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https://github.com/p-e-w/heretic.git
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feat: A better logic for detecting the thinking prefix in the response. (#423)
* fix: Check response prefix. In case if the model adds <think> at the end of user prompt and only generates </think> end, then the detection goes wrong. * fix: Handle whitespace in CoT, remove redundant checks * fix: Type checker * fix: try looking at tag positions, not text end regex * ruff, fix import sorting * fix: rich markup * fix: I missed other ones * feat: Update SHA256SUMS file hashes in the tests. A major change that affects reproducibility. * fix: It is now sensible to also update the extra SHA256SUMS.ci2 file. * fix: Only consider whitespace, no other text or instructions. because mistral-3 as additional reasoning instructions in its chat template. And I suppose many other models can have it too. * fix: Update windows hashes. * fix: Update CI hashes too * as always update case two of mistral-3 (ci2 hash) * docs: update comment * feat: Handle the edge case for models having additional instructions. * fix: Update windows hash for mistral-3 * docs: remove a line from the comments because I'm not sure about GPT-OSS models' thinking tags and it cannot be confirmed using an untrained tiny GPT-OSS model. And inference fallback would of course generate gibberish as the model cannot understand additional instructions about 'how to generate response and how to think' from the chat_template. * fix: a few things. * fix: Update hash for qwen3.5 after the whitespace fix for its response prefix. * docs: Update comment * fix: Update qwen3.5 hash for CI * fix: Remove Case 2 which only serves tests unnecessary * fix: Hash * fix: concern is valid enough, so we use a small text. add a comment too * docs: minor
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@@ -39,13 +39,14 @@ import logging
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import math
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import os
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import random
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import re
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import time
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import warnings
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from dataclasses import asdict
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from importlib.metadata import version
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from os.path import commonprefix
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from pathlib import Path
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from typing import Any
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from typing import Any, cast
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import huggingface_hub
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import lm_eval
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@@ -65,6 +66,7 @@ from optuna.storages.journal import JournalFileBackend, JournalFileOpenLock
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from optuna.trial import FrozenTrial, TrialState, create_trial
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from pydantic import ValidationError
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from questionary import Choice, Style
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from rich.markup import escape
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from rich.table import Table
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from rich.text import Text
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from rich.traceback import install
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@@ -477,40 +479,88 @@ def run():
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print()
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print("Checking for common response prefix...")
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prefix_check_prompts = good_prompts[:100] + bad_prompts[:100]
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responses = model.get_responses_batched(prefix_check_prompts)
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# Despite being located in os.path, commonprefix actually performs
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# a naive string operation without any path-specific logic,
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# which is exactly what we need here. Trailing spaces are removed
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# to avoid issues where multiple different tokens that all start
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# with a space character lead to the common prefix ending with
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# a space, which would result in an uncommon tokenization.
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settings.response_prefix = commonprefix(responses).rstrip(" ")
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# Detect if the model's chat template inserts a reasoning tag on its own
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# at the end of user's prompt (e.g. <think>) by using a dummy prompt.
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# If found, then we use the full closed CoT as the response prefix.
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# LiquidAI's LFM models do this (Lfm2ForCausalLM).
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if settings.response_prefix:
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print(f"* Prefix found: [bold]{settings.response_prefix!r}[/]")
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# This cast is valid because str is the return type
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# for a single chat operation with tokenize=False.
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dummy_prompt = cast(
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str,
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model.tokenizer.apply_chat_template(
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[{"role": "user", "content": "This is a dummy prompt."}],
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add_generation_prompt=True,
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tokenize=False,
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),
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)
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for cot_initializer, closed_cot_block in settings.chain_of_thought_skips:
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if settings.response_prefix.startswith(cot_initializer):
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settings.response_prefix = closed_cot_block
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print(
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f"* Closed Chain-of-Thought block: [bold]{settings.response_prefix!r}[/]"
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)
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cot_skip_applied = False
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# When using a Chain-of-Thought skip, we need to check that the prefix
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# is actually complete (e.g. not missing a trailing newline).
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print("* Rechecking with prefix...")
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responses = model.get_responses_batched(prefix_check_prompts)
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additional_prefix = commonprefix(responses).rstrip(" ")
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if additional_prefix:
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settings.response_prefix += additional_prefix
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for cot_initializer, closed_cot_block in settings.chain_of_thought_skips:
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# Match the tag and ignore any whitespace characters following it at the end
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# (if any), including spaces, tabs, and linebreaks. This is required for models
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# having whitespaces after the tags.
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pattern = rf"{re.escape(cot_initializer)}\s*$"
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match = re.search(pattern, dummy_prompt)
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if match:
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# We use only the closed CoT block here. Any whitespaces
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# will be handled by the 'Rechecking with prefix' logic below.
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settings.response_prefix = closed_cot_block
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print(
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f"* Closed Chain-of-Thought block: [bold]{escape(repr(settings.response_prefix))}[/]"
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)
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cot_skip_applied = True
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break
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# Fallback to inference for models like mistral-3 which are specifically
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# instructed to generate thinking tags using the system prompt in their
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# chat template, instead of inserting a prefix tag (e.g. <think>) at
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# the end of user prompt like the case above. We expect the model to
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# generate those tags.
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if settings.response_prefix is None:
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responses = model.get_responses_batched(prefix_check_prompts)
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# Despite being located in os.path, commonprefix actually performs
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# a naive string operation without any path-specific logic,
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# which is exactly what we need here. Trailing spaces are removed
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# to avoid issues where multiple different tokens that all start
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# with a space character lead to the common prefix ending with
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# a space, which would result in an uncommon tokenization.
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settings.response_prefix = commonprefix(responses).rstrip(" ")
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if settings.response_prefix:
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print(
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f"* Prefix found: [bold]{escape(repr(settings.response_prefix))}[/]"
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)
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for (
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cot_initializer,
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closed_cot_block,
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) in settings.chain_of_thought_skips:
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if settings.response_prefix.startswith(cot_initializer):
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settings.response_prefix = closed_cot_block
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print(
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f"* Extended prefix found: [bold]{settings.response_prefix!r}[/]"
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f"* Closed Chain-of-Thought block: [bold]{escape(repr(settings.response_prefix))}[/]"
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)
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cot_skip_applied = True
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break
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else:
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print("* None found")
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break
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else:
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print("* None found")
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if cot_skip_applied:
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# When using a Chain-of-Thought skip, we need to check that the prefix
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# is actually complete (e.g. not missing a trailing newline).
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print("* Rechecking with prefix...")
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responses = model.get_responses_batched(prefix_check_prompts)
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additional_prefix = commonprefix(responses).rstrip(" ")
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if additional_prefix:
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settings.response_prefix += additional_prefix
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print(
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f"* Extended prefix found: [bold]{escape(repr(settings.response_prefix))}[/]"
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)
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evaluator = Evaluator(settings, model)
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@@ -1,7 +1,7 @@
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72f84af4ea36b82409c35e31b584361534305ef7c0d90fce20d0dc38a7efead8 *chat_template.jinja
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e4c5278b361c57621253c27a2c3db358e1580aec8a14be8e19d4420a224137cf *config.json
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8dde85c000ae807be907421465826c7c63a39f6acf6d04a5a84efaf116ed4ef7 *generation_config.json
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29aff97d5633dead9e1ccd29a2cc153b4b7431d22f63c8d6cf60bc6547681cc9 *model.safetensors
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20b5a820b38438202c64e4fc9807bd19e29678bebd678d29b2ee2d2f5bf71587 *model.safetensors
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20e7a6dcde0a6f60ea3b4fb08f6f7afa62532dda93a3111e28384ba5150575f9 *processor_config.json
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c3a8d92e371b92a2cd6e678e31ebc27d0235e929a51fbf290f74742b341fa96f *tokenizer.json
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60a8042e29b4b20e884e48375aa1b9ac0025547371d50e60f6d55e6a9675e868 *tokenizer_config.json
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@@ -1,7 +1,7 @@
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a4aee8afcf2e0711942cf848899be66016f8d14a889ff9ede07bca099c28f715 *chat_template.jinja
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749b56d1b1e08081981169db6f2c44ab0be4fd6ebb452d15baafa5e09c21586a *config.json
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4625d1d64d41d1fa9dae7af4ba1e1d7e65a194073d4efa58acb266a916eaaa74 *generation_config.json
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5fb94c65bcd9d736735a45e50c2b0bfafd3bb09a444c49b8cff2e131ed35797e *model.safetensors
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2b3e575ac065f11ae5d4a7c3740efccbed294b646f1645239191ee8393354e03 *model.safetensors
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01562eddd6f9e9ec4bc31656a3b7055284cafbf889acc6c4348dca431ae31f68 *processor_config.json
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87a7830d63fcf43bf241c3c5242e96e62dd3fdc29224ca26fed8ea333db72de4 *tokenizer.json
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2e31d1126e81bddf8d15c3f95260fb487b48c5131b24fcbb5bb9d2537e7afac0 *tokenizer_config.json
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@@ -1,7 +1,7 @@
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a92e1dd97cb1cb175c9b70c0828e146bea4371c2643319b661b777e89811972e *chat_template.jinja
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b75e911805663da79fb9fbbbcc917b8f1a285d2da54d95c2c63ea7c1ffe9a05a *config.json
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2cbd9df0e99570efcced23b8d777bdf1fc692efda54b21eb59ad56ade76c9db6 *generation_config.json
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5f099b32807d0b84ed90765ca0ed53f8771da4738767bc1940486fec954570cf *model.safetensors
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6061519a9595326df41abcdd093892463793d4d026d6fd23548f1792f622a252 *model.safetensors
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0c29f9491e769aabbc389ad5912127cf6d9d5fceda2db8767f73d48131348c81 *processor_config.json
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87a7830d63fcf43bf241c3c5242e96e62dd3fdc29224ca26fed8ea333db72de4 *tokenizer.json
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4796e48d790a26d65f167bec8fc742beaa71f79f9468a6cd8b3ffa97f6e2a198 *tokenizer_config.json
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