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AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Connects Git repos to answer plain-English questions about your code with file references and dependency context.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Pay-as-you-go API aggregating thousands of image, video, audio and LLM models with custom inference hardware for lower per-request cost.
No public pricing
Free trial available
No public pricing
Free trial available
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦Natural-language search across a codebase
- ✦Architecture explanations and dependency graphs
- ✦Bug hunter that traces issues across files
- ✦AI code review before opening a PR
- ✦Automatic documentation generation
- ✦Multi-repo support via OAuth
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦Single API for image, video, audio, 3D and LLM models
- ✦Standardized model addressing across hosted, partner and custom uploads
- ✦Support for LoRAs, ControlNets, VAEs and embeddings on open-source models
- ✦WebSocket and REST access with async webhook delivery
- ✦Pay-per-request billing with no infrastructure to manage
- ✦Raw serverless GPU/CPU compute for custom workloads
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Adding AI image or video generation to an app without managing infra
- →Batching multi-modal generation tasks in one API call
- →Running custom fine-tuned models via Model Upload
- →Cutting inference costs at high generation volume