tool_call_end|>"
|
||
"<|tool_calls_section_end|>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "b"
|
||
assert _json.loads(result[0]["function"]["arguments"]) == {"city": "Shanghai"}
|
||
|
||
|
||
class TestParserCrossFormatRouting:
|
||
"""Ensure the per-format dispatch order doesn't misroute any
|
||
family. Real emissions for each new family + every old family
|
||
must still parse correctly when intermixed."""
|
||
|
||
def test_dispatch_routes_each_family_correctly(self):
|
||
cases = [
|
||
(
|
||
"Qwen",
|
||
'<tool_call>{"name":"a","arguments":{"x":1}}</tool_call>',
|
||
"a",
|
||
),
|
||
(
|
||
"DeepSeek V3.1",
|
||
"<｜tool▁calls▁begin｜>"
|
||
"<｜tool▁call▁begin｜>get_time"
|
||
"<｜tool▁sep｜>"
|
||
'{"city":"Tokyo"}'
|
||
"<｜tool▁call▁end｜>"
|
||
"<｜tool▁calls▁end｜>",
|
||
"get_time",
|
||
),
|
||
(
|
||
"GLM",
|
||
"<tool_call>web_search\n"
|
||
"<arg_key>q</arg_key>\n<arg_value>x</arg_value>\n"
|
||
"</tool_call>",
|
||
"web_search",
|
||
),
|
||
(
|
||
"Kimi",
|
||
"<|tool_calls_section_begin|>"
|
||
"<|tool_call_begin|>functions.add:0"
|
||
"<|tool_call_argument_begin|>"
|
||
'{"a":1}'
|
||
"<|tool_call_end|>"
|
||
"<|tool_calls_section_end|>",
|
||
"add",
|
||
),
|
||
]
|
||
for label, text, expected_name in cases:
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1, f"{label}: parser missed the call"
|
||
assert result[0]["function"]["name"] == expected_name, (
|
||
f"{label}: got {result[0]['function']['name']!r}, " f"expected {expected_name!r}"
|
||
)
|
||
|
||
def test_all_new_markers_in_tool_xml_signals(self):
|
||
# The safetensors / MLX streaming buffer must wake on every supported emission marker --
|
||
# otherwise the BUFFERING state leaks tool content to the user before parse.
|
||
from core.inference.tool_call_parser import TOOL_XML_SIGNALS
|
||
for marker in (
|
||
"<｜tool▁calls▁begin｜>",
|
||
"<｜tool▁call▁begin｜>",
|
||
"<|tool_calls_section_begin|>",
|
||
"<|tool_call_begin|>",
|
||
):
|
||
assert marker in TOOL_XML_SIGNALS, f"streaming loop would not wake on {marker!r}"
|
||
|
||
|
||
def test_active_tools_are_passed_to_single_turn_after_render_html_success():
|
||
captured_tool_names: list[list[str]] = []
|
||
exec_fn = FakeExecuteTool(["Rendered HTML canvas."])
|
||
|
||
def fake_single_turn(_messages, *, active_tools = None):
|
||
captured_tool_names.append(
|
||
[
|
||
(tool.get("function") or {}).get("name")
|
||
for tool in (active_tools or [])
|
||
if (tool.get("function") or {}).get("name")
|
||
]
|
||
)
|
||
if len(captured_tool_names) == 1:
|
||
yield '<tool_call>{"name":"render_html","arguments":{"code":"<html>one</html>"}}</tool_call>'
|
||
else:
|
||
yield "Done."
|
||
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = fake_single_turn,
|
||
messages = [{"role": "user", "content": "make html"}],
|
||
tools = [
|
||
{"type": "function", "function": {"name": "render_html"}},
|
||
{"type": "function", "function": {"name": "web_search"}},
|
||
],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 3,
|
||
)
|
||
)
|
||
|
||
assert exec_fn.calls == [("render_html", {"code": "<html>one</html>"})]
|
||
assert captured_tool_names == [["render_html", "web_search"], ["web_search"]]
|
||
assert any(event.get("type") == "content" and event.get("text") == "Done." for event in events)
|
||
|
||
|
||
def test_spent_one_shot_rehearsal_repeat_is_detected_not_blank_continuation():
|
||
# A spent one-shot (render_html) stays in the ORIGINAL tool list; detection is gated on
|
||
# that list (matching the strip gate) so a re-emitted repeat is drained and routed to the
|
||
# repeat no-op instead of stripped into a blank continuation.
|
||
exec_fn = FakeExecuteTool(["Rendered HTML canvas."])
|
||
turns = iter(
|
||
[
|
||
[
|
||
'<tool_call>{"name":"render_html","arguments":{"code":"<html>one</html>"}}</tool_call>'
|
||
],
|
||
['render_html[ARGS]{"code":"<html>two</html>"}'], # spent one-shot rehearsal
|
||
["The chart is above."],
|
||
]
|
||
)
|
||
|
||
def gen(_messages, *, active_tools = None):
|
||
try:
|
||
chunks = next(turns)
|
||
except StopIteration:
|
||
return
|
||
acc = ""
|
||
for c in chunks:
|
||
acc += c
|
||
yield acc
|
||
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = gen,
|
||
messages = [{"role": "user", "content": "make a chart"}],
|
||
tools = [
|
||
{"type": "function", "function": {"name": "render_html"}},
|
||
{"type": "function", "function": {"name": "web_search"}},
|
||
],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 5,
|
||
)
|
||
)
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
# render_html ran exactly once; the repeat was a no-op, not a second execution.
|
||
assert exec_fn.calls == [("render_html", {"code": "<html>one</html>"})], exec_fn.calls
|
||
# The loop continued past the repeat to the real answer (not a blank continuation).
|
||
assert any("The chart is above." in t for t in contents), contents
|
||
# The raw rehearsal markup never leaked as visible content.
|
||
assert not any("render_html[ARGS]" in t for t in contents), contents
|
||
|
||
|
||
def test_rehearsal_call_name_is_not_streamed_before_args():
|
||
# A rehearsal whose name and [ARGS] arrive together must drain, not stream the bare name.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [['web_search[ARGS]{"query":"cats"}'], ["Found."]],
|
||
exec_results = ["RESULT"],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "cats"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any("web_search" in t for t in contents), contents
|
||
|
||
|
||
def test_rehearsal_call_name_split_before_args_is_not_streamed():
|
||
# Finding 5: name and [ARGS] in separate chunks -- the bare name is held until [ARGS] arrives.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [["web_search", '[ARGS]{"query":"cats"}'], ["Found."]],
|
||
exec_results = ["RESULT"],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "cats"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any("web_search" in t for t in contents), contents
|
||
|
||
|
||
def test_plain_word_matching_no_tool_still_streams():
|
||
# The prefix guard must not swallow prose: a non-tool bare word streams.
|
||
loop, _exec = _make_loop(
|
||
turns = [["weather", " is nice today."]],
|
||
max_tool_iterations = 1,
|
||
)
|
||
events = _collect_events(loop)
|
||
contents = "".join(e["text"] for e in events if e["type"] == "content")
|
||
assert "weather is nice today." in contents, contents
|
||
|
||
|
||
def test_rehearsal_name_after_prose_in_streaming_is_not_streamed():
|
||
# After prose has streamed (STREAMING state), a split rehearsal name must still be held.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
# _make_loop accumulates these deltas into cumulative snapshots.
|
||
["Let me think. ", "I will search ", "web_search", '[ARGS]{"query":"cats"}'],
|
||
["Found."],
|
||
],
|
||
exec_results = ["RESULT"],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "cats"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any("web_search" in t for t in contents), contents
|
||
|
||
|
||
def test_rehearsal_name_after_prose_same_chunk_in_streaming_is_not_streamed():
|
||
# Prose then ``web_search[ARGS]{...}`` in one chunk: the boundary is pulled back over the name.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
["Sure. ", 'now web_search[ARGS]{"query":"cats"}'],
|
||
["Found."],
|
||
],
|
||
exec_results = ["RESULT"],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "cats"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any("web_search" in t for t in contents), contents
|
||
|
||
|
||
def test_initial_buffer_flush_holds_split_rehearsal_name():
|
||
# First flush out of BUFFERING applies the same trailing-name hold as STREAMING.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [["I will use python", '[ARGS]{"code":"print(1)"}'], ["done"]],
|
||
exec_results = ["RESULT"],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("python", {"code": "print(1)"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any("python" in t for t in contents), contents
|
||
|
||
|
||
def test_think_rehearsal_streams_monotonically_and_keeps_reasoning():
|
||
# A think rehearsal streams the same text the final strip keeps: cumulative content is
|
||
# monotonically non-decreasing and ends with the markup intact.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [["<think>plan ", 'search[ARGS]{"q":"x"}', "</think> visible"]],
|
||
max_tool_iterations = 1,
|
||
)
|
||
events = _collect_events(loop)
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert exec_fn.calls == [], exec_fn.calls
|
||
assert all(len(b) >= len(a) for a, b in zip(contents, contents[1:])), contents
|
||
final = contents[-1] if contents else ""
|
||
assert 'search[ARGS]{"q":"x"}' in final, contents
|
||
assert "visible" in final, contents
|
||
|
||
|
||
def test_plain_answer_ending_with_tool_name_word_is_preserved():
|
||
# End-of-stream flush: a plain answer ending on a tool-name word is prose, not dropped.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [["I think ", "you should ", "web_search"]],
|
||
max_tool_iterations = 1,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert any(t.rstrip().endswith("web_search") for t in contents), contents
|
||
|
||
|
||
def test_long_tool_name_split_rehearsal_is_not_capped_and_executes():
|
||
# Finding 10/11: an MCP name longer than the buffer cap, split before [ARGS], is still
|
||
# held (self-bounding prefix); no leak and the call executes.
|
||
from core.inference.safetensors_agentic import _MAX_BUFFER_CHARS
|
||
|
||
name = "mcp__github__create_pull_request"
|
||
assert len(name) >= _MAX_BUFFER_CHARS, len(name)
|
||
exec_fn = FakeExecuteTool(["RESULT"])
|
||
_turns = iter([[name, name + '[ARGS]{"x":1}'], ["done"]])
|
||
|
||
def st(_messages, active_tools = None):
|
||
yield from next(_turns)
|
||
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = st,
|
||
messages = [{"role": "user", "content": "go"}],
|
||
tools = [{"type": "function", "function": {"name": name}}],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 2,
|
||
)
|
||
)
|
||
assert exec_fn.calls == [(name, {"x": 1})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any(name in t for t in contents), contents
|
||
|
||
|
||
def test_unrestricted_mode_split_rehearsal_name_is_not_streamed():
|
||
# Finding 6: unrestricted mode treats any bare identifier as a possible rehearsal NAME.
|
||
exec_fn = FakeExecuteTool(["RESULT"])
|
||
_turns = iter([["web_search", 'web_search[ARGS]{"q":"x"}'], ["done"]])
|
||
|
||
def st(_messages, active_tools = None):
|
||
yield from next(_turns)
|
||
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = st,
|
||
messages = [{"role": "user", "content": "go"}],
|
||
tools = [], # unrestricted
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 2,
|
||
)
|
||
)
|
||
assert exec_fn.calls == [("web_search", {"q": "x"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any("web_search" in t for t in contents), contents
|
||
|
||
|
||
def test_unrestricted_mode_split_after_bracket_is_not_streamed():
|
||
# Unrestricted mode: a chunk split right after ``NAME[`` is still held (parity with the
|
||
# restricted-mode startswith hold).
|
||
exec_fn = FakeExecuteTool(["RESULT"])
|
||
_turns = iter([["web_search[", 'web_search[ARGS]{"q":"x"}'], ["done"]])
|
||
|
||
def st(_messages, active_tools = None):
|
||
yield from next(_turns)
|
||
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = st,
|
||
messages = [{"role": "user", "content": "go"}],
|
||
tools = [], # unrestricted
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 2,
|
||
)
|
||
)
|
||
assert exec_fn.calls == [("web_search", {"q": "x"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any("web_search[" in t for t in contents), contents
|
||
|
||
|
||
def test_unrestricted_mode_plain_prose_still_streams():
|
||
# The unrestricted hold releases a held identifier once the rest of the sentence follows.
|
||
def st(_messages, active_tools = None):
|
||
for snap in ("Hello", "Hello there friend."):
|
||
yield snap
|
||
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = st,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [],
|
||
execute_tool = FakeExecuteTool([]),
|
||
max_tool_iterations = 1,
|
||
)
|
||
)
|
||
contents = "".join(e["text"] for e in events if e["type"] == "content")
|
||
assert "Hello there friend." in contents, contents
|
||
|
||
|
||
def test_safety_net_honors_disabled_auto_heal_for_late_incomplete_call():
|
||
# A late call caught by the safety net: an unclosed ``<tool_call>`` heals only with Auto-Heal on;
|
||
# off, the safety net must not pass ``allow_incomplete=True`` and execute a truncated call.
|
||
prose = "Sure, let me look that up for you right now. "
|
||
incomplete = '<tool_call>{"name":"web_search","arguments":{"query":"weather in Sydney"}}'
|
||
|
||
loop_off, exec_off = _make_loop(
|
||
turns = [[prose, incomplete], ["Final answer."]],
|
||
exec_results = ["RESULT"],
|
||
auto_heal_tool_calls = False,
|
||
max_tool_iterations = 3,
|
||
)
|
||
events_off = _collect_events(loop_off)
|
||
assert exec_off.calls == [], "disabled Auto-Heal must not execute a healed incomplete call"
|
||
assert not [e for e in events_off if e.get("type") == "tool_start"]
|
||
|
||
loop_on, exec_on = _make_loop(
|
||
turns = [[prose, incomplete], ["Final answer."]],
|
||
exec_results = ["RESULT"],
|
||
auto_heal_tool_calls = True,
|
||
max_tool_iterations = 3,
|
||
)
|
||
_collect_events(loop_on)
|
||
assert exec_on.calls == [("web_search", {"query": "weather in Sydney"})], exec_on.calls
|
||
|
||
|
||
def test_bare_json_tool_call_is_not_streamed_as_content():
|
||
# Llama-3.2 ``custom_tools`` bare form ``{"name":..,"parameters":..}`` carries no
|
||
# XML signal. The loop must BUFFER it until the object closes and execute it via
|
||
# the safety net, never leaking the raw JSON to streaming clients as content.
|
||
bare = '{"name":"web_search","parameters":{"query":"cats"}}'
|
||
loop, exec_fn = _make_loop(
|
||
turns = [[bare], ["Here are the results."]],
|
||
exec_results = ["RESULT"],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "cats"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any('"name"' in t or "web_search" in t for t in contents), contents
|
||
assert any("Here are the results." in t for t in contents)
|
||
|
||
|
||
def test_ordinary_json_with_name_key_is_shown_not_treated_as_tool_call():
|
||
# Markerless JSON whose "name" is not an enabled tool (e.g. a person record
|
||
# ``{"name":"Alice",...}``) must be shown as the answer, not misread as a call
|
||
# to a disabled tool and dropped. _make_loop enables web_search/python/terminal.
|
||
answer = '{"name":"Alice","parameters":{"age":30}}'
|
||
loop, exec_fn = _make_loop(turns = [[answer]], max_tool_iterations = 1)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [], exec_fn.calls
|
||
contents = "".join(e["text"] for e in events if e["type"] == "content")
|
||
assert "Alice" in contents, contents
|
||
|
||
|
||
def test_bare_json_tool_call_split_across_chunks_is_not_streamed():
|
||
# Same as above but the bare object arrives split mid-key, so the buffer is
|
||
# held open across chunks before it balances.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['{"name":"web_', 'search","parameters":{"query":"cats"}}'],
|
||
["Done."],
|
||
],
|
||
exec_results = ["RESULT"],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "cats"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any('"name"' in t or "web_search" in t for t in contents), contents
|
||
|
||
|
||
def test_gemma_wrapperless_call_is_not_streamed_as_content():
|
||
# Gemma 4 wrapper-less ``call:NAME{...}`` has no XML signal; the loop must hold
|
||
# it (BUFFERING) and execute it, never streaming the raw call text.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [["call:web_search{query:cats}"], ["Found."]],
|
||
exec_results = ["RESULT"],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "cats"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any("call:web_search" in t for t in contents), contents
|
||
|
||
|
||
def test_gemma_wrapperless_call_with_whitespace_is_suppressed_when_streamed():
|
||
# Gemma may emit ``call : NAME{...}`` with whitespace around the colon, split across stream
|
||
# chunks.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [["call", " : ", "web_search", "{query:cats}"], ["Found."]],
|
||
exec_results = ["RESULT"],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "cats"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any("call" in t for t in contents), contents
|
||
|
||
|
||
def test_long_gemma_tool_name_is_not_streamed_as_content():
|
||
# A tool name longer than the small buffer cap (OpenAI 64 chars, MCP longer)
|
||
# must still be held: the ``call:NAME`` prefix keeps buffering until ``{``
|
||
# instead of leaking ``call:longname`` as visible text.
|
||
long_name = "mcp__github__list_repository_issues" # 35 chars
|
||
turns = iter([list('call:%s{repo:"octo/hello"}' % long_name), ["Done."]])
|
||
|
||
def _gen(_messages):
|
||
try:
|
||
chunks = next(turns)
|
||
except StopIteration:
|
||
return
|
||
acc = ""
|
||
for c in chunks:
|
||
acc += c
|
||
yield acc
|
||
|
||
exec_fn = FakeExecuteTool(["RESULT"])
|
||
loop = run_safetensors_tool_loop(
|
||
single_turn = _gen,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [{"type": "function", "function": {"name": long_name}}],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [(long_name, {"repo": "octo/hello"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any("call:" in t for t in contents), contents
|
||
|
||
|
||
def test_leading_json_answer_is_not_dropped():
|
||
# A leading ``{...}`` that is NOT a tool call must still surface as content:
|
||
# the bare-JSON hold can only ever delay it to end-of-object, never drop it.
|
||
obj = '{"answer": 42, "note": "done"}'
|
||
loop, exec_fn = _make_loop(
|
||
turns = [[obj]],
|
||
exec_results = [],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == []
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert any('"answer"' in t for t in contents), contents
|
||
|
||
|
||
def _reprompt_loop(*, auto_heal_tool_calls):
|
||
"""Drive one restricted tool with an intent-only first turn to exercise the nudge; returns conversations and events."""
|
||
captured: list[list] = []
|
||
|
||
def fake_single_turn(messages, active_tools = None):
|
||
captured.append(list(messages))
|
||
if len(captured) == 1:
|
||
yield "I'll search for that now." # forward-looking intent, no call
|
||
else:
|
||
yield "Final answer."
|
||
|
||
exec_fn = FakeExecuteTool([])
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = fake_single_turn,
|
||
messages = [{"role": "user", "content": "find X"}],
|
||
tools = [{"type": "function", "function": {"name": "search_knowledge_base"}}],
|
||
execute_tool = exec_fn,
|
||
auto_heal_tool_calls = auto_heal_tool_calls,
|
||
max_tool_iterations = 3,
|
||
)
|
||
)
|
||
return captured, events
|
||
|
||
|
||
def test_reprompt_names_only_active_tools_not_hardcoded():
|
||
# The plan-without-action nudge must name the tools actually enabled, never the
|
||
# old hardcoded ``web_search``/``python`` (which a restricted set would reject).
|
||
captured, _events = _reprompt_loop(auto_heal_tool_calls = True)
|
||
assert len(captured) >= 2, "intent prose should have triggered a re-prompt turn"
|
||
reprompt = captured[1][-1]
|
||
assert reprompt["role"] == "user"
|
||
assert "search_knowledge_base" in reprompt["content"]
|
||
assert "web_search" not in reprompt["content"]
|
||
assert "python" not in reprompt["content"]
|
||
|
||
|
||
def test_reprompt_suppressed_when_auto_heal_disabled():
|
||
# With Auto-Heal off the safetensors nudge must stay silent for backend parity
|
||
# with the GGUF loop, so only the single initial generation runs.
|
||
captured, events = _reprompt_loop(auto_heal_tool_calls = False)
|
||
assert len(captured) == 1, captured
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert any("search for that" in t for t in contents)
|
||
|
||
|
||
class TestLoopBasic:
|
||
def test_plain_answer(self):
|
||
# No tool XML; loop should yield content then status="".
|
||
loop, _exec = _make_loop(
|
||
turns = [["Hello", " world", "!"]],
|
||
exec_results = [],
|
||
)
|
||
events = _collect_events(loop)
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
statuses = [e for e in events if e["type"] == "status"]
|
||
assert contents, "expected at least one content event"
|
||
# Final cumulative content must contain the answer.
|
||
final_text = contents[-1]["text"]
|
||
assert "Hello world!" in final_text
|
||
assert statuses and statuses[-1]["text"] == ""
|
||
|
||
def test_single_tool_then_answer(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
# Tool call only.
|
||
[
|
||
'<tool_call>{"name":"web_search",',
|
||
'"arguments":{"query":"weather"}}',
|
||
"</tool_call>",
|
||
],
|
||
# Final answer.
|
||
["The ", "weather is ", "sunny."],
|
||
],
|
||
exec_results = ["Sunny and 22C"],
|
||
)
|
||
events = _collect_events(loop)
|
||
kinds = [e["type"] for e in events]
|
||
|
||
assert "tool_start" in kinds
|
||
assert "tool_end" in kinds
|
||
# Tool was called with the parsed arguments.
|
||
assert exec_fn.calls == [("web_search", {"query": "weather"})]
|
||
|
||
tool_start = next(e for e in events if e["type"] == "tool_start")
|
||
assert tool_start["tool_name"] == "web_search"
|
||
tool_end = next(e for e in events if e["type"] == "tool_end")
|
||
assert tool_end["result"] == "Sunny and 22C"
|
||
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
assert contents and "sunny" in contents[-1]["text"].lower()
|
||
|
||
def test_function_xml_form(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
["<function=python><parameter=code>print(1)</parameter></function>"],
|
||
["Result: 1"],
|
||
],
|
||
exec_results = ["1\n"],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("python", {"code": "print(1)"})]
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
assert "Result: 1" in contents[-1]["text"]
|
||
|
||
def test_llama3_python_tag_form(self):
|
||
# The agentic loop must recognise Llama-3's <|python_tag|>
|
||
# marker, drain the rest of the turn, and execute the call.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
[
|
||
"<|python_tag|>web_search.call(",
|
||
'query="weather in Tokyo"',
|
||
")",
|
||
],
|
||
["The weather is sunny."],
|
||
],
|
||
exec_results = ["Sunny, 22C"],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "weather in Tokyo"})]
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
assert "sunny" in contents[-1]["text"].lower()
|
||
|
||
def test_llama3_bare_json_form_fires_tool(self):
|
||
# Llama-3.1 / 3.2 emit a bare-JSON tool call
|
||
# ``{"name":..,"parameters":..}`` with NO XML signal. The loop's
|
||
# safety-net parse must still fire the tool instead of treating the
|
||
# turn as "planned without calling tools" and re-prompting the model
|
||
# into giving up. Regression for the has_tool_signal gate that
|
||
# dropped these; GGUF's llama-server parses them natively.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['{"name": "web_search", "parameters": {"query": "weather in SF"}}'],
|
||
["The weather is sunny."],
|
||
],
|
||
exec_results = ["Sunny, 18C"],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "weather in SF"})]
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
assert "sunny" in contents[-1]["text"].lower()
|
||
|
||
def test_mistral_pre_v11_form(self):
|
||
# Pre-v11 Mistral emission: ``[TOOL_CALLS] [{...}]``.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
[
|
||
'[TOOL_CALLS] [{"name":"web_search",',
|
||
'"arguments":{"query":"hi"},"id":"abc"}]',
|
||
],
|
||
["done"],
|
||
],
|
||
exec_results = ["ok"],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "hi"})]
|
||
# Mistral-provided ids must propagate to tool_start events.
|
||
tool_start = next(e for e in events if e["type"] == "tool_start")
|
||
assert tool_start["tool_call_id"] == "abc"
|
||
|
||
def test_mistral_v11_form(self):
|
||
# v11+ Mistral emission: bare ``name{json}`` after the trigger.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['[TOOL_CALLS]web_search{"query":"hi"}'],
|
||
["done"],
|
||
],
|
||
exec_results = ["ok"],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "hi"})]
|
||
|
||
def test_gemma4_form(self):
|
||
# Gemma 4 emission: ``<|tool_call>call:NAME{...}<tool_call|>``.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
[
|
||
"<|tool_call>call:web_search{",
|
||
'query:<|"|>weather<|"|>',
|
||
"}<tool_call|>",
|
||
],
|
||
["sunny"],
|
||
],
|
||
exec_results = ["Sunny, 22C"],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "weather"})]
|
||
|
||
def test_deepseek_v3_1_form(self):
|
||
# DeepSeek V3.1 emission inside the agentic loop -- the buffer state machine must wake on
|
||
# ``<｜tool▁calls▁begin｜>`` and the parser must extract the V3.1 bare-JSON body.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
[
|
||
"<｜tool▁calls▁begin｜>",
|
||
"<｜tool▁call▁begin｜>web_search",
|
||
"<｜tool▁sep｜>",
|
||
'{"query":"Tokyo weather"}',
|
||
"<｜tool▁call▁end｜>",
|
||
"<｜tool▁calls▁end｜>",
|
||
],
|
||
["The weather is sunny."],
|
||
],
|
||
exec_results = ["Sunny, 22C"],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "Tokyo weather"})]
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
assert contents and "sunny" in contents[-1]["text"].lower()
|
||
|
||
def test_glm_form(self):
|
||
# GLM 4.x emission: ``<tool_call>NAME\n<arg_key>...``.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
[
|
||
"<tool_call>web_search\n",
|
||
"<arg_key>query</arg_key>\n",
|
||
"<arg_value>Tokyo</arg_value>\n",
|
||
"</tool_call>",
|
||
],
|
||
["found"],
|
||
],
|
||
exec_results = ["..."],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "Tokyo"})]
|
||
|
||
def test_kimi_form(self):
|
||
# Kimi K2 emission ``<|tool_calls_section_begin|>...``.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
[
|
||
"<|tool_calls_section_begin|>",
|
||
"<|tool_call_begin|>functions.web_search:0",
|
||
"<|tool_call_argument_begin|>",
|
||
'{"query":"Tokyo"}',
|
||
"<|tool_call_end|>",
|
||
"<|tool_calls_section_end|>",
|
||
],
|
||
["done"],
|
||
],
|
||
exec_results = ["..."],
|
||
)
|
||
events = _collect_events(loop)
|
||
# The bare name must reach execute_tool, even though the model
|
||
# emitted ``functions.web_search:0`` as the formatted id.
|
||
assert exec_fn.calls == [("web_search", {"query": "Tokyo"})]
|
||
# tool_start carries the original full id so the conversation
|
||
# roundtrip can replay it verbatim.
|
||
tool_start = next(e for e in events if e["type"] == "tool_start")
|
||
assert tool_start["tool_call_id"] == "functions.web_search:0"
|
||
|
||
def test_render_html_emits_provisional_tool_start(self):
|
||
exec_fn = FakeExecuteTool(["Rendered HTML canvas."])
|
||
turn_iter = iter(
|
||
[
|
||
[
|
||
"<function=render_html>",
|
||
"<parameter=code><!doctype html><html>",
|
||
"<body>Hi</body></html></parameter></function>",
|
||
],
|
||
["Done."],
|
||
]
|
||
)
|
||
|
||
def _gen(_messages):
|
||
chunks = next(turn_iter)
|
||
acc = ""
|
||
for chunk in chunks:
|
||
acc += chunk
|
||
yield acc
|
||
|
||
loop = run_safetensors_tool_loop(
|
||
single_turn = _gen,
|
||
messages = [{"role": "user", "content": "make html"}],
|
||
tools = [{"type": "function", "function": {"name": "render_html"}}],
|
||
execute_tool = exec_fn,
|
||
)
|
||
events = _collect_events(loop)
|
||
tool_starts = [e for e in events if e["type"] == "tool_start"]
|
||
|
||
assert len(tool_starts) == 2
|
||
assert tool_starts[0]["tool_name"] == "render_html"
|
||
assert tool_starts[0]["arguments"] == {}
|
||
assert tool_starts[1]["tool_name"] == "render_html"
|
||
assert "<!doctype html>" in tool_starts[1]["arguments"]["code"]
|
||
assert exec_fn.calls[0][0] == "render_html"
|
||
assert "<!doctype html>" in exec_fn.calls[0][1]["code"]
|
||
|
||
def test_render_html_confirmation_gate_suppresses_early_provisional(self, monkeypatch):
|
||
"""When a human confirmation gate is active, render_html must not surface
|
||
an early provisional tool_start: that card (keyed by tool_call_id, no
|
||
approval) would show the tool 'running' before the user approves. The
|
||
gated real tool_start is the first signal the UI receives instead."""
|
||
monkeypatch.setattr(safetensors_agentic, "new_approval_id", lambda: "approval-rh")
|
||
monkeypatch.setattr(safetensors_agentic, "begin_tool_decision", lambda *_a, **_k: object())
|
||
monkeypatch.setattr(safetensors_agentic, "wait_tool_decision", lambda *_a, **_k: "allow")
|
||
|
||
exec_fn = FakeExecuteTool(["Rendered HTML canvas."])
|
||
turn_iter = iter(
|
||
[
|
||
[
|
||
"<function=render_html>",
|
||
"<parameter=code><!doctype html><html>",
|
||
"<body>Hi</body></html></parameter></function>",
|
||
],
|
||
["Done."],
|
||
]
|
||
)
|
||
|
||
def _gen(_messages):
|
||
chunks = next(turn_iter)
|
||
acc = ""
|
||
for chunk in chunks:
|
||
acc += chunk
|
||
yield acc
|
||
|
||
loop = run_safetensors_tool_loop(
|
||
single_turn = _gen,
|
||
messages = [{"role": "user", "content": "make html"}],
|
||
tools = [{"type": "function", "function": {"name": "render_html"}}],
|
||
execute_tool = exec_fn,
|
||
confirm_tool_calls = True,
|
||
session_id = "sess",
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
tool_starts = [e for e in events if e["type"] == "tool_start"]
|
||
|
||
# No early provisional (empty-args) card while confirmation is pending.
|
||
assert [e for e in tool_starts if e.get("arguments") == {}] == []
|
||
# The real, gated tool_start still surfaces with the full arguments.
|
||
real = [e for e in tool_starts if e.get("arguments", {}).get("code")]
|
||
assert len(real) == 1
|
||
assert real[0].get("awaiting_confirmation") is True
|
||
assert "<!doctype html>" in real[0]["arguments"]["code"]
|
||
assert exec_fn.calls[0][0] == "render_html"
|
||
|
||
def test_render_html_bypass_permissions_keeps_early_provisional(self, monkeypatch):
|
||
"""bypass_permissions wins over the confirm gate, so the early provisional
|
||
card is preserved (no human approval is required)."""
|
||
exec_fn = FakeExecuteTool(["Rendered HTML canvas."])
|
||
turn_iter = iter(
|
||
[
|
||
[
|
||
"<function=render_html>",
|
||
"<parameter=code><!doctype html><html>",
|
||
"<body>Hi</body></html></parameter></function>",
|
||
],
|
||
["Done."],
|
||
]
|
||
)
|
||
|
||
def _gen(_messages):
|
||
chunks = next(turn_iter)
|
||
acc = ""
|
||
for chunk in chunks:
|
||
acc += chunk
|
||
yield acc
|
||
|
||
loop = run_safetensors_tool_loop(
|
||
single_turn = _gen,
|
||
messages = [{"role": "user", "content": "make html"}],
|
||
tools = [{"type": "function", "function": {"name": "render_html"}}],
|
||
execute_tool = exec_fn,
|
||
confirm_tool_calls = True,
|
||
bypass_permissions = True,
|
||
session_id = "sess",
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
tool_starts = [e for e in events if e["type"] == "tool_start"]
|
||
|
||
assert len(tool_starts) == 2
|
||
assert tool_starts[0]["arguments"] == {}
|
||
assert "<!doctype html>" in tool_starts[1]["arguments"]["code"]
|
||
|
||
def test_render_html_provisional_card_closed_on_generator_exception(self):
|
||
"""If the model generator raises mid-stream after a provisional render_html
|
||
card was surfaced, the loop must close that card as errored before the
|
||
exception propagates, so the UI never leaves a tool spinning forever."""
|
||
exec_fn = FakeExecuteTool([])
|
||
|
||
def _gen(_messages):
|
||
acc = ""
|
||
for chunk in ["<function=render_html>", "<parameter=code><!doctype html><html>"]:
|
||
acc += chunk
|
||
yield acc
|
||
raise RuntimeError("model pipeline exploded")
|
||
|
||
loop = run_safetensors_tool_loop(
|
||
single_turn = _gen,
|
||
messages = [{"role": "user", "content": "make html"}],
|
||
tools = [{"type": "function", "function": {"name": "render_html"}}],
|
||
execute_tool = exec_fn,
|
||
)
|
||
|
||
collected: list[dict] = []
|
||
raised = False
|
||
try:
|
||
for event in loop:
|
||
collected.append(event)
|
||
except RuntimeError as exc:
|
||
raised = True
|
||
assert "exploded" in str(exc)
|
||
|
||
assert raised
|
||
provisional = [
|
||
e for e in collected if e["type"] == "tool_start" and e.get("arguments") == {}
|
||
]
|
||
assert len(provisional) == 1
|
||
# The provisional card is closed (as an error) before the exception
|
||
# propagates, so it never dangles.
|
||
closing = [
|
||
e
|
||
for e in collected
|
||
if e["type"] == "tool_end" and e.get("tool_call_id") == provisional[0]["tool_call_id"]
|
||
]
|
||
assert len(closing) == 1
|
||
assert "Error" in (closing[0].get("result") or "")
|
||
|
||
def test_python_tool_containing_render_html_signal_does_not_emit_provisional_start(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
[
|
||
"<function=python>",
|
||
"<parameter=code>print('<function=render_html>')",
|
||
"</parameter></function>",
|
||
],
|
||
["Done."],
|
||
],
|
||
exec_results = ["ok"],
|
||
)
|
||
events = _collect_events(loop)
|
||
tool_starts = [e for e in events if e["type"] == "tool_start"]
|
||
|
||
assert len(tool_starts) == 1
|
||
assert tool_starts[0]["tool_name"] == "python"
|
||
assert exec_fn.calls == [("python", {"code": "print('<function=render_html>')"})]
|
||
|
||
def test_render_html_rehearsed_in_think_block_emits_no_provisional_start(self):
|
||
# BUG B: a render_html rehearsed inside think before a real python call must not emit a
|
||
# provisional render_html card; only the outside-think call fires.
|
||
exec_fn = FakeExecuteTool(["ok"])
|
||
turn_iter = iter(
|
||
[
|
||
[
|
||
'<think>draft render_html[ARGS]{"code":"x"}</think>',
|
||
'python[ARGS]{"code":"print(1)"}',
|
||
],
|
||
["Done."],
|
||
]
|
||
)
|
||
|
||
def _gen(_messages):
|
||
chunks = next(turn_iter)
|
||
acc = ""
|
||
for chunk in chunks:
|
||
acc += chunk
|
||
yield acc
|
||
|
||
loop = run_safetensors_tool_loop(
|
||
single_turn = _gen,
|
||
messages = [{"role": "user", "content": "run code"}],
|
||
tools = [
|
||
{"type": "function", "function": {"name": "render_html"}},
|
||
{"type": "function", "function": {"name": "python"}},
|
||
],
|
||
execute_tool = exec_fn,
|
||
)
|
||
events = _collect_events(loop)
|
||
tool_starts = [e for e in events if e["type"] == "tool_start"]
|
||
|
||
assert [e["tool_name"] for e in tool_starts] == ["python"], tool_starts
|
||
assert exec_fn.calls == [("python", {"code": "print(1)"})]
|
||
|
||
def test_render_html_success_blocks_second_canvas_call(self):
|
||
exec_fn = FakeExecuteTool(["Rendered HTML canvas."])
|
||
turn_iter = iter(
|
||
[
|
||
[
|
||
'<tool_call>{"name":"render_html",',
|
||
'"arguments":{"code":"<html>one</html>"}}',
|
||
],
|
||
[
|
||
'<tool_call>{"name":"render_html",',
|
||
'"arguments":{"code":"<html>two</html>"}}',
|
||
],
|
||
["Done."],
|
||
]
|
||
)
|
||
|
||
def _gen(_messages):
|
||
chunks = next(turn_iter)
|
||
acc = ""
|
||
for chunk in chunks:
|
||
acc += chunk
|
||
yield acc
|
||
|
||
loop = run_safetensors_tool_loop(
|
||
single_turn = _gen,
|
||
messages = [{"role": "user", "content": "make html"}],
|
||
tools = [{"type": "function", "function": {"name": "render_html"}}],
|
||
execute_tool = exec_fn,
|
||
)
|
||
events = _collect_events(loop)
|
||
tool_starts = [e for e in events if e["type"] == "tool_start"]
|
||
|
||
assert exec_fn.calls == [("render_html", {"code": "<html>one</html>"})]
|
||
assert [e["arguments"] for e in tool_starts] == [{}, {"code": "<html>one</html>"}]
|
||
|
||
def test_truncated_unclosed_tool_call(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
# No </tool_call>; balanced-brace parser still succeeds because
|
||
# the JSON itself is balanced.
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}'],
|
||
["done"],
|
||
],
|
||
exec_results = ["result"],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "x"})]
|
||
|
||
def test_bad_json_healed_to_query(self):
|
||
# Non-JSON string arguments heal to {"query": ...} under auto_heal_tool_calls.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
# ``arguments`` is a string _coerce_arguments can't parse, so heal runs.
|
||
['<tool_call>{"name":"web_search","arguments":"hello world"}</tool_call>'],
|
||
["ok"],
|
||
],
|
||
exec_results = ["..."],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls and exec_fn.calls[0][0] == "web_search"
|
||
assert exec_fn.calls[0][1] == {"query": "hello world"}
|
||
|
||
|
||
class TestLoopBehaviour:
|
||
def test_duplicate_tool_call_internal_noop(self):
|
||
captured_messages: list[list[dict]] = []
|
||
turns = iter(
|
||
[
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
["final"],
|
||
]
|
||
)
|
||
|
||
def fake_single_turn(messages):
|
||
captured_messages.append([dict(message) for message in messages])
|
||
chunks = next(turns)
|
||
acc = ""
|
||
for chunk in chunks:
|
||
acc += chunk
|
||
yield acc
|
||
|
||
exec_fn = FakeExecuteTool(["search-result-1"])
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = fake_single_turn,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 3,
|
||
)
|
||
)
|
||
|
||
assert exec_fn.calls == [("web_search", {"query": "x"})]
|
||
assert [e["tool_call_id"] for e in events if e["type"] == "tool_end"] == ["call_0"]
|
||
assert not [
|
||
e
|
||
for e in events
|
||
if e.get("tool_call_id") == "call_1" and e.get("type") in {"tool_start", "tool_end"}
|
||
]
|
||
duplicate_nudges = [
|
||
message
|
||
for message in captured_messages[-1]
|
||
if message.get("role") == "user"
|
||
and "already completed successfully" in message.get("content", "")
|
||
]
|
||
assert len(duplicate_nudges) == 1
|
||
|
||
def test_duplicate_tool_call_internal_noop_allows_distinct_followup_tool(self):
|
||
captured_messages: list[list[dict]] = []
|
||
captured_tool_names: list[list[str]] = []
|
||
turns = iter(
|
||
[
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
['<tool_call>{"name":"python","arguments":{"code":"print(1)"}}</tool_call>'],
|
||
["final"],
|
||
]
|
||
)
|
||
|
||
def fake_single_turn(messages, active_tools = None):
|
||
captured_messages.append([dict(message) for message in messages])
|
||
captured_tool_names.append(
|
||
[
|
||
tool["function"]["name"]
|
||
for tool in (active_tools or [])
|
||
if tool.get("function", {}).get("name")
|
||
]
|
||
)
|
||
chunks = next(turns)
|
||
acc = ""
|
||
for chunk in chunks:
|
||
acc += chunk
|
||
yield acc
|
||
|
||
exec_fn = FakeExecuteTool(["search-result-1", "python-result"])
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = fake_single_turn,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [
|
||
{"type": "function", "function": {"name": "web_search"}},
|
||
{"type": "function", "function": {"name": "python"}},
|
||
],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 4,
|
||
)
|
||
)
|
||
|
||
assert exec_fn.calls == [
|
||
("web_search", {"query": "x"}),
|
||
("python", {"code": "print(1)"}),
|
||
]
|
||
assert [e["tool_call_id"] for e in events if e["type"] == "tool_end"] == [
|
||
"call_0",
|
||
"call_2",
|
||
]
|
||
assert not [
|
||
e
|
||
for e in events
|
||
if e.get("tool_call_id") == "call_1" and e.get("type") in {"tool_start", "tool_end"}
|
||
]
|
||
duplicate_nudges = [
|
||
message
|
||
for message in captured_messages[2]
|
||
if message.get("role") == "user"
|
||
and "already completed successfully" in message.get("content", "")
|
||
]
|
||
assert len(duplicate_nudges) == 1
|
||
assert captured_tool_names[2] == ["web_search", "python"]
|
||
|
||
def test_duplicate_noop_does_not_consume_budget_at_small_cap(self):
|
||
# A duplicate/disabled no-op turn is a correction turn and must NOT spend the
|
||
# caller's tool budget, so with max_tool_iterations=2 the model can still make a
|
||
# DISTINCT valid call after repeating one. Only turns that actually execute a
|
||
# tool count -- matching the GGUF loop. (The budget used to be charged per
|
||
# non-re-prompt iteration, so the duplicate burned the second slot and the third
|
||
# turn was sent with no tools, dropping the ``python`` call.)
|
||
captured_tool_names: list[list[str]] = []
|
||
turns = iter(
|
||
[
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
['<tool_call>{"name":"python","arguments":{"code":"print(1)"}}</tool_call>'],
|
||
["final"],
|
||
]
|
||
)
|
||
|
||
def fake_single_turn(messages, active_tools = None):
|
||
captured_tool_names.append(
|
||
[
|
||
tool["function"]["name"]
|
||
for tool in (active_tools or [])
|
||
if tool.get("function", {}).get("name")
|
||
]
|
||
)
|
||
chunks = next(turns)
|
||
acc = ""
|
||
for chunk in chunks:
|
||
acc += chunk
|
||
yield acc
|
||
|
||
exec_fn = FakeExecuteTool(["search-result", "python-result"])
|
||
_collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = fake_single_turn,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [
|
||
{"type": "function", "function": {"name": "web_search"}},
|
||
{"type": "function", "function": {"name": "python"}},
|
||
],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 2,
|
||
)
|
||
)
|
||
|
||
# Both distinct tools execute; the repeated call in between did not cost a slot.
|
||
assert exec_fn.calls == [
|
||
("web_search", {"query": "x"}),
|
||
("python", {"code": "print(1)"}),
|
||
]
|
||
# The turn after the duplicate still offered tools (budget not yet spent).
|
||
assert captured_tool_names[2] == ["web_search", "python"]
|
||
|
||
def test_repeated_duplicate_noop_transitions_to_final_attempt(self):
|
||
captured_tool_names: list[list[str]] = []
|
||
turns = iter(
|
||
[
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
["final from first result"],
|
||
]
|
||
)
|
||
|
||
def fake_single_turn(messages, active_tools = None):
|
||
captured_tool_names.append(
|
||
[
|
||
(tool.get("function") or {}).get("name")
|
||
for tool in (active_tools or [])
|
||
if (tool.get("function") or {}).get("name")
|
||
]
|
||
)
|
||
chunks = next(turns)
|
||
acc = ""
|
||
for chunk in chunks:
|
||
acc += chunk
|
||
yield acc
|
||
|
||
exec_fn = FakeExecuteTool(["search-result"])
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = fake_single_turn,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 10,
|
||
)
|
||
)
|
||
|
||
assert exec_fn.calls == [("web_search", {"query": "x"})]
|
||
assert [
|
||
event.get("tool_call_id") for event in events if event.get("type") == "tool_end"
|
||
] == ["call_0"]
|
||
assert captured_tool_names[-1] == []
|
||
assert any(
|
||
event.get("type") == "content" and "final from first result" in event.get("text", "")
|
||
for event in events
|
||
)
|
||
|
||
def test_kb_search_capped_per_turn(self):
|
||
# Paraphrased KB searches differ by args (dup guard misses them); the
|
||
# per-turn cap stops the runaway re-search loop.
|
||
n = RAG_MAX_SEARCHES_PER_TURN
|
||
queries = [f"paraphrase {i}" for i in range(n + 1)]
|
||
turns = [
|
||
[
|
||
'<tool_call>{"name":"search_knowledge_base",'
|
||
f'"arguments":{{"query":"{q}"}}}}</tool_call>'
|
||
]
|
||
for q in queries
|
||
] + [["final answer"]]
|
||
turn_iter = iter(turns)
|
||
|
||
def _gen(_messages):
|
||
try:
|
||
chunks = next(turn_iter)
|
||
except StopIteration:
|
||
return
|
||
acc = ""
|
||
for c in chunks:
|
||
acc += c
|
||
yield acc
|
||
|
||
exec_fn = FakeExecuteTool([f"chunk-{i}" for i in range(n)])
|
||
loop = run_safetensors_tool_loop(
|
||
single_turn = _gen,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [{"type": "function", "function": {"name": "search_knowledge_base"}}],
|
||
execute_tool = exec_fn,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert len(exec_fn.calls) == n
|
||
assert all(c[0] == "search_knowledge_base" for c in exec_fn.calls)
|
||
tool_end_events = [e for e in events if e["type"] == "tool_end"]
|
||
assert len(tool_end_events) == n + 1
|
||
assert "do not search again" in tool_end_events[n]["result"].lower()
|
||
|
||
def test_image_sentinel_stripped_from_model_feed(self):
|
||
# The image sentinel is stripped before the next turn, but tool_end still
|
||
# carries the raw result for the UI.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['<tool_call>{"name":"python","arguments":{"code":"plot()"}}</tool_call>'],
|
||
["see chart"],
|
||
],
|
||
exec_results = ["chart\n__IMAGES__:/tmp/chart.png"],
|
||
)
|
||
events = _collect_events(loop)
|
||
tool_end = next(e for e in events if e["type"] == "tool_end")
|
||
assert "__IMAGES__" in tool_end["result"]
|
||
|
||
def test_image_sentinel_stripped_with_leading_marker(self):
|
||
# Sentinel at start (no newline) must not leak to the model.
|
||
from core.inference import safetensors_agentic as _sa
|
||
|
||
captured: list[list[dict]] = []
|
||
|
||
def fake_single_turn(messages, **_kw):
|
||
captured.append([dict(m) for m in messages])
|
||
if len(captured) == 1:
|
||
yield '<tool_call>{"name":"python","arguments":{"code":"plot()"}}</tool_call>'
|
||
else:
|
||
yield "done"
|
||
|
||
events = list(
|
||
_sa.run_safetensors_tool_loop(
|
||
single_turn = fake_single_turn,
|
||
messages = [{"role": "user", "content": "plot please"}],
|
||
tools = [{"function": {"name": "python"}}],
|
||
execute_tool = lambda *_a, **_kw: "__IMAGES__:/tmp/x.png",
|
||
cancel_event = threading.Event(),
|
||
max_tool_iterations = 3,
|
||
auto_heal_tool_calls = True,
|
||
)
|
||
)
|
||
# The model's second turn must not see "__IMAGES__".
|
||
assert len(captured) >= 2
|
||
tool_msgs = [m for m in captured[1] if m.get("role") == "tool"]
|
||
assert tool_msgs, "no tool message reached the model"
|
||
for tm in tool_msgs:
|
||
assert "__IMAGES__" not in tm["content"], f"sentinel leaked to model: {tm['content']!r}"
|
||
|
||
def test_image_sentinel_stripped_with_multiple_markers(self):
|
||
# Consecutive sentinels: cut at the first, nothing leaks.
|
||
from core.inference import safetensors_agentic as _sa
|
||
|
||
captured: list[list[dict]] = []
|
||
|
||
def fake_single_turn(messages, **_kw):
|
||
captured.append([dict(m) for m in messages])
|
||
if len(captured) == 1:
|
||
yield '<tool_call>{"name":"python","arguments":{"code":"plot()"}}</tool_call>'
|
||
else:
|
||
yield "done"
|
||
|
||
multi = "panel\n__IMAGES__:/tmp/a.png\n__IMAGES__:/tmp/b.png"
|
||
events = list(
|
||
_sa.run_safetensors_tool_loop(
|
||
single_turn = fake_single_turn,
|
||
messages = [{"role": "user", "content": "plot please"}],
|
||
tools = [{"function": {"name": "python"}}],
|
||
execute_tool = lambda *_a, **_kw: multi,
|
||
cancel_event = threading.Event(),
|
||
max_tool_iterations = 3,
|
||
auto_heal_tool_calls = True,
|
||
)
|
||
)
|
||
tool_msgs = [m for m in captured[1] if m.get("role") == "tool"]
|
||
assert tool_msgs
|
||
for tm in tool_msgs:
|
||
assert "__IMAGES__" not in tm["content"], f"second sentinel leaked: {tm['content']!r}"
|
||
assert tm["content"] == "panel", f"expected payload-only 'panel', got {tm['content']!r}"
|
||
|
||
def test_tool_execution_error_is_emitted_but_loop_continues(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
["sorry, that failed"],
|
||
],
|
||
exec_results = ["Error: network unreachable"],
|
||
)
|
||
events = _collect_events(loop)
|
||
tool_end = next(e for e in events if e["type"] == "tool_end")
|
||
assert tool_end["result"].startswith("Error")
|
||
# The loop must still emit a content event after the failure.
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
assert contents
|
||
|
||
def test_exception_in_executor_does_not_raise(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
["recovered"],
|
||
],
|
||
exec_results = [RuntimeError("boom")],
|
||
)
|
||
events = _collect_events(loop)
|
||
tool_end = next(e for e in events if e["type"] == "tool_end")
|
||
assert "boom" in tool_end["result"]
|
||
|
||
|
||
class TestLoopRePrompt:
|
||
"""Plan-without-action re-prompt parity with GGUF: nudge instead of terminating, up to ``_MAX_REPROMPTS`` extra slots."""
|
||
|
||
def test_intent_signal_triggers_reprompt(self):
|
||
# Turn 1: intent signal, no tool call.
|
||
# Turn 2 (re-prompt): proper tool call -> executes.
|
||
# Turn 3: final answer.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
["Let me search for that."],
|
||
[
|
||
'<tool_call>{"name":"web_search","arguments":'
|
||
'{"query":"sky color"}}</tool_call>'
|
||
],
|
||
["The sky is blue."],
|
||
],
|
||
exec_results = ["Blue (Rayleigh scattering)"],
|
||
)
|
||
events = _collect_events(loop)
|
||
# web_search must have been called once (after the re-prompt).
|
||
assert exec_fn.calls == [("web_search", {"query": "sky color"})]
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
assert contents and "blue" in contents[-1]["text"].lower()
|
||
|
||
def test_intent_signal_without_tools_does_not_reprompt(self):
|
||
# Same intent signal but no tools enabled -- must NOT re-prompt.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [["Let me think about that for a moment."]],
|
||
exec_results = [],
|
||
)
|
||
# _make_loop hard-codes three tools; rebuild without tools.
|
||
from core.inference.safetensors_agentic import run_safetensors_tool_loop
|
||
|
||
def _gen(_messages):
|
||
yield "Let me think about that for a moment."
|
||
|
||
exec_fn = FakeExecuteTool([])
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = _gen,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [],
|
||
execute_tool = exec_fn,
|
||
)
|
||
)
|
||
assert exec_fn.calls == []
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
assert contents and "think" in contents[-1]["text"].lower()
|
||
|
||
def test_direct_answer_does_not_trigger_reprompt(self):
|
||
# Plain answer with no intent words: do NOT re-prompt.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [["4"]],
|
||
exec_results = [],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == []
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
assert contents and contents[-1]["text"].strip() == "4"
|
||
|
||
def test_max_reprompts_capped_at_three(self):
|
||
# Model keeps stalling with intent -- after 3 re-prompts the
|
||
# loop must give up rather than burn forever.
|
||
turns = [["Let me search for that."]] * 6 # well over the cap
|
||
loop, exec_fn = _make_loop(
|
||
turns = turns,
|
||
exec_results = [],
|
||
)
|
||
events = _collect_events(loop, max_events = 500)
|
||
# No tool ever ran, but the loop terminated cleanly.
|
||
assert exec_fn.calls == []
|
||
statuses = [e for e in events if e["type"] == "status"]
|
||
assert statuses and statuses[-1]["text"] == ""
|
||
|
||
def test_short_intent_below_buffer_threshold_triggers_reprompt(self):
|
||
# Short emission that never exits BUFFERING (< 32 chars + no
|
||
# marker prefix). The unified buffer-end path must still
|
||
# trigger the intent re-prompt, not silently terminate.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
["Let me check."],
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
["found"],
|
||
],
|
||
exec_results = ["..."],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "x"})]
|
||
|
||
def test_reprompt_does_not_consume_tool_budget(self):
|
||
# max_tool_iterations=1: one re-prompt, then one real tool call,
|
||
# then the budget-exhausted final answer must still fire. If the
|
||
# re-prompt ate the slot the tool call would never run.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
# 1. Intent stall (re-prompt 1/3).
|
||
["Let me search for that."],
|
||
# 2. Real tool call (uses the budget slot).
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"weather"}}</tool_call>'],
|
||
# 3. Budget exhausted -> nudged final answer.
|
||
["Final: it is sunny"],
|
||
],
|
||
exec_results = ["sunny"],
|
||
max_tool_iterations = 1,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "weather"})]
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
assert contents and "sunny" in contents[-1]["text"].lower()
|
||
|
||
|
||
class TestLoopCanonicalHealKey:
|
||
"""Per-tool canonical heal key (``code``/``command``/``query``), mirroring GGUF."""
|
||
|
||
def test_python_bare_string_heals_to_code(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['<tool_call>{"name":"python","arguments":"print(1)"}' "</tool_call>"],
|
||
["done"],
|
||
],
|
||
exec_results = ["1\n"],
|
||
)
|
||
events = _collect_events(loop)
|
||
# The bare string must heal to {"code": "print(1)"}, not
|
||
# {"query": ...}, so the python sandbox actually executes it.
|
||
assert exec_fn.calls == [("python", {"code": "print(1)"})]
|
||
|
||
def test_terminal_bare_string_heals_to_command(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['<tool_call>{"name":"terminal","arguments":"ls -la"}' "</tool_call>"],
|
||
["done"],
|
||
],
|
||
exec_results = ["..."],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("terminal", {"command": "ls -la"})]
|
||
|
||
def test_unknown_tool_bare_string_heals_to_query(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['<tool_call>{"name":"web_search","arguments":"hello"}' "</tool_call>"],
|
||
["ok"],
|
||
],
|
||
exec_results = ["..."],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "hello"})]
|
||
|
||
|
||
class TestGGUFSafetensorsHealingParity:
|
||
"""Pin GGUF vs safetensors/MLX loop parity so a regression on either side breaks CI."""
|
||
|
||
def test_gguf_imports_shared_signal_markers(self):
|
||
# The GGUF BUFFERING state machine must wake on every emission
|
||
# marker the shared parser knows -- otherwise Llama-3 / Mistral
|
||
# / Gemma 4 emissions slip past as plain prose when the
|
||
# llama-server structured channel fails.
|
||
import inspect
|
||
|
||
from core.inference.llama_cpp import LlamaCppBackend
|
||
|
||
src = inspect.getsource(LlamaCppBackend.generate_chat_completion_with_tools)
|
||
assert "_SHARED_TOOL_XML_SIGNALS" in src, (
|
||
"GGUF agentic loop must reuse the shared TOOL_XML_SIGNALS "
|
||
"tuple so it wakes on all five emission formats"
|
||
)
|
||
|
||
def test_gguf_uses_shared_strip_helper(self):
|
||
# The GGUF stream-cleanup function must delegate to the shared
|
||
# strip_tool_markup so closed-pair markup is removed for every
|
||
# emission family (Llama-3 <|python_tag|>, Mistral [TOOL_CALLS],
|
||
# Gemma 4 <|tool_call>...<tool_call|>).
|
||
import inspect
|
||
|
||
from core.inference.llama_cpp import LlamaCppBackend
|
||
|
||
src = inspect.getsource(LlamaCppBackend.generate_chat_completion_with_tools)
|
||
assert (
|
||
"_shared_strip_tool_markup" in src
|
||
), "GGUF stream cleanup must delegate to the shared strip_tool_markup helper"
|
||
|
||
def test_gguf_uses_canonical_heal_keys(self):
|
||
# GGUF and safetensors heal a bare-string ``arguments`` to the same
|
||
# per-tool canonical key -- ``code`` for python, ``command`` for
|
||
# terminal, ``query`` for everything else. The mapping is centralised in
|
||
# the shared ToolLoopController (both backends route bare-string args
|
||
# through ``coerce_tool_arguments``), so the two paths cannot drift.
|
||
from core.inference.tool_loop_controller import (
|
||
_CANONICAL_HEAL_ARG,
|
||
coerce_tool_arguments,
|
||
)
|
||
|
||
assert _CANONICAL_HEAL_ARG["python"] == "code"
|
||
assert _CANONICAL_HEAL_ARG["terminal"] == "command"
|
||
assert coerce_tool_arguments("print(1)", heal = True, tool_name = "python").arguments == {
|
||
"code": "print(1)"
|
||
}
|
||
assert coerce_tool_arguments("ls -la", heal = True, tool_name = "terminal").arguments == {
|
||
"command": "ls -la"
|
||
}
|
||
assert coerce_tool_arguments("weather", heal = True, tool_name = "web_search").arguments == {
|
||
"query": "weather"
|
||
}
|
||
|
||
def test_intent_regex_matches_same_phrases_as_gguf(self):
|
||
# The intent re-prompt regex must match the SAME forward-looking
|
||
# phrases on both backends so behaviour is the same on Mac (MLX
|
||
# / safetensors) and on Linux (GGUF).
|
||
from core.inference.llama_cpp import _INTENT_SIGNAL as gguf_re
|
||
from core.inference.safetensors_agentic import (
|
||
_INTENT_SIGNAL as sf_re,
|
||
)
|
||
|
||
for phrase in (
|
||
"I'll search for that",
|
||
"I will look it up",
|
||
"Let me check",
|
||
"I am going to call the tool",
|
||
"First, I will explore",
|
||
"Here's my plan",
|
||
"Now I need to call web_search",
|
||
):
|
||
assert gguf_re.search(phrase), f"GGUF missed {phrase!r}"
|
||
assert sf_re.search(phrase), f"safetensors missed {phrase!r}"
|
||
|
||
for plain in (
|
||
"4",
|
||
"Hello!",
|
||
"The sky is blue.",
|
||
"I can help with that.",
|
||
"I should mention",
|
||
"Let's go.",
|
||
# Negated intent is a refusal, not a plan: neither backend may
|
||
# force a tool-call re-prompt on it.
|
||
"I will not search the web for that.",
|
||
"I'll never call that tool.",
|
||
):
|
||
assert not gguf_re.search(plain), f"GGUF wrongly fired on {plain!r}"
|
||
assert not sf_re.search(plain), f"safetensors wrongly fired on {plain!r}"
|
||
|
||
def test_max_reprompts_equal_on_both_backends(self):
|
||
from core.inference.llama_cpp import _MAX_REPROMPTS as gguf_cap
|
||
from core.inference.safetensors_agentic import _MAX_REPROMPTS as sf_cap
|
||
assert gguf_cap == sf_cap == 3
|
||
|
||
|
||
class TestLoopControl:
|
||
def test_cancel_event_breaks_loop(self):
|
||
cancel = threading.Event()
|
||
cancel.set()
|
||
# With cancel set, the loop bails before invoking execute_tool.
|
||
exec_fn = FakeExecuteTool([])
|
||
events = list(
|
||
run_safetensors_tool_loop(
|
||
single_turn = _const_stream(
|
||
'<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'
|
||
),
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [],
|
||
execute_tool = exec_fn,
|
||
cancel_event = cancel,
|
||
)
|
||
)
|
||
assert events == []
|
||
assert exec_fn.calls == []
|
||
|
||
def test_max_iterations_caps_loop(self):
|
||
# The loop stops after max_tool_iterations even if the model keeps
|
||
# asking for tools, then emits a final-attempt round.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
# Tool call (executes once).
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"a"}}</tool_call>'],
|
||
# Model gives a final answer when nudged.
|
||
["here is the final answer"],
|
||
],
|
||
exec_results = ["result"],
|
||
max_tool_iterations = 1,
|
||
)
|
||
events = _collect_events(loop)
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
# Final content must contain the final answer.
|
||
assert contents and "final answer" in contents[-1]["text"]
|
||
|
||
|
||
class TestStatusFormatting:
|
||
def test_status_for_known_tools(self):
|
||
# Call the private helper directly to verify status formatting.
|
||
assert (
|
||
safetensors_agentic._status_for_tool("web_search", {"query": "abc"}) == "Searching: abc"
|
||
)
|
||
assert (
|
||
safetensors_agentic._status_for_tool("web_search", {"url": "https://www.example.com/x"})
|
||
== "Reading: example.com"
|
||
)
|
||
assert safetensors_agentic._status_for_tool("python", {"code": "x = 1"}).startswith(
|
||
"Running Python:"
|
||
)
|
||
assert safetensors_agentic._status_for_tool("terminal", {"command": "ls"}).startswith(
|
||
"Running:"
|
||
)
|
||
assert safetensors_agentic._status_for_tool("unknown_tool", {}).startswith("Calling:")
|
||
|
||
|
||
class TestProseMentioningToolCall:
|
||
def test_assistant_prose_with_literal_tool_call_text_survives(self):
|
||
# Regression: prose that mentions a literal ``<tool_call>`` (no real call)
|
||
# must surface in full, not be stripped past the marker.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
# A real tool call so the loop advances a turn.
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
# Prose that mentions the literal text.
|
||
["the docs say <tool_call> means an LLM tool call wrapper"],
|
||
],
|
||
exec_results = ["result"],
|
||
)
|
||
events = _collect_events(loop)
|
||
contents = [e for e in events if e["type"] == "content"]
|
||
assert contents, "expected at least one content event"
|
||
final = contents[-1]["text"]
|
||
assert (
|
||
"LLM tool" in final
|
||
), f"prose mentioning <tool_call> should not be truncated; got {final!r}"
|
||
|
||
def test_tool_result_with_tool_call_text_does_not_retrigger(self):
|
||
# A literal ``<tool_call>`` in the tool result must not re-trigger: the
|
||
# loop parses only model output, so exactly one call.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
["the docs mention <tool_call> wrappers"],
|
||
],
|
||
exec_results = ["Page text: <tool_call> appears here in the docs"],
|
||
)
|
||
events = _collect_events(loop)
|
||
assert len(exec_fn.calls) == 1
|
||
|
||
|
||
class TestChatTemplateHelper:
|
||
"""Cover the dependency-light helper used by InferenceBackend."""
|
||
|
||
def setup_method(self):
|
||
from core.inference.chat_template_helpers import (
|
||
apply_chat_template_for_generation,
|
||
)
|
||
self.apply = apply_chat_template_for_generation
|
||
|
||
class _Tok:
|
||
def __init__(self, accepted):
|
||
self.accepted = accepted
|
||
self.call_count = 0
|
||
self.last_kwargs = None
|
||
|
||
def apply_chat_template(
|
||
self,
|
||
messages,
|
||
*,
|
||
tokenize = False,
|
||
add_generation_prompt = True,
|
||
**kw,
|
||
):
|
||
self.call_count += 1
|
||
unknown = set(kw) - self.accepted
|
||
if unknown:
|
||
raise TypeError(f"unexpected kwargs: {sorted(unknown)}")
|
||
self.last_kwargs = dict(kw)
|
||
return "PROMPT"
|
||
|
||
def test_richest_call_wins_when_template_supports_all(self):
|
||
tok = self._Tok({"tools", "enable_thinking"})
|
||
self.apply(tok, [], tools = [{}], enable_thinking = True)
|
||
assert tok.call_count == 1
|
||
assert tok.last_kwargs is not None
|
||
assert "tools" in tok.last_kwargs
|
||
assert "enable_thinking" in tok.last_kwargs
|
||
|
||
def test_falls_back_when_template_rejects_reasoning_kwarg(self):
|
||
tok = self._Tok({"tools"})
|
||
self.apply(tok, [], tools = [{}], enable_thinking = True)
|
||
assert tok.call_count >= 2
|
||
assert tok.last_kwargs == {"tools": [{}]}
|
||
|
||
def test_falls_back_to_bare_call(self):
|
||
tok = self._Tok(set())
|
||
self.apply(tok, [], tools = [{}], enable_thinking = True)
|
||
assert tok.last_kwargs == {}
|
||
|
||
def test_jinja_error_propagates(self):
|
||
class Boom:
|
||
def apply_chat_template(self, *a, **kw):
|
||
raise ValueError("jinja: missing var")
|
||
|
||
with pytest.raises(ValueError):
|
||
self.apply(Boom(), [])
|
||
|
||
def test_no_kwargs_single_call(self):
|
||
tok = self._Tok(set())
|
||
self.apply(tok, [])
|
||
assert tok.call_count == 1
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────────
|
||
# Guardrails (allowlist, budget, streaming-leak, dedup, id offset,
|
||
# auto_heal=False, canonical healed-arg key)
|
||
# ────────────────────────────────────────────────────────────────────
|
||
|
||
|
||
class TestGuardrails:
|
||
def test_disabled_tool_is_not_executed(self):
|
||
captured_messages: list[list[dict]] = []
|
||
|
||
def fake_single_turn(messages):
|
||
captured_messages.append([dict(message) for message in messages])
|
||
if len(captured_messages) == 1:
|
||
yield '<tool_call>{"name":"terminal","arguments":{"command":"echo bypass"}}</tool_call>'
|
||
else:
|
||
yield "final"
|
||
|
||
exec_fn = FakeExecuteTool([])
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = fake_single_turn,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 2,
|
||
)
|
||
)
|
||
|
||
assert exec_fn.calls == []
|
||
assert not [event for event in events if event.get("type") in {"tool_start", "tool_end"}]
|
||
disabled_nudges = [
|
||
message
|
||
for message in captured_messages[-1]
|
||
if message.get("role") == "user" and "not enabled" in message.get("content", "")
|
||
]
|
||
assert len(disabled_nudges) == 1
|
||
|
||
def test_empty_tools_list_means_allow_all_in_core_loop(self):
|
||
turns = iter(
|
||
[
|
||
['<tool_call>{"name":"python","arguments":{"code":"print(1)"}}</tool_call>'],
|
||
["done"],
|
||
]
|
||
)
|
||
|
||
def fake_single_turn(_messages, active_tools = None):
|
||
assert active_tools == []
|
||
acc = ""
|
||
for chunk in next(turns):
|
||
acc += chunk
|
||
yield acc
|
||
|
||
exec_fn = FakeExecuteTool(["OK"])
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = fake_single_turn,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 2,
|
||
)
|
||
)
|
||
assert exec_fn.calls == [("python", {"code": "print(1)"})]
|
||
assert any(event.get("type") == "tool_end" for event in events)
|
||
|
||
def test_max_iterations_zero_executes_no_tools(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>']],
|
||
exec_results = ["OK"],
|
||
max_tool_iterations = 0,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == []
|
||
assert events and events[-1] == {"type": "status", "text": ""}
|
||
|
||
def test_streaming_clips_before_tool_signal_no_leak(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
[
|
||
"I will look this up. ",
|
||
"Some more prose that's long enough to leave the buffer. ",
|
||
'<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>',
|
||
],
|
||
["all done"],
|
||
],
|
||
exec_results = ["weather: sunny"],
|
||
max_tool_iterations = 2,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "x"})]
|
||
for e in events:
|
||
if e["type"] == "content":
|
||
assert "<tool_call>" not in e["text"]
|
||
assert "web_search" not in e["text"]
|
||
|
||
def test_auto_heal_disabled_still_parses_valid_tool_call(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
["done"],
|
||
],
|
||
exec_results = ["OK"],
|
||
auto_heal_tool_calls = False,
|
||
max_tool_iterations = 2,
|
||
)
|
||
_collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "x"})]
|
||
|
||
def test_confirm_tool_calls_close_after_prompt_cleans_slot(self, monkeypatch):
|
||
approval_id = "approval-close-sf"
|
||
monkeypatch.setattr(safetensors_agentic, "new_approval_id", lambda: approval_id)
|
||
|
||
loop, exec_fn = _make_loop(
|
||
turns = [['<tool_call>{"name":"python","arguments":{"code":"print(1)"}}</tool_call>']],
|
||
exec_results = ["OK"],
|
||
confirm_tool_calls = True,
|
||
session_id = "sess",
|
||
max_tool_iterations = 1,
|
||
)
|
||
|
||
with tool_approvals._lock:
|
||
tool_approvals._pending.clear()
|
||
|
||
try:
|
||
assert next(loop)["type"] == "status"
|
||
start = next(loop)
|
||
assert start["type"] == "tool_start"
|
||
assert start["approval_id"] == approval_id
|
||
with tool_approvals._lock:
|
||
assert approval_id in tool_approvals._pending
|
||
finally:
|
||
loop.close()
|
||
|
||
with tool_approvals._lock:
|
||
assert approval_id not in tool_approvals._pending
|
||
assert resolve_tool_decision(approval_id, "allow", session_id = "sess") is False
|
||
assert exec_fn.calls == []
|
||
|
||
def test_confirm_tool_calls_skips_rag_autoinject(self, monkeypatch):
|
||
def fail_autoinject(*_args, **_kwargs):
|
||
raise AssertionError("RAG autoinject must not run before approval")
|
||
|
||
monkeypatch.setattr("core.inference.tools.build_rag_autoinject", fail_autoinject)
|
||
loop, exec_fn = _make_loop(
|
||
turns = [["plain answer"]],
|
||
confirm_tool_calls = True,
|
||
rag_scope = {"thread_id": "t1"},
|
||
)
|
||
events = _collect_events(loop)
|
||
assert any(e.get("type") == "content" and e.get("text") == "plain answer" for e in events)
|
||
assert exec_fn.calls == []
|
||
|
||
def test_auto_heal_disabled_preserves_xml_on_final_no_tools_pass(self):
|
||
turns = iter(
|
||
[
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"literal"}}</tool_call>'],
|
||
]
|
||
)
|
||
|
||
def fake_single_turn(_messages, active_tools = None):
|
||
acc = ""
|
||
for chunk in next(turns):
|
||
acc += chunk
|
||
yield acc
|
||
|
||
exec_fn = FakeExecuteTool(["OK"])
|
||
events = _collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = fake_single_turn,
|
||
messages = [{"role": "user", "content": "show literal"}],
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 1,
|
||
auto_heal_tool_calls = False,
|
||
)
|
||
)
|
||
assert exec_fn.calls == [("web_search", {"query": "x"})]
|
||
assert any(
|
||
event.get("type") == "content" and "<tool_call>" in event.get("text", "")
|
||
for event in events
|
||
)
|
||
|
||
def test_auto_heal_disabled_does_not_repair_unclosed_tool_call(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"x"}}'],
|
||
],
|
||
exec_results = ["OK"],
|
||
auto_heal_tool_calls = False,
|
||
max_tool_iterations = 1,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == []
|
||
assert any(
|
||
event.get("type") == "content" and "<tool_call>" in event.get("text", "")
|
||
for event in events
|
||
)
|
||
|
||
def test_auto_heal_enabled_strips_unparseable_xml_tool_call(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [["<tool_call>{not valid json}</tool_call>"]],
|
||
exec_results = ["OK"],
|
||
auto_heal_tool_calls = True,
|
||
max_tool_iterations = 1,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == []
|
||
assert not any(
|
||
event.get("type") == "content" and "<tool_call>" in event.get("text", "")
|
||
for event in events
|
||
)
|
||
|
||
def test_non_consecutive_duplicate_is_short_circuited(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"A"}}</tool_call>'],
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"B"}}</tool_call>'],
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"A"}}</tool_call>'],
|
||
["final"],
|
||
],
|
||
exec_results = ["res-A", "res-B"],
|
||
max_tool_iterations = 4,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "A"}), ("web_search", {"query": "B"})]
|
||
assert [
|
||
event.get("tool_call_id") for event in events if event.get("type") == "tool_end"
|
||
] == ["call_0", "call_1"]
|
||
assert not [
|
||
event
|
||
for event in events
|
||
if event.get("tool_call_id") == "call_2"
|
||
and event.get("type") in {"tool_start", "tool_end"}
|
||
]
|
||
|
||
def test_same_turn_duplicate_is_short_circuited(self):
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
[
|
||
'<tool_call>{"name":"web_search","arguments":{"query":"A"}}</tool_call>'
|
||
'<tool_call>{"name":"web_search","arguments":{"query":"A"}}</tool_call>'
|
||
],
|
||
["final"],
|
||
],
|
||
exec_results = ["res-A"],
|
||
max_tool_iterations = 2,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "A"})]
|
||
assert [
|
||
event.get("tool_call_id") for event in events if event.get("type") == "tool_end"
|
||
] == ["call_0"]
|
||
assert not [
|
||
event
|
||
for event in events
|
||
if event.get("tool_call_id") == "call_1"
|
||
and event.get("type") in {"tool_start", "tool_end"}
|
||
]
|
||
|
||
def test_same_turn_distinct_calls_are_capped(self):
|
||
# >_MAX_TOOL_CALLS_PER_TURN DISTINCT calls in one turn must be capped so a runaway turn
|
||
# cannot fan out into many executions (the GGUF path is held back by llama-server's lazy ...
|
||
from core.inference.safetensors_agentic import _MAX_TOOL_CALLS_PER_TURN
|
||
|
||
n = _MAX_TOOL_CALLS_PER_TURN + 4
|
||
turn = "".join(
|
||
'<tool_call>{"name":"web_search","arguments":{"query":"q%d"}}</tool_call>' % i
|
||
for i in range(n)
|
||
)
|
||
loop, exec_fn = _make_loop(
|
||
turns = [[turn], ["final"]],
|
||
exec_results = ["r"] * n,
|
||
max_tool_iterations = 2,
|
||
)
|
||
_collect_events(loop)
|
||
assert len(exec_fn.calls) == _MAX_TOOL_CALLS_PER_TURN
|
||
# The first N distinct queries executed, in document order.
|
||
assert [a["query"] for _name, a in exec_fn.calls] == [
|
||
"q%d" % i for i in range(_MAX_TOOL_CALLS_PER_TURN)
|
||
]
|
||
|
||
def test_coerce_string_args_python_uses_code_key(self):
|
||
assert _coerce_arguments("print(1)", heal = True, tool_name = "python") == {"code": "print(1)"}
|
||
|
||
def test_coerce_string_args_terminal_uses_command_key(self):
|
||
assert _coerce_arguments("ls -la", heal = True, tool_name = "terminal") == {"command": "ls -la"}
|
||
|
||
def test_tool_call_ids_unique_across_loop_iterations(self):
|
||
loop, _exec = _make_loop(
|
||
turns = [
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"A"}}</tool_call>'],
|
||
['<tool_call>{"name":"web_search","arguments":{"query":"B"}}</tool_call>'],
|
||
["done"],
|
||
],
|
||
exec_results = ["A", "B"],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
ids = [e["tool_call_id"] for e in events if e["type"] == "tool_start"]
|
||
assert len(ids) == 2 and ids[0] != ids[1]
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────────
|
||
# Shared gpt-oss name detector
|
||
# ────────────────────────────────────────────────────────────────────
|
||
|
||
|
||
class TestGptOssNameDetection:
|
||
def test_substring_match(self):
|
||
assert is_gpt_oss_model_name("unsloth/gpt-oss-20b") is True
|
||
|
||
def test_negative_known_non_oss_model(self):
|
||
assert is_gpt_oss_model_name("meta-llama/Llama-3.1-8B-Instruct") is False
|
||
|
||
def test_empty_or_none_returns_false(self):
|
||
assert is_gpt_oss_model_name("") is False
|
||
assert is_gpt_oss_model_name(cast(str, None)) is False
|
||
|
||
|
||
# Routes-level python_tag strip (multi-line; stop on next sentinel)
|
||
class TestRoutesPythonTagStrip:
|
||
"""``_TOOL_XML_RE`` must consume multi-line code, embedded JSON, and bare ``<`` (earlier ``[^\n<]*`` / ``[^\n]*`` revisions leaked tails); the streaming route-level strip is the regression-prone path."""
|
||
|
||
def _strip(self, text: str) -> str:
|
||
# Import inside the test so a routes-module import error does
|
||
# not blow up the entire test file at collection time.
|
||
from routes.inference import _strip_tool_xml
|
||
return _strip_tool_xml(text)
|
||
|
||
def test_single_line_python_tag_stripped(self):
|
||
# Floor: the original 5620 single-line behaviour still works.
|
||
text = '<|python_tag|>brave_search.call(query="weather")'
|
||
assert self._strip(text) == ""
|
||
|
||
def test_python_tag_with_less_than_in_code(self):
|
||
# 5615 regression: literal ``<`` inside code must NOT terminate
|
||
# the strip early.
|
||
text = '<|python_tag|>python.call(code="if x < 10: pass")'
|
||
assert self._strip(text) == ""
|
||
|
||
def test_python_tag_multiline_code_stripped(self):
|
||
# 5620 round-1 regression: multi-line code's second line leaked.
|
||
text = '<|python_tag|>python.call(code="line1\nline2\nline3")'
|
||
assert self._strip(text) == ""
|
||
|
||
def test_python_tag_multiline_with_less_than(self):
|
||
# Combined: multi-line code AND literal ``<`` in code.
|
||
text = (
|
||
'<|python_tag|>python.call(code="for i in range(10):\n'
|
||
" if i < 5:\n"
|
||
' print(i)")'
|
||
)
|
||
assert self._strip(text) == ""
|
||
|
||
def test_python_tag_stops_at_eom_sentinel(self):
|
||
# Strip stops at the next Llama-3 ``<|`` sentinel so any
|
||
# trailing assistant content survives.
|
||
text = '<|python_tag|>python.call(code="multi\nline")' "<|eom_id|>final answer text"
|
||
assert self._strip(text) == "<|eom_id|>final answer text"
|
||
|
||
def test_python_tag_stops_at_eot_sentinel(self):
|
||
text = '<|python_tag|>brave_search.call(query="x")' "<|eot_id|>after"
|
||
assert self._strip(text) == "<|eot_id|>after"
|
||
|
||
def test_python_tag_json_form_multiline_stripped(self):
|
||
# The JSON form of python_tag with newlines inside string args.
|
||
text = '<|python_tag|>{"name":"python","parameters":{"code":"a = 1\nb = 2\nprint(a+b)"}}'
|
||
assert self._strip(text) == ""
|
||
|
||
def test_python_tag_with_eom_then_trailing_python_tag(self):
|
||
# Two python_tag emissions back-to-back across a sentinel: both
|
||
# should strip independently.
|
||
text = (
|
||
'<|python_tag|>brave_search.call(query="a")'
|
||
"<|eom_id|>"
|
||
'<|python_tag|>python.call(code="x=1")'
|
||
)
|
||
# ``<|eom_id|>`` between the two strips remains; both
|
||
# python_tag blocks are fully consumed.
|
||
assert self._strip(text) == "<|eom_id|>"
|
||
|
||
|
||
# Robustness fixes uncovered while validating against vLLM / sglang.
|
||
class TestParserRobustness:
|
||
def test_tool_call_json_accepts_parameters_key(self):
|
||
# Hermes wrapper around a Llama-3.2 bare-JSON object that uses
|
||
# ``parameters`` instead of ``arguments``. The bare-JSON and
|
||
# python_tag paths already accept both keys; this path now does
|
||
# too. Was extracting name only and silently dropping the args.
|
||
import json
|
||
|
||
text = "<tool_call>\n" '{"name": "search", "parameters": {"q": "ramen"}}\n' "</tool_call>"
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "search"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"q": "ramen"}
|
||
|
||
def test_function_xml_attribute_form(self):
|
||
# MiniCPM-5 / MiniMax-M2 attribute syntax:
|
||
# ``<function name="..."><param name="...">v</param></function>``.
|
||
import json
|
||
|
||
text = '<function name="get_weather">' '<param name="city">Tokyo</param>' "</function>"
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "get_weather"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"city": "Tokyo"}
|
||
|
||
def test_function_xml_attribute_form_multi_param(self):
|
||
import json
|
||
|
||
text = (
|
||
'<function name="get_weather">'
|
||
'<param name="city">Tokyo</param>'
|
||
'<param name="unit">celsius</param>'
|
||
"</function>"
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
args = json.loads(result[0]["function"]["arguments"])
|
||
assert args == {"city": "Tokyo", "unit": "celsius"}
|
||
|
||
def test_function_xml_legacy_equals_form_still_works(self):
|
||
# Regression guard: the old ``<function=name><parameter=k>v``
|
||
# syntax must keep parsing after the regex broadening.
|
||
import json
|
||
|
||
text = "<function=get_weather><parameter=city>Tokyo</parameter></function>"
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "get_weather"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"city": "Tokyo"}
|
||
|
||
def test_function_attribute_form_has_tool_signal(self):
|
||
# The standalone ``<function name="...">`` attribute form must flip
|
||
# the streaming buffer; otherwise the end-of-turn safety-net parse in
|
||
# the agentic loop is gated off and the real call is dropped.
|
||
assert has_tool_signal('<function name="get_weather">') is True
|
||
|
||
def test_function_attribute_form_strip_markup(self):
|
||
# The attribute form must also be stripped from displayed text, like
|
||
# the legacy ``<function=...>`` form.
|
||
text = 'result <function name="g"><param name="c">X</param></function>'
|
||
assert strip_tool_markup(text, final = True) == "result"
|
||
|
||
def test_llama3_chat_template_round_trip(self):
|
||
# Meta's official Llama-3.x chat template prefixes every
|
||
# assistant turn with
|
||
# ``<|start_header_id|>assistant<|end_header_id|>\n\n``. The
|
||
# sentinel-strip in ``_parse_llama3_bare_json`` must reach past
|
||
# the role label to the JSON body, else every round-tripped
|
||
# tool call in history silently drops.
|
||
import json
|
||
|
||
text = (
|
||
"<|start_header_id|>assistant<|end_header_id|>\n\n"
|
||
'{"name": "get_weather", "parameters": {"city": "Tokyo"}}'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "get_weather"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"city": "Tokyo"}
|
||
|
||
def test_llama3_round_trip_all_roles(self):
|
||
# Same logic must work for every role the chat template inserts.
|
||
import json
|
||
for role in ("assistant", "user", "system", "tool", "ipython"):
|
||
text = (
|
||
f"<|start_header_id|>{role}<|end_header_id|>\n\n"
|
||
'{"name": "f", "parameters": {"x": 1}}'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1, f"failed for role={role}"
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"x": 1}
|
||
|
||
def test_llama3_round_trip_with_eot_prefix(self):
|
||
# Prior assistant turn closes with ``<|eot_id|>``, then the
|
||
# new header opens. Both sentinels + the role must be consumed.
|
||
import json
|
||
|
||
text = (
|
||
"<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
|
||
'{"name": "f", "parameters": {}}'
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert result[0]["function"]["name"] == "f"
|
||
|
||
def test_function_xml_followed_by_prose(self):
|
||
# Models routinely follow a tool call with explanatory prose.
|
||
# Body must terminate at ``</function>`` even without a
|
||
# ``</tool_call>`` wrapper, else trailing prose leaks into the
|
||
# last parameter value.
|
||
import json
|
||
|
||
text = (
|
||
"<function=get_weather>"
|
||
"<parameter=city>Tokyo</parameter>"
|
||
"</function>\n\nHere is what I found."
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"city": "Tokyo"}
|
||
|
||
def test_function_attribute_xml_followed_by_prose(self):
|
||
# Same expectation for the MiniCPM-5 attribute form.
|
||
import json
|
||
|
||
text = (
|
||
'<function name="get_weather">'
|
||
'<param name="city">Tokyo</param>'
|
||
"</function>\n\nLet me know if you need anything else."
|
||
)
|
||
result = parse_tool_calls_from_text(text)
|
||
assert len(result) == 1
|
||
assert json.loads(result[0]["function"]["arguments"]) == {"city": "Tokyo"}
|
||
|
||
|
||
def test_render_with_native_template_returns_render_only_when_tools_emitted():
|
||
# The native-template fallback re-renders with the model's repo template when an override drops
|
||
# the tools schema.
|
||
from types import SimpleNamespace
|
||
|
||
from core.inference.chat_template_helpers import render_native_template
|
||
|
||
messages = [{"role": "user", "content": "hi"}]
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}]
|
||
model_info = {
|
||
"native_chat_template": "TPL",
|
||
"tokenizer": SimpleNamespace(chat_template = "OVERRIDE"),
|
||
}
|
||
|
||
def emitting(tokenizer, msgs, *, tools, **_kw):
|
||
body = "".join(m["content"] for m in msgs)
|
||
return body + ("|TOOLS=" + ",".join(t["function"]["name"] for t in tools) if tools else "")
|
||
|
||
def ignoring(tokenizer, msgs, *, tools, **_kw):
|
||
return "".join(m["content"] for m in msgs) # never reflects tools
|
||
|
||
out = render_native_template(
|
||
model_info = dict(model_info),
|
||
active_model_name = "x",
|
||
messages = messages,
|
||
tools = tools,
|
||
apply_fn = emitting,
|
||
)
|
||
assert out == "hi|TOOLS=web_search"
|
||
# The native template must be restored on the live tokenizer after probing.
|
||
assert model_info["tokenizer"].chat_template == "OVERRIDE"
|
||
|
||
assert (
|
||
render_native_template(
|
||
model_info = dict(model_info),
|
||
active_model_name = "x",
|
||
messages = messages,
|
||
tools = tools,
|
||
apply_fn = ignoring,
|
||
)
|
||
is None
|
||
)
|
||
|
||
# No tokenizer and no processor -> return None instead of an AttributeError.
|
||
no_tok = {"native_chat_template": "TPL"}
|
||
assert (
|
||
render_native_template(
|
||
model_info = no_tok,
|
||
active_model_name = "x",
|
||
messages = messages,
|
||
tools = tools,
|
||
apply_fn = emitting,
|
||
)
|
||
is None
|
||
)
|
||
|
||
|
||
def test_render_with_native_template_does_not_mutate_shared_tokenizer():
|
||
# The shared tokenizer must never carry the temporary native template, even mid-render: this
|
||
# runs outside the generation lock, so a concurrent request could otherwise render with the ...
|
||
from types import SimpleNamespace
|
||
|
||
from core.inference.chat_template_helpers import render_native_template
|
||
|
||
shared = SimpleNamespace(chat_template = "OVERRIDE")
|
||
seen = []
|
||
|
||
def capture(tokenizer, msgs, *, tools, **_kw):
|
||
seen.append((tokenizer is shared, shared.chat_template))
|
||
body = "".join(m["content"] for m in msgs)
|
||
return body + ("|T" if tools else "")
|
||
|
||
model_info = {"native_chat_template": "TPL", "tokenizer": shared}
|
||
render_native_template(
|
||
model_info = model_info,
|
||
active_model_name = "x",
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}],
|
||
apply_fn = capture,
|
||
)
|
||
# Rendering happened on a copy, and the shared tokenizer stayed "OVERRIDE"
|
||
# throughout (never the temporary "TPL").
|
||
assert seen and all(not is_shared for is_shared, _ in seen)
|
||
assert all(tpl == "OVERRIDE" for _, tpl in seen)
|
||
assert shared.chat_template == "OVERRIDE"
|
||
|
||
|
||
def test_native_template_loads_from_base_model_for_lora(monkeypatch):
|
||
# For a LoRA adapter the chat template lives on the base model; active_model_name
|
||
# is the adapter id and may ship no template. The loader must read base_model.
|
||
from types import SimpleNamespace
|
||
|
||
import transformers
|
||
|
||
from core.inference.chat_template_helpers import render_native_template
|
||
|
||
captured = {}
|
||
|
||
def fake_from_pretrained(name, *args, **kwargs):
|
||
captured["source"] = name
|
||
return SimpleNamespace(chat_template = "BASE_TPL")
|
||
|
||
monkeypatch.setattr(transformers.AutoTokenizer, "from_pretrained", fake_from_pretrained)
|
||
|
||
def emitting(tokenizer, msgs, *, tools, **_kw):
|
||
body = "".join(m["content"] for m in msgs)
|
||
return body + ("|T" if tools else "")
|
||
|
||
model_info = {
|
||
"base_model": "base/model-id",
|
||
"tokenizer": SimpleNamespace(chat_template = "OVERRIDE"),
|
||
}
|
||
out = render_native_template(
|
||
model_info = model_info,
|
||
active_model_name = "adapter/path",
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}],
|
||
apply_fn = emitting,
|
||
)
|
||
assert captured["source"] == "base/model-id"
|
||
assert out == "hi|T"
|
||
|
||
|
||
def test_render_with_native_template_fallback_swaps_when_override_drops_tools():
|
||
# The shared gate (used by the transformers and MLX backends): when the live render is
|
||
# identical with and without tools, re-render with the native template and return it.
|
||
from types import SimpleNamespace
|
||
|
||
from core.inference.chat_template_helpers import render_with_native_template_fallback
|
||
|
||
messages = [{"role": "user", "content": "hi"}]
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}]
|
||
|
||
# apply_fn that IGNORES tools -> live render drops the schema.
|
||
def ignoring(tokenizer, msgs, *, tools, **_kw):
|
||
return "".join(m["content"] for m in msgs)
|
||
|
||
model_info = {
|
||
"native_chat_template": "TPL",
|
||
"tokenizer": SimpleNamespace(chat_template = "OVERRIDE"),
|
||
}
|
||
|
||
# Native render emits the tools, so the fallback swaps to it.
|
||
def native_emits(tokenizer, msgs, *, tools, **_kw):
|
||
body = "".join(m["content"] for m in msgs)
|
||
return body + ("|TOOLS" if tools else "")
|
||
|
||
out = render_with_native_template_fallback(
|
||
formatted_prompt = ignoring(None, messages, tools = tools),
|
||
tokenizer = SimpleNamespace(),
|
||
model_info = dict(model_info),
|
||
active_model_name = "x",
|
||
messages = messages,
|
||
tools = tools,
|
||
apply_fn = lambda tok, msgs, *, tools, **kw: (
|
||
native_emits(tok, msgs, tools = tools)
|
||
if getattr(tok, "chat_template", None) == "TPL"
|
||
else ignoring(tok, msgs, tools = tools)
|
||
),
|
||
)
|
||
assert out == "hi|TOOLS", out
|
||
|
||
|
||
def test_render_with_native_template_fallback_keeps_prompt_when_tools_emitted():
|
||
# Live render already differs with vs without tools -> no fallback, returned
|
||
# unchanged. Also a no-tools call is a passthrough.
|
||
from types import SimpleNamespace
|
||
|
||
from core.inference.chat_template_helpers import render_with_native_template_fallback
|
||
|
||
messages = [{"role": "user", "content": "hi"}]
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}]
|
||
|
||
def emitting(tokenizer, msgs, *, tools, **_kw):
|
||
body = "".join(m["content"] for m in msgs)
|
||
return body + ("|T" if tools else "")
|
||
|
||
kept = render_with_native_template_fallback(
|
||
formatted_prompt = emitting(None, messages, tools = tools),
|
||
tokenizer = SimpleNamespace(),
|
||
model_info = {"native_chat_template": "TPL", "tokenizer": SimpleNamespace()},
|
||
active_model_name = "x",
|
||
messages = messages,
|
||
tools = tools,
|
||
apply_fn = emitting,
|
||
)
|
||
assert kept == "hi|T", kept
|
||
|
||
# No tools -> passthrough (native template never consulted).
|
||
passthrough = render_with_native_template_fallback(
|
||
formatted_prompt = "hi",
|
||
tokenizer = SimpleNamespace(),
|
||
model_info = {},
|
||
active_model_name = "x",
|
||
messages = messages,
|
||
tools = None,
|
||
apply_fn = emitting,
|
||
)
|
||
assert passthrough == "hi"
|
||
|
||
|
||
def test_render_with_native_template_fallback_keeps_prompt_when_no_tools_probe_raises():
|
||
# A template that REQUIRES tools can raise on the no-tools probe.
|
||
from types import SimpleNamespace
|
||
|
||
from core.inference.chat_template_helpers import render_with_native_template_fallback
|
||
|
||
messages = [{"role": "user", "content": "hi"}]
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}]
|
||
|
||
def raises_without_tools(tokenizer, msgs, *, tools, **_kw):
|
||
if not tools:
|
||
raise RuntimeError("template requires tools")
|
||
return "".join(m["content"] for m in msgs) + "|T"
|
||
|
||
out = render_with_native_template_fallback(
|
||
formatted_prompt = "hi|T",
|
||
tokenizer = SimpleNamespace(),
|
||
model_info = {"native_chat_template": "TPL", "tokenizer": SimpleNamespace()},
|
||
active_model_name = "x",
|
||
messages = messages,
|
||
tools = tools,
|
||
apply_fn = raises_without_tools,
|
||
)
|
||
assert out == "hi|T", out
|
||
|
||
|
||
def test_truncated_bare_json_at_eof_is_not_leaked():
|
||
# Stream ends mid bare-JSON object: the held fragment must be dropped at the
|
||
# EOF resolver, not flushed as plain assistant content (GGUF parity).
|
||
loop, _exec = _make_loop(
|
||
turns = [['{"name":"web_search","parameters":{"query":"weather in S']],
|
||
max_tool_iterations = 1,
|
||
)
|
||
events = _collect_events(loop)
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any('"name"' in t for t in contents), contents
|
||
|
||
|
||
def test_oversized_bare_json_call_is_not_leaked_and_executes():
|
||
# A bare-JSON call whose arguments exceed _MAX_BARE_JSON_BUFFER must DRAIN
|
||
# (suppress) rather than stream the raw JSON prefix, and still execute once
|
||
# the full object is parsed by the safety net.
|
||
from core.inference.safetensors_agentic import _MAX_BARE_JSON_BUFFER
|
||
|
||
big = "A" * (_MAX_BARE_JSON_BUFFER + 5000)
|
||
full = '{"name":"python","parameters":{"code":"' + big + '"}}'
|
||
chunks = [full[i : i + 2000] for i in range(0, len(full), 2000)]
|
||
loop, exec_fn = _make_loop(turns = [chunks, ["done"]], exec_results = ["OK"], max_tool_iterations = 2)
|
||
events = _collect_events(loop)
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert not any(t.lstrip().startswith('{"name') for t in contents), contents[:1]
|
||
assert exec_fn.calls and exec_fn.calls[0][0] == "python"
|
||
assert len(exec_fn.calls[0][1].get("code", "")) > _MAX_BARE_JSON_BUFFER
|
||
|
||
|
||
def test_oversized_plain_json_answer_still_streams():
|
||
# A giant plain JSON answer (no "name" key) is NOT a tool call and must still
|
||
# stream -- the oversized DRAIN route is gated on a "name" key.
|
||
from core.inference.safetensors_agentic import _MAX_BARE_JSON_BUFFER
|
||
|
||
big = "A" * (_MAX_BARE_JSON_BUFFER + 5000)
|
||
full = '{"result":"' + big + '"}'
|
||
chunks = [full[i : i + 2000] for i in range(0, len(full), 2000)]
|
||
loop, _exec = _make_loop(turns = [chunks], max_tool_iterations = 1)
|
||
events = _collect_events(loop)
|
||
contents = "".join(e["text"] for e in events if e["type"] == "content")
|
||
assert '"result"' in contents
|
||
|
||
|
||
def test_oversized_disabled_name_json_answer_still_streams():
|
||
# A giant still-open JSON answer whose "name" is NOT an enabled tool must stream:
|
||
# the oversized DRAIN branch was gated only on the presence of a "name" key, so a
|
||
# large ordinary record ({"name":"Alice",...}) was drained instead of shown.
|
||
from core.inference.safetensors_agentic import _MAX_BARE_JSON_BUFFER
|
||
|
||
big = "A" * (_MAX_BARE_JSON_BUFFER + 5000)
|
||
answer = '{"name":"Alice","parameters":{"bio":"' + big # never closes
|
||
chunks = [answer[i : i + 2000] for i in range(0, len(answer), 2000)]
|
||
loop, exec_fn = _make_loop(turns = [chunks], max_tool_iterations = 1)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [], exec_fn.calls
|
||
contents = "".join(e["text"] for e in events if e["type"] == "content")
|
||
assert "Alice" in contents, contents[:80]
|
||
|
||
|
||
def test_truncated_disabled_name_json_is_shown_at_eof():
|
||
# A truncated ordinary JSON answer whose name is not an enabled tool, held to EOF,
|
||
# must be shown -- the EOF bare-JSON DRAIN branch was gated only on a "name" key.
|
||
truncated = '{"name":"Alice","parameters":{"age":'
|
||
loop, exec_fn = _make_loop(turns = [[truncated]], max_tool_iterations = 1)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [], exec_fn.calls
|
||
contents = "".join(e["text"] for e in events if e["type"] == "content")
|
||
assert "Alice" in contents, contents
|
||
|
||
|
||
def test_truncated_plain_json_with_nested_enabled_name_is_visible():
|
||
# A truncated ordinary JSON answer with a NESTED ``"name"`` matching an enabled
|
||
# tool ({"result":{"name":"web_search",...) must be shown, not suppressed: the
|
||
# gate now extracts the TOP-LEVEL name only, so the nested field is just data.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [['{"result":{"name":"web_search","age":']],
|
||
max_tool_iterations = 1,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == []
|
||
contents = "".join(e["text"] for e in events if e["type"] == "content")
|
||
assert '"result"' in contents and "web_search" in contents, contents
|
||
|
||
|
||
def test_bare_json_call_not_replayed_in_next_turn_content():
|
||
# After a complete bare-JSON call executes, the assistant content fed to the
|
||
# next turn must not contain the raw call (next-turn contamination).
|
||
captured: list[list[dict]] = []
|
||
exec_fn = FakeExecuteTool(["RESULT"])
|
||
|
||
def st(messages, active_tools = None):
|
||
captured.append([dict(m) for m in messages])
|
||
if len(captured) == 1:
|
||
yield '{"name":"web_search","parameters":{"query":"cats"}}'
|
||
else:
|
||
yield "Found."
|
||
|
||
_collect_events(
|
||
run_safetensors_tool_loop(
|
||
single_turn = st,
|
||
messages = [{"role": "user", "content": "cats"}],
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 3,
|
||
)
|
||
)
|
||
assert len(captured) >= 2, captured
|
||
asst = [m for m in captured[1] if m.get("role") == "assistant"]
|
||
assert asst and not any('"name"' in (m.get("content") or "") for m in asst), asst
|
||
|
||
|
||
if __name__ == "__main__":
|
||
pytest.main([__file__, "-v"])
|
||
|
||
|
||
def test_streaming_strip_keeps_bare_args_before_think_block():
|
||
# F3: a bare ``foo[ARGS]`` before a think block is prose; EOS-anchored tail arms run only
|
||
# on the last segment.
|
||
text = "Please pass foo[ARGS] <think>pause</think> to the template."
|
||
out = strip_tool_markup_streaming(text, tool_protocol_active = True)
|
||
assert out == text
|
||
|
||
|
||
def test_streaming_strip_still_removes_complete_call_before_think_block():
|
||
# A complete bracket call before a think block still strips in the non-last segment.
|
||
text = 'go web_search[ARGS]{"q":"x"} <think>z</think> done'
|
||
out = strip_tool_markup_streaming(text, tool_protocol_active = True)
|
||
assert "web_search[ARGS]" not in out
|
||
assert "<think>z</think>" in out
|
||
assert "go" in out and "done" in out
|
||
|
||
|
||
def test_prose_args_marker_before_real_call_does_not_drain_the_prose():
|
||
# F5: an inactive ``foo[ARGS]`` in prose is not a call boundary; the prose streams in
|
||
# full and the later real call still executes.
|
||
loop, exec_fn = _make_loop(
|
||
turns = [
|
||
["Intro ", "foo[ARGS] syntax. ", 'web_search[ARGS]{"query":"cats"}'],
|
||
["Cats are great."],
|
||
],
|
||
exec_results = ["RESULT"],
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [("web_search", {"query": "cats"})], exec_fn.calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
# The prose between the bogus marker and the real call must survive.
|
||
assert any("foo[ARGS] syntax." in t for t in contents), contents
|
||
# The real call markup is never shown as content.
|
||
assert not any("web_search[ARGS]" in t for t in contents), contents
|
||
|
||
|
||
def test_inactive_name_args_with_body_is_not_parsed_into_disabled_noop():
|
||
# BUG A: a prose answer with an inactive ``foo[ARGS]{...}`` is not drained into a
|
||
# disabled no-op extra turn; the [ARGS] checks are name-gated.
|
||
turns = [['foo[ARGS]{"x":1} is just syntax.']]
|
||
turn_calls: list[int] = []
|
||
|
||
def _gen(_messages):
|
||
turn_calls.append(1)
|
||
chunks = turns[len(turn_calls) - 1] if len(turn_calls) <= len(turns) else []
|
||
acc = ""
|
||
for chunk in chunks:
|
||
acc += chunk
|
||
yield acc
|
||
|
||
exec_fn = FakeExecuteTool([])
|
||
loop = run_safetensors_tool_loop(
|
||
single_turn = _gen,
|
||
messages = [{"role": "user", "content": "explain"}],
|
||
tools = [{"type": "function", "function": {"name": "web_search"}}],
|
||
execute_tool = exec_fn,
|
||
max_tool_iterations = 3,
|
||
)
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == [], exec_fn.calls
|
||
assert not any(e["type"] in ("tool_start", "tool_end") for e in events), events
|
||
# Exactly one generation turn -- no disabled ``foo`` no-op re-prompt.
|
||
assert len(turn_calls) == 1, turn_calls
|
||
contents = [e["text"] for e in events if e["type"] == "content"]
|
||
assert any("is just syntax." in t for t in contents), contents
|
||
|
||
|
||
class TestEnabledToolNameGate:
|
||
"""The safetensors loop passes the active tool names into parse/strip so the
|
||
ambiguous bare-rehearsal ``NAME[ARGS]{json}`` is treated as a call only when NAME
|
||
is an active tool (#5704). Without the gate an inactive ``foo[ARGS]{...}`` in prose
|
||
was parsed into a disabled no-op call and stripped from the visible text."""
|
||
|
||
def _names(self, calls):
|
||
return [c["function"]["name"] for c in calls]
|
||
|
||
def test_parse_inactive_rehearsal_does_not_swallow_active_call(self):
|
||
text = 'foo[ARGS]{"a":1} web_search[ARGS]{"query":"cats"}'
|
||
calls = parse_tool_calls_from_text(text, enabled_tool_names = {"web_search"})
|
||
assert self._names(calls) == ["web_search"]
|
||
assert json.loads(calls[0]["function"]["arguments"]) == {"query": "cats"}
|
||
|
||
def test_parse_inactive_rehearsal_alone_is_prose(self):
|
||
assert (
|
||
parse_tool_calls_from_text('foo[ARGS]{"a":1}', enabled_tool_names = {"web_search"}) == []
|
||
)
|
||
|
||
def test_streaming_strip_keeps_inactive_rehearsal(self):
|
||
raw = 'answer foo[ARGS]{"x":1} tail'
|
||
assert strip_tool_markup_streaming(raw, enabled_tool_names = {"web_search"}) == raw
|
||
|
||
def test_streaming_strip_removes_active_rehearsal(self):
|
||
raw = 'answer web_search[ARGS]{"q":1} tail'
|
||
out = strip_tool_markup_streaming(raw, enabled_tool_names = {"web_search"})
|
||
assert "web_search[ARGS]" not in out
|
||
assert out == "answer tail"
|
||
|
||
def test_final_strip_keeps_inactive_rehearsal(self):
|
||
text = 'foo[ARGS]{"x":1} is just syntax.'
|
||
assert strip_tool_markup(text, final = True, enabled_tool_names = {"web_search"}) == text
|
||
|
||
def test_gate_none_preserves_legacy_strip_and_parse(self):
|
||
text = 'foo[ARGS]{"x":1} tail'
|
||
assert self._names(parse_tool_calls_from_text(text)) == ["foo"]
|
||
assert strip_tool_markup_streaming(text) == " tail"
|
||
|
||
|
||
def test_drain_truncated_enabled_name_json_preserved_when_auto_heal_disabled():
|
||
# F3: with Auto-Heal OFF, a truncated ENABLED-name bare-JSON fragment that did
|
||
# not parse must stay visible (disabled-Auto-Heal contract: malformed markup is
|
||
# preserved), matching the XML strip in the same drain branch. With Auto-Heal ON
|
||
# the same fragment is suppressed.
|
||
trunc = '{"name":"web_search","parameters":{"query":"weather'
|
||
off, exec_off = _make_loop(turns = [[trunc]], max_tool_iterations = 1, auto_heal_tool_calls = False)
|
||
events_off = _collect_events(off)
|
||
assert exec_off.calls == [], exec_off.calls
|
||
contents_off = "".join(e["text"] for e in events_off if e["type"] == "content")
|
||
assert "web_search" in contents_off, contents_off
|
||
|
||
on, exec_on = _make_loop(turns = [[trunc]], max_tool_iterations = 1, auto_heal_tool_calls = True)
|
||
events_on = _collect_events(on)
|
||
assert exec_on.calls == [], exec_on.calls
|
||
contents_on = "".join(e["text"] for e in events_on if e["type"] == "content")
|
||
assert "web_search" not in contents_on, contents_on
|
||
|
||
|
||
def test_looks_like_enabled_bare_json_accepts_function_alias():
|
||
# The safetensors buffering gate must recognise the "function" bare-JSON alias
|
||
# the parser accepts, so a truncated/complete {"function":<enabled tool>} call is
|
||
# buffered/healed instead of streaming as visible content.
|
||
from core.inference.safetensors_agentic import _looks_like_enabled_bare_json
|
||
|
||
enabled = {"web_search"}
|
||
assert _looks_like_enabled_bare_json(
|
||
'{"function":"web_search","parameters":{"q":"x"}}', enabled
|
||
)
|
||
# A non-tool "function" value is an ordinary JSON answer -> not gated.
|
||
assert not _looks_like_enabled_bare_json('{"function":"Alice","parameters":{}}', enabled)
|
||
|
||
|
||
class TestFalseAlarmMarkerProse:
|
||
def test_leading_marker_prose_streams_intact(self):
|
||
# An answer that starts with a literal marker is a false alarm: the
|
||
# drain finds no calls and the full prose must reach the client.
|
||
text = "[TOOL_CALLS] is the Mistral tool marker. More prose after."
|
||
loop, exec_fn = _make_loop(turns = [[text]])
|
||
events = _collect_events(loop)
|
||
assert exec_fn.calls == []
|
||
texts = [e["text"] for e in events if e["type"] == "content"]
|
||
assert texts and texts[-1] == text
|
||
|
||
def test_chained_bare_json_calls_not_replayed_in_history(self):
|
||
# Both chained calls execute; the kept content (next-turn assistant
|
||
# history) must not contain the second call's raw JSON.
|
||
chained = (
|
||
'{"name":"web_search","parameters":{"q":"first"}};'
|
||
'{"name":"python","parameters":{"code":"x"}}'
|
||
)
|
||
convs = []
|
||
turn_iter = iter([[chained], ["Final answer."]])
|
||
|
||
def gen(messages, active_tools = None):
|
||
convs.append([dict(m) for m in messages])
|
||
try:
|
||
chunks = next(turn_iter)
|
||
except StopIteration:
|
||
return
|
||
acc = ""
|
||
for c in chunks:
|
||
acc += c
|
||
yield acc
|
||
|
||
exec_fn = FakeExecuteTool(["r1", "r2"])
|
||
loop = run_safetensors_tool_loop(
|
||
single_turn = gen,
|
||
messages = [{"role": "user", "content": "hi"}],
|
||
tools = [
|
||
{"type": "function", "function": {"name": "web_search"}},
|
||
{"type": "function", "function": {"name": "python"}},
|
||
],
|
||
execute_tool = exec_fn,
|
||
)
|
||
_collect_events(loop)
|
||
assert [c[0] for c in exec_fn.calls] == ["web_search", "python"]
|
||
assistant = next(m for m in convs[1] if m["role"] == "assistant")
|
||
assert '"python"' not in (assistant.get("content") or "")
|