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vera-ai

Code search for AI agents. Vera indexes your codebase using tree-sitter parsing and hybrid search (BM25 + vector similarity + optional cross-encoder reranking), then returns ranked code snippets as Markdown codeblocks by default, or JSON with --json.

This package downloads and wraps the native Vera binary for your platform. It downloads the exact package version, checks the release archive size and SHA-256, and stores a completed binary cache. Later runs use that cache without network access. Older caches are downloaded and verified once before they can be reused offline. On Linux without glibc (such as Alpine or NixOS), the wrapper selects the musl binary. Other native targets use their platform system libraries; optional ONNX backends have additional runtime requirements. Set VERA_TARGET to override target detection (e.g., VERA_TARGET=x86_64-unknown-linux-musl uvx vera-ai install).

The default local embedding model, minishlab/potion-code-16M-v2, runs on CPU and works offline after its first download. API mode is also available; Qwen/OpenRouter is recommended among API presets (paid usage). The benchmark report separates the full 1,251-task suite from smaller screening subsets, and the agent benchmark records context measurements and their sample limits.

Install

pip install vera-ai && vera-ai install

Quick Start

vera-ai setup --potion-code --index .
vera-ai search "authentication logic"

vera-ai setup runs the full wizard: configure a backend, optionally install agent skills, and optionally index. Local CPU is first and selected by default; API mode is second. Indexing defaults to Yes for local backends and No for API mode. vera-ai setup --api uses the shorter API configuration flow, with Qwen/OpenRouter first and recommended (one shared key). See the models guide for other providers and non-interactive setup.

The preferred agent integration is the CLI plus the Vera skill: vera-ai agent install installs it for supported coding agents and can add a short usage snippet to your project's AGENTS.md, CLAUDE.md, COPILOT.md, or editor rules file. The client selector uses Space to toggle and Enter to continue. Empty selection changes nothing; unselected installations remain intact. Vera also ships an optional MCP server (vera-ai mcp); see the MCP guide if your client is MCP-first.

Common Tasks

Task Command
Use the interactive setup wizard vera-ai setup
Use the default local model vera-ai setup --potion-code
Configure API mode vera-ai setup --api
Use a local NVIDIA backend vera-ai setup --onnx-jina-cuda
Search semantically vera-ai search "authentication middleware"
Search only changed files vera-ai search "authentication middleware" --changed
Common structural tasks vera-ai structural routes / vera-ai structural env DATABASE_URL / vera-ai structural impls Loader
Find callers or callees vera-ai references foo / vera-ai references foo --callees
Explain why a file is missing vera-ai explain-path path/to/file
Inspect index health vera-ai stats --json
Keep the index up to date vera-ai update .
Watch for file changes vera-ai watch .
Run local HTTP inference server vera-ai serve
Diagnose setup issues vera-ai doctor
Run the deeper local probe vera-ai doctor --probe
Repair missing local assets vera-ai repair
Inspect binary upgrades vera-ai upgrade
Install agent skills vera-ai agent install

For the full backend matrix, model options, Docker setup, and troubleshooting, see the main README and Installation Guide.

What you get

  • 65 languages (61 with tree-sitter AST parsing)
  • Hybrid search: BM25 keyword + vector similarity, fused with Reciprocal Rank Fusion
  • Opt-in cross-encoder reranking for precision, disabled by default
  • Git-aware scopes and index debugging: --changed / --since / --base, explain-path, and index health in vera-ai stats
  • Markdown codeblock output by default with file paths, line ranges, and optional symbol info (use --json for compact JSON; --raw works with vera-ai search, vera-ai grep, and vera-ai references; --timing works with vera-ai search and vera-ai grep, before or after the subcommand)

For full documentation, including local model options and manual install steps, see the GitHub repo.

Metadata

Release files for vera-ai 2.1.2

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