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. On musl-based Linux (Alpine, NixOS), the correct static binary is selected automatically. 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 is minishlab/potion-code-16M-v2; it runs locally on CPU on any supported machine, no GPU or ONNX Runtime needed. In the current Semble comparison, Vera v1.2.0 scored 0.8450 nDCG@10 versus Semble 0.5.5 at 0.8514, using the same embeddings, harness, graded relevance, and suffix-corrected path matching. Full details live in the main repo docs.
Install
pip install vera-ai
Quick Start
vera-ai setup --potion-code --index .
vera-ai search "authentication logic"
vera-ai setup with no flags runs an interactive wizard and offers to index the current project, defaulting to yes. An interactive search also offers to create a missing index. vera-ai setup --api prompts for an OpenAI-compatible endpoint and key; the wizard offers presets for OpenAI, Jina, Voyage, and Qwen via OpenRouter, with the Qwen preset needing only one shared key (qwen/qwen3-embedding-8b + qwen/qwen3-reranker-8b via https://openrouter.ai/api/v1). Use --yes with EMBEDDING_MODEL_* variables for non-interactive setup. vera-ai agent install manages skill files for your coding agents and can update AGENTS.md / CLAUDE.md style project instructions.
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 invera-ai stats - Markdown codeblock output by default with file paths, line ranges, and optional symbol info (use
--jsonfor compact JSON;--rawworks withvera-ai search,vera-ai grep, andvera-ai references;--timingworks withvera-ai searchandvera-ai grep, before or after the subcommand)
For full documentation, including local model options and manual install steps, see the GitHub repo.
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