Open Source AI Tools to Research

[SAUMILDHANKAR]

Discussed in #150

^{Originally posted by evelynluu2 September 15, 2025}

Instructions

Select a tool to research. Go through the checklist and leave a comment below with your findings for each checklist question.

Research Checklist for Each Tool

• Does their tech stack work well with our tech stack?
• What parts of AI development do they support?
• Do they update often? Do they have a future roadmap? How well maintained is this project?
• How extensive is their documentation and community?
• Do they have tutorials? If yes, how extensive is it?
• Is there anything fabulous or concerning we should know about their maintainers or overall organization?

Tools to Research

• AgentScope
• Lovable
• Base44
  

[SAUMILDHANKAR]

I am starting with lovable, and will write significant notes in comments before finalizing all the notes for the tool.

[SAUMILDHANKAR]

Apologies team this is still on my radar. I haven't started working on this yet. If anybody has bandwidth to do this please unassign me and pick it up. Otherwise, I plan to update my progress in a week or two.

[SAUMILDHANKAR]

Lovable might not be open source
1) Tech Stack Comparison

map-dashboard uses:

✅ React
✅ Vite
✅ TypeScript
✅ ESLint
Custom CSS styling
Custom UI components
pnpm package manager

Lovable uses:

✅ React
✅ Vite
✅ TypeScript
✅ ESLint
Tailwind CSS styling
shadcn-ui components
npm (but pnpm compatible)

Compatibility: Excellent ✨ (as claimed by lovable)
(Saumil: Additionally, comparison can be made about how well these two will integrate with each other, that might require running some tasks which we will do if time permits)

2) Top 3 AI Development Approaches in Lovable:

Lovable AI (Built-in Gateway) - Pre-configured access to Gemini & GPT-5 models, no API keys needed
Lovable AI Documentation
Browser-based AI with Hugging Face - Run ML models entirely client-side (image segmentation, speech recognition, embeddings)
Transformers.js Documentation
OpenAI via Edge Functions - Full access to OpenAI models (GPT-5, Realtime API, DALL-E, Whisper)
OpenAI API Documentation

3) Lovable is actively maintained and updates frequently: (Claimed by lovable)

Recent Major Updates:
Lovable 2.0 (April 2025) - Smarter AI, multiplayer collaboration, security scanning
Lovable Cloud & AI (September 2025) - Built-in backend and AI gateway
Regular feature updates (Visual Edits improvements, file management optimizations)
Update Tracking:
Changelog - Official update history
Blog - Feature announcements
Status Page - System status and incidents
Community & Support:
Discord Community - Active community discussions
LinkedIn - Weekly feature announcements
Documentation - Continuously updated

(Saumil: documentation could be improved it is very generic and future roadmap is very hard to find)

4) How extensive is their documentation and community?
(Saumil: documentation can improve, hard to comment on community)

5) Do they have tutorials? If yes, how extensive is it?
(Saumil: They have tutorials, hard to say how extensive because best tutorial would be ongoing support.)

6) Is there anything fabulous or concerning we should know about their maintainers or overall organization? (lovable)
🎉 Fabulous aspects:
Meteoric Growth

Hit $10M ARR in just 60 days with only 15 people
Reached $120M ARR in 7 months (one of the fastest-growing companies ever)
Became a unicorn ($1.8B valuation) just 8 months after launch
$200M Series A from top-tier investors (Accel, 20VC, Creandum)
Founder Background

Co-founded by Anton Osika, creator of the viral open-source project GPT Engineer
Swedish startup with strong European backing
Proven track record in AI development tools
Investor Confidence

Backed by Accel, 20VC, byFounders, Creandum, Hummingbird, Visionaries Club
One of Europe's largest Series A investments ever
⚠️ Potential Concerns:
Extremely young company (launched 2024-2025)
Very fast growth can sometimes mean stability/support challenges
Heavy reliance on AI model providers

(Saumil: I will test it out for issue creation, PR review etc in future)

I tried getting help on OpenSourceFellows/amplify#1077 and since it is from different repo lovable got confused. It burnt credits pretty fast and spending about 20 mins for results did not get much useful. GitHub CoPilot has been more effective personally.

[SAUMILDHANKAR]

base44 is also not open source

1) Tech Stack Comparison

map-dashboard uses:

• ✅ React
• ✅ Vite
• ✅ TypeScript
• ✅ ESLint
• Custom CSS styling
• Custom UI components
• pnpm package manager

base44 uses:

• ✅ React
• ✅ Vite (implied)
• ✅ TypeScript
• ✅ ESLint
• ✅ Tailwind CSS styling
• ✅ shadcn-ui components
• npm/pnpm compatible

Compatibility: Excellent ✨

base44 is a perfect match for map-dashboard's tech stack. It uses the same core technologies (React, TypeScript) and actually enhances the stack with modern tooling like Tailwind CSS and shadcn-ui components that are industry standards.

---

2) What Parts of AI Development Does base44 Support?

Top 3 AI Development Capabilities:

1. Built-in LLM Integration (InvokeLLM) - Direct access to AI models with optional web context, structured JSON output, and file analysis

   • No API keys needed in the platform
   • Web search integration for real-time data
   • JSON schema validation for structured outputs

2. AI Agents with Tool Use - Create conversational AI agents that can interact with your database, perform CRUD operations, and integrate with WhatsApp

   • Entity CRUD operations as tools
   • Streaming responses
   • Multi-channel support (web, WhatsApp)

3. AI-Powered Data Extraction - Extract structured data from PDFs, images, and CSV files using ExtractDataFromUploadedFile

   • Invoice processing
   • Document parsing
   • Automated data entry

Additional AI Features:

• Image generation (GenerateImage)
• File analysis with AI
• Real-time AI conversation streaming

---

3) Update Frequency & Maintenance

Update Status: Actively Maintained ✅

base44 appears to be in active development based on:

• Modern tech stack (React, TypeScript, latest libraries)
• Comprehensive feature set indicating ongoing development
• Well-structured documentation suggesting active maintenance
• Support for latest AI models and integrations

Observable Indicators:

• Recent feature additions (AI agents, WhatsApp integration)
• Modern React patterns (React Query, hooks)
• Up-to-date dependencies (date-fns, recharts, etc.)
• Active integration ecosystem

Note: Public roadmap visibility could be improved for external evaluation.

---

4) Documentation & Community

Documentation Quality: Comprehensive 📚

Strengths:

• Detailed API documentation for all integrations
• Clear entity schema definitions
• Well-documented SDK methods
• Code examples throughout
• Component usage guidelines

Documentation Coverage:

• Entity management (CRUD operations)
• Authentication & user management
• Integrations (LLM, file upload, email, image generation)
• AI Agents configuration
• Frontend component library
• Layout and routing

Areas for Enhancement:

• Community forums or Discord visibility
• Public GitHub repository for community contributions
• User-generated content and tutorials
• Community showcase/examples

---

5) Tutorial Availability & Depth

Tutorial Status: Good Examples, Room for Growth 📖

What's Available:

• Inline code examples in documentation
• Entity schema examples
• Integration usage patterns
• Agent configuration examples
• Component implementation samples

Tutorial Strengths:

• Practical, production-ready examples
• Multiple complexity levels
• Real-world use cases (invoice processing, task management)
• Clear step-by-step patterns

Could Be Improved:

• Video tutorials
• End-to-end project walkthroughs
• Interactive learning path
• Troubleshooting guides
• Migration guides from other platforms

---

6) Organization & Maintainer Information

🎉 Fabulous Aspects:

Developer Experience Focus:

• Batteries-included approach (built-in auth, database, AI)
• No configuration needed for common use cases
• Pre-initialized SDKs reduce boilerplate
• Modern, clean API design

Comprehensive Feature Set:

• Full-stack platform (frontend + backend)
• Built-in user management
• Database with automatic schema
• AI integrations without API key management
• File storage and management
• Email capabilities

Rapid Development:

• Quick prototyping to production
• Minimal setup time
• Pre-built UI components (shadcn-ui)
• Auto-generated CRUD operations

⚠️ Considerations:

Vendor Lock-in:

• Proprietary platform with specific patterns
• Limited ability to self-host or migrate away
• Dependency on platform availability

Transparency:

• Limited public information about company/team
• No visible open-source community
• Unclear pricing model for scaling
• Platform maturity and longevity unknown

Control Trade-offs:

• Backend as a service means less control over infrastructure
• Limited customization beyond provided APIs
• Dependent on platform's AI model choices

---

Summary Recommendation

Best For: Rapid prototyping, MVPs, small to medium applications that benefit from managed infrastructure and built-in AI capabilities.

Integration Potential with map-dashboard: High - Tech stack alignment is excellent, could accelerate development of AI-powered features.

Primary Concerns: Vendor lock-in, platform maturity visibility, scaling costs unclear.

(Saumil: maybe I will test more for issue creation and PR review)

I tried getting help on OpenSourceFellows/amplify#1062 https://github.com/OpenSourceFellows/amplify/issue/1077
it was nothing remarkable, credits expired pretty soon in just 3 queries and the responses were confusing.