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[Bugfix][Tool Parser] Stream tool calls that arrive whole in a single delta in llama3_json, jamba and ernie45 parsers - #48295
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… delta in llama3_json, jamba and ernie45 parsers When an entire tool call message arrives in one streamed delta (e.g. with async scheduling or stream_interval > 1, or when the whole message is emitted at once), the llama3_json and jamba streaming parsers recorded state for the newly seen tool and returned None without ever emitting the tool name or arguments. Since no further deltas arrive, the tool calls were silently lost while the same output parsed correctly in non-streaming mode. The ernie45 parser emitted only the first complete tool call found in a delta, stranding the rest in its internal buffer. Fix, following the same approach as vllm-project#47955 did for the gigachat3 and granite parsers: - llama3_json, jamba: when the first parsed delta already contains only complete tool calls, emit all of them (name + full arguments) in one DeltaMessage instead of returning None. - llama3_json, jamba: when several tools appear at once, grow streamed_args_for_tool to match current_tool_id instead of appending a single slot, which previously caused a swallowed IndexError that dropped subsequent argument deltas. - ernie45: drain every complete <tool_call>...</tool_call> block from the buffer per invocation instead of at most one, emitting one DeltaToolCall per block with correct indices. Add streaming regression tests for all three parsers; they fail on the previous parser code and pass with this change. Co-authored-by: Claude <noreply@anthropic.com> Signed-off-by: Abhay Singh <abhaysingh0293@gmail.com>
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Checked out the branch and verified this concretely rather than trusting the "before/after" claim in the description.
- Ran the 6 new tests (
test_streaming_complete_tool_call_single_delta*,test_streaming_parallel_tool_calls_single_delta,test_extract_tool_calls_streaming_single_delta,test_extract_tool_calls_streaming_multiple_tools_single_delta) on the fix branch: all pass. Fullllama3_json/jamba/ernie45test files: 21 pass, no regressions (remaining failures in the llama3_json file are pre-existing and unrelated — they need the gatedmeta-llama/Llama-3.2-1B-Instructtokenizer, which this sandbox can't authenticate to, exactly as the PR description notes). - Checked out the exact parent commit cited in the description (735def4), overlaid just the new test files, and reran: all 6 new tests fail exactly as described (empty response for llama3_json/jamba, first-tool-only for ernie45). So the bug and the fix are both independently confirmed, not just asserted.
While poking at this, I tested a scenario the new tests don't cover: real per-token incremental streaming (not the "whole message in one delta" case this PR targets) with 2 tool calls, using the actual ai21labs/Jamba-tiny-dev tokenizer via split_string_into_token_deltas. The last tool call's arguments comes out truncated — missing its closing quote/brace:
get_current_weather {"city": "Dallas", "state": "TX"} <- tool 0, correct
get_current_weather {"city": "Orlando", "state": "FL <- tool 1 (last), truncated
Non-streaming extract_tool_calls on the same text returns both correctly, so it's specifically a streaming-reconstruction gap. Tracing it token-by-token, the token that closes the string+object+array-element ("}}") arrives as its own delta and yields an empty arguments string instead of the closing punctuation.
Important: this reproduces identically on the parent commit (735def4) too, so it's not a regression from this PR — this PR's fast path (_emit_initial_complete_tool_calls) actually sidesteps it entirely for the case it targets, since it emits the full json.dumps'd arguments in one shot rather than diffing incrementally. The existing parallel_tools streaming test in test_jamba_tool_parser.py doesn't catch it because its assertion helper runs the accumulated string through partial_json_parser.ensure_json(...) before comparing, which silently repairs the truncated JSON before the assert_tool_calls check — a real client concatenating raw deltas (like the StreamingToolReconstructor this PR adds) would receive invalid JSON for the last parallel tool call. I didn't have access to the gated Llama tokenizer to check whether llama3_json has the same tail-loss pattern at real token granularity (a quick char-by-char probe didn't reproduce it there, but that's not representative of real BPE token boundaries), so I can't say whether it's jamba-specific or shared.
Not asking for changes here since it's pre-existing and out of scope for what this PR claims to fix, but worth a follow-up issue given it affects any Jamba response with 2+ parallel tool calls streamed normally (arguably more common than the single-delta case this PR addresses). The fix itself is correctly scoped and verified for what it targets.
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Hi @abhay-codes07 — the bug #48295 targets is still live on main, so we are reviving your work in a fresh PR (#65784). We re-verified the ernie45 symptom at Your drain-loop approach is the right shape, and the new PR keeps it. It also applies the same approach to jamba and granite-20b-fc. Those parsers show the same family of bugs: lost calls, name-less argument fragments, and stranded arguments. Your contribution is credited in the commit and the PR description. @ErenAta16 — you validated this back in July; the new PR keeps that history in its description. Would either of you like to review the new PR? |
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FIX #48294
Purpose
When an entire tool-call message arrives in a single streamed delta (async scheduling,
stream_interval > 1, or a short message emitted at once), three streaming tool parsers lose tool calls that the non-streaming path extracts correctly:llama3_json(also used forllama4_json) andjamba: the "starting a new tool" branch records state for the newly seen tool and returnsNonewithout emitting the name or arguments. No further deltas arrive, so the tool call is never emitted — the client gets an empty response.ernie45: only the first complete<tool_call>...</tool_call>block in a delta is emitted; the rest stay stranded in the internal buffer and are lost.This is the same bug class as #47907, fixed for
gigachat3/granite/granite-20b-fcin #47955. This PR extends the same approach to the three parsers above:llama3_json,jamba: when the first parsed delta already contains only complete tool calls, emit all of them (name + full arguments) in oneDeltaMessagevia a new_emit_initial_complete_tool_callshelper, mirroring [Bugfix][Tool Parser] Stream full single-delta tool calls #47955.llama3_json,jamba: when several tools appear at once, growstreamed_args_for_toolto matchcurrent_tool_idinstead of appending a single slot. Previously the resultingIndexErrorwas swallowed by the broad exception handler and silently dropped subsequent argument deltas.ernie45: drain every complete<tool_call>...</tool_call>block from the buffer per invocation instead of at most one, emitting oneDeltaToolCallper block with correct indices.Duplicate check: #47955 covers only
gigachat3/granite/granite-20b-fc; #46934 coversgranite4content loss. I found no open PR or issue addressing this forllama3_json,jamba, orernie45(searched open PRs/issues for the parser names, "single delta tool",check_tool_usage, and related terms).Test Plan
New streaming regression tests (no GPU needed; the
llama3_jsontests use a tokenizer stub so the gated Llama tokenizer is not required):pytest tests/tool_parsers/test_llama3_json_tool_parser.py \ tests/tool_parsers/test_jamba_tool_parser.py \ tests/tool_parsers/test_ernie45_moe_tool_parser.pyTest Result
On the parent commit (735def4), the 6 new tests fail exactly as described (streaming emits nothing for
llama3_json/jamba; only the first tool call forernie45). With this change:All existing tests in the three files pass as well (21 passed total on Linux/CPU, Python 3.12). The remaining pre-existing
llama3_jsontests error at fixture setup in my environment only because the gatedmeta-llama/Llama-3.2-1B-Instructtokenizer needs an HF token; they are unaffected by this change.pre-commit(ruff check/format, mypy, typos) passes on all changed files.Disclosure per the contributing guidelines: this PR was developed with AI assistance (Claude); commits carry a
Co-authored-bytrailer. I reviewed the changes and ran the tests above locally.