Feat: add meta filter to search app. (#9554)

### What problem does this PR solve?


### Type of change

- [x] New Feature (non-breaking change which adds functionality)

api/apps/conversation_app.py

@@ -17,24 +17,18 @@ import json
 import re
 import traceback
 from copy import deepcopy
-
-import trio
 from flask import Response, request
 from flask_login import current_user, login_required
-
 from api import settings
 from api.db import LLMType
 from api.db.db_models import APIToken
 from api.db.services.conversation_service import ConversationService, structure_answer
-from api.db.services.dialog_service import DialogService, ask, chat
-from api.db.services.knowledgebase_service import KnowledgebaseService
+from api.db.services.dialog_service import DialogService, ask, chat, gen_mindmap
 from api.db.services.llm_service import LLMBundle
 from api.db.services.search_service import SearchService
 from api.db.services.tenant_llm_service import TenantLLMService
 from api.db.services.user_service import TenantService, UserTenantService
 from api.utils.api_utils import get_data_error_result, get_json_result, server_error_response, validate_request
-from graphrag.general.mind_map_extractor import MindMapExtractor
-from rag.app.tag import label_question
 from rag.prompts.prompt_template import load_prompt
 from rag.prompts.prompts import chunks_format
 
@@ -375,71 +369,12 @@ def ask_about():
 @validate_request("question", "kb_ids")
 def mindmap():
     req = request.json
-
     search_id = req.get("search_id", "")
-    search_app = None
-    search_config = {}
-    if search_id:
-        search_app = SearchService.get_detail(search_id)
-    if search_app:
-        search_config = search_app.get("search_config", {})
+    search_app = SearchService.get_detail(search_id) if search_id else {}
+    search_config = search_app.get("search_config", {}) if search_app else {}
+    kb_ids = search_config.get("kb_ids", req["kb_ids"])
 
-    kb_ids = req["kb_ids"]
-    if search_config.get("kb_ids", []):
-        kb_ids = search_config.get("kb_ids", [])
-    e, kb = KnowledgebaseService.get_by_id(kb_ids[0])
-    if not e:
-        return get_data_error_result(message="Knowledgebase not found!")
-
-    chat_id = ""
-    similarity_threshold = 0.3,
-    vector_similarity_weight = 0.3,
-    top = 1024,
-    doc_ids = []
-    rerank_id = ""
-    rerank_mdl = None
-
-    if search_config:
-        if search_config.get("chat_id", ""):
-            chat_id = search_config.get("chat_id", "")
-        if search_config.get("similarity_threshold", 0.2):
-            similarity_threshold = search_config.get("similarity_threshold", 0.2)
-        if search_config.get("vector_similarity_weight", 0.3):
-            vector_similarity_weight = search_config.get("vector_similarity_weight", 0.3)
-        if search_config.get("top_k", 1024):
-            top = search_config.get("top_k", 1024)
-        if search_config.get("doc_ids", []):
-            doc_ids = search_config.get("doc_ids", [])
-        if search_config.get("rerank_id", ""):
-            rerank_id = search_config.get("rerank_id", "")
-
-    tenant_id = kb.tenant_id
-    if search_app and search_app.get("tenant_id", ""):
-        tenant_id = search_app.get("tenant_id", "")
-
-    embd_mdl = LLMBundle(tenant_id, LLMType.EMBEDDING, llm_name=kb.embd_id)
-    chat_mdl = LLMBundle(tenant_id, LLMType.CHAT, llm_name=chat_id)
-    if rerank_id:
-        rerank_mdl = LLMBundle(tenant_id, LLMType.RERANK, rerank_id)
-    question = req["question"]
-    ranks = settings.retrievaler.retrieval(
-        question=question,
-        embd_mdl=embd_mdl,
-        tenant_ids=tenant_id,
-        kb_ids=kb_ids,
-        page=1,
-        page_size=12,
-        similarity_threshold=similarity_threshold,
-        vector_similarity_weight=vector_similarity_weight,
-        top=top,
-        doc_ids=doc_ids,
-        aggs=False,
-        rerank_mdl=rerank_mdl,
-        rank_feature=label_question(question, [kb]),
-    )
-    mindmap = MindMapExtractor(chat_mdl)
-    mind_map = trio.run(mindmap, [c["content_with_weight"] for c in ranks["chunks"]])
-    mind_map = mind_map.output
+    mind_map = gen_mindmap(req["question"], kb_ids, search_app.get("tenant_id", current_user.id), search_config)
     if "error" in mind_map:
         return server_error_response(Exception(mind_map["error"]))
     return get_json_result(data=mind_map)