Project Name: bot_jarviis

Table of Contents

1. Description
2. Features
3. Installation
4. Usage
5. Demo
6. Contributing
7. License
8. Database
9. Future features

Description:

bot_jarviis is a powerful and versatile chatbot designed to assist users with various tasks. It is built using advanced natural language processing techniques and can understand and respond to user queries in a human-like manner. Whether you need help with information retrieval, task automation, or just want to have a friendly conversation, bot_jarviis is here to assist you.

Features:

• Natural Language Processing: bot_jarviis utilizes NLP algorithms to understand and interpret user queries accurately.
• Voice answer: bot_jarviis can provide voice answers to user queries, allowing for a more interactive and engaging experience.
• Voice cloning: bot_jarviis can generate voice clones of different personalities, allowing for a more personalized and unique user experience.
• Information Retrieval: bot_jarviis can search the web and retrieve relevant information based on user queries, providing quick and accurate answers.
• Conversation Mode: Engage in a friendly conversation with bot_jarviis and enjoy its witty and intelligent responses.
• Customization: bot_jarviis can be easily customized and extended to suit your specific needs. Add new functionalities or integrate it with other systems seamlessly.

ML-Design

Installation:

1. Clone the repository: git clone https://github.com/vladimirdimitrov/bot_jarviis.git
2. Navigate to the project directory: cd bot_jarviis
3. Install the required dependencies: pip install -r requirements.txt
4. Create sqlite database cat database/init.sql | sqlite3 db.sqlite3
5. Create config.py in root directory and add this variables:
   • secret_key: used for API Yandex
   • API_TOKEN: This is the bot token used for interacting with the Telegram Bot API.
   • system_prompt: variable is used in service/yandex_gpt.py, and it's a prompt used for the Yandex GPT API to generate responses.
   • catalog_id: variable is also used in service/yandex_gpt.py. It is an identifier for a specific catalog used with the Yandex GPT API.
   • SQLITE_DB_FILE: : this is the path to the SQLite database file used in your project. It's used in database/database_manager.py to establish a connection to the database.

Usage:

1. Start the bot_jarviis application: python3 bot.py
2. Open your telegram app and connect to the bot_jarviis server.
3. Begin interacting with bot_jarviis by sending messages and queries.

Demo

Demo

Contributing:

We welcome contributions from the community to enhance the functionality and performance of bot_jarviis. To contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch: git checkout -b feature/your-feature-name
3. Make your changes and commit them: git commit -m 'Add your feature description'
4. Push to the branch: git push origin feature/your-feature-name
5. Submit a pull request.

License:

This project is licensed under the MIT License. See the LICENSE file for more details.

Database:

This project uses SQLite as its primary data store.

Setup:

SQLite comes pre-installed with Python. The database file is typically stored in the project directory.

Structure

bot_user Table

This table stores information about the users of the chatbot. It has the following columns:

• telegram_id (INTEGER): The unique identifier for each user.
• created_at (TIMESTAMP): The timestamp indicating when the user was created.
• count_prompt (INTEGER): The number of prompts sent by the user.

gpt_answer Table

This table stores the generated answers from the GPT model. It has the following columns:

• id (INTEGER): The unique identifier for each answer.
• created_at (TIMESTAMP): The timestamp indicating when the answer was generated.
• context (JSON): The context of the conversation in JSON format.
• gpt_answer (TEXT): The generated answer from the GPT model.
• telegram_id (FOREIGN KEY): The foreign key referencing the telegram_id column in the bot_user table.

analytics Table

This table stores analytics data related to the chatbot. It has the following columns:

• id (INTEGER): The unique identifier for each analytics entry.
• count_answers (INTEGER): The total count of answers generated.
• tokens_output (INTEGER): The number of tokens output by the GPT model.
• cost (FLOAT): The cost associated with generating the answers.

Future features

1. Multi-language Support: bot_jarviis will be able to understand and respond to queries in multiple languages, making it more accessible to a global audience.
2. Integration with External APIs: bot_jarviis will have the ability to integrate with external APIs, enabling it to fetch data from various sources and provide more comprehensive answers.
3. User Profiles: bot_jarviis will support user profiles, allowing users to save their preferences and personalize their interactions with the chatbot.
4. Sentiment Analysis: bot_jarviis will have the capability to analyze the sentiment of user queries, allowing it to respond with empathy and understanding.
5. Task Automation: bot_jarviis will be able to perform automated tasks based on user requests, such as sending emails, scheduling appointments, or performing system operations.
6. Documentation: bot_jarviis will have comprehensive documentation, including usage examples, API references, and tutorials to help users get started and make the most out of the chatbot.