DCA.Monster: Modular DeFi 2.0 Components for Cartesi

[md0x]

New POC Proposal

DCA.Monster: Modular DeFi 2.0 Components for Cartesi

Core Concept and purpose statement

The DCA.Monster project, an Automated Market Maker (AMM) previously distinguished at ETH Global Paris 2023, laid the groundwork for utilizing ERC20 streams for precise on-chain dollar-cost averaging (DCA). This Proof of Concept aims to extend its technical boundaries, improving both the power and flexibility of on-chain DCA mechanisms.

The crux of this POC centers around the development and optimization of Python-based Dockerized components, specifically crafted for compatibility with Cartesi’s DeFi applications. While they’re instrumental to the further advancement of DCA.Monster, these components have been architected to be modular and standalone building blocks, potentially contributing to other applications within the Cartesi ecosystem.

Key technical objectives for this POC include:

1. Streamable tokens: Implementing Streamable token mechanics designed for efficient management of large-scale ongoing streams and accurate real-time balance computations.
2. Cartesi Automated Market Maker & StreamableTokens Integration: Port the AMM model of Uniswap V2 to Cartesi, facilitating algorithmic token transfers without relying on an order book. Further, adapt this structure to integrate seamlessly with StreamableTokens, enabling advanced stream swaps. Unlike traditional Order Book-based exchanges that require users to manually set buy or sell orders and often await matching trades, an AMM provides instant, automated swaps by leveraging a liquidity pool. This ensures more efficient trades, reduced user intervention, and a smoother overall trading experience.

The underlying assumption driving this POC is that these individual modules, when cohesively integrated, can effectively elevate DCA.Monster’s functionalities. Each module is also engineered to be operationally independent, allowing for immediate deployment within the Cartesi framework upon finalization. The primary success criterion is the realization of a fully functional version of DCA.Monster and the individual operational readiness of each distinct module post-development of each deliverable (Detailed descriptions below).

How will you use Cartesi, specifically?

DCA.Monster’s implementation and each of it’s components hinges on Cartesi’s technology to enable its intricate functionalities on-chain. For this POC, Cartesi will be integrated in the following key areas:

1. Streamable tokens: Cartesi will provide the scalable environment for efficient handling of large-scale streams and precise real-time balance computations. This would be impossible to implement in classic EVM smart contracts.

2. Cartesi AMM & StreamableTokens Integration: Port Uniswap V2’s AMM to Cartesi, harnessing token transfer operations within Cartesi’s optimized computing environment. Further refine this framework to seamlessly integrate with StreamableTokens, pioneering the concept of “stream swaps”. Leveraging Cartesi’s distinct computational strengths, these advanced swap modalities are introduced, which would be computationally infeasible without the capabilities provided by Cartesi.

In summary, Cartesi’s capabilities will be crucial for the technical execution of each module, ensuring both the enhancement of DCA.Monster and standalone functionality for the wider Cartesi ecosystem.

For a clearer understanding, reference to the sections detailing the specific technical objectives would provide an in-depth view of how Cartesi’s features are intricately woven into the POC’s architecture.

Technical details

Our outlined deliverables aim to introduce robust functionalities tailored specifically for Cartesi DeFi applications and other Cartesi DApps. Crafted using the Cartesi custom app starter kit, each modular component is structured for easy Docker deployment in Python, ensuring adaptability and reusability. Consistent quality assurance is maintained with a target of 90-95% test coverage.

1. Streamable Tokens (Cartesi Streamable Tokens on-steroids)

   • Description: A python standardised implementation of a Cartesi Streamable token based on SuperfluidToken on-steroids that can handle a very high (almost infinite) number of ongoing streams and realtime balances. (See realtimeBalanceOf)
   • Features:
     • Standardised interface C-SERC-20 (Cartesi Streamable ERC-20) to have high composability with Cartesi DApps
     • Work seamlessly with Cartesi’s InputBox & Vouchers
     • Infinite (or extremely high) open streams that working graciously to allow building more sophisticated applications with them.
   • Benchmarking:
     • Objective: Performance evaluation with high demand this number should support for a DEX operating at peak demand. Support at least 25,000 simultaneous token streams.
   • Use Cases:
     • Programmable transfers (e.g. send X tokens at specific time during X seconds)
     • Subscription Services: Manage ongoing subscription payments.
     • DEX
   • Deliverable duration: 4 weeks
   • Funds request (USD) for the deliverable: 5000 USD

2. AMM: Combined Uniswap V2 Port & StreamableToken Enhancement for Cartesi

   • Description: An integrated approach to bringing the Uniswap V2 architecture to the Cartesi platform using Python, focusing on traditional transfer operations from Constant Function Market Maker (CFMM). Building on this foundational structure, we further optimize for StreamableTokens, introducing advanced stream swaps that leverage the computational capabilities of the Cartesi Dapp.

   • Features:

     • Uniswap V2 Base:
       • Adheres to the constant product formula inherent in the Uniswap V2 model.
       • Facilitates standard token exchange operations.
     • StreamableToken Enhancement:
       • Seamless integration with StreamableTokens, allowing for advanced stream swaps.
       • Inherits and builds upon the foundational features of the Uniswap V2 port.

   • Design:

     • Uniswap V2 Base: Meticulous adaptation of the Uniswap V2 system for Cartesi’s environment.
     • StreamableToken Enhancement: Evolves the Uniswap V2 port on Cartesi, honing in specifically for StreamableTokens’ functionalities.

   • Use Cases:

     • Uniswap V2 Base:
       • Decentralized token exchanges on the Cartesi platform.
       • Enables straightforward token swaps.
     • StreamableToken Enhancement:
       • Progressive decentralized token swaps incorporating streaming capabilities.
       • Pioneering DeFi operations that utilize token stream benefits like Dollar-Cost Averaging.

   • Deliverable Duration: 4 weeks

   • Funds Request (USD) for the Deliverable: 5000 USD

By housing all these modular deliverables within a single GitHub repository, we aim to simplify integration, ensuring Cartesi DApps can easily leverage them for varied use cases. Each module is constructed with a minimalistic approach, focusing on core functionalities while maintaining the flexibility for broader applications.

Value Proposition

This POC fortifies Cartesi’s developer ecosystem by delivering modular DeFi components tailored for both specific and general purposes. The areas of value are:

1. Advanced Financial Tools: With the refined DCA.Monster, developers have access to sophisticated on-chain dollar-cost averaging tools, expanding DeFi potential and enabling precise financial operations.

2. Modular DeFi Components: The POC emphasizes modularity. Each component functions independently, facilitating easier integration into various Cartesi DApps. This approach promotes innovation while decreasing development time and barriers for newcomers to Cartesi.

Estimated Duration and Funds Requested

Duration: 2 months

Funds request (USD) for the POC: 10,000 USD

Subsequent Vision and Extensibility

With the successful validation of the POC, we’re paving the way for transformative projects within Cartesi.

Vision: DCA.Monster exemplifies the pinnacle of what’s achievable, leveraging all the introduced modules to their full extent. It would stand as a testament to how comprehensive toolkits can lead to sophisticated DeFi platforms, offering advanced financial operations and granular controls. Beyond DCA.Monster, envision a Cartesi landscape flourishing with diverse DApps—each benefiting from the universally applicable modules—spanning areas from DeFi to gaming .

Immediate Next Steps Post-POC:

1. DCA.Monster Enhancement & Expansion: Drawing on the POC, accelerate the development and deployment of advanced features in DCA.Monster, solidifying its place as a premier DeFi platform in Cartesi.

2. Feedback Integration: Actively engage with DCA.Monster users and the broader Cartesi developer community to refine and optimize the modules, ensuring they meet real-world demands.

3. Educational Outreach: Roll out detailed documentation, workshops, and tutorials, facilitating developers in harnessing the new modules, and integrating them into varied DApps.

4. Community-Centric Initiatives: Spearhead events like hackathons, fostering innovation and possibly uncovering unanticipated applications of the new tools.

In sum, post-POC, the objective is twofold: bolstering DCA.Monster’s capabilities and stature, and simultaneously promoting the broader adoption and innovative use of the modules by the diverse Cartesi developer community. The POC isn’t just a foundation; it’s a launchpad for a more dynamic and capable Cartesi ecosystem.

Future Plans - Prospective Modules for Subsequent Grants

To transparently set expectations regarding DCA.Monster’s growth trajectory, we’ve delineated two potential modules for subsequent development phases. While these won’t be delivered under the current grant, their potential integration stands to considerably elevate the Cartesi ecosystem. Their merits suggest they could be prime candidates for an upcoming grant.

1. Cartesi Subgraphs: GraphQL API Integration with Postgres DB

• Overview: A GraphQL API layered over Cartesi Node’s native Postgres DB, mirroring EVM’s Subgraph. This innovation offers a familiar setup for developers and acts as a robust replacement for the “Inspect API”, ensuring timely data updates similar to EVM contract Subgraphs. The seamless plug-in design streamlines integration with Cartesi’s Postgres DB.

2. Off-chain Transactions Aggregator API based on EIP-4337 for Cartesi DApps

• Overview: This API, inspired by EIP-4337, is tailored for Cartesi DApps. It aggregates off-chain signed messages, organizes them into Merkle DAGs for IPFS storage, and broadcasts the latest CID via Libp2p, ensuring decentralization. Key features include gas-free transactions, transparent IPFS-stored transactions, verified timestamps and IDs, and optional automatic executions. This solution enhances Cartesi’s environment by providing user-friendly tools for DApps and protocols.

By championing these subsequent modules, we aim to further solidify the synergy between all components, catapulting DCA.Monster to the forefront of DeFi innovations while concurrently bolstering the Cartesi ecosystem.

Reusability and Other Use Cases

This POC, presents a modular design that is ripe for a plethora of applications within the Cartesi ecosystem.

Potential Uses:

1. Streamable Tokens: These can be employed beyond DeFi, finding applications in gaming for in-game assets, or for continuous subscription models in service platforms.

2. AMM Module with Advanced Stream Capabilities: Projects aiming to simplify token trading mechanics can integrate this module. Beyond facilitating programmatic tradable tokens, it showcases the future of AMMs that can operate with streamable tokens and handle intricate rules, leveraging the enhanced capabilities provided by Cartesi.

In a nutshell, the POC’s modules are versatile, ready-to-use components. Whether assimilated into expansive endeavors like DCA.Monster or integrated into smaller projects, they stand poised to redefine Cartesi-based developments, driving innovation and enhancing user-centric experiences.

Risks and Contingency Plans

1. Performance Benchmark with Simultaneous Streams :
   • Risk : There’s a possibility that we might not achieve the desired benchmarks when handling simultaneous on-going streams.
   • Contingency: Should we encounter this performance hurdle, we can introduce design constraints to reduce complexity or refactor using a more performant low-level language, enhancing both speed and efficiency.
2. Integration with Existing Cartesi Infrastructure:
   - Risk: Interoperability challenges may arise when trying to fuse our modules with Cartesi’s existing infrastructure.
   - Contingency: Proactively engaging with Cartesi’s core development community can facilitate smoother integration. If unforeseen incompatibilities emerge, we’ll collaborate with Cartesi’s team for potential workarounds or adjustments in our POC design.

In each case, constant monitoring, performance testing, and community feedback will be instrumental in detecting issues early. Such proactive measures will allow us to pivot or adjust our approach swiftly, ensuring the POC’s successful realization.

Success criteria

1. Performance Benchmarks:
   • Criteria: Achieve optimized handling of simultaneous on-going streams without significant lag or processing delays. Our goal is for the system to gracefully handle a predefined number of streams without noticeable performance degradation.
   • Verification: Detailed performance testing logs highlighting latency, throughput, and resource utilization.
2. Module Integration and Interoperability:
   • Criteria: Efficient module integration with Cartesi infrastructure, ensuring each component functions as intended.
   • Verification: A demonstration on DCA.Monster highlighting the cohesiveness and functionality of all integrated modules within the Cartesi platform.
3. Deliverables:
   • Criteria: Provide concise, well-documented code for each module, with user guidelines and sample applications to illustrate module utility.
   • Verification: Direct links to repositories, documentation briefs, and sample use cases.
4. Community Feedback and Adjustments:
   • Criteria: Obtain constructive feedback from Cartesi’s developer community or developer team to validate the modules’ utility and effectiveness.
   • Verification: Summaries from feedback sessions and consolidated survey insights.

The POC will be deemed complete when the outlined criteria are satisfied, supported by tangible evidence showcased on DCA.Monster.

Deliverables:

The detailed technicalities of each deliverable have been elucidated in the technical details section. Presented below is a brief list of the key deliverables for easy reference:

1. Streamable Tokens:

   • Python Implementation of a Cartesi Streamable token based on SuperfluidToken with capabilities to handle an extensive number of ongoing streams and realtime balances.
   • Standardized C-SERC-20 interface, Cartesi’s InputBox & Vouchers compatibility, and high-demand performance benchmarks.

2. AMM with StreamableToken Enhancement: Uniswap V2 Port for Cartesi:

   • Precise python port of Uniswap V2 for the Cartesi platform, integrated with the constant product formula and token exchange operations.
   • Advanced Automated Market Maker tailored specifically for StreamableTokens, further enhancing the Uniswap V2 port for Cartesi to cater to StreamableTokens’ unique requirements.

Each deliverable will be accessible within a consolidated GitHub repository, ensuring streamlined access and integration.

Final report

Upon a failure of the POC, the Grants Council may still issue prorated payment if the applicant provides a written debriefing that sufficiently details the approaches used, why they failed, and what next steps would be if someone else were to resume the project. This will be shared with the community. Do you agree to provide this?

YES

About Your Development team
Pablo

Role: Pablo will lead the entire project, overseeing the technical development, integration, testing and documentation of each module.

ERC-20 Payee address

0xDA0361A89f5c45f6414A6E46277D602d2AFf80Dc

[gabrielbarros]

Hi @md0x ! Great to see you’ve submitted your proposal after our discussions!

I really like the idea of this project because I think it showcases the capacity of Cartesi Rollups and, at the same time, it innovates the DeFi space in a way the Ethereum community will be able to grasp the value.

If it’s really successful, I can already see new trading ideas emerging from this new basic mechanic.

[felipeargento]

Hey there @md0x !

That’s a genuinely impressive proposal you’ve put together. Congratulations. While I can’t claim to grasp every detail, there are plenty of components that stand out as highly valuable. Additionally, I’m confident that as the project progresses, other beneficial features will emerge.

As a side note, I believe there’s immense potential in the “2. Off-chain Transactions Aggregator API based on EIP-4337 for Cartesi DApps.” plan. I would wholeheartedly support a grant dedicated just to that.

To clarify a point: You’re planning to implement a version of Uniswap v2 on Cartesi, correct? Instead of users trading tokens directly on Uniswap, they’d be using the liquidity pools available on a Cartesi rollup. You’d ensure consistency with Uniswap pair prices through arbitration, right? This approach sounds promising, though I’m curious to see how the challenge period might impact the pair prices on this L2.

Once again, I’m genuinely impressed by the depth and scope of your proposal. The enthusiasm shines through, and I’m eager to see where this goes.

[md0x]

Hey @gabrielbarros ,

Thanks for your feedback! I’m excited about the project too. Agree! If things go well, I bet we’ll see some cool new trading ideas pop up built on top of these DeFi primitives. Thanks again for being on board with this!

[md0x]

Hey @felipeargento ,

Thanks for the insights! I’m genuinely enthusiastic about this proposal’s potential to not only bolster our initial proof-of-concept but also bring versatility to our components.

I’m also eager about the Off-chain Transactions Aggregator. This could pave the way for “intents” allowing users to swap gas-less, not only improving UX but also branching into areas like gaming or SocialFi!

Regarding arbitrage: You’ve hit the nail on the head. For our AMM to function optimally, price updates through arbitrage are essential. You are right, just like Uniswap has its liquidity pools in L1, DCA.Monster has its own liquidity pools in the rollup made of bridged tokens.

@gabrielbarros and I talked about potential shorter dispute windows in Paris, perhaps to as little as 15 minutes, to expedite withdrawals and reduce risks. Achieving maximum efficiency in the streamable tokens is crucial to facilitate such a reduction. Even with a longer window, I believe it’s workable.

While non-atomic transactions (e.g. arbitrate in a single tx in L1) might pose higher risks to arbitrators, the rewards could be enticing. For example:

• If a token’s price is higher on DCA.Monster, the process of buying on L1, bridging, and then selling could still qualify as quick arbitrage with main risks being L1 front running.
• Arbitrators might also benefit from maintaining liquidity on both sides (L1 and rollup), ensuring they can instantly leverage price gaps.

I believe that given profitable arbitration opportunities, there will certainly be those eager to capitalize on them!

Thanks again for all your thoughts and guidance on this!

[MaxH]

I’m strongly in support of this proposal! @md0x demonstrates a deep understanding of Cartesi and claimed victory at the Paris hackathon. I can envision both primitives (streamable tokens and AMM) being beneficial to other applications built on Cartesi. (Here are some high-level ideas that come to mind: a built-in AMM for games or other complex financial apps, streamable debt repayment, streamable payments for intricate enterprise use cases, value streams in economic games etc)

Merging both into a streamable token AMM introduces an intriguing new use case that, in my opinion, would necessitate a solution like Cartesi. Currently, there aren’t any impressive on-chain DCA options (as far as I know), and this proposal pushes the envelope by introducing streams.

I’m looking forward to potential add-ons and future plans.

[md0x]

Hey @MaxH,
Thank you for your feedback and support! I’m genuinely excited about building these two modules and exploring all the composability options they could unlock in the Cartesi environment. Looking forward to what the future holds!

[hellen]

Thanks everyone for your valuable input on this proposal. The Grants Council is set to place the proposal for a vote on Snapshot on Monday, October 9th. If you wish to participate in voting, please stake your CTSI ahead of the voting window. The Snapshot link will be shared here once it’s live!

[hellen]

This proposal is now live for voting on snapshot.

[hellen]

Congratulations, @md0x The proposal has passed. Thank you to all who participated and shared their insights. The Grants Council will connect with you to discuss next steps and offer guidance and support on your project.

Edit: This project has been moved to the “Funded projects” category.

[md0x]

Thanks, @hellen! I’m thrilled to bring these components to life. Grateful for the support and looking forward to collaborating with the Grants Council. Cheers!

[md0x]

I am excited to announce the completion of the second part of our grant, which is available here: GitHub - dcamonster/cartesi-defi-modular-components.

In this latest release, you’ll find the new AMM module, developed using the same technology stack as StreamableTokens, specifically Python and SQLite. This update includes tests that integrate the new AMM with Streamable Tokens, as well as a Jupyter notebook to demonstrate its use in any Cartesi DApp written in Python. Additionally, we have a Cartesi DApp that is fully prepared for local production mode and can be deployed to any testnet. The new implementation has already been deployed on Sepolia and can be accessed at https://dca.monster/