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Sharma","email":"imdheeraj@gmail.com"},"license":"MIT","homepage":"https://github.com/imdheerajKube/agent-nuvira#readme","keywords":["ai","cli","llm","code-generation","multi-agent","ollama","groq","gemini","nim","openrouter","inference","devops","coding-agent","code-review","automation","developer-tools","typescript","mcp","model-context-protocol"],"repository":{"url":"git+https://github.com/imdheerajKube/agent-nuvira.git","type":"git"},"description":"Agent-Nuvira: Multi-agent AI coding CLI — plan, write, review, test, and publish code with local models (Ollama) or cloud APIs (Groq, NVIDIA NIM, Google Gemini, OpenRouter)","maintainers":[{"name":"imdheerajsharma","email":"imdheeraj@gmail.com"}],"readme":"# ---\nname: agent-nuvira\nshort_description: \"Autonomous AI agent — codes, creates, writes, analyzes, and automates anything\"\narchitecture: \"multi-agent pipeline\"\nagents: \"Swarm (100+ agents, consensus)\"\norchestration: \"Sequential sub-agent pipeline\"\norchestration_details: \"planner, gatherer, writer, reviewer, tester, security auditor; GOAP & swarm topologies\"\nmemory: \"Persistent AgentDB (vector DB) + JSON cache; optional session-only modes\"\nparallel_execution: \"Yes (parallel agent execution & async pipelines)\"\nsecurity_guardrails:\n  - \"Privacy-focused\"\n  - \"AI Defence (prompt injection, PII detection)\"\n  - \"Security scan CLI\"\npublishing: \"Standalone eject available; npm publishing & npx installer\"\nfeatures:\n  - \"multi-provider routing\"\n  - \"native FAISS backend\"\n  - \"checkpoint and resume\"\n  - \"plugin marketplace\"\n---\n\n# Agent-Nuvira — `agent-nuvira`\n\n> **Developed by Dheeraj Sharma <imdheeraj@gmail.com>** · 🌐 **[www.agent-nuvira.com](https://www.agent-nuvira.com)**\n\n[![npm version](https://img.shields.io/npm/v/agent-nuvira.svg)](https://www.npmjs.com/package/agent-nuvira)\n[![npm downloads](https://img.shields.io/npm/dw/agent-nuvira.svg)](https://www.npmjs.com/package/agent-nuvira)\n[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](./LICENSE)\n[![Website](https://img.shields.io/badge/website-www.agent-nuvira.com-6363f2.svg)](https://www.agent-nuvira.com)\n\n**Autonomous AI agent** with a **visual dashboard** and **powerful CLI** — codes, creates, writes, analyzes, and automates anything. Run models locally (Ollama) or route across 22+ cloud providers (Groq, Gemini, OpenRouter, Bedrock, Azure, Anthropic, OpenAI, and more). Specialized agents plan, write, review, test, create images, generate videos, write documents, and ship code — learning from every run.\n\n```bash\n# Quick examples\nagent-nuvira chat \"explain recursion in Rust\"\nagent-nuvira chat \"write a birthday poem for my daughter\"\nagent-nuvira chat \"generate an image of a sunset over mountains\"\nagent-nuvira models --provider groq\nagent-nuvira edit main.go --instruction \"add input validation\"\nagent-nuvira plan . --task \"implement user authentication\"\nagent-nuvira config list\n```\n\n> 📖 **[Every command, with examples → docs/COMMANDS.md](docs/COMMANDS.md)**\n> The complete CLI reference — **all 288 commands**, each with what it is for, the\n> exact syntax, and copy-pasteable examples, plus a **first-run walkthrough** that\n> explains why the first launch is slower and the model list looks incomplete.\n> If you only open one file in this repo, open that one.\n>\n> 🔧 Machine-readable surface: [docs/COMMANDS_SURFACE.md](docs/COMMANDS_SURFACE.md)\n> (generated from the live CLI tree, drift-guarded in CI).\n>\n> 🎬 **[Watch the CLI tour → docs/demos/nuvira-cli-tour.cast](docs/demos/nuvira-cli-tour.cast)**\n> A reproducible asciinema recording of a 21-command sweep across the whole\n> surface — every line captured from the live CLI, with private paths and\n> secrets redacted. Regenerate it with `npm run demo:cli`\n> (see [docs/demos/README.md](docs/demos/README.md)).\n\n---\n\n## Traction\n\nNumbers below come from the **public npm registry** (`api.npmjs.org`, package\n`agent-nuvira`), read on **22 Sep 2026**. They are reproducible with the exact\nURLs shown — no self-reported figures.\n\n| Metric | Value | Source |\n|---|---|---|\n| **Peak installs in a single week** | **11,341** | `api.npmjs.org/downloads/range/2026-08-01:2026-09-22/agent-nuvira` — best 7-day window, 25–31 Aug 2026 |\n| Total installs since first publish (16 Jul 2026) | **45,635** | `api.npmjs.org/downloads/point/2026-01-01:2026-09-22/agent-nuvira` |\n| Installs, last 30 days | **18,259** | `api.npmjs.org/downloads/point/last-month/agent-nuvira` |\n\n> **We publish the peak, not a flattering average, and we date it.** Install counts move;\n> re-run the URLs above to see the current figure. Download counts include CI and\n> mirror traffic, so they measure reach rather than active users — stated here so the\n> number can be read for what it is.\n\n---\n\n## Feature Matrix (concise)\n\nThis table highlights core capabilities for quick machine parsing and comparison.\n\n| Feature | Agent-Nuvira |\n|---|---|\n| Architecture | Multi-agent pipeline; Swarm (100+ agents, consensus) |\n| Orchestration | Sequential sub-agent pipeline; GOAP & swarm topologies |\n| Memory | Persistent AgentDB (vector DB) + JSON cache; optional session-only modes |\n| Parallel execution | Yes — parallel agent execution and async pipelines |\n| Security guardrails | Privacy-focused; PII detection; prompt-injection defenses; security scan CLI |\n| Publishing | Standalone eject & npm publishing (`npx agent-nuvira`) |\n| **Routing strategy** | **Model-first scoring (6 dimensions) + tiered failover + 1-token warmup + Thompson-sampling bandit + quota pre-check + 22 providers + 300+ models** |\n| **Test suite** | **5,000+ tests across 220+ files — 100% passing** |\n| **Vector backend** | **Native FAISS (automatic), pure-JS IVF fallback, exact JSON fallback** |\n\n\n## Why Agent-Nuvira? (The Core Edge)\n\n- **🎯 Understands what you asked — then shows you the contract before it runs** — every\n  request in `chat`, `execute`, `plan`, and `edit` resolves through one shared understanding\n  layer: a deterministic rule fast-path (<5ms, works offline) with LLM verification behind it,\n  collapsing to a single action every command consumes identically. Before any work begins,\n  Agent-Nuvira prints a 🧠 Understanding card — the resolved goal, target, scope, acceptance\n  criteria, and risk flags — so the request is **seen before it is run**. The live activity\n  board then renders each agent step as it happens — no black box, no silently\n  half-understood goals\n- **🛠️ Execution that repairs itself** — a failed task is not just reported: failures are\n  classified, automatically repaired with escalating retries, independently verified after the\n  fix, and the lesson is stored in persistent failure memory so the same mistake is less likely\n  next time. Runs finish — or they tell you exactly why and what to do next\n- **🪙 Model-First Smart Routing** — stop paying flat premium fees. Nuvira dynamically routes every task across **22 providers** and **300+ discovered models** using **model-first scoring** (not provider-first). Each model is scored on 6 dimensions: cost per million tokens, capability fit, health, quota availability, provider speed, and verification status. The router picks the BEST MODEL for the task, then finds which provider serves it cheapest. **Tiered failover** with quota pre-check: same model → same tier → escalate → de-escalate → local → neural response. **1-token warmup daemon** keeps frequently-used models hot. A **central quota ledger** tracks tokens per provider × model with calendar-aware reset windows, parks exhausted providers until free quota resets, and **auto-fails-over mid-session** when a token expires or a rate limit hits — never a stuck session, never a quota error thrown at you\n- **🧠 Learning Router that gets better with use** — a Thompson-sampling bandit learns per provider × complexity bucket from *real* task outcomes (cost-adjusted rewards), with hard constraints (`maxCostUsd`, `minSpeed`, `minReasoning`), regex routing rules, uncertainty-driven escalation when the bandit has no data, and **promotion gates** that only keep router changes that measurably improve quality without regressing cost\n- **🐝 17 Specialized Agent Swarm** — no generic single-prompt boxes. Your goal is decomposed into a DAG of tasks handled by dedicated agents working in parallel: Planner, Context-Gatherer, Writer, Reviewer, Runner, Tester, Debugger, Security Auditor, Git/GitLab specialist, Package installer, PR Reviewer, Issue Triage, Branch Automation, and more\n- **⚡ Deterministic Tier-0 routing** — mechanical edits (remove `console.log`, rename symbols, dedupe imports) complete in **<1ms for $0**, AST-validated before apply, and never touch an LLM unless the goal genuinely needs one\n- **🧠 Local FAISS Context Indexing** — blazing-fast, private, semantic code search and retrieval with an optional **native FAISS backend** (pure-JS fallback) that strictly respects your `.gitignore`. Retrieval shrinks a 20k-token gathered context to the top-k relevant chunks — saving tokens so free quotas stretch further\n- **📌 Persistent project memory** — facts, preferences, and trajectories are stored per project and recalled automatically in later sessions; memory is pluggable (local by default, external backends optional)\n- **🔌 First-Class MCP Integration** — seamlessly connect to Jira, Slack, PostgreSQL, GitHub Issues, and file systems using standard Model Context Protocol servers with SSE transport\n- **👥 Real-Time Team Collaboration** — share context, synchronized vector indices, custom agents, and review pipelines across your engineering team via Git-synced config and memory\n- **🎨 Adaptive Modality Routing** — intelligent routing for image/audio/video with failover across backends. **Data-driven providers** — add new providers via config, no code changes required. Image: ComfyUI (free) → Pollinations (free) → DALL-E (paid) → Stability (paid). TTS: OpenAI TTS (paid) → ElevenLabs (paid). Video: FAL (paid) → Runway (paid). Transcription: OpenAI Whisper (paid). Users can add custom providers:\n  ```bash\n  # Add Replicate for image generation\n  nuvira config set modality.image.replicate.apiKey=r8_xxxxx\n  nuvira config set modality.image.replicate.baseUrl=https://api.replicate.com/v1\n  nuvira config set modality.image.replicate.models=\"stability-ai/sdxl\"\n  \n  # Add Azure TTS\n  nuvira config set modality.tts.azure.apiKey=xxxxx\n  nuvira config set modality.tts.azure.region=eastus\n  ```\n- **🖥️ Runs anywhere** — zero native dependencies, tested on macOS / Windows / Linux (3,806 tests), no server, no telemetry, no subscriptions, and bring-your-own-keys for every provider. For the reasoning behind the architecture, see [DESIGN_DECISIONS.md](DESIGN_DECISIONS.md). For benchmark results, see [docs/benchmarks/INDEX.md](docs/benchmarks/INDEX.md)\n\n---\n\n## Features\n\n- **Unified interface** across 17+ providers: 5 built-in (local/Ollama, Groq, NVIDIA NIM, Google Gemini, OpenRouter) + 12 configurable via environment variables (OpenAI, Anthropic, Mistral, Cohere, Together, DeepInfra, Fireworks, Perplexity, Azure, LM Studio, Anyscale, vLLM)\n- **Model discovery** — `agent-nuvira models` lists available models from any configured provider, with search/filter support\n- **Interactive chat** with conversation history, file context, and session commands\n- **AI-assisted file editing** with dry-run mode for safe previews\n- **Codebase planning** that analyzes directory structure and generates implementation plans\n- **Multi-agent orchestration** — `agent-nuvira execute \"goal\"` runs a pipeline of planner, gatherer, writer, reviewer, tester, and more\n- **Response caching** via SQLite to reduce costs and latency\n- **Plugin system** with auto-discovery — drop `.js` files into `~/.nuvira/plugins/` for automatic loading\n- **Project scaffolding** — `agent-nuvira init` generates starter projects with interactive template + provider selection\n- **Context-preserving model switching** — `agent-nuvira model switch` changes providers mid-session without losing agent state\n- **Auto model routing** — `agent-nuvira model switch auto` lets the agent pick the best provider/model for every task based on complexity, cost, latency, privacy, and reliability (with fallback chains + circuit-breaker awareness). Cost scoring uses **real per-1K-token provider pricing** (overridable via `agent-nuvira config set pricing.<provider>.inputPer1K`), adjusted at runtime by **benchmark quality + per-agent best-model stats**. See why a decision was made with `agent-nuvira model explain` (or `--json` for CI) — walk through a full decision with the 🎯 fit / 📏 measured / ⏳ ctx chips in [`MODELS_EXPLAIN_DEMO.md`](MODELS_EXPLAIN_DEMO.md). Benchmark the router's exact picks with `agent-nuvira benchmark --routing`, validate them end-to-end with `agent-nuvira eval --routing`, and track actual picks + a full audit trail in the dashboard's **Routing** panel\n- **Learned-from-real-usage telemetry** — every LLM call (chat, execute, plan, edit, skill, learn, ci, doctor) writes through to the Model Availability Registry **with its action tag**, so the registry learns which provider × model each action **killed** (predictive skip) or **verified** (routable) from real usage — not just probes. `agent-nuvira models status --verbose` prints registry-blocked providers + per-action verified/killed chips, and the dashboard's **Models** panel shows the same per-action feed with a daily timeline chart. A provider killed by ANY action is skipped predictively by all others; a later real success re-verifies it and un-parks it (the recovery loop), and `agent-nuvira models unblock <provider>` is the manual escape hatch (demotes the block, clears quota parks + ledger cooldown, then re-probes the live API with an honest `stillBlocked` verdict — `--json` for CI). Proven end-to-end by a hermetic `tests/e2e/` test (mock 429 provider → registry learns → next pick skips). The **VS Code extension** attributes its usage too — every IDE-driven call (chat panel → `ide-chat`, inline suggestions → `ide-inline`, execute/edit/workflow → `ide-<command>`) is tagged via `BUFF_TELEMETRY_ACTION` at spawn, so the same per-action panel shows IDE usage as its own rows\n- **Skill compiler** — automatically extracts reusable patterns from successful agent runs into executable skills (`agent-nuvira skill run`)\n- **Context-window memory pruner** — prevents long multi-agent chains from exceeding model token limits\n- **Complete streaming support** — all 17+ providers support real-time token-by-token output\n- **Cost tracking** — per-provider/session/monthly costs with `agent-nuvira stats cost`\n- **Prompt history search** — keyword and semantic search across past conversations (`/search`, `agent-nuvira history`)\n- **Native embedding support** — 3-tier embedder with `@huggingface/transformers` for 10x faster semantic search\n- **Workflow template marketplace** — 10 built-in templates + GitHub registry with install/publish lifecycle\n- **Model benchmarking** — 21 standardized coding tasks with scoring and A/B comparison\n- **Docker sandbox isolation** — resource-limited, network-isolated container execution with 8 base images\n- **Provider health dashboard** — `agent-nuvira doctor` with color-coded status, watch mode, and auto-fix\n- **Memory compression & pruning** — automatic trajectory summarization with configurable retention policies\n- **VS Code extension** — Chat Panel with streaming responses, slash commands, and session history;\n  Diagnostic → AI Fix from lightbulb menu; Code Lens actions (Test/Review/Explain/Fix) above functions\n  and classes; 9 commands, inline code suggestions, diff viewer, agent progress panel\n- **22-platform multi-channel gateway** — `agent-nuvira gateway start / send / status / alias` runs the agent from Telegram, Discord, Slack, WhatsApp (Cloud API + Baileys personal bridge), Email, Signal, DingTalk, Feishu, WeCom, Mattermost, Matrix, generic Webhook, BlueBubbles (iMessage), ntfy, Teams, Google Chat, Weixin, SMS (Twilio), IRC (two-way), SimpleX (two-way),  and Home Assistant — all opt-in via standard env vars per platform, with a guaranteed delivery ledger (auto-retry on `agent-nuvira gateway start`), the dashboard Channels send-test, and a `X/22 platforms configured` status line\n- **Remote agent federation** — multi-machine collaboration with protocol, server, and client\n- **Web UI dashboard** — React dashboard with DAG visualization, model health, cost charts, and history browser\n- **Hybrid model routing** — intelligent model selection based on task complexity, cost, and availability\n- **Team collaboration** — Git-synced shared config, memory, and review pipelines\n- **Agent SDK** — `@agent-nuvira/sdk` npm package for building custom agents with scaffolding CLI\n- **Provider CLI** — `agent-nuvira provider list` with color-coded status table, `agent-nuvira provider health` with per-provider diagnostics\n- **Provider fallback routing** — automatic failover between providers with circuit breaker and configurable chain\n- **Startup progress feedback** — first launch never looks like a silent hang: a live spinner reports each startup phase (plugins → history & search → semantic index) as it runs\n- **Auto-mode session failover** — in Auto routing, a provider whose API key/token expires or rate-limits mid-session is automatically swapped for the next-best provider (auth failures excluded for the session, rate-limit failures for a 120s cooldown, 5xx/network through the circuit breaker) — no more stuck sessions on a dead key\n- **Central quota ledger** — tokens/requests per provider × model with calendar-aware reset windows; exhausted providers are **parked** until the window rolls (auto re-enable, no timers), and Auto routing sinks parked providers below healthy candidates **before** a call — plus an optional free/local-first `allowPaid` gate and a `agent-nuvira model quota` CLI with a cost summary (free vs paid tokens + estimated $ saved)\n- **Learning Router CLI** — `agent-nuvira model bandit` inspects the Thompson-sampling state (α/β priors per provider × complexity bucket, expected win %, learning history, `--json` for CI) and `agent-nuvira model bandit reset` clears it; routing decisions record a `routedBy` source (`heuristic | rule | bandit`) for full auditability\n- **Routing rules & hard constraints** — regex/string task-pattern rules force a provider/model before scoring (first match wins); per-call filters (`routing.maxCostUsd`, `routing.minSpeed`, `routing.minReasoning`) *eliminate* violating providers with a safe fallback when constraints would remove everything\n- **Deterministic Tier-0 routing** — mechanical edits short-circuit the LLM entirely (strip `console.*` lines, word-boundary symbol renames, import dedupes) with AST validation and graceful fallthrough to the LLM when a goal isn't mechanical — `$0` and `<1ms` per edit\n- **Native FAISS vector backend** — `agent-nuvira memory backend` shows the active backend (`faiss-native` / `faiss-ivf` / `json`) and why it was chosen; `--check` runs a native-FAISS availability probe with install guidance, and `@faiss-node/native` is used automatically whenever it builds\n- **Vector retrieval (token-efficient context)** — large gathered contexts are chunked, embedded locally (`bge-small-en-v1.5` via @huggingface/transformers, zero new deps) and reduced to the top-k semantically-relevant chunks before the LLM call — saving tokens so free quotas stretch further. Complements the quota ledger: **retrieval saves tokens, the ledger manages quotas**. Small contexts pass through untouched (zero overhead); any retrieval failure fails over to full context. `agent-nuvira retrieval index/query/stats/clear` + a dashboard Retrieval card show the savings\n- **Checkpoint / resume** — `agent-nuvira execute \"<goal>\" --checkpoint` saves a resume-able snapshot after every task batch; `--resume [id]` rehydrates the plan and continues from the first pending step (a crash / quota kill / token expiry mid-pipeline no longer restarts the whole plan); `--checkpoint-list` shows saved pipelines\n- **Security scan CLI** — `agent-nuvira security scan` detects PII, prompt injections, and dangerous code patterns\n- **Feedback & rating system** — `agent-nuvira feedback record/list/stats/clear` drives self-improvement scoring\n- **Marketplace unified CLI** — `agent-nuvira marketplace browse/search/install/info` for workflow templates + plugins\n- **MCP (Model Context Protocol) integration** — connect to databases, APIs, and file systems via MCP servers with SSE transport support\n- **AST-aware code editing** — structural analysis engine understands functions, classes, methods across JS/TS/Python/Go/Rust\n- **Auto error-repair engine** — automatic diagnosis and repair of test failures with configurable retry budgets\n- **Cross-platform dependency installer (Runner)** — auto-detects 11 manifest types (npm/pnpm/yarn with\n  lockfile-first priority, pip, bundler, cargo, go, composer, dart pub), installs missing project dependencies\n  on failed commands, and bootstrap-installs missing package managers (npm, pip, bundler, cargo, go, composer,\n  dart, Homebrew) via brew/apt/dnf/yum/winget/choco/rustup — no manual setup required\n- **A2A (Agent-to-Agent) Protocol** — inter-agent communication standard for multi-machine collaboration\n- **CI/CD headless mode** — `agent-nuvira ci` for automated pipelines with GitHub Actions integration\n- **npm publishing & one-line install** — `npx agent-nuvira` and `npx buff` for zero-setup onboarding\n- **Marketing website** — `website/` directory with a full landing page, SEO meta tags, and Netlify-ready deployment config\n- **Branch Automation Hooks (Pillar A4)** — `agent-nuvira execute \"install branch hooks\" --auto-branch` installs\n  git post-checkout and pre-commit hooks for automated branch workflows; issue-driven branch creation\n  (`feat/PROJ-123-description`), PR label-triggered updates, file-watch auto-commit with conventional\n  commit messages, and CI failure detection with LLM diagnosis\n- **Issue Triage Engine (Pillar A3)** — Automated issue classification, prioritization, and labeling\n  across GitHub and GitLab via `agent-nuvira execute \"triage issues\"` with LLM-powered analysis\n- **GitHub PR Review Agent (Pillar A2)** — Automatic inline code review on open PRs; reads diffs,\n  runs security/quality verification, and posts inline review comments via GitHub API\n- **GitLab API Integration (Pillar A1)** — Full GitLab agent for merge request management, issue\n  discovery, pipeline monitoring, and code review comments\n- **Chat Panel DAG Pipeline Visualization (Pillar B6)** — Live multi-agent pipeline visualization\n  inline in chat messages for slash commands, showing agent nodes with real-time status updates\n- **Real-Time Token Streaming in AgentPanel (Pillar B2)** — Live typewriter-effect token streaming\n  with blinking cursor and animated progress indicator in the agent progress panel\n- **Interactive development mode** — `agent-nuvira execute` without a goal launches a guided interactive loop with session save/resume, follow-up suggestions, and failure analysis\n- **Session persistence** — save and resume development sessions across CLI restarts with full history\n- **Failure analysis** — automatic diagnosis of agent failures with specific recovery options per agent type\n- **Follow-up suggestions** — LLM-powered contextual next-step recommendations after goal completion\n- **Configuration** via JSON config file + environment variables\n- **No server dependency** — no telemetry, no subscriptions, no outbound calls to a hosted backend\n\n---\n\n## Quick Start\n\n### Prerequisites\n\n- **Node.js** 20+ and **npm**\n- **TypeScript** knowledge for development; none required to use the CLI\n\n### Install\n\n```bash\n# Install globally\nnpm install -g agent-nuvira\n\n# Or clone and build from source\ngit clone https://github.com/imdheerajKube/agent-nuvira.git buff\ncd agent-nuvira\nnpm install\nnpm run build\nnpm link\n```\n\n### One-command setup for new users (recommended)\n\nIf you're setting up on a **fresh machine** (or just don't want to deal with\ninstalling Node.js, Git, build tools, etc. by hand), use the platform setup\nscript. Each one **checks for the required tools, installs anything missing\nfor you, installs Agent-Nuvira, and then asks whether you want the optional\nperformance upgrades** (native FAISS + local embeddings) — with plain-English\nprompts the whole way.\n\n| OS | Run this |\n|---|---|\n| **macOS** | `bash <(curl -fsSL https://raw.githubusercontent.com/imdheerajKube/agent-nuvira/main/scripts/setup/install-macos.sh)` |\n| **Linux** (Ubuntu/Debian/Fedora/RHEL/Arch/Alpine) | `bash <(curl -fsSL https://raw.githubusercontent.com/imdheerajKube/agent-nuvira/main/scripts/setup/install-linux.sh)` |\n| **Windows** (PowerShell) | `Set-ExecutionPolicy -ExecutionPolicy Bypass -Scope Process -Force; irm https://raw.githubusercontent.com/imdheerajKube/agent-nuvira/main/scripts/setup/install-windows.ps1 | iex` |\n\nWhat each script does:\n\n1. **Detects what's missing** — Node.js, npm, Git, build tools (and Homebrew on\n   macOS / `winget` on Windows), and installs them automatically (with your\n   confirmation) using the right installer for your OS.\n2. **Installs Agent-Nuvira** — `npm install -g agent-nuvira` (with npm 11's\n   install-script security gate handled automatically so native components build).\n3. **Asks about optional upgrades** (recommended, each a yes/no):\n   - **Native FAISS** → faster semantic search / memory recall\n   - **Local embeddings** → free, offline, private embeddings (no cloud call)\n4. **Verifies** the install and prints next steps.\n\n> The scripts are safe to re-run — they skip tools that are already present.\n> Manual install instructions for every step are below for those who prefer\n> full control.\n\n### Native FAISS acceleration (optional, recommended)\n\nAgent-Nuvira includes an optional native FAISS backend for faster semantic retrieval. The runtime prefers this backend automatically when the native addon can build successfully; if that path is unavailable, it falls back to the pure-JS IVF implementation and then the exact JSON backend so your workflow stays reliable.\n\n> **How the auto-selection works:** At load time, `createFaissBackend()`\n> attempts to import `@faiss-node/native` and run a 1-vector smoke test.\n> If the native addon exists and passes the smoke test, the backend is\n> `faiss-native`. If the import fails (not installed, build error, or wrong\n> API), it falls back to the pure-JS IVF-flat ANN (`faiss-ivf`). If that\n> also fails to initialize, the exact JSON backend (`json`) is used as the\n> final safety net — semantic search NEVER breaks.\n\nFor npm-installed users, the setup is:\n\n```bash\n# 1) Install the CLI\nnpm install -g agent-nuvira\n\n# 2) Install the native build prerequisites (macOS example)\nbrew install faiss libomp openblas\n\n# 3) Rebuild the optional native addon\nnpm rebuild @faiss-node/native\n\n# 4) Enable the FAISS-style backend (or leave it on 'auto' to prefer it automatically)\n#    'auto' (default) — tries native FAISS first, then pure-JS IVF, then JSON\n#    'faiss'         — prefer FAISS-style (native or pure-JS IVF); JSON fallback\n#    'json'          — exact flat cosine (the original behavior, no FAISS at all)\nagent-nuvira config set memory.vectorBackend auto\n# or force it explicitly:\n# agent-nuvira config set memory.vectorBackend faiss\n```\n\nIf you want to confirm the backend in use:\n\n```bash\nagent-nuvira memory stats                    # Shows active backend\nagent-nuvira memory backend                  # Active backend name + why it was chosen\nagent-nuvira memory backend --check          # Same + native availability probe + install guidance\n```\n\n### Understanding the FAISS tiers\n\n| Tier | Backend name | When it's used | Performance |\n|---|---|---|---|\n| **1 — Native FAISS** | `faiss-native` | `@faiss-node/native` installed AND built successfully | Fastest — real FAISS C++ bindings |\n| **2 — Pure-JS IVF** | `faiss-ivf` | Native not available; runs TypeScript port of FAISS IndexIVFFlat | Approximate ANN; sub-linear search for large indexes |\n| **3 — Exact JSON** | `json` | Both FAISS paths unavailable; flat cosine scan | Exact results; O(n) linear scan |\n\nThe pure-JS IVF tier uses deterministic k-means++ clustering (nlist=sqrt(n)),\ninner product of L2-normalized vectors (= cosine similarity), and nprobe probe\nlists. For small indexes (≤ 512 entries) it runs an exact scan so results are\nidentical to the JSON backend. Filter-aware probe expansion ensures that\nmetadata filters don't miss results.\n\nIf the native addon cannot be built on your machine, Agent-Nuvira will continue to work using the pure-JS fallback path.\n\n### Local embeddings (optional, recommended)\n\nSemantic search and memory recall use embeddings. Agent-Nuvira's embedder has a\n3-tier strategy and **always prefers the local tier when it works**:\n\n| Tier | Engine | Notes |\n|---|---|---|\n| **1 — Local** | `@huggingface/transformers` (`onnxruntime-node`) | Free, offline, private — `Xenova/all-MiniLM-L6-v2` (384-dim). **Default when available** |\n| **2 — Python** | `sentence-transformers` via subprocess | Used when Tier 1 is unavailable and Python is present |\n| **3 — LLM** | Any configured inference provider | Last-resort fallback; costs tokens |\n\nWith `@huggingface/transformers` installed and its native binary present, no\nconfiguration is needed — local embeddings are used automatically, offline,\nwith zero API cost. The one-command setup scripts above enable this for you.\nTo verify which tier is active, run:\n\n```bash\nagent-nuvira memory backend --check\n```\n\n### Verify\n\n```bash\nagent-nuvira --help\n```\n\nYou should see:\n\n```\nUsage: agent-nuvira [options] [command]\n\nFlexible AI inference CLI tool — local models & cloud APIs\n\nOptions:\n  -V, --version  output the version number\n  -d, --debug    enable debug logging\n  -h, --help     display help for command\n\nCommands:\n  chat [options] [prompt]       Start an interactive chat session with AI\n  edit [options] <file>         Edit a file using AI assistance\n  models [options]              List available models from inference providers\n  plan [options] [target]       Generate an implementation plan for a codebase task\n  execute [options] <goal>      Execute a multi-agent pipeline for a goal\n  model                         Switch providers and manage active models\n  skill                         List, compile, and run reusable skill scripts\n  init [name]                   Scaffold a new project from a template\n  history                       Search and manage chat history\n  doctor                        Provider health dashboard\n  benchmark                     Run model benchmarks\n  workflow                      Workflow template marketplace\n  federation                    Remote agent federation\n  team                          Team collaboration\n  dashboard                     Launch web UI dashboard\n  dashboard stop                Gracefully stop a running dashboard server\n  memory                        Memory compression and stats\n  provider                      Provider list and health diagnostics\n  security                      Security scan for PII, injections, and dangerous code\n  feedback                      Feedback and rating system\n  marketplace                   Browse, search, and install plugins and workflows\n  mcp                           Model Context Protocol — connect to MCP servers\n  plugins                       Manage auto-discovered plugins\n  sandbox                       Docker sandbox management\n  sdk                           Agent SDK scaffolding\n  config                        Manage Buff configuration\n  cache                         Manage inference cache\n```\n\n---\n\n## Getting API Keys\n\nEach cloud provider requires an API key. Sign up and get your key from the links below.\n\n### 🔷 Groq (Fast — LPU Cloud Inference)\n\nGroq runs open-source models at blazing speeds on their custom LPU hardware.\n\n1. Sign up at **[console.groq.com](https://console.groq.com)** (free tier available)\n2. Go to **API Keys** → **Create API Key**\n3. Copy your key (starts with `gsk_`)\n\n```bash\nexport GROQ_API_KEY=\"gsk_xxxxxxxxxxxxxxxx\"\n```\n\n### 🔶 NVIDIA NIM\n\nNVIDIA NIM provides hosted API access to a wide catalog of models (121+ models).\n\n1. Sign up at **[build.nvidia.com](https://build.nvidia.com)** (free tier with rate limits)\n2. Generate an API key from the **Get API Key** button\n3. Copy your key (starts with `nvapi-`)\n\n```bash\nexport NVIDIA_NIM_API_KEY=\"nvapi-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\"\n```\n\n### 🔷 Google Gemini\n\nGoogle's Gemini API has a generous free tier with competitive models.\n\n1. Visit **[aistudio.google.com/apikey](https://aistudio.google.com/apikey)** and click **Create API Key**\n2. Select your Google Cloud project or create one\n3. Copy your key (starts with `AIzaSy`)\n\n```bash\nexport GEMINI_API_KEY=\"AIzaSyxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\"\n```\n\n### 🟣 OpenRouter\n\nOpenRouter gives you access to 200+ models from OpenAI, Anthropic, Google, Meta, and more — all through one API.\n\n1. Sign up at **[openrouter.ai/keys](https://openrouter.ai/keys)** (free credits on sign-up)\n2. Click **Create Key**\n3. Copy your key (starts with `sk-or-v1-`)\n\n```bash\nexport OPENROUTER_API_KEY=\"sk-or-v1-xxxxxxxxxxxxxxxxxxxxxxxxxxxx\"\n```\n\n## MCP (Model Context Protocol) Configuration\n\nMCP servers extend your agent's capabilities by connecting to external tools and data sources — databases, APIs, file systems, search engines, code repositories, and more. Agent-Nuvira supports the MCP standard for discovering and invoking tools from connected servers.\n\n### Configuration Files\n\nMCP server configs are JSON files placed in '~/.nuvira/mcp/'. Each file defines one server connection. Files are auto-discovered at startup.\n\n```bash\nmkdir -p ~/.nuvira/mcp\n```\n\n### Configuration Fields\n\n| Field | Type | Required | Description |\n|-------|------|----------|-------------|\n| `name` | string | Yes | Unique name for this server connection |\n| `transport` | `\"stdio\"` or `\"sse\"` | Yes | Transport protocol (stdio for local subprocess, sse for remote HTTP) |\n| `command` | string | For stdio | The command to run (e.g., `npx`, `node`, a binary path) |\n| `args` | string[] | For stdio | Command arguments |\n| `url` | string | For sse | The SSE endpoint URL (e.g., `https://example.com/mcp`) |\n| `headers` | object | Optional | Custom HTTP headers for SSE transport (e.g., `Authorization`) |\n| `env` | object | Optional | Environment variables for the stdio subprocess |\n| `enabled` | boolean | Yes | Set to `false` to temporarily disable the server |\n\n### Transport Types\n\n#### stdio (Local Subprocess)\n\nSpawns a local process (Node.js, Python, Go binary, etc.) and communicates via stdin/stdout using JSON-RPC 2.0.\n\n```json\n{\n  \"name\": \"filesystem\",\n  \"transport\": \"stdio\",\n  \"command\": \"npx\",\n  \"args\": [\"-y\", \"@modelcontextprotocol/server-filesystem\", \".\"],\n  \"enabled\": true\n}\n```\n\n#### sse (Remote HTTP)\n\nConnects to a remote HTTP endpoint using Server-Sent Events (SSE). Supports custom headers for authentication.\n\n```json\n{\n  \"name\": \"exa\",\n  \"transport\": \"sse\",\n  \"url\": \"https://websetsmcp.exa.ai/mcp\",\n  \"headers\": {\n    \"Authorization\": \"Bearer YOUR_EXA_API_KEY\"\n  },\n  \"enabled\": true\n}\n```\n\n### Examples\n\n#### 1. Filesystem Server\n\nRead/write files and directories on your local machine.\n\n```json\n{\n  \"name\": \"filesystem\",\n  \"transport\": \"stdio\",\n  \"command\": \"npx\",\n  \"args\": [\"-y\", \"@modelcontextprotocol/server-filesystem\", \"/path/to/your/project\"],\n  \"enabled\": true\n}\n```\n\n```bash\nagent-nuvira mcp connect filesystem\nagent-nuvira mcp call read_file --server filesystem --args '{\"path\":\"/path/to/file.txt\"}'\n```\n\n#### 2. GitHub Server\n\nSearch repositories, issues, PRs, and code on GitHub. Requires a GitHub Personal Access Token.\n\n**Setup:**\n1. Build the binary: `git clone https://github.com/github/github-mcp-server.git && cd github-mcp-server && go build -o github-mcp-server ./cmd/github-mcp-server/`\n2. Move it to your PATH: `mv github-mcp-server /usr/local/bin/`\n3. Create a GitHub PAT at https://github.com/settings/tokens\n4. Add the config below to '~/.nuvira/mcp/github.json'\n\n```json\n{\n  \"name\": \"github\",\n  \"transport\": \"stdio\",\n  \"command\": \"/usr/local/bin/github-mcp-server\",\n  \"args\": [\"stdio\"],\n  \"env\": {\n    \"GITHUB_PERSONAL_ACCESS_TOKEN\": \"github_pat_xxxxxxxxxxxx\"\n  },\n  \"enabled\": true\n}\n```\n\n```bash\nagent-nuvira mcp connect github\nagent-nuvira mcp list\n# Tools include: search_repositories, search_issues, search_code, search_pull_requests, etc.\nagent-nuvira mcp call search_repositories --server github --args '{\"query\":\"react\",\"limit\":5}'\n```\n\n#### 3. Exa WebSets Server (SSE with Bearer Auth)\n\nSearch and enrich web entities (companies, people, research papers) using Exa's AI-powered search API. Uses SSE transport with Bearer token authentication.\n\n**Setup:**\n1. Get your Exa API key at https://dashboard.exa.ai\n2. Add the config below to '~/.nuvira/mcp/exa.json'\n\n```json\n{\n  \"name\": \"exa\",\n  \"transport\": \"sse\",\n  \"url\": \"https://websetsmcp.exa.ai/mcp\",\n  \"headers\": {\n    \"Authorization\": \"Bearer YOUR_EXA_API_KEY\"\n  },\n  \"enabled\": true\n}\n```\n\n```bash\nagent-nuvira mcp connect exa\nagent-nuvira mcp list\n# Tools include: create_webset, create_search, create_enrichment, list_websets, etc.\n```\n\n### CLI Commands\n\n| Command | Description |\n|---------|-------------|\n| `agent-nuvira mcp list` | List all discovered MCP servers and their tools |\n| `agent-nuvira mcp connect <name>` | Connect to a specific MCP server |\n| `agent-nuvira mcp connect --all` | Connect to all discovered MCP servers |\n| `agent-nuvira mcp call <tool> --server <name> --args '{\"key\":\"val\"}'` | Call a tool on a connected server |\n| `agent-nuvira mcp info <name>` | Show detailed information for an MCP server |\n| `agent-nuvira mcp refresh` | Re-discover and reconnect to all MCP servers |\n\n### Auto-Discovery with the Orchestrator\n\nWhen you run `agent-nuvira execute`, the orchestrator automatically:\n\n1. Scans '~/.nuvira/mcp/' for JSON config files\n2. Connects to all enabled MCP servers\n3. Injects tool descriptions into the agent's context\n4. The planner can schedule MCP tool calls as pipeline steps\n\n### Finding More MCP Servers\n\nBrowse the official MCP server directory at **[modelcontextprotocol.io/servers](https://modelcontextprotocol.io/servers)**. Popular servers include:\n\n- **Filesystem** — Read/write local files\n- **GitHub** — Repository, issue, PR, and code search\n- **PostgreSQL** — Query databases\n- **SQLite** — Query SQLite databases\n- **Brave Search** — Web search\n- **Docker** — Container management\n- **Puppeteer** — Browser automation\n- **Slack** — Channel and message access\n\n\n\n---\n\n## Configuration\n\n### Config File\n\nConfiguration lives at `~/.nuvira/nuvirarc.json`. It is created with sensible defaults on first use.\n\nYou can inspect and modify it through the CLI:\n\n```bash\n# Show full configuration\nagent-nuvira config\n\n# Set the default provider\nagent-nuvira config set defaultProvider gemini\n\n# Set a provider's model\nagent-nuvira config set providers.nim.model \"meta/llama-3.1-8b-instruct\"\n\n# List all providers with their status\nagent-nuvira config list\n```\n\n### Default Configuration\n\n```json\n{\n  \"defaultProvider\": \"local\",\n  \"providers\": {\n    \"nim\": {\n      \"model\": \"meta/llama-3.1-8b-instruct\",\n      \"temperature\": 0.7,\n      \"maxTokens\": 4096\n    },\n    \"gemini\": {\n      \"model\": \"gemini-2.0-flash-exp\",\n      \"temperature\": 0.7,\n      \"maxTokens\": 8192\n    },\n    \"openrouter\": {\n      \"model\": \"mistralai/mistral-7b-instruct\",\n      \"temperature\": 0.7,\n      \"maxTokens\": 4096\n    },\n    \"groq\": {\n      \"model\": \"llama-3.3-70b-versatile\",\n      \"temperature\": 0.7,\n      \"maxTokens\": 4096\n    },\n    \"local\": {\n      \"runner\": \"ollama\",\n      \"model\": \"llama2\",\n      \"temperature\": 0.7,\n      \"maxTokens\": 4096\n    }\n  }\n}\n```\n\n### Environment Variables\n\nAPI keys can be set via environment variables instead of the config file. They take **priority** over the config file.\n\n| Variable | Provider | Required? | Get Your Key |\n|---|---|---|---|\n| `GROQ_API_KEY` | Groq | Yes, unless using local | [console.groq.com](https://console.groq.com) |\n| `NVIDIA_NIM_API_KEY` | NVIDIA NIM | Yes, unless using local | [build.nvidia.com](https://build.nvidia.com) |\n| `GEMINI_API_KEY` | Google Gemini | Yes, unless using local | [aistudio.google.com/apikey](https://aistudio.google.com/apikey) |\n| `OPENROUTER_API_KEY` | OpenRouter | Yes, unless using local | [openrouter.ai/keys](https://openrouter.ai/keys) |\n\nYou can place a `.env` file in the project root or at `~/.nuvira/.env`:\n\n```env\n# ~/.nuvira/.env\nGROQ_API_KEY=gsk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\nNVIDIA_NIM_API_KEY=nvapi-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\nGEMINI_API_KEY=AIzaSyxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\nOPENROUTER_API_KEY=sk-or-v1-xxxxxxxxxxxxxxxxxxxxxxxxxxxx\n```\n\n### Modality Providers (Image/Audio/Video)\n\nAgent-Nuvira routes image generation, TTS, video, and transcription to the best available backend. Built-in providers are automatically detected from environment variables. You can add custom providers via config:\n\n```bash\n# Add Replicate for image generation\nagent-nuvira config set modality.image.replicate.apiKey=r8_xxxxx\nagent-nuvira config set modality.image.replicate.baseUrl=https://api.replicate.com/v1\nagent-nuvira config set modality.image.replicate.models='[\"stability-ai/sdxl\", \"black-forest-labs/flux-schnell\"]'\nagent-nuvira config set modality.image.replicate.costPerUnit=0.003\nagent-nuvira config set modality.image.replicate.quality=0.9\n\n# Add Azure TTS\nagent-nuvira config set modality.tts.azure.apiKey=xxxxx\nagent-nuvira config set modality.tts.azure.baseUrl=https://eastus.tts.speech.microsoft.com\nagent-nuvira config set modality.tts.azure.endpoint='/cognitiveservices/v1'\nagent-nuvira config set modality.tts.azure.models='[\"en-US-AriaNeural\", \"en-US-JennyNeural\"]'\n\n# Add custom video provider\nagent-nuvira config set modality.video.myprovider.apiKey=xxxxx\nagent-nuvira config set modality.video.myprovider.baseUrl=https://api.myprovider.com/v1\nagent-nuvira config set modality.video.myprovider.models='[\"model-1\"]'\n```\n\n**Built-in providers (auto-detected from env vars):**\n\n| Modality | Provider | Env Var | Cost | Quality |\n|----------|----------|---------|------|----------|\n| Image | Pollinations.ai | None (free) | Free | 0.7 |\n| Image | DALL-E 3 | `OPENAI_API_KEY` | $0.04/image | 0.95 |\n| Image | Stability AI | `STABILITY_API_KEY` | $0.002/gen | 0.85 |\n| Image | ComfyUI (local) | `BUFF_IMAGE_API_URL` | Free | 0.9 |\n| TTS | OpenAI TTS | `OPENAI_API_KEY` | $15/1M chars | 0.9 |\n| TTS | ElevenLabs | `ELEVENLABS_API_KEY` | $30/1M chars | 0.95 |\n| Video | FAL AI | `FAL_KEY` | $0.05/video | 0.85 |\n| Video | Runway ML | `RUNWAY_API_KEY` | $0.10/video | 0.95 |\n| Transcription | OpenAI Whisper | `OPENAI_API_KEY` | $0.006/min | 0.95 |\n\n**How routing works:**\n\n1. Score all available providers by: cost (35%), quality (30%), speed (20%), availability (15%)\n2. Try best provider first\n3. On failure, automatically failover to next best provider\n4. Continue until success or all providers exhausted\n\n---\n\n## Messaging Gateway — Permissions, Sending, and Reading Traces Honestly\n\nThis section exists because two different ideas get conflated and it causes real confusion. Read it before you let anyone else message your bot.\n\n### 1. Two separate permissions (they are NOT the same thing)\n\n| Permission | Where it lives | What it controls |\n|---|---|---|\n| **Who may trigger the agent** | `gateway.policies.<platform>.allowedUsers` (Agent Hub → Channels → **Permissions**, or `agent-nuvira config gateway allow …`) | Who can *talk to* the bot at all |\n| **Who may send to others** | `gateway.policies.<platform>.outboundSenders` (Agent Hub → Permissions → **Send authority**, Contacts page, or `config gateway send-authority …`) | Who can tell the bot to *deliver a message to a third party* |\n\nA third concept, a **contact's approval status**, only gates sending **to** that person — it does not make that person a trusted sender.\n\n**Open by default — know this.** If you never set `outboundSenders`, a platform is **OPEN**: every sender who is allowed to trigger the agent can also direct it to send to anyone. This is the legacy behaviour so nothing silently breaks. To restrict it, set an explicit list:\n\n```bash\n# Only YOU may direct the bot to message other people on WhatsApp\nagent-nuvira config gateway send-authority add whatsapp +919876543210\n# The list is now RESTRICTED to that number. Everyone else is refused.\n\nagent-nuvira config gateway send-authority list whatsapp      # show current state\nagent-nuvira config gateway send-authority remove whatsapp +91… # drop one\nagent-nuvira config gateway send-authority reset whatsapp      # back to OPEN\nagent-nuvira config gateway send-authority require-target whatsapp on  # recipients must be approved contacts\n```\n\nOr do the same visually: **Dashboard → Contacts → “🔐 Send authority”** (a platform card per channel, with add/remove, an `open`/`restricted` badge, and “Require approved recipients”), or **Agent Hub → Channels → Permissions → Send authority**.\n\nThe list follows the same rules as `allowedUsers`: specific ids restrict it, an empty list means *nobody*, and the `Allow-All` wildcard means *anyone*. A sender can always reply inside their own conversation; send authority only governs messages to **other** targets.\n\n> A CLI/dashboard chat turn (you typing at the keyboard) is trusted and never blocked by this gate — it only applies to remote senders arriving through a messaging platform.\n\n### 2. Who appears where (Contacts vs Agent Hub)\n\n- **Contacts tab** — the directory of people the bot can message. **Telegram** users are auto-registered here on their first message with status **⏳ pending** until you approve them. WhatsApp senders are *not* auto-registered.\n- **Agent Hub → Permissions → “Send authority”** — who may command sends to others.\n- **Tick `Require approved recipients`** if you want every outbound target to be an approved contact (an explicit `platform:+number` target is otherwise allowed).\n\n### What “pending” means — and what it does not\n\n| Label | Where | Meaning |\n|---|---|---|\n| **⏳ pending** | Contacts tab | A real **approval** state — the person messaged the bot and is awaiting your decision |\n| **· unsaved** | Agent Hub → Permissions | **Not a state at all** — a local edit you have not saved yet. Reloading the page discards it. Press **💾 Save permissions** before leaving. |\n\nThese used to share the word “pending”, which made unsaved edits look like they had vanished. Agent Hub now says **unsaved** so the two can never be confused.\n\n### 3. Reading traces honestly\n\nA trace's `success` flag means **“a reply was generated”** — it does **not** mean an action happened. A model can write `{\"tool\":\"gateway_send\", …}` as plain **text** (the loop now recovers that into a real call) or skip tools entirely and simply *say* “I have sent it”.\n\nEvery chat trace therefore also carries an **outcome** badge, visible in **Dashboard → Traces**:\n\n| Badge | Meaning |\n|---|---|\n| 💬 **answered — no action taken** | A text reply only; no tool ran |\n| 🔧 **acted — N tool(s)** | One or more tools actually executed |\n| ✅ **action performed — message sent** | `gateway_send` ran and reported success |\n| ⚠️ **unverified claim** | The answer asserted a delivery that **no tool performed** — treat it as NOT done |\n| ❌ / ⏹ | Generation failed / you cancelled the turn |\n\nIf a gateway answer claims a send that never happened, the agent now **appends a correction** (“I could not confirm that message was actually sent…”) instead of leaving a false confirmation standing.\n\n**To be sure a message really went out:** look for the ✅ outcome badge on the trace, or a `✅ sent to …` line in the tool result — never trust the model's prose alone.\n\n---\n\n## CLI Commands\n\n### `agent-nuvira models` — Model Discovery (New in v1.1.0)\n\nList available models from any configured provider. Query each provider's model catalog without leaving the terminal.\n\n```bash\n# List models from the default provider\nagent-nuvira models\n\n# List models from a specific provider\nagent-nuvira models --provider nim\nagent-nuvira models --provider groq\nagent-nuvira models --provider openrouter\n\n# Search for models by keyword\nagent-nuvira models --search deepseek\nagent-nuvira models --search llama\n\n# Show all providers (even unconfigured ones)\nagent-nuvira models --all\n```\n\n**Examples:**\n\n```bash\n# See all models on Groq\nagent-nuvira models --provider groq\n\n# Find DeepSeek models across all configured providers\nagent-nuvira models --search deepseek\n\n# Output:\n# ════════════════════════════════════════════\n# 📋 Available Models (3)\n# ════════════════════════════════════════════\n#\n# Groq:\n# ----------------------------------------\n#   deepseek-ai/deepseek-v4-pro [deepseek]\n#   deepseek-ai/deepseek-v4-flash [deepseek]\n#   deepseek-ai/deepseek-coder-6.7b-instruct [deepseek]\n#\n# ════════════════════════════════════════════\n```\n\nUse a discovered model immediately:\n\n```bash\nagent-nuvira chat --provider groq --model deepseek-ai/deepseek-v4-flash\nagent-nuvira edit src/server.ts --provider openrouter --model openai/gpt-4o\n```\n\n**Model Availability Registry** — the registry is the sub-ms FAISS/JSON store\nrouting reads on every pick. `models status` shows verified / unavailable /\nquota-parked models; `--verbose` adds the two things routing learned from real\nusage: which providers are **registry-blocked** (skipped predictively — with the\nlearned reason for each blocked model) and the **per-action telemetry** (which\naction verified/killed which provider × model):\n\n```bash\n# Show the registry (verified / unavailable / quota-parked)\nagent-nuvira models status\n\n# Same + registry-blocked providers (why routing skips them) + per-action\n# \"learned from real usage\" telemetry (chat/execute/plan/edit verified/killed)\nagent-nuvira models status --verbose\n\n# The dashboard's Models panel charts the same feed per action — scrub across\n# days (drag / click / range slider / ▶ play) to see each day's exact\n# verified vs killed provider × model chips\nagent-nuvira dashboard\n\n# Probe + spot-check now (proactive health, not reactive)\nagent-nuvira models refresh\n# Background maintenance daemon\nagent-nuvira models watch\n\n# Escape hatch: manually release a registry-blocked provider (demotes\n# unavailable → unverified, clears quota parks + ledger cooldown, then\n# re-probes the live API to re-learn the truth — honest stillBlocked output)\nagent-nuvira models unblock gemini\n# Same, but skip the live re-probe (demote + un-park only)\nagent-nuvira models unblock nim --no-spot-check\n# Machine-readable for CI\nagent-nuvira models unblock groq --json\n```\n\n---\n\n### `agent-nuvira chat` — Interactive Chat\n\nStart a terminal-based chat session with any provider.\n\n```bash\n# Interactive mode (default provider)\nagent-nuvira chat\n\n# One-shot prompt\nagent-nuvira chat \"what is the difference between TCP and UDP?\"\n\n# Specify provider and model\nagent-nuvira chat --provider gemini --model gemini-2.0-flash-exp\n\n# Include a file as context\nagent-nuvira chat --file ./src/main.ts \"explain this code\"\n\n# Disable caching\nagent-nuvira chat --no-cache\n```\n\n**Interactive commands** within a chat session:\n\n| Command | Action |\n|---|---|\n| `/exit` or `/quit` | End the session |\n| `/clear` | Clear conversation history |\n| `/info` | Show current provider details |\n| `/help` | Show available commands |\n\n---\n\n### `agent-nuvira edit` — AI-Assisted File Editing\n\nEdit a file using natural language instructions. The AI reads the file, applies your instruction, and writes the result back.\n\n```bash\n# Edit with default instruction (\"Review and improve this code\")\nagent-nuvira edit src/server.ts\n\n# Provide a specific instruction\nagent-nuvira edit src/server.ts --instruction \"add rate limiting middleware\"\n\n# Use a specific provider\nagent-nuvira edit src/server.ts --provider openrouter --model openai/gpt-4o\n\n# Preview changes without modifying the file\nagent-nuvira edit src/server.ts --instruction \"add error handling\" --dry-run\n```\n\n---\n\n### `agent-nuvira plan` — Implementation Plans\n\nAnalyze a directory or file and generate a structured implementation plan.\n\n```bash\n# Plan for the current directory\nagent-nuvira plan\n\n# Plan for a specific target with a task description\nagent-nuvira plan ./src --task \"add user authentication with JWT\"\n\n# Use a cloud provider for complex planning\nagent-nuvira plan . --task \"refactor to microservices\" --provider gemini\n\n# Verbose mode shows the full context sent to the model\nagent-nuvira plan -v\n```\n\nThe plan includes:\n1. **Summary** — high-level overview\n2. **Files to Modify** — specific files and changes\n3. **Architecture Changes** — structural modifications\n4. **Implementation Steps** — ordered guide\n5. **Potential Risks** — edge cases and breaking changes\n6. **Testing Strategy** — verification approach\n\n---\n\n### `agent-nuvira config` — Configuration Management\n\n```bash\n# Show full config\nagent-nuvira config\n\n# Set a value\nagent-nuvira config set defaultProvider openrouter\n\n# Get a specific value\nagent-nuvira config get providers.nim.model\n\n# List all providers with their status\nagent-nuvira config list\n\n# Initialize (show defaults)\nagent-nuvira config init\n```\n\n---\n\n### `agent-nuvira cache` — Cache Management\n\nInference responses are cached in a local SQLite database (`~/.nuvira/cache.db`) with a default TTL of 1 hour.\n\n```bash\n# Show cache statistics\nagent-nuvira cache stats\n\n# Clear all cached responses\nagent-nuvira cache clear\n```\n\n---\n\n### `agent-nuvira model` — Context-Preserving Model Switching\n\nSwitch inference providers and models on the fly without losing conversation history, agent state, or session continuity. The active model persists across CLI restarts.\n\n```bash\n# Show current active model + prompt to switch\nagent-nuvira model\n\n# List all providers with their status\nagent-nuvira model list\n\n# Interactive categorized model picker\n# (choose \"Browse by provider\" to drill into ONE provider's full model list,\n#  e.g. OpenRouter's 100+ models, and pick a specific one)\nagent-nuvira model switch\n\n# Switch to a provider with its default model\nagent-nuvira model switch groq\n\n# Switch to a specific provider/model pair\nagent-nuvira model switch groq/llama-3.3-70b-versatile\n\n# Auto routing — agent decides the best provider/model per task\n# (fast cheap models for simple work, stronger models for complex tasks,\n#  local models for private tasks)\nagent-nuvira model switch auto\n\n# Show detailed active configuration\nagent-nuvira model info\n\n# Get model routing recommendations\nagent-nuvira model recommend\n\n# Explain why Auto routing picks a model for a task (transparency/debugging)\nagent-nuvira model explain \"implement JWT auth with refresh tokens\"\nagent-nuvira model explain                  # walks 5 sample complexities\nagent-nuvira model explain --agent writer \"your task\"\nagent-nuvira model explain \"your task\" --json  # machine-readable (scripting/CI)\n\n# Walk through a narrated decision (the 🎯 fit / 📏 measured / ⏳ ctx chips)\n# → see MODELS_EXPLAIN_DEMO.md for a full annotated example\n\n# Benchmark the exact provider/model pairs the Auto router picks\nagent-nuvira benchmark --routing\n\n# Evaluate the Auto router's picks end-to-end (full multi-agent pipeline + hidden tests)\nagent-nuvira eval --routing\n\n# Every explain snapshot + routing-mode pick is recorded to the dashboard's audit trail\n# (Routing panel → 'Audit Trail — routing decision timeline')\n\n# Quick health check for the active provider\nagent-nuvira model health\n```\n\n**Priority chain:** CLI `--provider`/`--model` flags → `agent-nuvira model switch` active state → default config file — the most specific wins.\n\n#### Learning Router — Thompson-sampling bandit + hard constraints (v1.51.0 Enhanced)\n\nAuto routing can **learn from real outcomes** (ruflo-inspired `model-router` math, generalized to all providers). The routing engine scores providers across 5 weighted dimensions (reasoning, speed, cost, privacy, reliability) with per-complexity weight matrices for all 5 levels.\n\n```bash\n# Enable bandit learning — each provider's score is multiplied by a Beta draw\n# learned per complexity bucket from actual task successes/failures\nagent-nuvira config set routing.bandit true\n\n# Hard per-call budget (USD) — providers whose typical call exceeds this are\n# eliminated, not just scored lower\nagent-nuvira config set routing.maxCostUsd 0.005\n\n# Minimum capability floors for auto-routed tasks (0–1)\nagent-nuvira config set routing.minSpeed 0.5\nagent-nuvira config set routing.minReasoning 0.6\n```\n\n#### How the routing engine works (v1.51.0)\n\n**5 scoring dimensions:** Every provider has a static capability profile (0–1) for reasoning, speed, cost, privacy, reliability. The cost dimension is computed from **real per-1K-token pricing** (free tiers = $0) — configurable via `agent-nuvira config set pricing.<provider>.inputPer1K`.\n\n**5 complexity levels:** The task description is analyzed for keywords to determine complexity (trivial → critical). Each level has a distinct weight matrix that shifts dominance:\n- **Trivial/simple:** cost + speed dominate (fast small model)\n- **Moderate:** balanced\n- **Complex/critical:** reasoning + reliability dominate (deep reasoning with larger model)\n\n**4 preference modes:** `balanced`, `performance-first`, `cost-first`, `privacy-first` — each applies additive weight adjustments that shift the routing decision predictably.\n\n**1. Thompson-sampling bandit** — Each provider keeps a **Beta(α, β) prior per complexity bucket** so learning is task-type-local. Final score = `deterministicScore × θ` where `θ ~ Beta(α, β)`. Cold start `Beta(1,1)` behaves like the plain heuristic router until outcomes accumulate. The orchestrator **records every auto-routed task's outcome** (success/failure) into the bandit. Success rewards are **cost-adjusted** — a cheap provider's success is worth the most. State persists to `~/.nuvira/memory/router-bandit.json`.\n\n**2. Uncertainty-driven escalation** — When the bandit's winner has no learned data (α+β < default 8 samples), routing escalates to the next-ranked provider that HAS learned data with a ≥55% win-rate floor. This prevents a cold-start winner from committing to a coin flip.\n\n**3. Per-modelId learning** — Both provider-level and model-level Beta priors track which concrete model won (e.g., `llama-3.3-70b-versatile` ≠ `openai/gpt-oss-20b` on the same provider). Cold start keeps the configured pin; learned models prefer the best Thompson-sampled one.\n\n**4. Promotion gate A/B** — Every auto-routed task records both the deterministic heuristic pick and the bandit pick for the same task. The `agent-nuvira model bandit` command evaluates 3 criteria (quality improvement >2%, cost regression ≤1%, p95 latency regression ≤5%) before promoting the bandit over the heuristic.\n\n**5. Routing rules** — Regex/string task-pattern rules force a specific provider/model before scoring (first match wins). Rules also note the forced provider for correct bandit outcome attribution.\n\n**6. Hard constraints** — `routing.maxCostUsd`, `routing.minSpeed`, `routing.minReasoning` eliminate violating providers with graceful fallback when constraints would remove everything.\n\n**7. Credential-aware filtering** — Auto routing never picks a provider without configured credentials. The ModelRegistry fast path verifies usable models; explicit `allowedProviders` always win.\n\n**8. Quota-ledger integration** — Exhausted providers sink below healthy ones like circuit-breaker cooldown, only picked when every candidate is parked.\n\n**9. Runtime stats blending** — Benchmark quality scores (30%) + per-agent best-model stats adjust provider capability scores in real time.\n\n**10. Verification-aware escalation** — Verification-heavy tasks (deploy, security audit) boost reasoning+reliability weights and reorder candidates so the strongest provider for verification is tried first.\n\n**11. Free/local-first gate** — `routing.allowPaid: false` keeps paid providers out of trivial/simple/moderate tasks; complex/critical tasks may still use high-capacity models.\n\nInspect and manage the bandit from the CLI:\n\n```bash\n# Show the bandit state (α/β priors + expected win % per provider × complexity bucket)\nagent-nuvira model bandit\n\n# Machine-readable snapshot (priors, expected win rates, learning history)\nagent-nuvira model bandit --json\n\n# Reset all Beta priors back to Beta(1,1)\nagent-nuvira model bandit reset\n```\n\nThe dashboard's 🤖 **Routing** panel shows the same bandit live — an α/β heatmap plus a learning-history timeline (enable `routing.bandit` and run auto-routed tasks to populate it). It also renders a live **🎖️ Promotion Gate** card: an A/B verdict on whether the bandit is actually **better than the deterministic heuristic**, judged on real trajectories (`router-promotion.jsonl`) — quality must improve >2% while cost and latency don't regress.\n\n**Routing rules** — force a specific provider/model for task patterns (regex/string, evaluated before scoring, first match wins):\n\n```jsonc\n// ~/.nuvira/nuvirarc.json\n{\n  \"routing\": {\n    \"bandit\": true,\n    \"maxCostUsd\": 0.005,\n    \"rules\": [\n      { \"name\": \"marketing → groq\", \"pattern\": \"email|sales|copy\", \"provider\": \"groq\" },\n      { \"name\": \"refactor → local\", \"pattern\": \"refactor\", \"provider\": \"local\" }\n    ]\n  }\n}\n```\n\nEvery decision records a `routedBy` source (`heuristic` | `rule` | `bandit`) in the dashboard's routing audit trail so you can see exactly how each pick was produced. The `routedBy` field is also exposed in the `AutoRouteResult` for programmatic access.\n\n#### Auto-mode session failover — providers that die mid-session get swapped automatically\n\nA provider can look healthy at pick time and still fail mid-session: Gemini's\n`token limit exceeded`, OpenRouter 401s, quota exhaustion, or a rate limit on a\nfree tier. In Auto mode, `chat` now **remembers failed providers for the session**\nand routes around them instead of getting stuck:\n\n| Failure kind | Handling |\n|---|---|\n| **Auth** (expired/invalid key, 401) | Provider excluded from Auto routing for the **whole session** — re-picked routes skip it entirely |\n| **Rate limit** (429, quota exceeded, `token limit`, `insufficient_quota`, `resource has been exhausted`) | Provider parked for a **120s cooldown** (aligned with the circuit breaker), then automatically re-admitted |\n| **5xx / network** | Flows through the shared **circuit breaker** (3 failures in 60s → 120s cooldown); never session-excluded |\n\nOn failure the chat loop prints `⚠️ <provider> failed — automatically switching to\n<provider> (<model>)` and transparently re-routes to the next-best candidate.\nIn-cooldown providers are deprioritized by router scoring (via circuit-breaker\nstate), the final fallback always prefers a provider that hasn't failed this\nsession, and the failover path is crash-proof — a throwing re-route can't kill\nthe interactive loop. Works for both streaming and non-streaming responses.\n\n#### Deterministic Tier-0 routing — mechanical edits without an LLM\n\nSimple mechanical edits never touch an LLM (ruflo's `enhanced-model-router` Tier-1 codemod idea, built on agent-nuvira's editing engine):\n\n| Goal pattern | Deterministic transform | Cost |\n|---|---|---|\n| `remove all console.log statements` / `clean up debug logging` | Strips standalone `console.*` lines | **$0 · <1ms** |\n| `rename foo to bar` (symbol present in context) | Word-boundary rename across all references | **$0 · <1ms** |\n| `remove duplicate imports` | Deduplicates same-module import lines | **$0 · <1ms** |\n\n- Runs **before** the LLM in the edit pipeline; every transformed file is **AST-validated** first, so tier-0 never emits broken code.\n- If the goal isn't mechanical (or validation fails), the pipeline **falls through to the LLM** unchanged.\n- Tier-0 results flow through the same safe-apply pipeline (dry-run, sandbox, review bundles) and emit `edit:written` events tagged `via: tier0`.\n- Disable per call with `useTier0: false` in the EditModule API.\n\n#### Central quota ledger — free/local-first routing with reset windows\n\nEvery Auto-routed call is write-through recorded into a **central quota ledger** (tokens/requests per provider × model). The ledger powers four things:\n\n1. **Calendar-aware reset windows** — daily/hourly free-tier limits with automatic re-enable exactly when the window rolls (no arbitrary timers).\n2. **Predictive parking** — a provider that exhausts its window is **parked** and sinks below healthy candidates **before** the next call, not after a reactive failure.\n3. **Free/local-first gate** — `routing.allowPaid: false` keeps paid providers out of trivial/simple/moderate tasks; complex/critical tasks may still use paid high-capacity models.\n4. **Cost transparency** — `agent-nuvira model quota` shows free vs paid tokens and an **estimated $ saved** figure (what the free-tier usage would have cost at a typical paid rate).\n\n```bash\n# Set per-provider quota limits (requests per reset window)\nagent-nuvira config set routing.quota.gemini.requestsPerWindow 1500\nagent-nuvira config set routing.quota.groq.requestsPerWindow 14400\nagent-nuvira config set routing.quota.groq.tokensPerWindow 1000000\nagent-nuvira config set routing.quota.groq.windowMs 86400000   # 24h reset window\n\n# Free/local-only unless complexity demands paid (assessment-gap gate)\nagent-nuvira config set routing.allowPaid false\n\n# Inspect the ledger (tokens/requests per provider × model, resets in, parked state)\n# and the cost summary (free vs paid tokens + estimated $ saved)\nagent-nuvira model quota\n\n# Same data machine-readable (costSummary field) for scripting/CI\nagent-nuvira model quota --json\n\n# Clear all ledger entries\nagent-nuvira model quota reset\n```\n\nThe dashboard's 📒 **Quota Ledger** card shows the same data live — per-entry status plus a free/local-first cost split (free tokens = savings, paid tokens = actual spend) with an estimated $ saved badge.\n\n**Failover timeline (transparency: when failover occurred).** Every park, window-reset re-enable, manual release, and mid-session failover is appended to `~/.nuvira/memory/quota-events.jsonl` (capped at 200). The dashboard's Quota card renders it as a **Failover Timeline**, and `agent-nuvira model quota` prints the last 20 events:\n\n```bash\nagent-n","readmeFilename":"README.md"}