update

components/dbo/alembic/versions/d6124aee7cce_add_chat_id_to_log.py

@@ -0,0 +1,32 @@
+"""Add chat_id to Log
+
+Revision ID: d6124aee7cce
+Revises: 12bb1ebae3ff
+Create Date: 2025-04-18 16:02:17.245022
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = 'd6124aee7cce'
+down_revision: Union[str, None] = '12bb1ebae3ff'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.add_column('log', sa.Column('chat_id', sa.String(), nullable=True))
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_column('log', 'chat_id')
+    # ### end Alembic commands ###

components/dbo/models/log.py

@@ -1,8 +1,7 @@
 from sqlalchemy import (
-    Integer,
-    String,
+    String
 )
-from sqlalchemy.orm import relationship, mapped_column
+from sqlalchemy.orm import mapped_column
 from components.dbo.models.base import Base
 
 
@@ -15,4 +14,5 @@ class Log(Base):
     llm_result = mapped_column(String)
     llm_settings = mapped_column(String)
     user_name = mapped_column(String)
-    error = mapped_column(String)
+    error = mapped_column(String)
+    chat_id = mapped_column(String) 

components/llm/common.py

@@ -1,4 +1,4 @@
-from pydantic import BaseModel, Field
+from pydantic import UUID4, BaseModel, Field
 from typing import Optional, List, Protocol
 
 class LlmPredictParams(BaseModel):
@@ -77,4 +77,5 @@ class Message(BaseModel):
     reasoning: Optional[str] = ''
 
 class ChatRequest(BaseModel):
-    history: List[Message]
+    history: List[Message]
+    chat_id: Optional[str] = None

components/services/log.py

@@ -34,11 +34,15 @@ class LogService:
     def get_list(self, filters: LogFilterSchema) -> PaginatedLogResponse:
         logger.info(f"Fetching logs with filters: {filters.model_dump(exclude_none=True)}")
         with self.db() as session:
-            query = session.query(LogSQL)
+            query = session.query(LogSQL).order_by(LogSQL.date_created.desc())
             
             # Применение фильтра по user_name
             if filters.user_name:
                 query = query.filter(LogSQL.user_name == filters.user_name)
+                
+            # Применение фильтра по chat_id (contains)
+            if filters.chat_id:
+                query = query.filter(LogSQL.chat_id.startswith(filters.chat_id))
             
             # Применение фильтра по диапазону date_created
             if filters.date_from:
@@ -46,6 +50,15 @@ class LogService:
             if filters.date_to:
                 query = query.filter(LogSQL.date_created <= filters.date_to)
             
+            # Сортировка
+            if filters.sort:
+                for sort_param in filters.sort:
+                    if sort_param.field == "date_created":
+                        if sort_param.direction == "asc":
+                            query = query.order_by(LogSQL.date_created.asc())
+                        elif sort_param.direction == "desc":
+                            query = query.order_by(LogSQL.date_created.desc())
+            
             total = query.count()
             
             # Применение пагинации

requirements.txt

@@ -3,6 +3,7 @@ fastapi==0.113.0
 unicorn==2.0.1.post1
 transformers==4.42.4
 pandas==2.2.2
+openpyxl==3.1.5
 numpy==1.26.4
 tqdm==4.66.5
 nltk==3.8.1

routes/llm.py

@@ -1,7 +1,7 @@
 import json
 import logging
 import os
-from typing import Annotated, AsyncGenerator, Optional
+from typing import Annotated, AsyncGenerator, List, Optional
 
 from fastapi import APIRouter, Depends, HTTPException
 from fastapi.responses import StreamingResponse
@@ -87,7 +87,7 @@ def try_insert_reasoning(
         if msg.role == "user":
             msg.reasoning = reasoning
 
-def collapse_history_to_first_message(chat_request: ChatRequest) -> ChatRequest:
+def collapse_history_to_first_message(chat_history: List[Message]) -> List[Message]:
     """
     Сворачивает историю в первое сообщение и возвращает новый объект ChatRequest.
     Формат:
@@ -118,18 +118,18 @@ def collapse_history_to_first_message(chat_request: ChatRequest) -> ChatRequest:
         </last-request>
         assistant:
     """
-    if not chat_request.history:
-        return ChatRequest(history=[])
+    if not chat_history:
+        return []
     
-    last_user_message = chat_request.history[-1]
-    if chat_request.history[-1].role != "user":
+    last_user_message = chat_history[-1]
+    if chat_history[-1].role != "user":
         logger.warning("Last message is not user message")
         
 
     # Собираем историю в одну строку
     collapsed_content = []
     collapsed_content.append("<INPUT><history>\n")
-    for msg in chat_request.history[:-1]:
+    for msg in chat_history[:-1]:
         if msg.content.strip():
             tabulated_content = msg.content.strip().replace("\n", "\n\t\t")
             collapsed_content.append(f"\t<{msg.role.strip()}>\n\t\t{tabulated_content}\n\t</{msg.role.strip()}>\n")
@@ -160,7 +160,7 @@ def collapse_history_to_first_message(chat_request: ChatRequest) -> ChatRequest:
         content=new_content,
         searchResults=''
     )
-    return ChatRequest(history=[new_message])
+    return [new_message]
         
 async def sse_generator(request: ChatRequest, llm_api: DeepInfraApi, system_prompt: str, 
                         predict_params: LlmPredictParams,
@@ -173,7 +173,7 @@ async def sse_generator(request: ChatRequest, llm_api: DeepInfraApi, system_prom
     Генератор для стриминга ответа LLM через SSE.
     """
     # Создаем экземпляр "сквозного" лога через весь процесс
-    log = LogCreateSchema(user_name=current_user.username)
+    log = LogCreateSchema(user_name=current_user.username, chat_id=request.chat_id)
     
     try:
         old_history = request.history
@@ -259,7 +259,10 @@ async def sse_generator(request: ChatRequest, llm_api: DeepInfraApi, system_prom
     log_error = None
     try:          
         # Сворачиваем историю в первое сообщение
-        collapsed_request = collapse_history_to_first_message(request)
+        collapsed_request = ChatRequest(
+            history=collapse_history_to_first_message(request.history), 
+            chat_id = request.chat_id
+        )
         
         log.llm_result = ''
         

routes/log.py

@@ -1,8 +1,11 @@
+from io import BytesIO
 import logging
 from datetime import datetime
+import sys
 from typing import Annotated, List, Optional
 
 from fastapi import APIRouter, Depends, HTTPException, Query
+from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
 
 from common import auth
@@ -10,6 +13,7 @@ from common.common import configure_logging
 from components.services.log import LogService
 from schemas.log import LogCreateSchema, LogFilterSchema, LogSchema, PaginatedLogResponse
 import common.dependencies as DI
+import pandas as pd
 
 router = APIRouter(tags=['Logs'])
 
@@ -22,6 +26,7 @@ async def get_all_logs(
     log_service: Annotated[LogService, Depends(DI.get_log_service)], 
     current_user: Annotated[any, Depends(auth.get_current_user)]
 ):
+    logger.info(f"Fetching logsываыва with filters: {filters.model_dump(exclude_none=True)}")
     logger.info(f'GET /logs')
 
     try:
@@ -29,4 +34,52 @@ async def get_all_logs(
     except HTTPException as e:
         raise e
     except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+    
+@router.get('/logs/excel')
+async def get_all_logs_excel(
+    filters: LogFilterSchema = Depends(),
+    log_service: LogService = Depends(DI.get_log_service),
+    current_user: any = Depends(auth.get_current_user)
+):
+    logger.info(f'GET /logs/excel with filters: {filters.model_dump(exclude_none=True)}')
+
+    try:
+        # Получаем логи без пагинации (все записи по фильтру)
+        filters.page = 1
+        filters.page_size = sys.maxsize
+        logs_response = log_service.get_list(filters)
+
+        logs_data = [
+            {
+                'ID': log.id,
+                'Date Created': log.date_created,
+                'User Name': log.user_name or '',
+                'Chat ID': log.chat_id or '',
+                'User Request': log.user_request or '',
+                'QE Result': log.qe_result or '',
+                'Search Result': log.search_result or '',
+                'LLM Result': log.llm_result or ''
+            }
+            for log in logs_response.data
+        ]
+
+        df = pd.DataFrame(logs_data)
+        
+        output = BytesIO()
+        with pd.ExcelWriter(output, engine='openpyxl') as writer:
+            df.to_excel(writer, index=False, sheet_name='Logs')
+
+        headers = {
+            'Content-Disposition': 'attachment; filename="logs.xlsx"',
+            'Content-Type': 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'
+        }
+
+        output.seek(0)
+        return StreamingResponse(output, headers=headers, media_type='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet')
+
+    except HTTPException as e:
+        raise e
+    except Exception as e:
+        logger.error(f'Error generating Excel: {str(e)}')
         raise HTTPException(status_code=500, detail=str(e))

schemas/chat.py

@@ -0,0 +1,30 @@
+from typing import List, Optional
+from pydantic import BaseModel
+
+from components.llm.common import ChatRequest, Message
+
+
+class MessageSchema(BaseModel):
+    role: str
+    content: str
+    searchResults: Optional[str] = ''
+    searchEntities: Optional[List[str]] = []
+    reasoning: Optional[str] = ''
+    
+    def to_bl(self) -> Message:
+        return ChatRequest.model_validate(self.model_dump())
+    
+    
+class ChatRequestSchema(BaseModel):
+    history: List[MessageSchema]
+    chat_id: Optional[str]
+    
+    def to_bl(self) -> ChatRequest:
+        return ChatRequest.model_validate(self.model_dump(exclude={"chat_id"}))
+    
+    @classmethod
+    def from_bl(cls, bl: ChatRequest, chat_id: Optional[str] = None) -> "ChatRequestSchema":
+        return cls.model_validate({
+            "history": [msg.model_dump() for msg in bl.history],
+            "chat_id": chat_id
+        })

schemas/log.py

@@ -1,7 +1,7 @@
 from datetime import datetime
 from typing import List, Optional
 
-from pydantic import BaseModel
+from pydantic import UUID4, BaseModel
 
 
 class LogSchema(BaseModel):
@@ -13,6 +13,7 @@ class LogSchema(BaseModel):
     llm_result: Optional[str] = None
     llm_settings: Optional[str] = None
     user_name: Optional[str] = None
+    chat_id: Optional[str] = None
     error: Optional[str] = None
     
 class LogCreateSchema(BaseModel):
@@ -23,14 +24,21 @@ class LogCreateSchema(BaseModel):
     llm_settings: Optional[str] = None
     user_name: Optional[str] = None
     error: Optional[str] = None
+    chat_id: Optional[str] = None
 
+class SortParam(BaseModel):
+    field: str
+    direction: str  # "asc" | "desc"
+    
 class LogFilterSchema(BaseModel):
     user_name: Optional[str] = None
+    chat_id: Optional[str] = None
     date_from: Optional[datetime] = None
     date_to: Optional[datetime] = None
     
     page: int = 1  # Номер страницы, по умолчанию 1
     page_size: int = 50  # Размер страницы, по умолчанию 50
+    sort: Optional[List[SortParam]] = None  # Список параметров сортировки
     
     class Config:
         json_schema_extra = {
@@ -39,7 +47,10 @@ class LogFilterSchema(BaseModel):
                 "date_from": "2024-01-01T00:00:00",
                 "date_to": "2026-12-31T23:59:59",
                 "page": 1,
-                "page_size": 50
+                "page_size": 50,
+                "sort": [
+                    {"field": "date_created", "direction": "desc"}
+                ]
             }
         }
 
@@ -48,4 +59,7 @@ class PaginatedLogResponse(BaseModel):
     total: int
     page: int
     page_size: int
-    total_pages: int
+    total_pages: int
+    
+
+