feat: 重构了智能思维导图和摘要插件的事件发射逻辑，并新增了插件开发指南。
This commit is contained in:
fujie
@@ -305,11 +305,11 @@ CONTENT_TEMPLATE_SUMMARY = """
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class Action:
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class Valves(BaseModel):
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show_status: bool = Field(
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SHOW_STATUS: bool = Field(
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default=True,
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description="Whether to show operation status updates in the chat interface.",
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)
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LLM_MODEL_ID: str = Field(
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MODEL_ID: str = Field(
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default="",
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description="Built-in LLM Model ID used for text analysis. If empty, uses the current conversation's model.",
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)
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@@ -381,6 +381,20 @@ class Action:
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"actions_html": actions_html,
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}
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async def _emit_status(self, emitter, description: str, done: bool = False):
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"""Emits a status update event."""
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if self.valves.SHOW_STATUS and emitter:
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await emitter(
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{"type": "status", "data": {"description": description, "done": done}}
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)
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async def _emit_notification(self, emitter, content: str, ntype: str = "info"):
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"""Emits a notification event (info/success/warning/error)."""
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if emitter:
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await emitter(
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{"type": "notification", "data": {"type": ntype, "content": content}}
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)
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def _remove_existing_html(self, content: str) -> str:
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"""Removes existing plugin-generated HTML code blocks from the content."""
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pattern = r"```html\s*<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?```"
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@@ -485,13 +499,9 @@ class Action:
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if len(original_content) < self.valves.MIN_TEXT_LENGTH:
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short_text_message = f"Text content too short ({len(original_content)} chars), recommended at least {self.valves.MIN_TEXT_LENGTH} chars for effective deep analysis.\n\n💡 Tip: For short texts, consider using '⚡ Flash Card' for quick refinement."
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if __event_emitter__:
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await __event_emitter__(
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{
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"type": "notification",
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"data": {"type": "warning", "content": short_text_message},
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}
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)
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await self._emit_notification(
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__event_emitter__, short_text_message, "warning"
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)
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return {
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"messages": [
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{"role": "assistant", "content": f"⚠️ {short_text_message}"}
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@@ -500,37 +510,22 @@ class Action:
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# Recommend for longer texts
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if len(original_content) < self.valves.RECOMMENDED_MIN_LENGTH:
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if __event_emitter__:
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await __event_emitter__(
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{
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"type": "notification",
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"data": {
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"type": "info",
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"content": f"Text length is {len(original_content)} chars. Recommended {self.valves.RECOMMENDED_MIN_LENGTH}+ chars for best analysis results.",
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},
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}
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)
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if __event_emitter__:
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await __event_emitter__(
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{
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"type": "notification",
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"data": {
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"type": "info",
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"content": "📖 Deep Reading started, analyzing deeply...",
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},
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}
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await self._emit_notification(
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__event_emitter__,
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f"Text length is {len(original_content)} chars. Recommended {self.valves.RECOMMENDED_MIN_LENGTH}+ chars for best analysis results.",
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"info",
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)
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if self.valves.show_status:
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await __event_emitter__(
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{
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"type": "status",
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"data": {
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"description": "📖 Deep Reading: Analyzing text, extracting essence...",
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"done": False,
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},
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}
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)
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await self._emit_notification(
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__event_emitter__,
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"📖 Deep Reading started, analyzing deeply...",
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"info",
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)
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await self._emit_status(
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__event_emitter__,
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"📖 Deep Reading: Analyzing text, extracting essence...",
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False,
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)
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formatted_user_prompt = USER_PROMPT_GENERATE_SUMMARY.format(
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user_name=user_name,
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@@ -542,7 +537,7 @@ class Action:
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)
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# Determine model to use
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target_model = self.valves.LLM_MODEL_ID
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target_model = self.valves.MODEL_ID
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if not target_model:
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target_model = body.get("model")
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@@ -611,25 +606,14 @@ class Action:
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html_embed_tag = f"```html\n{final_html}\n```"
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body["messages"][-1]["content"] = f"{original_content}\n\n{html_embed_tag}"
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if self.valves.show_status and __event_emitter__:
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await __event_emitter__(
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{
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"type": "status",
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"data": {
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"description": "📖 Deep Reading: Analysis complete!",
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"done": True,
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},
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}
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)
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await __event_emitter__(
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{
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"type": "notification",
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"data": {
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"type": "success",
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"content": f"📖 Deep Reading complete, {user_name}! Deep analysis report generated.",
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},
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}
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)
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await self._emit_status(
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__event_emitter__, "📖 Deep Reading: Analysis complete!", True
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)
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await self._emit_notification(
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__event_emitter__,
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f"📖 Deep Reading complete, {user_name}! Deep analysis report generated.",
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"success",
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)
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except Exception as e:
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error_message = f"Deep Reading processing failed: {str(e)}"
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@@ -639,25 +623,13 @@ class Action:
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"content"
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] = f"{original_content}\n\n❌ **Error:** {user_facing_error}"
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if __event_emitter__:
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if self.valves.show_status:
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await __event_emitter__(
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{
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"type": "status",
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"data": {
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"description": "Deep Reading: Processing failed.",
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"done": True,
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},
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}
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)
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await __event_emitter__(
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{
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"type": "notification",
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"data": {
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"type": "error",
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"content": f"Deep Reading processing failed, {user_name}!",
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},
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}
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)
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await self._emit_status(
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__event_emitter__, "Deep Reading: Processing failed.", True
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)
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await self._emit_notification(
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__event_emitter__,
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f"Deep Reading processing failed, {user_name}!",
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"error",
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)
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return body
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