$1,350
$2
958
Learning Outcomes
By the end of this quest, you will be able to:
- Set up and configure a chat agent that intelligently integrates a QA dataset with athe Llama 2 model.
- Implement functionality that updates the QA dataset with new entries when an answer is generated by a Llama 2 model.
- Develop an interactive user interface for your chat agent using Gradio, allowing users to interact with it through a web-based platform.
- Understand how to balance between pre-existing knowledge (QA dataset) and AI-generated content in a conversational agent.
- Deploy your chat agent as a web application that becomes more intelligent over time as it learns from new questions and answers.
Quest Details
Introduction
In this quest, you will take your skills to the next level by building a dynamic chat agent using the Llama 2 model from Hugging Face Transformers. Unlike a basic chatbot, this chat agent will first check if the question has a predefined answer in a QA dataset, and if not, it will generate a response using the Llama 2 model.
The agent will also automatically update the dataset with new Q&A pairs, ensuring that it becomes more knowledgeable over time. By integrating Gradio, you’ll create an interactive user interface for your chat agent, making it accessible and user-friendly.
This quest will equip you with practical experience in handling both structured (QA dataset) and unstructured (LLM-based responses) data sources, as well as deploying an AI-powered chat service.
For technical help on the StackUp platform & quest-related questions, join our Discord, head to the quest-helpdesk channel and look for the correct thread to ask your question.
Deliverables
This quest has 1 deliverable.
- A screenshot
This quest is part of a campaign so do check out other quests!
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