llm configuation refine and trievalTest API refine (#40)

api/apps/__init__.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/apps/chunk_app.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.
@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import datetime
 
 from flask import request
 from flask_login import login_required, current_user
@@ -177,6 +178,7 @@ def create():
     d["content_sm_ltks"] = huqie.qieqie(d["content_ltks"])
     d["important_kwd"] = req.get("important_kwd", [])
     d["important_tks"] = huqie.qie(" ".join(req.get("important_kwd", [])))
+    d["create_time"] = str(datetime.datetime.now()).replace("T", " ")[:19]
 
     try:
         e, doc = DocumentService.get_by_id(req["doc_id"])
@@ -223,7 +225,7 @@ def retrieval_test():
         embd_mdl = TenantLLMService.model_instance(
             kb.tenant_id, LLMType.EMBEDDING.value)
         ranks = retrievaler.retrieval(question, embd_mdl, kb.tenant_id, [kb_id], page, size, similarity_threshold,
-                          vector_similarity_weight, top, doc_ids)
+                                      vector_similarity_weight, top, doc_ids)
 
         return get_json_result(data=ranks)
     except Exception as e:
@@ -231,4 +233,3 @@ def retrieval_test():
             return get_json_result(data=False, retmsg=f'Index not found!',
                                    retcode=RetCode.DATA_ERROR)
         return server_error_response(e)
-

api/apps/conversation_app.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.
@@ -13,22 +13,16 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-import re
-
-import tiktoken
 from flask import request
-from flask_login import login_required, current_user
+from flask_login import login_required
 from api.db.services.dialog_service import DialogService, ConversationService
-from api.db import StatusEnum, LLMType
-from api.db.services.kb_service import KnowledgebaseService
+from api.db import LLMType
 from api.db.services.llm_service import LLMService, TenantLLMService
-from api.db.services.user_service import TenantService
 from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
 from api.utils import get_uuid
 from api.utils.api_utils import get_json_result
 from rag.llm import ChatModel
 from rag.nlp import retrievaler
-from rag.nlp.query import EsQueryer
 from rag.utils import num_tokens_from_string, encoder
 
 
@@ -142,6 +136,27 @@ def message_fit_in(msg, max_length=4000):
     return max_length, msg
 
 
+@manager.route('/completion', methods=['POST'])
+@login_required
+@validate_request("dialog_id", "messages")
+def completion():
+    req = request.json
+    msg = []
+    for m in req["messages"]:
+        if m["role"] == "system":continue
+        if m["role"] == "assistant" and not msg:continue
+        msg.append({"role": m["role"], "content": m["content"]})
+    try:
+        e, dia = DialogService.get_by_id(req["dialog_id"])
+        if not e:
+            return get_data_error_result(retmsg="Dialog not found!")
+        del req["dialog_id"]
+        del req["messages"]
+        return get_json_result(data=chat(dia, msg, **req))
+    except Exception as e:
+        return server_error_response(e)
+
+
 def chat(dialog, messages, **kwargs):
     assert messages[-1]["role"] == "user", "The last content of this conversation is not from user."
     llm = LLMService.query(llm_name=dialog.llm_id)
@@ -156,7 +171,7 @@ def chat(dialog, messages, **kwargs):
             prompt_config["system"] = prompt_config["system"].replace("{%s}"%p["key"], " ")
 
     model_config = TenantLLMService.get_api_key(dialog.tenant_id, LLMType.CHAT.value, dialog.llm_id)
-    if not model_config: raise LookupError("LLM(%s) API key not found"%dialog.llm_id)
+    if not model_config: raise LookupError("LLM({}) API key not found".format(dialog.llm_id))
 
     question = messages[-1]["content"]
     embd_mdl = TenantLLMService.model_instance(
@@ -183,25 +198,4 @@ def chat(dialog, messages, **kwargs):
                                  embd_mdl,
                                  tkweight=1-dialog.vector_similarity_weight,
                                  vtweight=dialog.vector_similarity_weight)
-    return {"answer": answer, "retrieval": kbinfos}
-
-
-@manager.route('/completion', methods=['POST'])
-@login_required
-@validate_request("dialog_id", "messages")
-def completion():
-    req = request.json
-    msg = []
-    for m in req["messages"]:
-        if m["role"] == "system":continue
-        if m["role"] == "assistant" and not msg:continue
-        msg.append({"role": m["role"], "content": m["content"]})
-    try:
-        e, dia = DialogService.get_by_id(req["dialog_id"])
-        if not e:
-            return get_data_error_result(retmsg="Dialog not found!")
-        del req["dialog_id"]
-        del req["messages"]
-        return get_json_result(data=chat(dia, msg, **req))
-    except Exception as e:
-        return server_error_response(e)
+    return {"answer": answer, "retrieval": kbinfos}

api/apps/dialog_app.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/apps/document_app.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/apps/kb_app.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/apps/llm_app.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.
@@ -71,18 +71,12 @@ def my_llms():
 def list():
     try:
         objs = TenantLLMService.query(tenant_id=current_user.id)
-        objs = [o.to_dict() for o in objs if o.api_key]
-        fct = {}
-        for o in objs:
-            if o["llm_factory"] not in fct: fct[o["llm_factory"]] = []
-            if o["llm_name"]: fct[o["llm_factory"]].append(o["llm_name"])
-
+        mdlnms = set([o.to_dict()["llm_name"] for o in objs if o.api_key])
         llms = LLMService.get_all()
         llms = [m.to_dict() for m in llms if m.status == StatusEnum.VALID.value]
         for m in llms:
-            m["available"] = False
-            if m["fid"] in fct and (not fct[m["fid"]] or m["llm_name"] in fct[m["fid"]]):
-                m["available"] = True
+            m["available"] = m.llm_name in mdlnms
+
         res = {}
         for m in llms:
             if m["fid"] not in res: res[m["fid"]] = []

api/apps/user_app.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.
@@ -13,12 +13,14 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import re
+
 from flask import request, session, redirect, url_for
 from werkzeug.security import generate_password_hash, check_password_hash
 from flask_login import login_required, current_user, login_user, logout_user
 
 from api.db.db_models import TenantLLM
-from api.db.services.llm_service import TenantLLMService
+from api.db.services.llm_service import TenantLLMService, LLMService
 from api.utils.api_utils import server_error_response, validate_request
 from api.utils import get_uuid, get_format_time, decrypt, download_img
 from api.db import UserTenantRole, LLMType
@@ -185,8 +187,6 @@ def rollback_user_registration(user_id):
 
       
 def user_register(user_id, user):
-
-    user_id = get_uuid()
     user["id"] = user_id
     tenant = {
         "id": user_id,
@@ -203,12 +203,14 @@ def user_register(user_id, user):
         "invited_by": user_id,
         "role": UserTenantRole.OWNER
     }
-    tenant_llm = {"tenant_id": user_id, "llm_factory": "OpenAI", "api_key": "infiniflow API Key"}
+    tenant_llm = []
+    for llm in LLMService.query(fid="Infiniflow"):
+        tenant_llm.append({"tenant_id": user_id, "llm_factory": "Infiniflow", "llm_name": llm.llm_name, "model_type":llm.model_type, "api_key": "infiniflow API Key"})
 
     if not UserService.save(**user):return
     TenantService.save(**tenant)
     UserTenantService.save(**usr_tenant)
-    TenantLLMService.save(**tenant_llm)
+    TenantLLMService.insert_many(tenant_llm)
     return UserService.query(email=user["email"])
 
 
@@ -218,6 +220,9 @@ def user_add():
     req = request.json
     if UserService.query(email=req["email"]):
         return get_json_result(data=False, retmsg=f'Email: {req["email"]} has already registered!', retcode=RetCode.OPERATING_ERROR)
+    if not re.match(r"^[\w\._-]+@([\w_-]+\.)+[\w-]{2,4}$", req["email"]):
+        return get_json_result(data=False, retmsg=f'Invaliad e-mail: {req["email"]}!',
+                               retcode=RetCode.OPERATING_ERROR)
 
     user_dict = {
         "access_token": get_uuid(),

api/db/__init__.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/db/db_models.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.
@@ -426,8 +426,8 @@ class LLMFactories(DataBaseModel):
 
 
 class LLM(DataBaseModel):
-    # defautlt LLMs for every users
-    llm_name = CharField(max_length=128, null=False, help_text="LLM name", primary_key=True)
+    # LLMs dictionary
+    llm_name = CharField(max_length=128, null=False, help_text="LLM name", index=True)
     model_type = CharField(max_length=128, null=False, help_text="LLM, Text Embedding, Image2Text, ASR")
     fid = CharField(max_length=128, null=False, help_text="LLM factory id")
     max_tokens = IntegerField(default=0)
@@ -448,6 +448,7 @@ class TenantLLM(DataBaseModel):
     llm_name = CharField(max_length=128, null=True, help_text="LLM name", default="")
     api_key = CharField(max_length=255, null=True, help_text="API KEY")
     api_base = CharField(max_length=255, null=True, help_text="API Base")
+    used_tokens = IntegerField(default=0)
 
     def __str__(self):
         return self.llm_name
@@ -468,8 +469,8 @@ class Knowledgebase(DataBaseModel):
     doc_num = IntegerField(default=0)
     token_num = IntegerField(default=0)
     chunk_num = IntegerField(default=0)
-    #similarity_threshold = FloatField(default=0.4)
-    #vector_similarity_weight = FloatField(default=0.3)
+    similarity_threshold = FloatField(default=0.4)
+    vector_similarity_weight = FloatField(default=0.3)
 
     parser_id = CharField(max_length=32, null=False, help_text="default parser ID")
     status = CharField(max_length=1, null=True, help_text="is it validate(0: wasted，1: validate)", default="1")

api/db/db_utils.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/db/init_data.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.
@@ -46,6 +46,11 @@ def init_llm_factory():
             "logo": "",
             "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
             "status": "1",
+        },{
+            "name": "Infiniflow",
+            "logo": "",
+            "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
+            "status": "1",
         },{
             "name": "智普AI",
             "logo": "",
@@ -130,6 +135,30 @@ def init_llm_factory():
             "tags": "LLM,CHAT,IMAGE2TEXT",
             "max_tokens": 765,
             "model_type": LLMType.IMAGE2TEXT.value
+        },{
+            "fid": factory_infos[2]["name"],
+            "llm_name": "gpt-3.5-turbo",
+            "tags": "LLM,CHAT,4K",
+            "max_tokens": 4096,
+            "model_type": LLMType.CHAT.value
+        },{
+            "fid": factory_infos[2]["name"],
+            "llm_name": "text-embedding-ada-002",
+            "tags": "TEXT EMBEDDING,8K",
+            "max_tokens": 8191,
+            "model_type": LLMType.EMBEDDING.value
+        },{
+            "fid": factory_infos[2]["name"],
+            "llm_name": "whisper-1",
+            "tags": "SPEECH2TEXT",
+            "max_tokens": 25*1024*1024,
+            "model_type": LLMType.SPEECH2TEXT.value
+        },{
+            "fid": factory_infos[2]["name"],
+            "llm_name": "gpt-4-vision-preview",
+            "tags": "LLM,CHAT,IMAGE2TEXT",
+            "max_tokens": 765,
+            "model_type": LLMType.IMAGE2TEXT.value
         },
     ]
     for info in factory_infos:

api/db/operatioins.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/db/reload_config_base.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/db/runtime_config.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/db/services/__init__.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/db/services/common_service.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/db/services/dialog_service.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/db/services/document_service.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/db/services/kb_service.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/db/services/knowledgebase_service.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/db/services/llm_service.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.
@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+from api.db.services.user_service import TenantService
 from rag.llm import EmbeddingModel, CvModel
 from api.db import LLMType
 from api.db.db_models import DB, UserTenant
@@ -34,40 +35,39 @@ class TenantLLMService(CommonService):
 
     @classmethod
     @DB.connection_context()
-    def get_api_key(cls, tenant_id, model_type, model_name=""):
-        objs = cls.query(tenant_id=tenant_id, model_type=model_type)
-        if objs and len(objs)>0 and objs[0].llm_name:
-            return objs[0]
-
-        fields = [LLM.llm_name, cls.model.llm_factory, cls.model.api_key]
-        objs = cls.model.select(*fields).join(LLM, on=(LLM.fid == cls.model.llm_factory)).where(
-            (cls.model.tenant_id == tenant_id),
-            ((cls.model.model_type == model_type) | (cls.model.llm_name == model_name)),
-            (LLM.status == StatusEnum.VALID)
-        )
-
-        if not objs:return
+    def get_api_key(cls, tenant_id, model_name):
+        objs = cls.query(tenant_id=tenant_id, llm_name=model_name)
+        if not objs: return
         return objs[0]
 
     @classmethod
     @DB.connection_context()
     def get_my_llms(cls, tenant_id):
         fields = [cls.model.llm_factory, LLMFactories.logo, LLMFactories.tags, cls.model.model_type, cls.model.llm_name]
-        objs = cls.model.select(*fields).join(LLMFactories, on=(cls.model.llm_factory==LLMFactories.name)).where(cls.model.tenant_id==tenant_id).dicts()
+        objs = cls.model.select(*fields).join(LLMFactories, on=(cls.model.llm_factory == LLMFactories.name)).where(
+            cls.model.tenant_id == tenant_id).dicts()
 
         return list(objs)
 
     @classmethod
     @DB.connection_context()
     def model_instance(cls, tenant_id, llm_type):
-        model_config = cls.get_api_key(tenant_id, model_type=LLMType.EMBEDDING.value)
-        if not model_config:
-            model_config = {"llm_factory": "local", "api_key": "", "llm_name": ""}
-        else:
-            model_config = model_config[0].to_dict()
-        if llm_type == LLMType.EMBEDDING:
+        e,tenant = TenantService.get_by_id(tenant_id)
+        if not e: raise LookupError("Tenant not found")
+
+        if llm_type == LLMType.EMBEDDING.value: mdlnm = tenant.embd_id
+        elif llm_type == LLMType.SPEECH2TEXT.value: mdlnm = tenant.asr_id
+        elif llm_type == LLMType.IMAGE2TEXT.value: mdlnm = tenant.img2txt_id
+        elif llm_type == LLMType.CHAT.value: mdlnm = tenant.llm_id
+        else: assert False, "LLM type error"
+
+        model_config = cls.get_api_key(tenant_id, mdlnm)
+        if not model_config: raise LookupError("Model({}) not found".format(mdlnm))
+        model_config = model_config[0].to_dict()
+        if llm_type == LLMType.EMBEDDING.value:
             if model_config["llm_factory"] not in EmbeddingModel: return
             return EmbeddingModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"])
-        if llm_type == LLMType.IMAGE2TEXT:
+
+        if llm_type == LLMType.IMAGE2TEXT.value:
             if model_config["llm_factory"] not in CvModel: return
-            return CvModel[model_config.llm_factory](model_config["api_key"], model_config["llm_name"])
+            return CvModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"])

api/db/services/user_service.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/errors/general_error.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/ragflow_server.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/settings.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/utils/__init__.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/utils/api_utils.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/utils/file_utils.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/utils/log_utils.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

api/versions.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

rag/llm/__init__.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.
@@ -19,7 +19,7 @@ from .cv_model import *
 
 
 EmbeddingModel = {
-    "local": HuEmbedding,
+    "Infiniflow": HuEmbedding,
     "OpenAI": OpenAIEmbed,
     "通义千问": QWenEmbed,
 }
@@ -27,12 +27,14 @@ EmbeddingModel = {
 
 CvModel = {
     "OpenAI": GptV4,
+    "Infiniflow": GptV4,
     "通义千问": QWenCV,
 }
 
 
 ChatModel = {
     "OpenAI": GptTurbo,
+    "Infiniflow": GptTurbo,
     "通义千问": QWenChat,
 }
 

rag/llm/chat_model.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

rag/llm/cv_model.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

rag/llm/embedding_model.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.
@@ -24,6 +24,9 @@ import numpy as np
 
 from rag.utils import num_tokens_from_string
 
+flag_model = FlagModel("BAAI/bge-large-zh-v1.5",
+                       query_instruction_for_retrieval="为这个句子生成表示以用于检索相关文章：",
+                       use_fp16=torch.cuda.is_available())
 
 class Base(ABC):
     def __init__(self, key, model_name):
@@ -47,9 +50,7 @@ class HuEmbedding(Base):
         ^_-
 
         """
-        self.model = FlagModel("BAAI/bge-large-zh-v1.5",
-                               query_instruction_for_retrieval="为这个句子生成表示以用于检索相关文章：",
-                               use_fp16=torch.cuda.is_available())
+        self.model = flag_model
 
 
     def encode(self, texts: list, batch_size=32):

rag/nlp/query.py

@@ -42,7 +42,7 @@ class EsQueryer:
 
     def question(self, txt, tbl="qa", min_match="60%"):
         txt = re.sub(
-            r"[ \t,，。？?/`!！&]+",
+            r"[ \r\n\t,，。？?/`!！&]+",
             " ",
             huqie.tradi2simp(
                 huqie.strQ2B(

rag/parser/pdf_parser.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+import fitz
 import xgboost as xgb
 from io import BytesIO
 import torch
@@ -1527,8 +1528,6 @@ class HuParser:
         return "\n\n".join(res)
 
     def __call__(self, fnm, need_image=True, zoomin=3, return_html=False):
-        self.pdf = pdfplumber.open(fnm) if isinstance(
-            fnm, str) else pdfplumber.open(BytesIO(fnm))
         self.lefted_chars = []
         self.mean_height = []
         self.mean_width = []
@@ -1536,13 +1535,26 @@ class HuParser:
         self.garbages = {}
         self.page_cum_height = [0]
         self.page_layout = []
-        self.page_images = [p.to_image(
-            resolution=72 * zoomin).annotated for i, p in enumerate(self.pdf.pages[:299])]
+        try:
+            self.pdf = pdfplumber.open(fnm) if isinstance(fnm, str) else pdfplumber.open(BytesIO(fnm))
+            self.page_images = [p.to_image(resolution=72*zoomin).annotated for i,p in enumerate(self.pdf.pages[:299])]
+            self.page_chars = [[c for c in self.pdf.pages[i].chars if self._has_color(c)] for i in range(len(self.page_images))]
+        except Exception as e:
+            self.pdf = fitz.open(fnm) if isinstance(fnm, str) else fitz.open(stream=fnm, filetype="pdf")
+            self.page_images = []
+            self.page_chars = []
+            mat = fitz.Matrix(zoomin, zoomin)
+            for page in self.pdf:
+                pix = page.getPixmap(matrix = mat)
+                img = Image.frombytes("RGB", [pix.width, pix.height],
+                                      pix.samples)
+                self.page_images.append(img)
+                self.page_chars.append([])
+
         logging.info("Images converted.")
-        logging.info("Table processed.")
 
         for i, img in enumerate(self.page_images):
-            chars = [c for c in self.pdf.pages[i].chars if self._has_color(c)]
+            chars = self.page_chars[i]
             self.mean_height.append(
                 np.median(sorted([c["height"] for c in chars])) if chars else 0
             )

rag/settings.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.

rag/svr/parse_user_docs.py

@@ -1,5 +1,5 @@
 #
-#  Copyright 2019 The InfiniFlow Authors. All Rights Reserved.
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
 #  you may not use this file except in compliance with the License.