Merge branch 'main' of http://10.10.14.176:3000/huanghai/dsProject

dsAiTeachingModel/api/controller/TeachingModelController.py

@@ -78,3 +78,38 @@ async def get_question(request: Request):
     print(select_question_sql)
     page = await get_page_data_by_sql(select_question_sql, page_number, page_size)
     return {"success": True, "message": "查询成功！", "data": page}
+
+
+
+# 【TeachingModel-5】提问
+@router.post("/sendQuestion")
+async def send_question(request: Request):
+    # 获取参数
+    bureau_id = await get_request_str_param(request, "bureau_id", True, True)
+    person_id = await get_request_str_param(request, "person_id", True, True)
+    theme_id = await get_request_num_param(request, "theme_id", True, True, None)
+    question = await get_request_str_param(request, "question_type", True, True)
+
+    theme_object = await find_by_id("t_ai_teaching_model_theme", "id", theme_id)
+    if theme_object is None:
+        return {"success": False, "message": "主题不存在！"}
+
+    # 保存个人历史问题
+    param = {}
+    param["stage_id"] = int(theme_object["stage_id"])
+    param["subject_id"] = int(theme_object["subject_id"])
+    param["theme_id"] = theme_id
+    param["question"] = question
+    param["question_type"] = 2
+    param["question_person_id"] = person_id
+    param["person_id"] = person_id
+    param["bureau_id"] = bureau_id
+    question_id = await insert("t_ai_teaching_model_question", param)
+
+    # 处理theme的调用次数
+
+
+
+    # 向rag提问
+
+

dsLightRag/Start.py

@@ -37,12 +37,17 @@ app = FastAPI(lifespan=lifespan)
 app.mount("/static", StaticFiles(directory="Static"), name="static")
 
 
+# 访问根的跳转
+@app.get("/")
+async def redirect_to_ai():
+    return fastapi.responses.RedirectResponse(url="/static/ai.html")
+
+
 @app.post("/api/rag")
 async def rag(request: fastapi.Request):
     data = await request.json()
-    logger.info(f"Received request: {data}")
     workspace = data.get("topic", "ShiJi")  # Chinese, Math ,ShiJi 默认是少年读史记
-    mode = data.get("mode", "hybrid")  # 默认为hybrid模式
+    logger.info("工作空间:" + workspace)
     # 查询的问题
     query = data.get("query")
 
@@ -104,9 +109,7 @@ async def rag(request: fastapi.Request):
             rag = await initialize_pg_rag(WORKING_DIR=WORKING_DIR, workspace=workspace)
             resp = await rag.aquery(
                 query=query,
-                param=QueryParam(mode=mode, stream=True, user_prompt=user_prompt))
+                param=QueryParam(mode="hybrid", stream=True, user_prompt=user_prompt))
-            # hybrid naive
-
             async for chunk in resp:
                 if not chunk:
                     continue
@@ -306,10 +309,11 @@ async def get_sources(page: int = 1, limit: int = 10):
             offset = (page - 1) * limit
             rows = await conn.fetch(
                 """
-                SELECT id, account_id,account_name, created_at 
+                SELECT id, account_id, account_name, created_at
                 FROM t_wechat_source
                 ORDER BY created_at DESC
-                LIMIT $1 OFFSET $2
+                    LIMIT $1
+                OFFSET $2
                 """,
                 limit, offset
             )
@@ -348,11 +352,16 @@ async def get_articles(page: int = 1, limit: int = 10):
             offset = (page - 1) * limit
             rows = await conn.fetch(
                 """
-                SELECT a.id, a.title, a.source as name, 
+                SELECT a.id,
-                       a.publish_time, a.collection_time,a.url
+                       a.title,
+                       a.source as name,
+                       a.publish_time,
+                       a.collection_time,
+                       a.url
                 FROM t_wechat_articles a
                 ORDER BY a.collection_time DESC
-                LIMIT $1 OFFSET $2
+                    LIMIT $1
+                OFFSET $2
                 """,
                 limit, offset
             )

dsLightRag/Util/LightRagUtil.py

@@ -152,14 +152,14 @@ os.environ["POSTGRES_PASSWORD"] = POSTGRES_PASSWORD
 os.environ["POSTGRES_DATABASE"] = POSTGRES_DATABASE
 
 
-async def initialize_pg_rag(WORKING_DIR, workspace='default'):
+async def initialize_pg_rag(WORKING_DIR, workspace):
     rag = LightRAG(
         working_dir=WORKING_DIR,
         llm_model_func=llm_model_func,
         llm_model_name=LLM_MODEL_NAME,
         llm_model_max_async=4,
         llm_model_max_token_size=32768,
-        enable_llm_cache_for_entity_extract=True,
+        enable_llm_cache_for_entity_extract=False,  # 这里黄海修改了一下，不知道是不是有用
         embedding_func=EmbeddingFunc(
             embedding_dim=EMBED_DIM,
             max_token_size=EMBED_MAX_TOKEN_SIZE,