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8b306b3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 | # Copyright (c) 2025 ByteDance Ltd. and/or its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import annotations
from typing import Any, Dict, List, Tuple
from jinja2 import Environment, BaseLoader
# —— 模板：用显式 \n 控制换行，并用 -%} / {%- 去掉多余空白 ——
JINJA_PROMPT_TMPL = (
"<|im_start|>system\n"
"{{ system_prompt }}<|im_end|>\n"
"{% for m in msgs -%}"
"<|im_start|>{{ m.role }}\n"
"{% if not (m.role == 'assistant' and not include_assistant_content) -%}"
"{{ m.content | render_mm_list }}"
"{% endif -%}"
"{% if (not (loop.last and m.role == 'assistant')) or include_assistant_content -%}"
"<|im_end|>\n"
"{% endif -%}"
"{% endfor -%}"
)
VS, VE = "<|vision_start|>", "<|vision_end|>"
VP, IP = "<|video_pad|>", "<|image_pad|>"
def expand_and_index_by_token_ids_new(
rendered_text: str,
tokens: List[int], # 遇到 VP/IP 的顺序逐个取 K
tokenizer, # HF tokenizer（需含 VP/IP/VE/VS 等special tokens）
target_text: str = "", # 如 "assistant\n"
search_text: str = "", # 如 ""
) -> Tuple[str, List[int], List[List[int]], List[int]]:
"""
返回:
new_rendered_text: 扩展后的文本
all_token_id : new_rendered_text 的 token ids
spans_index : 每个pad块在 all_token_id 中的索引列表（按出现顺序），如 [[100..199], [350..549], ...]
tgt_index : target_text 在 all_token_id 中的索引列表（找不到返回 []）
"""
vs_ids = tokenizer(VS, add_special_tokens=False)["input_ids"]
ve_ids = tokenizer(VE, add_special_tokens=False)["input_ids"]
vp_ids = tokenizer(VP, add_special_tokens=False)["input_ids"]
ip_ids = tokenizer(IP, add_special_tokens=False)["input_ids"]
enc = tokenizer(rendered_text, add_special_tokens=False)
base_ids = enc["input_ids"]
# ---------- 1) 扫描并按出现顺序扩展 VP/IP 为 K 次，占位信息入 pad_blocks ----------
# find all VS positions and pair them with nearest VE after each VS
all_ids: List[int] = []
spans_index: List[List[int]] = []
i = 0 # base_ids 扫描指针
tk_ptr = 0 # tokens(K) 指针
while True:
try:
vs_positions_ = base_ids[i:].index(vs_ids[0]) + i
except:
all_ids.extend(base_ids[i:])
break
all_ids.extend(base_ids[i: vs_positions_])
i = vs_positions_ + 3
# 进行序列扩展，插入占位信息入 pad_ids
pad_ids = base_ids[vs_positions_ + 1:vs_positions_ + 2]
K = int(tokens[tk_ptr])
start, end = len(all_ids) + 1, len(all_ids) + 1 + K
all_ids.extend(vs_ids + pad_ids * K + ve_ids)
tk_ptr += 1
# 获取 每个pad token 在 all_token_id 中的索引列表（按出现顺序），如 [[100..199], [350..549], ...]
#start, end = vs_positions_ + 1, vs_positions_ + 1 + K
spans_index.append(list(range(start, end)))
tgt_index: List[int] = []
if target_text:
tgt_ids_identify = tokenizer(target_text, add_special_tokens=False)["input_ids"]
i = 0 # base_ids 扫描指针
while i < len(all_ids):
tgt_positions_ = all_ids[i:].index(tgt_ids_identify[0]) + i
if all_ids[tgt_positions_+len(tgt_ids_identify)-1] == tgt_ids_identify[-1]:
tgt_index = list(range(tgt_positions_+len(tgt_ids_identify), len(all_ids)))
break
else:
i = tgt_positions_ + 1
search_index: List[int] = []
if search_text:
search_ids_identify = tokenizer(search_text, add_special_tokens=False)["input_ids"]
i = 0 # base_ids 扫描指针
while i < len(all_ids):
search_positions_ = all_ids[i:].index(search_ids_identify[0]) + i
if all_ids[search_positions_:search_positions_+len(search_ids_identify)] == search_ids_identify:
search_index = list(range(search_positions_, search_positions_+len(search_ids_identify)))
break
else:
i = search_positions_ + 1
return all_ids, spans_index, tgt_index, search_index
def _extract_system_prompt(messages: List[Dict[str, Any]], default_system: str) -> str:
for m in messages:
if m.get("role") == "system":
c = m.get("content", "")
if isinstance(c, str):
return c
if isinstance(c, list):
texts = [it.get("text", "") for it in c if isinstance(it, dict) and it.get("type") == "text"]
if texts:
return "".join(texts)
return default_system
def _normalize_messages(messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
norm: List[Dict[str, Any]] = []
for m in messages:
role = m.get("role")
if role == "system":
continue
c = m.get("content", "")
if isinstance(c, str):
items = [{"type": "text", "text": c}]
elif isinstance(c, list):
items = c
else:
items = []
norm.append({"role": role, "content": items})
return norm
def render_qwenvl_prompt(
messages: List[Dict[str, Any]],
default_system: str = "You are a helpful assistant.",
include_assistant_content: bool = False, # 关键参数：是否渲染 assistant 文本
force_video_pad: bool = False,
) -> str:
system_prompt = _extract_system_prompt(messages, default_system)
msgs = _normalize_messages(messages)
def _render_mm_list(items: Any) -> str:
if isinstance(items, str):
return items
if not isinstance(items, list):
return ""
parts: List[str] = []
for it in items:
if not isinstance(it, dict):
continue
t = it.get("type")
if t == "text":
parts.append(it.get("text", ""))
elif t == "image":
if force_video_pad:
parts.append("<|vision_start|><|image_pad|><|vision_end|>")
else:
parts.append("<|vision_start|><|video_pad|><|vision_end|>")
elif t == "video":
parts.append("<|vision_start|><|video_pad|><|vision_end|>")
# 其他模态可在这里扩展
return "".join(parts)
env = Environment(
loader=BaseLoader(),
autoescape=False,
trim_blocks=True, # 去掉块结束后的换行
lstrip_blocks=True, # 去掉块起始前的空白
newline_sequence="\n",
keep_trailing_newline=False,
)
env.filters["render_mm_list"] = _render_mm_list
template = env.from_string(JINJA_PROMPT_TMPL)
return template.render(
system_prompt=system_prompt,
msgs=msgs,
include_assistant_content=include_assistant_content,
)
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