Welcome to the Context-Aware Slackbot project! This bot leverages advanced technologies to provide intelligent responses within Slack channels.
The Context-Aware Slackbot combines state-of-the-art components to deliver enhanced functionality:
- LlamaIndex: A powerful tool for natural language processing (NLP), enabling the bot to understand and analyze messages within Slack channels.
- OpenAI LLM: Empowers the bot with context-awareness, allowing it to generate meaningful responses based on the conversation history.
- Qdrant: Provides efficient data storage capabilities, ensuring seamless retrieval and management of chat messages and associated metadata.
- Intelligent Responses: The bot can understand user queries and generate relevant responses by analyzing the context of the conversation.
- Real-time Learning: Continuously learns from new messages to improve its understanding and response accuracy over time.
- Efficient Data Storage: Utilizes Qdrant for efficient storage and retrieval of chat messages, enabling fast and reliable access to historical conversations.
- Speaker Metadata: Metadata about the speaker is attached to each message, allowing the bot to answer questions like "What did Logan say about the project?"
- Threaded Conversation Support: The bot can recognize and respond to follow-up questions within threads, mimicking human conversation dynamics.
To use the Context-Aware Slackbot:
- Deploy the Bot: Deploy the bot using the provided instructions, ensuring all necessary dependencies and environment variables are set up correctly.
- Join Channels: Add the bot to Slack channels where you want it to operate, allowing it to listen to and respond to messages.
- Interact: Users can interact with the bot by sending messages or asking questions. The bot will analyze the incoming messages, generate context-aware responses, and provide assistance or information as needed.