Practical Exercises for New Members: Automate DeFi Actions with Curve, Frax, and AAVE
Gemach DAO
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September 20th, 2024

Practical Exercises for New Members: Automate DeFi Actions with Curve, Frax, and AAVE

Welcome aboard! We're excited to have you join us in exploring the powerful capabilities of D.A.T.A (Decentralized Autonomous Trading Agents). To help you get hands-on experience, we've crafted a series of practical exercises focused on automating blockchain actions with popular DeFi protocols: Curve, Frax, and AAVE. These exercises will guide you through building agents and workflows that interact with these platforms, enhancing your skills and knowledge in the DeFi space.

Exercise 1: Automate Liquidity Provision on Curve

Objective: Build an agent that adds liquidity to a Curve pool, allowing you to earn fees from trades.

Steps:

  1. Understand Curve Finance:

    • Curve is a decentralized exchange optimized for low-slippage swaps between similar assets, like stablecoins.

    • By providing liquidity, you earn a portion of the trading fees.

  2. Define a Skill:

    • Name: add_liquidity_curve

    • Description: "Adds liquidity to a specified Curve pool using provided tokens."

    • Content: Implement a function to interact with Curve's add_liquidity method.

      def add_liquidity_curve(pool_address, amounts, min_mint_amount, blockchain):
    # Interact with the Curve pool contract to add liquidity
    # pool_address: Address of the Curve pool
    # amounts: List of token amounts to deposit
    # min_mint_amount: Minimum amount of LP tokens expected
    # blockchain: 'ETH' for Ethereum
    pass  # Replace with actual implementation

  3. Create an Agent:

    • Name: CurveLiquidityAgent

    • Description: "An agent that automates adding liquidity to Curve pools."

    • Maximum Auto Reply: 2

    • Instructions: "When the user requests, use add_liquidity_curve to add liquidity to the specified Curve pool."

  4. Configure an Agent Workflow:

    • Navigate to Agent Workflows and create a Workflow Two Agents.

    • Sender Agent: UserAgent (represents user inputs).

    • Receiver Agent: CurveLiquidityAgent

    • Summary Method: Last Message

  5. Test the Agent in the Playground:

    • Go to the Playground section and start a new session with your workflow.

    • In the Chat View, instruct: "Add liquidity to the 3pool on Curve using 1000 USDC and 1000 DAI."

    • The agent should confirm the details and execute the transaction.

Outcome: You'll learn how to automate liquidity provision on Curve, earning fees and enhancing your DeFi participation.

Exercise 2: Automate Minting FRAX Stablecoins

Objective: Create an agent that mints FRAX by depositing collateral on the Frax Protocol.

Steps:

  1. Understand Frax Protocol:

    • Frax is the first fractional-algorithmic stablecoin, maintaining its peg through collateral and algorithmic mechanisms.

    • Users can mint FRAX by supplying collateral like USDC.

  2. Define a Skill:

    • Name: mint_frax

    • Description: "Mints FRAX stablecoins by providing collateral."

    • Content: Implement a function to interact with Frax's mintFrax method.

      def mint_frax(collateral_amount, collateral_token, min_frax_out, blockchain):
    # Interact with the Frax contract to mint FRAX
    # collateral_amount: Amount of collateral to deposit
    # collateral_token: Address of the collateral token (e.g., USDC)
    # min_frax_out: Minimum FRAX expected
    # blockchain: 'ETH' for Ethereum
    pass  # Replace with actual implementation

  3. Create an Agent:

    • Name: FraxMintingAgent

    • Description: "An agent that automates minting FRAX stablecoins."

    • Maximum Auto Reply: 2

    • Instructions: "Use mint_frax when the user wants to mint FRAX by providing collateral."

  4. Configure an Agent Workflow:

    • Create a Workflow Two Agents with UserAgent and FraxMintingAgent.

    • Summary Method: Last Message

  5. Test the Agent:

    • In the Playground, start a session.

    • Ask: "Mint 5000 FRAX using 5000 USDC as collateral."

    • The agent should process the request and execute the minting.

Outcome: You'll gain experience in automating stablecoin minting on Frax, broadening your DeFi toolkit.

Exercise 3: Automate Depositing Assets into AAVE

Objective: Build an agent to deposit assets into AAVE, earning interest on your holdings.

Steps:

  1. Understand AAVE Protocol:

    • AAVE is a decentralized lending platform where users can lend and borrow a variety of cryptocurrencies.

    • Depositing assets earns you interest and allows you to borrow against your collateral.

  2. Define a Skill:

    • Name: deposit_aave

    • Description: "Deposits assets into AAVE lending pools."

    • Content: Implement a function to interact with AAVE's deposit method.

      def deposit_aave(asset_address, amount, on_behalf_of, blockchain):
    # Interact with the AAVE protocol to deposit assets
    # asset_address: Address of the asset to deposit (e.g., ETH)
    # amount: Amount to deposit
    # on_behalf_of: Your wallet address
    # blockchain: 'ETH' for Ethereum
    pass  # Replace with actual implementation

  3. Create an Agent:

    • Name: AaveDepositAgent

    • Description: "An agent that automates asset deposits into AAVE."

    • Maximum Auto Reply: 2

    • Instructions: "When the user wants to deposit assets into AAVE, use deposit_aave."

  4. Configure an Agent Workflow:

    • Set up a Workflow Two Agents with UserAgent and AaveDepositAgent.

    • Summary Method: Last Message

  5. Test the Agent:

    • In the Playground, start a session.

    • Command: "Deposit 2 ETH into AAVE."

    • The agent should execute the deposit and confirm.

Outcome: You'll learn to automate lending operations on AAVE, enhancing your earning potential.

Exercise 4: Automate Borrowing Assets from AAVE

Objective: Create an agent that borrows assets from AAVE using your deposited collateral.

Steps:

  1. Define a Skill:

    • Name: borrow_aave

    • Description: "Borrows assets from AAVE against your collateral."

    • Content: Implement a function to interact with AAVE's borrow method.

      def borrow_aave(asset_address, amount, interest_rate_mode, on_behalf_of, blockchain):
    # Interact with AAVE to borrow assets
    # asset_address: Address of the asset to borrow (e.g., DAI)
    # amount: Amount to borrow
    # interest_rate_mode: 1 for stable, 2 for variable
    # on_behalf_of: Your wallet address
    # blockchain: 'ETH' for Ethereum
    pass  # Replace with actual implementation

  2. Create an Agent:

    • Name: AaveBorrowAgent

    • Description: "An agent that automates borrowing assets from AAVE."

    • Maximum Auto Reply: 2

    • Instructions: "Use borrow_aave when the user requests to borrow assets."

  3. Configure an Agent Workflow:

    • Set up a Workflow Two Agents with UserAgent and AaveBorrowAgent.

    • Summary Method: Last Message

  4. Test the Agent:

    • In the Playground, start a session.

    • Request: "Borrow 1000 DAI from AAVE at a variable interest rate."

    • The agent should process the request and execute the borrowing.

Outcome: You'll understand how to automate borrowing operations, enabling leveraged positions and advanced strategies.

Exercise 5: Automate Staking LP Tokens on Curve and Frax

Objective: Create agents that not only provide liquidity but also stake LP tokens to earn additional rewards.

Steps:

  1. Define Skills:

    • Skill 1:

      • Name: provide_liquidity_frax_curve

      • Description: "Adds liquidity to a Curve pool involving FRAX."

      • Content: Similar to Exercise 1 but tailored for FRAX pools.

    • Skill 2:

      • Name: stake_lp_tokens

      • Description: "Stakes LP tokens to earn staking rewards."

      • Content: Implement a function to interact with staking contracts.

      def stake_lp_tokens(staking_contract_address, lp_token_amount, blockchain):
    # Stake LP tokens in the staking contract
    # staking_contract_address: Address of the staking contract
    # lp_token_amount: Amount of LP tokens to stake
    # blockchain: 'ETH' for Ethereum
    pass  # Replace with actual implementation

  2. Create Agents:

    • Agent 1:

      • Name: LiquidityProviderAgent

      • Description: "Provides liquidity to FRAX pools on Curve."

      • Instructions: "Use provide_liquidity_frax_curve when adding liquidity."

    • Agent 2:

      • Name: LPStakingAgent

      • Description: "Stakes LP tokens to earn rewards."

      • Instructions: "After liquidity is added, use stake_lp_tokens to stake the LP tokens."

  3. Configure a Group Chat Workflow:

    • Navigate to Agent Workflows and select Workflow Group Chat.

    • Add both LiquidityProviderAgent and LPStakingAgent to the workflow.

    • Include a Wallet Manager to enable transactions.

    • Summary Method: LLM

  4. Test the Workflow:

    • In the Playground, initiate a session.

    • Command: "Add liquidity to the FRAX/USDC pool on Curve and stake the LP tokens."

    • The agents should coordinate to execute both actions seamlessly.

Outcome: You'll experience multi-step automation, enhancing your yield through liquidity provision and staking.

Exercise 6: Automate Risk Management on AAVE

Objective: Set up agents that monitor your AAVE positions and adjust them to prevent liquidation.

Steps:

  1. Define Skills:

    • Skill 1:

      • Name: monitor_aave_health_factor

      • Description: "Monitors the health factor of your AAVE account."

      • Content: Implement a function to retrieve and evaluate your health factor.

      def monitor_aave_health_factor(user_address, blockchain):
    # Retrieve health factor from AAVE
    # user_address: Your wallet address
    # blockchain: 'ETH' for Ethereum
    pass  # Replace with actual implementation

    • Skill 2:

      • Name: adjust_aave_position

      • Description: "Adjusts your AAVE position to maintain a healthy status."

      • Content: Implement functions to repay loans or add collateral.

  2. Create Agents:

    • Agent 1:

      • Name: HealthMonitorAgent

      • Description: "Monitors your AAVE health factor."

      • Instructions: "Use monitor_aave_health_factor regularly."

    • Agent 2:

      • Name: PositionManagerAgent

      • Description: "Adjusts positions based on health factor alerts."

      • Instructions: "Use adjust_aave_position when the health factor drops below a threshold."

  3. Configure a Group Chat Workflow:

    • Create a Workflow Group Chat including both agents.

    • Schedule the workflow to run at regular intervals.

    • Summary Method: LLM

  4. Test the Workflow:

    • In the Playground, start a session.

    • The HealthMonitorAgent should periodically check your health factor.

    • If the health factor is low (simulate this if possible), PositionManagerAgent should act to adjust your position.

Outcome: You'll learn how to automate risk management, a crucial aspect of DeFi investing.

Exercise 7: Automate Swapping Tokens via Curve for Optimal Rates

Objective: Build an agent that swaps tokens using Curve to minimize slippage and fees.

Steps:

  1. Define a Skill:

    • Name: swap_tokens_curve

    • Description: "Swaps tokens on Curve for the best possible rates."

    • Content: Implement a function to interact with Curve's exchange method.

      def swap_tokens_curve(pool_address, from_token, to_token, amount, min_amount_out, blockchain):
    # Perform token swap on Curve
    # pool_address: Address of the Curve pool
    # from_token: Address of the token to swap from
    # to_token: Address of the token to swap to
    # amount: Amount to swap
    # min_amount_out: Minimum acceptable amount after swap
    # blockchain: 'ETH' for Ethereum
    pass  # Replace with actual implementation

  2. Create an Agent:

    • Name: CurveSwapAgent

    • Description: "An agent that performs token swaps on Curve."

    • Maximum Auto Reply: 2

    • Instructions: "Use swap_tokens_curve when the user requests a token swap."

  3. Configure an Agent Workflow:

    • Create a Workflow Two Agents with UserAgent and CurveSwapAgent.

    • Summary Method: Last Message

  4. Test the Agent:

    • In the Playground, start a session.

    • Request: "Swap 5000 USDC for DAI on Curve."

    • The agent should execute the swap, ensuring optimal rates.

Outcome: You'll understand how to automate token swaps efficiently, a common DeFi activity.

General Tips for All Exercises:

  • Consult Protocol Documentation: Refer to Curve, Frax, and AAVE documentation for specific contract addresses and function parameters.

  • Handle Sensitive Data Securely: Ensure your agents do not expose private keys or sensitive wallet information.

  • Test on Testnets: Use Ethereum testnets like Ropsten or Kovan to test your agents without risking real assets.

  • Iterate and Improve: After initial testing, refine your agents for efficiency and reliability.

  • Stay Updated: DeFi protocols frequently update; ensure your agents adapt to any changes.

By completing these exercises, you'll:

  • Enhance Your DeFi Skills: Gain practical experience interacting with major DeFi protocols.

  • Automate Complex Tasks: Learn to build agents that handle multi-step processes seamlessly.

  • Improve Risk Management: Understand how to monitor and adjust positions automatically.

  • Contribute Effectively: Be prepared to tackle advanced projects and contribute to our team's success.

Happy Building! We're eager to see the innovative solutions you'll create with D.A.T.A, leveraging the power of Curve, Frax, and AAVE to advance your DeFi journey.

If you have any questions or need assistance, don't hesitate to reach out. Let's make the most of these powerful tools together!

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