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Sherpa Coder
✓ verifiedFree
VS Code extension letting developers chat with their own custom OpenAI assistants without leaving the editor.
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Runcell - Jupyter AI Agent
✓ verifiedFreemium
Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
👁 170K/mo♥ 5.5K
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Softgen
✓ verifiedFreemium
AI app builder that turns plain-English prompts into deployable full-stack web apps with a managed database and full code ownership.
👁 103K/mo♥ 16K
Pricing
No public pricing
No public pricing
No public pricing
No public pricing
Starting plan: $25/mo (entry-level tier per pricing comparison)
Free trial available
Core features
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
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- ✦in-editor chat with OpenAI assistants
- ✦workspace source-code context sharing
- ✦support for custom, user-defined assistants
- ✦secure management of the user's OpenAI account
- ✦Cross-session project memory recalling prior decisions and state
- ✦Autonomous execution of long, multi-step notebook tasks
- ✦Reads cell outputs (plots, tables, metrics), not just code
- ✦In-notebook cell-level assistance and error fixing
- ✦Installs directly into existing JupyterLab via pip, no new editor
- ✦Concept explanations with runnable example cells
- ✦Builds full-stack apps from plain-English descriptions
- ✦Choice of 12+ underlying AI models
- ✦Managed Supabase database included
- ✦GitHub code export on all plans
- ✦One-click Vercel deployment
- ✦Credits that don't expire while subscribed
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
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- →getting coding help without switching out of VS Code
- →using a personalized OpenAI assistant tuned to a project
- →quick in-editor Q&A while writing code
- →Data scientists running multi-week model iteration projects
- →Domain experts (e.g. risk/fintech) who know the problem but not deep Python
- →Researchers wanting an agent that remembers project context across days
- →Analysts needing help understanding unfamiliar algorithms or libraries
- →Non-technical founders shipping an MVP quickly
- →Agencies delivering client projects faster
- →Developers prototyping SaaS ideas without boilerplate setup
- →Solo builders launching small businesses without hiring engineers
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