Merge pull request #17 from it-at-m/renovate/quart-0.x

Update dependency quart to v0.19.6 and werkzeug 3.0.3, fixed tests and cleaned up some code

.github/workflows/python-test.yaml

@@ -36,6 +36,6 @@ jobs:
             python -m pip install --upgrade pip
             pip install -r requirements-dev.txt
         - name: Lint with ruff
-          run: ruff .
+          run: ruff check .
         - name: Run Python tests
           run: python3 -m pytest

app/backend/app.py

@@ -3,6 +3,7 @@
 import os
 import time
 from typing import cast
+
 from azure.monitor.opentelemetry import configure_azure_monitor
 from opentelemetry.instrumentation.aiohttp_client import AioHttpClientInstrumentor
 from opentelemetry.instrumentation.asgi import OpenTelemetryMiddleware
@@ -14,15 +15,16 @@
     jsonify,
     make_response,
     request,
+    send_file,
     send_from_directory,
-    send_file
 )
-from init_app import initApp
-from core.modelhelper import num_tokens_from_message
+
 from core.authentification import AuthentificationHelper, AuthError
+from core.helper import format_as_ndjson
+from core.modelhelper import num_tokens_from_message
 from core.types.AppConfig import AppConfig
 from core.types.countresult import CountResult
-from core.helper import format_as_ndjson
+from init_app import initApp
 
 bp = Blueprint("routes", __name__, static_folder='static')
 
@@ -35,7 +37,7 @@ async def handleAuthError(error: AuthError):
 
 @bp.route("/")
 async def index():
-    cfg = get_config_and_authentificate()
+    get_config_and_authentificate()
     return await bp.send_static_file("index.html")
 
 @bp.route("/favicon.ico")
@@ -44,7 +46,7 @@ async def favicon():
 
 @bp.route("/assets/<path:path>")
 async def assets(path):
-    cfg = get_config_and_authentificate()
+    get_config_and_authentificate()
     return await send_from_directory("static/assets", path)
 
 

app/backend/brainstorm/brainstorm.py

@@ -1,18 +1,18 @@
-from typing import Any, Optional
-from langchain.chains import LLMChain
+from typing import Optional
+
+from langchain.chains import LLMChain, SequentialChain
 from langchain.prompts import PromptTemplate
-from langchain.chains import SequentialChain
 from langchain_community.callbacks import get_openai_callback
 from langchain_core.runnables.base import RunnableSerializable
 
 from brainstorm.brainstormresult import BrainstormResult
-from core.types.LlmConfigs import LlmConfigs
-from core.datahelper import Repository
-from core.types.Config import ApproachConfig
+from core.datahelper import Repository, Requestinfo
 from core.types.AzureChatGPTConfig import AzureChatGPTConfig
-from core.datahelper import Requestinfo
+from core.types.Config import ApproachConfig
+from core.types.LlmConfigs import LlmConfigs
+
 
-class Brainstorm():
+class Brainstorm:
     """
     Simple brainstorm implementation. One shot generation of certain markdown files. Translates the result into a target language.
     """

app/backend/chat/chat.py

@@ -1,28 +1,29 @@
-from typing import Any, AsyncGenerator, Optional, Sequence, Tuple
 import asyncio
+from typing import Any, AsyncGenerator, Optional, Sequence, Tuple
+
+from langchain.callbacks.streaming_aiter import AsyncIteratorCallbackHandler
+from langchain.chains import LLMChain
+from langchain.memory import ConversationBufferMemory
 from langchain.prompts import (
     ChatPromptTemplate,
-    MessagesPlaceholder,
     HumanMessagePromptTemplate,
-    SystemMessagePromptTemplate
+    MessagesPlaceholder,
+    SystemMessagePromptTemplate,
 )
-from langchain.chains import LLMChain
-from langchain.memory import ConversationBufferMemory
-from langchain.callbacks.streaming_aiter import AsyncIteratorCallbackHandler
-from langchain_core.messages import AIMessage
 from langchain_community.callbacks import get_openai_callback
+from langchain_core.messages import AIMessage
 from langchain_core.runnables.base import RunnableSerializable
 
 from chat.chatresult import ChatResult
-from core.datahelper import Requestinfo
+from core.datahelper import Repository, Requestinfo
 from core.modelhelper import num_tokens_from_message, num_tokens_from_messages
-from core.datahelper import Repository
-from core.types.Config import ApproachConfig
+from core.types.AzureChatGPTConfig import AzureChatGPTConfig
 from core.types.Chunk import Chunk, ChunkInfo
+from core.types.Config import ApproachConfig
 from core.types.LlmConfigs import LlmConfigs
-from core.types.AzureChatGPTConfig import AzureChatGPTConfig
 
-class Chat():
+
+class Chat:
     """Chat with a llm via multiple steps.
     """
 

app/backend/chat/chatresult.py

@@ -1,4 +1,5 @@
 from typing import TypedDict
 
+
 class ChatResult(TypedDict):
     content: str

app/backend/core/authentification.py

@@ -1,8 +1,10 @@
 import functools
+
 import requests
 from joserfc import jwt
 from joserfc.jwk import KeySet
 
+
 class AuthError(Exception):
     def __init__(self, error, status_code):
         self.error = error
@@ -44,7 +46,7 @@ def authentificate(self, accesstoken):
 
         if self.role not in roles:
             raise AuthError("Sie haben noch keinen Zugang zu MUCGPT freigeschalten.  Wie das geht, erfahren sie in im folgendem WILMA Artikel: https://wilma.muenchen.de/pages/it-steuerung-management/apps/wiki/kuenstliche-intelligenz/list/view/91f43afa-3315-478f-a9a4-7f50ae2a32f2.", status_code=401)
-        return claims;
+        return claims
 
     def decode(self, token):
         keyset = self.get_jwks_data(self.issuer)

app/backend/core/confighelper.py

@@ -1,6 +1,7 @@
 import json
 
-from core.types.Config import to_typed_config, Config
+from core.types.Config import Config, to_typed_config
+
 
 class ConfigHelper:
     """Loads an available configuration.
@@ -10,9 +11,9 @@ def __init__(self, base_path: str, env: str, base_config_name: str = "base"):
         self.base_config_name = base_config_name
         self.env = env
     def loadData(self) -> Config:
-        with open(self.base_path + self.env + ".json", 'r') as f:
+        with open(self.base_path + self.env + ".json") as f:
             env_config = json.load(f)
-        with open(self.base_path + self.base_config_name + ".json", 'r') as f:
+        with open(self.base_path + self.base_config_name + ".json") as f:
             base_config = json.load(f)
         result_dict =  dict(env_config,**base_config)
         return to_typed_config(result_dict)

app/backend/core/datahelper.py

@@ -1,13 +1,11 @@
 
-from sqlalchemy.orm import declarative_base
-from sqlalchemy import Column, Integer, String, DateTime
-from datetime import datetime
-from sqlalchemy import create_engine
-from sqlalchemy.engine import URL
-from sqlalchemy.orm import Session
-from sqlalchemy import func
 import csv
 import io
+from datetime import datetime
+
+from sqlalchemy import Column, DateTime, Integer, String, create_engine, func
+from sqlalchemy.engine import URL
+from sqlalchemy.orm import Session, declarative_base
 
 Base = declarative_base()
 
@@ -25,7 +23,8 @@ class Requestinfo(Base):
     updated_on = Column(DateTime(), default=datetime.now, onupdate=datetime.now)
 
     def __repr__(self):
-        return '<ID %r, Department %r, Tokencount %r, Method %r, Messagecount %r> ' % (self.id, self.department, self.tokencount, self.method, self.messagecount)
+        return f'<ID {self.id!r}, Department {self.department!r}, Tokencount {self.tokencount!r}, Method {self.method!r}, Messagecount {self.messagecount!r}>'
+
 
 
 

app/backend/core/helper.py

@@ -1,9 +1,11 @@
 
-from typing import AsyncGenerator
 import json
 import logging
+from typing import AsyncGenerator
+
 from core.types.Chunk import Chunk
 
+
 async def format_as_ndjson(r: AsyncGenerator[Chunk, None]) -> AsyncGenerator[str, None]:
     """Converts stream of Chunks into Stream of serialized JSON Objects
 

app/backend/core/llmhelper.py

@@ -1,9 +1,11 @@
-from langchain_openai import AzureChatOpenAI
+from langchain_community.llms.fake import FakeListLLM
 from langchain_core.runnables import ConfigurableField
-from langchain_community.llms.fake import  FakeListLLM  
 from langchain_core.runnables.base import RunnableSerializable
+from langchain_openai import AzureChatOpenAI
+
 from core.types.SupportedModels import SupportedModels
 
+
 def getModel(chatgpt_model: str,
              max_tokens: int,
              n: int,

app/backend/core/modelhelper.py

@@ -34,7 +34,7 @@ def get_token_limit(model_id: str) -> int:
     return MODELS_2_TOKEN_LIMITS[model_id]
 
 
-def num_tokens_from_messages(messages: 'list[dict[str, str]]', model: str) -> int:
+def num_tokens_from_messages(messages: list[dict[str, str]], model: str) -> int:
     """  Calculate the number of tokens required to encode a list of messages
 
     Args:

app/backend/core/textsplit.py

@@ -1,8 +1,8 @@
 from typing import List
-from langchain.text_splitter import TokenTextSplitter
+
 import PyPDF2
 from langchain.docstore.document import Document
-
+from langchain.text_splitter import TokenTextSplitter
 
 
 def textToDocs(text: str, chunk_size=2500, chunk_overlap=100) -> List[Document]:

app/backend/core/types/AppConfig.py

@@ -1,13 +1,15 @@
 from typing import TypedDict
+
 from azure.identity.aio import DefaultAzureCredential
-from core.types.AzureChatGPTConfig import AzureChatGPTConfig
-from summarize.summarize import Summarize
-from chat.chat import Chat
+
 from brainstorm.brainstorm import Brainstorm
+from chat.chat import Chat
 from core.authentification import AuthentificationHelper
-from core.types.Config import Config
 from core.datahelper import Repository
-from core.types.Config import BackendConfig
+from core.types.AzureChatGPTConfig import AzureChatGPTConfig
+from core.types.Config import BackendConfig, Config
+from summarize.summarize import Summarize
+
 
 class AppConfig(TypedDict):
     """Config for the app, contains all clients and informations, that are needed

app/backend/core/types/AzureChatGPTConfig.py

@@ -1,6 +1,7 @@
-from azure.core.credentials import AccessToken
 from typing import TypedDict
 
+from azure.core.credentials import AccessToken
+
 
 class AzureChatGPTConfig(TypedDict):
     """Contains all information, that describes an AzureOpenAI endpoint

app/backend/core/types/Chunk.py

@@ -1,4 +1,6 @@
-from typing import TypedDict, Literal
+from typing import Literal, TypedDict
+
+
 class Chunk(TypedDict):
     """Represents a chunk during streaming. Has 3 modes:
     E: Error, message contains the error message.

app/backend/core/types/LlmConfigs.py

@@ -1,4 +1,6 @@
-from typing_extensions import List, NotRequired, TypedDict
+from typing import List
+
+from typing_extensions import NotRequired, TypedDict
 
 
 class LlmConfigs(TypedDict, total=False):

app/backend/core/types/countresult.py

@@ -1,4 +1,5 @@
 from typing import TypedDict
 
+
 class CountResult(TypedDict):
     count: int

app/backend/init_app.py

@@ -1,16 +1,19 @@
 import os
 from typing import Tuple
-from core.types.AzureChatGPTConfig import AzureChatGPTConfig
-from core.types.Config import BackendConfig
-from core.llmhelper import getModel
-from core.datahelper import Repository, Base
+
+from azure.identity.aio import DefaultAzureCredential
+
+from brainstorm.brainstorm import Brainstorm
+from chat.chat import Chat
 from core.authentification import AuthentificationHelper
 from core.confighelper import ConfigHelper
+from core.datahelper import Base, Repository
+from core.llmhelper import getModel
 from core.types.AppConfig import AppConfig
+from core.types.AzureChatGPTConfig import AzureChatGPTConfig
+from core.types.Config import BackendConfig
 from summarize.summarize import Summarize
-from chat.chat import Chat
-from brainstorm.brainstorm import Brainstorm
-from azure.identity.aio import DefaultAzureCredential
+
 
 def read_env():
     """reads configured values from env

app/backend/requirements.txt

@@ -1,5 +1,5 @@
 azure-identity==1.15.0
-quart==0.19.3
+quart==0.19.6
 langchain==0.1.20
 langchain_openai 
 tiktoken
@@ -9,7 +9,7 @@ azure-monitor-opentelemetry==1.0.0b15
 opentelemetry-instrumentation-asgi==0.40b0
 opentelemetry-instrumentation-requests==0.40b0
 opentelemetry-instrumentation-aiohttp-client==0.40b0
-werkzeug==3.0.1
+werkzeug==3.0.3
 joserfc
 requests
 sqlalchemy==2.0.19

app/backend/summarize/summarize.py

@@ -1,22 +1,22 @@
-from concurrent.futures import ThreadPoolExecutor
-from typing import Any, List, Optional, Tuple
 import json
 import re
+from concurrent.futures import ThreadPoolExecutor
+from typing import Any, List, Optional, Tuple
+
+from langchain.chains import LLMChain, SequentialChain
 from langchain.prompts import PromptTemplate
-from langchain.chains import SequentialChain, LLMChain
 from langchain_community.callbacks import get_openai_callback
 from langchain_core.runnables.base import RunnableSerializable
 
-from summarize.summarizeresult import SummarizeResult
-from core.datahelper import Repository
-from core.types.Config import ApproachConfig
-from core.datahelper import Requestinfo
-from core.textsplit import  splitPDF, splitText
+from core.datahelper import Repository, Requestinfo
+from core.textsplit import splitPDF, splitText
 from core.types.AzureChatGPTConfig import AzureChatGPTConfig
+from core.types.Config import ApproachConfig
 from core.types.LlmConfigs import LlmConfigs
+from summarize.summarizeresult import SummarizeResult
 
 
-class Summarize():
+class Summarize:
     """Summarizes text. Chunks long texts. Individual chunks where summarized with Chain of Density prompting: https://arxiv.org/abs/2309.04269. Afterwards the text is translated into the target language."""
 
     user_sum_prompt = """

app/frontend/src/components/UserChatMessage/RollbackMessage.tsx

@@ -1,6 +1,6 @@
 import { Button, Tooltip } from "@fluentui/react-components"
 import { useTranslation } from "react-i18next";
-import { indexedDBStorage, popLastInDB } from "../../service/storage";
+import { deleteFromDB, indexedDBStorage, popLastInDB } from "../../service/storage";
 import { DeleteArrowBackRegular } from "@fluentui/react-icons";
 
 import styles from "./UserChatMessage.module.css"
@@ -30,6 +30,7 @@ export const RollBackMessage = ({ message, setQuestion, answers, setAnswers, sto
         }
         if (answers.length == 0) {
             lastQuestionRef.current = ""
+            deleteFromDB(storage)
         } else {
             lastQuestionRef.current = last[1]
         }