mirror of
https://github.com/zhenxun-org/zhenxun_bot.git
synced 2026-10-06 20:29:59 +08:00
✨ feat(llm): 增强LLM服务，支持图片生成、响应验证与OpenRouter集成 (#2054)
* ✨ feat(llm): 增强LLM服务，支持图片生成、响应验证与OpenRouter集成 - 【新功能】统一图片生成与编辑API `create_image`，支持文生图、图生图及多图输入 - 【新功能】引入LLM响应验证机制，通过 `validation_policy` 和 `response_validator` 确保响应内容符合预期，例如强制返回图片 - 【新功能】适配OpenRouter API，扩展LLM服务提供商支持，并添加OpenRouter特定请求头 - 【重构】将日志净化逻辑重构至 `log_sanitizer` 模块，提供统一的净化入口，并应用于NoneBot消息、LLM请求/响应日志 - 【修复】优化Gemini适配器，正确解析图片生成响应中的Base64图片数据，并更新模型能力注册表 * ✨ feat(image): 优化图片生成响应并返回完整LLMResponse * ✨ feat(llm): 为 OpenAI 兼容请求体添加日志净化 * 🐛 fix(ui): 截断UI调试HTML日志中的长base64图片数据 --------- Co-authored-by: webjoin111 <455457521@qq.com>
This commit is contained in:
Rumio
@@ -0,0 +1,202 @@
|
||||
import copy
|
||||
import re
|
||||
from typing import Any
|
||||
|
||||
from nonebot.adapters import Message, MessageSegment
|
||||
|
||||
|
||||
def _truncate_base64_string(value: str, threshold: int = 256) -> str:
|
||||
"""如果字符串是超长的base64或data URI，则截断它。"""
|
||||
if not isinstance(value, str):
|
||||
return value
|
||||
|
||||
prefixes = ("base64://", "data:image", "data:video", "data:audio")
|
||||
if value.startswith(prefixes) and len(value) > threshold:
|
||||
prefix = next((p for p in prefixes if value.startswith(p)), "base64")
|
||||
return f"[{prefix}_data_omitted_len={len(value)}]"
|
||||
return value
|
||||
|
||||
|
||||
def _sanitize_ui_html(html_string: str) -> str:
|
||||
"""
|
||||
专门用于净化UI渲染调试HTML的函数。
|
||||
它会查找所有内联的base64数据（如字体、图片）并将其截断。
|
||||
"""
|
||||
if not isinstance(html_string, str):
|
||||
return html_string
|
||||
|
||||
pattern = re.compile(r"(data:[^;]+;base64,)[A-Za-z0-9+/=\s]{100,}")
|
||||
|
||||
def replacer(match):
|
||||
prefix = match.group(1)
|
||||
original_len = len(match.group(0)) - len(prefix)
|
||||
return f"{prefix}[...base64_omitted_len={original_len}...]"
|
||||
|
||||
return pattern.sub(replacer, html_string)
|
||||
|
||||
|
||||
def _sanitize_nonebot_message(message: Message) -> Message:
|
||||
"""净化nonebot.adapter.Message对象，用于日志记录。"""
|
||||
sanitized_message = copy.deepcopy(message)
|
||||
for seg in sanitized_message:
|
||||
seg: MessageSegment
|
||||
if seg.type in ("image", "record", "video"):
|
||||
file_info = seg.data.get("file", "")
|
||||
if isinstance(file_info, str):
|
||||
seg.data["file"] = _truncate_base64_string(file_info)
|
||||
return sanitized_message
|
||||
|
||||
|
||||
def _sanitize_openai_response(response_json: dict) -> dict:
|
||||
"""净化OpenAI兼容API的响应体。"""
|
||||
try:
|
||||
sanitized_json = copy.deepcopy(response_json)
|
||||
if "choices" in sanitized_json and isinstance(sanitized_json["choices"], list):
|
||||
for choice in sanitized_json["choices"]:
|
||||
if "message" in choice and isinstance(choice["message"], dict):
|
||||
message = choice["message"]
|
||||
if "images" in message and isinstance(message["images"], list):
|
||||
for i, image_info in enumerate(message["images"]):
|
||||
if "image_url" in image_info and isinstance(
|
||||
image_info["image_url"], dict
|
||||
):
|
||||
url = image_info["image_url"].get("url", "")
|
||||
message["images"][i]["image_url"]["url"] = (
|
||||
_truncate_base64_string(url)
|
||||
)
|
||||
return sanitized_json
|
||||
except Exception:
|
||||
return response_json
|
||||
|
||||
|
||||
def _sanitize_openai_request(body: dict) -> dict:
|
||||
"""净化OpenAI兼容API的请求体，主要截断图片base64。"""
|
||||
try:
|
||||
sanitized_json = copy.deepcopy(body)
|
||||
if "messages" in sanitized_json and isinstance(
|
||||
sanitized_json["messages"], list
|
||||
):
|
||||
for message in sanitized_json["messages"]:
|
||||
if "content" in message and isinstance(message["content"], list):
|
||||
for i, part in enumerate(message["content"]):
|
||||
if part.get("type") == "image_url":
|
||||
if "image_url" in part and isinstance(
|
||||
part["image_url"], dict
|
||||
):
|
||||
url = part["image_url"].get("url", "")
|
||||
message["content"][i]["image_url"]["url"] = (
|
||||
_truncate_base64_string(url)
|
||||
)
|
||||
return sanitized_json
|
||||
except Exception:
|
||||
return body
|
||||
|
||||
|
||||
def _sanitize_gemini_response(response_json: dict) -> dict:
|
||||
"""净化Gemini API的响应体，处理文本和图片生成两种格式。"""
|
||||
try:
|
||||
sanitized_json = copy.deepcopy(response_json)
|
||||
|
||||
def _process_candidates(candidates_list: list):
|
||||
"""辅助函数，用于处理任何 candidates 列表。"""
|
||||
if not isinstance(candidates_list, list):
|
||||
return
|
||||
for candidate in candidates_list:
|
||||
if "content" in candidate and isinstance(candidate["content"], dict):
|
||||
content = candidate["content"]
|
||||
if "parts" in content and isinstance(content["parts"], list):
|
||||
for i, part in enumerate(content["parts"]):
|
||||
if "inlineData" in part and isinstance(
|
||||
part["inlineData"], dict
|
||||
):
|
||||
data = part["inlineData"].get("data", "")
|
||||
if isinstance(data, str) and len(data) > 256:
|
||||
content["parts"][i]["inlineData"]["data"] = (
|
||||
f"[base64_data_omitted_len={len(data)}]"
|
||||
)
|
||||
|
||||
if "candidates" in sanitized_json:
|
||||
_process_candidates(sanitized_json["candidates"])
|
||||
|
||||
if "image_generation" in sanitized_json and isinstance(
|
||||
sanitized_json["image_generation"], dict
|
||||
):
|
||||
if "candidates" in sanitized_json["image_generation"]:
|
||||
_process_candidates(sanitized_json["image_generation"]["candidates"])
|
||||
|
||||
return sanitized_json
|
||||
except Exception:
|
||||
return response_json
|
||||
|
||||
|
||||
def _sanitize_gemini_request(body: dict) -> dict:
|
||||
"""净化Gemini API的请求体，进行结构转换和总结。"""
|
||||
try:
|
||||
sanitized_body = copy.deepcopy(body)
|
||||
if "contents" in sanitized_body and isinstance(
|
||||
sanitized_body["contents"], list
|
||||
):
|
||||
for content_item in sanitized_body["contents"]:
|
||||
if "parts" in content_item and isinstance(content_item["parts"], list):
|
||||
media_summary = []
|
||||
new_parts = []
|
||||
for part in content_item["parts"]:
|
||||
if "inlineData" in part and isinstance(
|
||||
part["inlineData"], dict
|
||||
):
|
||||
data = part["inlineData"].get("data")
|
||||
if isinstance(data, str):
|
||||
mime_type = part["inlineData"].get(
|
||||
"mimeType", "unknown"
|
||||
)
|
||||
media_summary.append(f"{mime_type} ({len(data)} chars)")
|
||||
continue
|
||||
new_parts.append(part)
|
||||
|
||||
if media_summary:
|
||||
summary_text = (
|
||||
f"[多模态内容: {len(media_summary)}个文件 - "
|
||||
f"{', '.join(media_summary)}]"
|
||||
)
|
||||
new_parts.insert(0, {"text": summary_text})
|
||||
|
||||
content_item["parts"] = new_parts
|
||||
return sanitized_body
|
||||
except Exception:
|
||||
return body
|
||||
|
||||
|
||||
def sanitize_for_logging(data: Any, context: str | None = None) -> Any:
|
||||
"""
|
||||
统一的日志净化入口。
|
||||
|
||||
Args:
|
||||
data: 需要净化的数据 (dict, Message, etc.).
|
||||
context: 净化场景的上下文标识，例如 'gemini_request', 'openai_response'.
|
||||
|
||||
Returns:
|
||||
净化后的数据。
|
||||
"""
|
||||
if context == "nonebot_message":
|
||||
if isinstance(data, Message):
|
||||
return _sanitize_nonebot_message(data)
|
||||
elif context == "openai_response":
|
||||
if isinstance(data, dict):
|
||||
return _sanitize_openai_response(data)
|
||||
elif context == "gemini_response":
|
||||
if isinstance(data, dict):
|
||||
return _sanitize_gemini_response(data)
|
||||
elif context == "gemini_request":
|
||||
if isinstance(data, dict):
|
||||
return _sanitize_gemini_request(data)
|
||||
elif context == "openai_request":
|
||||
if isinstance(data, dict):
|
||||
return _sanitize_openai_request(data)
|
||||
elif context == "ui_html":
|
||||
if isinstance(data, str):
|
||||
return _sanitize_ui_html(data)
|
||||
else:
|
||||
if isinstance(data, str):
|
||||
return _truncate_base64_string(data)
|
||||
|
||||
return data
|
||||
Reference in New Issue
Block a user