Guideline Manual
Our step-by-step guide will walk you through each function of the platform, including model customisation, knowledge contribution, quality assurance, and model evaluation.
Model Customisation
Create your own chatbot by following these steps:
Connect your Wallet
Go to the co-creation page.
In the top right corner, you will find a button labeled "Create new model." Click on the button, and a pop-up will appear.
When you open the pop-up, you'll see an example of how the data is organized. It's important to have documents that are closely related to each other to improve the accuracy of the model. Make sure to review and adjust the documents to ensure they are relevant and coherent, which will help enhance the AI model's performance and effectiveness.
| Parameter Name | Description |
|---|---|
Model Name | The name for you Chat bot |
Description | Tell us what is your chat bot going to do |
Data Required | What data do you want |
Example Knowledge | The preset training document can be one of the following options. Users must contribute at least three verified knowledge documents in order to create a model:
|
PDF and TXT upload
Raw text upload
Link upload
After the clicking the “Create” we will validate the data you submitted.After clicking the "Create" button, we will validate the data you submitted.
The success page
To check the model status, you can go to “My models” for more status.
Knowledge Contribution
This interaction allows the user to continuously provide information to the model for accuracy and improvement of the knowledge base. Here, you can truly experience how co-creation can be achieved!
Select a model and click the "Contribute Knowledge" button.
Before contributing knowledge, please carefully read the "Data Required" field.
Each person can contribute documents in any of the following formats:
PDF,TXT
Raw text
Website links
After selecting the document, click "Complete" to proceed.
The data validation process will approximately take 1 minute to complete.
You can always check the progress of your data contribution in the "My Model" section.
Similarly, you can go to "My Models" and check the points allocation.
Quality Assurance
Quality assurance is crucial in evaluating and refining the knowledge base to ensure its alignment with specific use cases. To recognize their valuable contributions, we have implemented a reward system to incentivize and appreciate their efforts. By voting on the data sources, we can assess and acknowledge their contributions, ensuring they are duly recognized and rewarded.
Click on the Preview button; here, we will list out all the data sources contributed to the chatbot.
You can preview the data source to validate the data.
You can then vote the data source in terms of the quality
Model Evaluation
Evaluate the model and interact with the AI agent to assess the performance and accuracy of the RAG-enhanced LLM by chatting with the chatbot. You can test if the bot has learnt all the data we contributed or not. Each user can chat with the bot 10 times per day free of charge.
Simply click on the Chat button
Feel free to ask any questions or seek information about the data provided. For instance, the bot has been trained on a wide range of information concerning FLock. So, don't hesitate to ask anything related to FLock and its associated topics.
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