Develop

.github/workflows/develop.yml

@@ -82,8 +82,8 @@ jobs:
  run: pip install -r api/requirements.txt pyinstaller==6.6.0
 
  - name: Build flask exe
- run: pyinstaller --name app --onefile --console api/app.py --hidden-import=tiktoken_ext.openai_public --hidden-import=tiktoken_ext
-
+ run: pyinstaller api/app.spec
+ 
  - name: Install dependencies
  run: npm install
 

.github/workflows/main.yml

@@ -82,7 +82,7 @@ jobs:
  run: pip install -r api/requirements.txt pyinstaller==6.6.0
 
  - name: Build flask exe
- run: pyinstaller --name app --onefile --console api/app.py --hidden-import=tiktoken_ext.openai_public --hidden-import=tiktoken_ext
+ run: pyinstaller app.spec
 
  - name: Install dependencies
  run: npm install

README.md

@@ -1,23 +1,35 @@
 # LinguifAI
+
 Projeto NLP 2 - 2023.2
 
 ## Tecnologias utilizadas:
+
 O projeto utiliza das seguintes tecnologias e ferramentas:
 
 ### Front-End
-* React
-* React-Router
-* Axios
-* ElectronJs
-* Tailwind
+
+- React
+- React-Router
+- Axios
+- ElectronJs
+- Tailwind
 
 ### Back-End
-* Python
-* Flask
+
+- Python
+- Flask
 
 ## Como rodar a aplicação:
 
-Primeiramente, instale as depencencias:
+Primeiramente, instale as dependências:
+
+Dependências do back-end:
+
+```bash
+pip install -r api/requirements.txt
+```
+
+Dependências do front-end:
 
 ```bash
 yarn
@@ -48,6 +60,6 @@ npm run electron
 - [x] Abrir CSV
 - [x] Exibir Preview de N linhas do CSV
 - [x] Escolher colunas de entrada
-- [X] Selecionar classificador e enviar dados
+- [x] Selecionar classificador e enviar dados
 - [x] Exibir resultado do classificador
-- [x] Exportar resultado em csv?
+- [x] Exportar resultado em csv?

api/Neural_Network2.py

@@ -381,7 +381,7 @@ def create_and_train_rnn_model(df, name, epochs = 10, batch_size = 32, learning_
 
  if len(valid_losses) > 2 and all(valid_loss >= loss for loss in valid_losses[-3:]):
  print('Stopping early due to lack of improvement in validation loss.')
- break
+ # break
 
  train_losses.append(train_loss)
  valid_losses.append(valid_loss)

api/app.py

@@ -58,7 +58,10 @@ def chat():
  chat_history = data.get('history', [])
  api_key = data.get('apikey')
 
+
  if df is not None:
+
+ print(df.head(1))
  documents = split_dataframe_into_documents(df)
 
  embeddings = OpenAIEmbeddings(api_key=api_key)
@@ -74,27 +77,24 @@ def chat():
 
  return jsonify(reply=bot_reply)
  else:
- print("No df")
- return jsonify(reply="No data available."), 400
-
- # messages = [{"role": "system", "content": "You are a helpful assistant."}]
- # for msg in chat_history:
- # messages.append({"role": "user" if msg['origin'] == 'user' else "assistant", "content": msg['text']})
- # messages.append({"role": "user", "content": user_message})
-
- # try:
- # client = openai.OpenAI(api_key = api_key)
- # response = client.chat.completions.create(
- # model="gpt-3.5-turbo",
- # messages=messages,
- # max_tokens=200
- # )
- # bot_reply = response.choices[0].message.content.strip()
-
- # return jsonify(reply=bot_reply)
- # except Exception as e:
- # print(f"Error: {e}")
- # return jsonify(reply="Desculpe, ocorreu um erro ao processar sua mensagem."), 500
+ messages = [{"role": "system", "content": "You are a helpful assistant."}]
+ for msg in chat_history:
+ messages.append({"role": "user" if msg['origin'] == 'user' else "assistant", "content": msg['text']})
+ messages.append({"role": "user", "content": user_message})
+
+ try:
+ client = openai.OpenAI(api_key = api_key)
+ response = client.chat.completions.create(
+ model="gpt-3.5-turbo",
+ messages=messages,
+ max_tokens=200
+ )
+ bot_reply = response.choices[0].message.content.strip()
+
+ return jsonify(reply=bot_reply)
+ except Exception as e:
+ print(f"Error: {e}")
+ return jsonify(reply="Desculpe, ocorreu um erro ao processar sua mensagem."), 500
 
 
 def shutdown_server():
@@ -116,7 +116,7 @@ def receive_file():
  if file.filename == '':
  return jsonify({'error': 'No selected file'}), 400
  if file:
- df = pd.read_csv(file)
+ df = pd.read_csv(file, on_bad_lines='skip')
  return jsonify({'message': 'File uploaded successfully'}), 200
 
 
@@ -282,40 +282,6 @@ def apikey():
  return jsonify(reply="Desculpe, ocorreu um erro ao processar sua mensagem."), 500
 
 
-# @app.route('/chat', methods=['POST'])
-# def chat():
-# global df
-# if df is not None:
-# # run rag
-# print(df.head(1))
-# else:
-# print("No df")
-# data = request.get_json()
-# user_message = data.get('message')
-# chat_history = data.get('history', [])
-# api_key = data.get('apikey')
-
-# messages = [{"role": "system", "content": "You are a helpful assistant."}]
-# for msg in chat_history:
-# messages.append({"role": "user" if msg['origin'] == 'user' else "assistant", "content": msg['text']})
-# messages.append({"role": "user", "content": user_message})
-
-# try:
-# client = openai.OpenAI(api_key = api_key)
-# response = client.chat.completions.create(
-# model="gpt-3.5-turbo", # ou a gente poderia ver com gpt 4 mas por enquanto coloquei 3.5
-# messages=messages,
-# max_tokens=200
-# )
-# bot_reply = response.choices[0].message.content.strip()
-
-# return jsonify(reply=bot_reply)
-# except Exception as e:
-# print(f"Error: {e}")
-# return jsonify(reply="Desculpe, ocorreu um erro ao processar sua mensagem."), 500
-
-
-
 if __name__ == '__main__':
  training_progress = {
  'training_progress': 0,

api/app.spec

@@ -1,3 +1,4 @@
+
 # -*- mode: python ; coding: utf-8 -*-
 
 entry_point = 'app.py'
@@ -9,7 +10,7 @@ a = Analysis(
  pathex=[],
  binaries=[],
  datas=[],
- hiddenimports=[],
+ hiddenimports=['tiktoken_ext.openai_public', 'tiktoken_ext'],
  hookspath=[],
  hooksconfig={},
  runtime_hooks=[],
@@ -48,4 +49,4 @@ coll = COLLECT(
  upx=True,
  upx_exclude=[],
  name='app',
-)
+)

package.json

@@ -5,7 +5,7 @@
  "name": "Cameron",
  "email": "[email protected]"
  },
- "version": "0.2.5",
+ "version": "0.2.8",
  "main": "./public/electron.js",
  "homepage": "./",
  "private": true,
@@ -32,6 +32,8 @@
  "react-papaparse": "^4.1.0",
  "react-router-dom": "^6.15.0",
  "react-scripts": "5.0.0",
+ "react-spinners": "^0.13.8",
+ "react-toastify": "^10.0.5",
  "react-transition-group": "^4.4.5",
  "serve": "^14.2.1",
  "typescript": "^4.9.5"

src/components/chatbot/chatbot.tsx

@@ -50,21 +50,22 @@ const ChatBot: React.FC = () => {
  const errorMessage: Message = { text: "Desculpe, ocorreu um erro. Tente novamente.", origin: 'bot' };
  setChatHistory(prevHistory => [...prevHistory, errorMessage]);
  }
-
+ console.log(message)
  setMessage("");
+ console.log(message)
  };
 
  const sendAPIKeyMessage = () => {
  setChatHistory(prevHistory => [
  ...prevHistory,
- { text: "Olá! Eu sou o (LinguiTalk ou LinguaBot). Coloca a sua chave:", origin: 'bot' }
+ { text: "Olá! Eu sou o LinguiTalk, um chatbot para lhe auxiliar na exploração dos seus dados! Primeiro, insira uma chave API válida do ChatGPT:", origin: 'bot' }
  ]);
  };
 
  const sendInitialMessage = () => {
  setChatHistory(prevHistory => [
  ...prevHistory,
- { text: "Olá! Eu sou o (LinguiTalk ou LinguaBot). Como posso ajudar?", origin: 'bot' }
+ { text: "Olá! Eu sou o LinguiTalk. Como posso ajudar?", origin: 'bot' }
  ]);
  };
 
@@ -98,7 +99,7 @@ const ChatBot: React.FC = () => {
  {isOpen && (
  <div className="fixed bottom-20 right-4 bg-white border border-gray-300 shadow-lg rounded-lg w-80 flex flex-col max-h-[600px]">
  <div className="bg-blue-500 text-white p-4 flex justify-between items-center">
- <h2 className="text-lg">LinguiTalk ou LinguaBot</h2>
+ <h2 className="text-lg">LinguiTalk</h2>
  <button
  className="text-white hover:text-gray-200"
  onClick={toggleChat}
@@ -130,7 +131,7 @@ const ChatBot: React.FC = () => {
  value={message}
  onChange={(e) => setMessage(e.target.value)}
  onKeyPress={(e) => {
- if (e.key === 'Enter') sendMessage();
+ if (e.key === 'Enter') sendMessage()
  }}
  />
  <button