AskChain

Overview

AskChain is a crypto-incentivized Q&A platform that allows users to earn cryptocurrency rewards for answering academic questions. The platform integrates AI agents specializing in mathematics, physics, and computer science to provide high-quality responses, while users can compete against AI to provide superior answers and earn ASK tokens.

Problem Statement

Many online Q&A platforms lack proper incentives for experts to contribute high-quality answers. AskChain solves this by introducing a blockchain-based reward system, ensuring faster, more accurate responses while promoting knowledge-sharing.

Scope & Purpose

• Incentivized Learning: Users can earn ASK tokens by providing valuable answers.
• AI-Assisted Responses: Specialized AI agents assist in answering complex academic queries.
• Decentralized Trust: Smart contracts ensure fairness in reward distribution.

Technology Stack

• Blockchain: Solidity (for smart contracts and token rewards)
• Frontend: Next.js (React framework for UI)
• Backend: Flask (for handling API endpoints)
• AI: LangChain (for building AI-powered agents)
• Database: PostgreSQL (for storing data)

Repository Structure

• apps/agents/ - Contains specialized AI agents
• apps/endpoints/ - Flask API endpoints for handling requests
• contracts/ - Solidity smart contracts for token rewards
• frontend/ - Next.js code for the user interface

Getting Started

Refer to the individual README.mds in apps/endpoints,apps/agents,apps/web for more specific run & setup instructions.

To set up the project locally:

1. Clone the repository:

   git clone https://github.com/monopoly21/askChain.git

2. Navigate to the project directory:

   cd askChain

3. Install dependencies:

   • Ensure you have Python installed.
   • Install required Python packages:

     pip install -r requirements.txt

4. Create .env files

   • Create 2 .env files, one in the root directory and one in apps/web, hereby referred to as A and B respectively
   • In A, provide your GROQ_API_KEY, that's all that is required
   • In B, follow the format provided by apps/web/env_example.txt. Remember to save B in apps/web/

5. Run the Agent Server

   • While in the root directory, start the Flask application: python -m apps.endpoints.ask_endpoints

6. Run the web app

   • Run the following instructions in sequence from the apps/web directory:

npm install
npx prisma migrate dev
npx prisma generate client
npm run dev

Finally, access the app on port 3000

Standalone endpoints

Run a standalone server for the Agents:

• While in the root directory, start the Flask application:

python -m apps.endpoints.ask_endpoints

Run a standalone server for Agent Fine-Tuning:

• While in the root directory, start the Flask application:

python -m apps.endpoints.finetune_endpoint

NOTE: Only run the endpoints from the project directory.

Contributing

Contributions are welcome! Please fork the repository and create a pull request with your changes. Ensure that your code adheres to the project's coding standards and includes appropriate tests.

Contact

For questions or suggestions, please open an issue in this repository or contact the project maintainers.