fuquan/nonebot-plugin-llmchat
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✨ 发送图片可参考

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slexce 2026-03-11 00:00:04 +08:00
parent 25a9cd0d76
commit 7e87981167
3 changed files with 86 additions and 16 deletions
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22
nonebot_plugin_llmchat/__init__.py
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@ -418,6 +418,9 @@ async def process_messages(context_id: int, is_group: bool = True):
content: list[ChatCompletionContentPartParam] = []
# 收集用户消息中的图片（用于传递给子模型作为参考）
user_message_images: list[str] = []
# 将机器人错过的消息推送给LLM
past_events_snapshot = list(state.past_events)
state.past_events.clear()
@ -426,11 +429,19 @@ async def process_messages(context_id: int, is_group: bool = True):
content.append({"type": "text", "text": text_content})
# 将消息中的图片转成 base64
base64_images = await process_images(ev)
# 收集图片用于子模型调用
user_message_images.extend(base64_images)
# 如果主模型支持图片输入，也传递给主模型
if preset.support_image:
base64_images = await process_images(ev)
for base64_image in base64_images:
content.append({"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}})
if user_message_images:
logger.info(f"用户消息中包含 {len(user_message_images)} 张图片，将用于子模型调用")
new_messages: list[ChatCompletionMessageParam] = [
{"role": "user", "content": content}
]
@ -484,6 +495,9 @@ async def process_messages(context_id: int, is_group: bool = True):
# 发送工具调用提示
await handler.send(Message(f"正在使用{mcp_client.get_friendly_name(tool_name)}"))
# 对于子模型调用，传递用户消息中的图片作为参考
images_for_submodel = user_message_images if tool_name.startswith("submodel__") else None
if is_group:
result = await mcp_client.call_tool(
tool_name,
@ -492,7 +506,8 @@ async def process_messages(context_id: int, is_group: bool = True):
bot_id=str(event.self_id),
user_id=event.user_id,
is_group=True,
current_preset=preset
current_preset=preset,
user_images=images_for_submodel
)
else:
result = await mcp_client.call_tool(
@ -501,7 +516,8 @@ async def process_messages(context_id: int, is_group: bool = True):
bot_id=str(event.self_id),
user_id=event.user_id,
is_group=False,
current_preset=preset
current_preset=preset,
user_images=images_for_submodel
)
# 处理子模型返回的结构化结果