Refactor (#537)

### What problem does this PR solve?

### Type of change

- [x] Refactoring

api/apps/document_app.py

@@ -58,7 +58,8 @@ def upload():
         if not e:
             return get_data_error_result(
                 retmsg="Can't find this knowledgebase!")
-        if DocumentService.get_doc_count(kb.tenant_id) >= int(os.environ.get('MAX_FILE_NUM_PER_USER', 8192)):
+        MAX_FILE_NUM_PER_USER = int(os.environ.get('MAX_FILE_NUM_PER_USER', 0))
+        if MAX_FILE_NUM_PER_USER > 0 and DocumentService.get_doc_count(kb.tenant_id) >= MAX_FILE_NUM_PER_USER:
             return get_data_error_result(
                 retmsg="Exceed the maximum file number of a free user!")
 

api/apps/llm_app.py

@@ -28,7 +28,7 @@ from rag.llm import EmbeddingModel, ChatModel
 def factories():
     try:
         fac = LLMFactoriesService.get_all()
-        return get_json_result(data=[f.to_dict() for f in fac if f.name not in ["QAnything", "FastEmbed"]])
+        return get_json_result(data=[f.to_dict() for f in fac if f.name not in ["Youdao", "FastEmbed"]])
     except Exception as e:
         return server_error_response(e)
 
@@ -174,7 +174,7 @@ def list():
         llms = [m.to_dict()
                 for m in llms if m.status == StatusEnum.VALID.value]
         for m in llms:
-            m["available"] = m["fid"] in facts or m["llm_name"].lower() == "flag-embedding" or m["fid"] in ["QAnything","FastEmbed"]
+            m["available"] = m["fid"] in facts or m["llm_name"].lower() == "flag-embedding" or m["fid"] in ["Youdao","FastEmbed"]
 
         llm_set = set([m["llm_name"] for m in llms])
         for o in objs:

api/db/db_models.py

@@ -697,7 +697,7 @@ class Dialog(DataBaseModel):
         null=True,
         default="Chinese",
         help_text="English|Chinese")
-    llm_id = CharField(max_length=32, null=False, help_text="default llm ID")
+    llm_id = CharField(max_length=128, null=False, help_text="default llm ID")
     llm_setting = JSONField(null=False, default={"temperature": 0.1, "top_p": 0.3, "frequency_penalty": 0.7,
                                                  "presence_penalty": 0.4, "max_tokens": 215})
     prompt_type = CharField(

api/db/init_data.py

@@ -120,7 +120,7 @@ factory_infos = [{
     "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
         "status": "1",
 },{
-    "name": "QAnything",
+    "name": "Youdao",
     "logo": "",
     "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
         "status": "1",
@@ -323,7 +323,7 @@ def init_llm_factory():
             "max_tokens": 2147483648,
             "model_type": LLMType.EMBEDDING.value
         },
-        # ------------------------ QAnything -----------------------
+        # ------------------------ Youdao -----------------------
         {
             "fid": factory_infos[7]["name"],
             "llm_name": "maidalun1020/bce-embedding-base_v1",
@@ -347,7 +347,9 @@ def init_llm_factory():
     LLMService.filter_delete([LLM.fid == "Local"])
     LLMService.filter_delete([LLM.fid == "Moonshot", LLM.llm_name == "flag-embedding"])
     TenantLLMService.filter_delete([TenantLLM.llm_factory == "Moonshot", TenantLLM.llm_name == "flag-embedding"])
-
+    LLMFactoriesService.filter_update([LLMFactoriesService.model.name == "QAnything"], {"name": "Youdao"})
+    LLMService.filter_update([LLMService.model.fid == "QAnything"], {"fid": "Youdao"})
+    TenantLLMService.filter_update([TenantLLMService.model.llm_factory == "QAnything"], {"llm_factory": "Youdao"})
     """
     drop table llm;
     drop table llm_factories;

api/db/services/llm_service.py

@@ -81,7 +81,7 @@ class TenantLLMService(CommonService):
         if not model_config:
             if llm_type == LLMType.EMBEDDING.value:
                 llm = LLMService.query(llm_name=llm_name)
-                if llm and llm[0].fid in ["QAnything", "FastEmbed"]:
+                if llm and llm[0].fid in ["Youdao", "FastEmbed"]:
                     model_config = {"llm_factory": llm[0].fid, "api_key":"", "llm_name": llm_name, "api_base": ""}
             if not model_config:
                 if llm_name == "flag-embedding":

api/db/services/task_service.py

@@ -21,6 +21,7 @@ from api.db import StatusEnum, FileType, TaskStatus
 from api.db.db_models import Task, Document, Knowledgebase, Tenant
 from api.db.services.common_service import CommonService
 from api.db.services.document_service import DocumentService
+from api.utils import current_timestamp
 
 
 class TaskService(CommonService):
@@ -70,6 +71,25 @@ class TaskService(CommonService):
                 cls.model.id == docs[0]["id"]).execute()
             return docs
 
+    @classmethod
+    @DB.connection_context()
+    def get_ongoing_doc_name(cls):
+        with DB.lock("get_task", -1):
+            docs = cls.model.select(*[Document.kb_id, Document.location]) \
+                .join(Document, on=(cls.model.doc_id == Document.id)) \
+                .where(
+                    Document.status == StatusEnum.VALID.value,
+                    Document.run == TaskStatus.RUNNING.value,
+                    ~(Document.type == FileType.VIRTUAL.value),
+                    cls.model.progress >= 0,
+                    cls.model.progress < 1,
+                    cls.model.create_time >= current_timestamp() - 180000
+                )
+            docs = list(docs.dicts())
+            if not docs: return []
+
+            return list(set([(d["kb_id"], d["location"]) for d in docs]))
+
     @classmethod
     @DB.connection_context()
     def do_cancel(cls, id):

deepdoc/parser/pdf_parser.py

@@ -49,7 +49,6 @@ class HuParser:
             self.updown_cnt_mdl.load_model(os.path.join(
                 model_dir, "updown_concat_xgb.model"))
 
-
         self.page_from = 0
         """
         If you have trouble downloading HuggingFace models, -_^ this might help!!
@@ -975,6 +974,7 @@ class HuParser:
                         self.outlines.append((a["/Title"], depth))
                         continue
                     dfs(a, depth + 1)
+
             dfs(outlines, 0)
         except Exception as e:
             logging.warning(f"Outlines exception: {e}")
@@ -1012,9 +1012,9 @@ class HuParser:
                 j += 1
 
             self.__ocr(i + 1, img, chars, zoomin)
-            #if callback:
+            if callback and i % 6 == 5:
-            #    callback(prog=(i + 1) * 0.6 / len(self.page_images), msg="")
+                callback(prog=(i + 1) * 0.6 / len(self.page_images), msg="")
-        #print("OCR:", timer()-st)
+        # print("OCR:", timer()-st)
 
         if not self.is_english and not any(
                 [c for c in self.page_chars]) and self.boxes:

rag/llm/__init__.py

@@ -25,7 +25,7 @@ EmbeddingModel = {
     "Tongyi-Qianwen": HuEmbedding, #QWenEmbed,
     "ZHIPU-AI": ZhipuEmbed,
     "FastEmbed": FastEmbed,
-    "QAnything": QAnythingEmbed
+    "Youdao": YoudaoEmbed
 }
 
 

rag/llm/embedding_model.py

@@ -229,19 +229,19 @@ class XinferenceEmbed(Base):
         return np.array(res.data[0].embedding), res.usage.total_tokens
 
 
-class QAnythingEmbed(Base):
+class YoudaoEmbed(Base):
     _client = None
 
     def __init__(self, key=None, model_name="maidalun1020/bce-embedding-base_v1", **kwargs):
         from BCEmbedding import EmbeddingModel as qanthing
-        if not QAnythingEmbed._client:
+        if not YoudaoEmbed._client:
             try:
                 print("LOADING BCE...")
-                QAnythingEmbed._client = qanthing(model_name_or_path=os.path.join(
+                YoudaoEmbed._client = qanthing(model_name_or_path=os.path.join(
                     get_project_base_directory(),
                     "rag/res/bce-embedding-base_v1"))
             except Exception as e:
-                QAnythingEmbed._client = qanthing(
+                YoudaoEmbed._client = qanthing(
                     model_name_or_path=model_name.replace(
                         "maidalun1020", "InfiniFlow"))
 
@@ -251,10 +251,10 @@ class QAnythingEmbed(Base):
         for t in texts:
             token_count += num_tokens_from_string(t)
         for i in range(0, len(texts), batch_size):
-            embds = QAnythingEmbed._client.encode(texts[i:i + batch_size])
+            embds = YoudaoEmbed._client.encode(texts[i:i + batch_size])
             res.extend(embds)
         return np.array(res), token_count
 
     def encode_queries(self, text):
-        embds = QAnythingEmbed._client.encode([text])
+        embds = YoudaoEmbed._client.encode([text])
         return np.array(embds[0]), num_tokens_from_string(text)

rag/svr/cache_file_svr.py

@@ -0,0 +1,43 @@
+import random
+import time
+import traceback
+
+from api.db.db_models import close_connection
+from api.db.services.task_service import TaskService
+from rag.utils import MINIO
+from rag.utils.redis_conn import REDIS_CONN
+
+
+def collect():
+    doc_locations = TaskService.get_ongoing_doc_name()
+    #print(tasks)
+    if len(doc_locations) == 0:
+        time.sleep(1)
+        return
+    return doc_locations
+
+def main():
+    locations = collect()
+    if not locations:return
+    print("TASKS:", len(locations))
+    for kb_id, loc in locations:
+        try:
+            if REDIS_CONN.is_alive():
+                try:
+                    key = "{}/{}".format(kb_id, loc)
+                    if REDIS_CONN.exist(key):continue
+                    file_bin = MINIO.get(kb_id, loc)
+                    REDIS_CONN.transaction(key, file_bin, 12 * 60)
+                    print("CACHE:", loc)
+                except Exception as e:
+                    traceback.print_stack(e)
+        except Exception as e:
+            traceback.print_stack(e)
+
+
+
+if __name__ == "__main__":
+    while True:
+        main()
+        close_connection()
+        time.sleep(1)

rag/svr/task_executor.py

@@ -107,8 +107,14 @@ def get_minio_binary(bucket, name):
     global MINIO
     if REDIS_CONN.is_alive():
         try:
+            for _ in range(30):
+                if REDIS_CONN.exist("{}/{}".format(bucket, name)):
+                    time.sleep(1)
+                    break
+                time.sleep(1)
             r = REDIS_CONN.get("{}/{}".format(bucket, name))
             if r: return r
+            cron_logger.warning("Cache missing: {}".format(name))
         except Exception as e:
             cron_logger.warning("Get redis[EXCEPTION]:" + str(e))
     return MINIO.get(bucket, name)

rag/utils/minio_conn.py

@@ -56,7 +56,6 @@ class HuMinio(object):
         except Exception as e:
             minio_logger.error(f"Fail rm {bucket}/{fnm}: " + str(e))
 
-
     def get(self, bucket, fnm):
         for _ in range(1):
             try:

rag/utils/redis_conn.py

@@ -25,6 +25,14 @@ class RedisDB:
     def is_alive(self):
         return self.REDIS is not None
 
+    def exist(self, k):
+        if not self.REDIS: return
+        try:
+            return self.REDIS.exists(k)
+        except Exception as e:
+            logging.warning("[EXCEPTION]exist" + str(k) + "||" + str(e))
+            self.__open__()
+
     def get(self, k):
         if not self.REDIS: return
         try:
@@ -51,5 +59,16 @@ class RedisDB:
             self.__open__()
         return False
 
+    def transaction(self, key, value, exp=3600):
+        try:
+            pipeline = self.REDIS.pipeline(transaction=True)
+            pipeline.set(key, value, exp, nx=True)
+            pipeline.execute()
+            return True
+        except Exception as e:
+            logging.warning("[EXCEPTION]set" + str(key) + "||" + str(e))
+            self.__open__()
+        return False
+
 
 REDIS_CONN = RedisDB()