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Jam — developer-first AI assistant CLI for the terminal. Ask questions, explain code, review diffs, generate patches, and run agentic tasks powered by Ollama.

Package Exports

    This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (@sunilp-org/jam-cli) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

    Readme

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    │   developer-first  AI  CLI        │
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    Jam CLI

    The developer-first AI assistant for the terminal.

    CI License: MIT Node.js 20+ PRs Welcome Conventional Commits

    Ask questions • Explain code • Review diffs • Generate patches • Run agentic tasks

    All from your command line, powered by any Ollama-hosted model.

    Getting Started · Commands · Configuration · Contributing · Security


    Why Jam?

    Most AI coding tools are built around a single vendor's model, require a browser or IDE plugin, and send your code to a remote server you don't control.

    Jam is different by design:

    • It runs entirely on your machine by default — your code never leaves your filesystem
    • It is not tied to any single model or provider — you choose the engine; Jam is the harness
    • It behaves like a proper Unix tool — pipeable, composable, and scriptable
    • It treats code modification as a transaction — validate first, preview always, confirm before applying
    • It is built to be contributed to — clean TypeScript, well-tested, architecture documented below

    Highlights

    Feature Description
    Streaming output Responses begin rendering on the first token
    💬 Interactive chat Multi-turn sessions with history and resume
    📂 Repo-aware Explain files, search code, review diffs with full workspace context
    🩹 Patch workflow Generate unified diffs, validate, preview, and apply with confirmation
    🤖 Tool-calling agent jam run gives the model access to local tools (read, search, diff, apply)
    🔌 Pluggable providers Ollama by default; adapter pattern for adding any LLM
    ⚙️ Layered config Global → repo → CLI flags; multiple named profiles
    🔐 Secure secrets OS keychain via keytar, env var fallback
    🐚 Shell completions Bash and Zsh
    🏠 Privacy-first Runs locally — your code never leaves your machine

    Design Philosophy

    The best developer tools disappear into your workflow. They don't ask you to change how you work — they work the way you already do.

    You own the model. Jam's ProviderAdapter is a clean interface — swap the AI engine with a config change, not a rewrite. No vendor lock-in, no model loyalty.

    Your code stays private. The default is localhost. Nothing leaves your machine unless you explicitly point Jam at a remote provider. This isn't just a feature — it's the architecture.

    Changes are transactions, not actions. jam patch validates with git apply --check before anything is touched, shows a full preview, and waits for explicit confirmation. No "undo" needed — changes never happen without your approval.

    Unix composability. jam ask reads stdin, writes stdout, supports --json. It's a pipe stage, not a walled garden.

    Security is configuration, not hope. Tool permissions (toolPolicy), allowed operations (toolAllowlist), and log redaction (redactPatterns) are declarative config — committable to .jamrc so your whole team inherits the same guardrails.


    Who Is Jam For?

    Situation Why Jam fits
    You work in a security-sensitive codebase Local-only by default — nothing leaves your machine
    You want to use different models for different tasks Named profiles + provider adapter — switch with --profile
    You live in the terminal and resent leaving it Every command is designed for the shell, not a browser tab
    You're on a corporate network that blocks AI services Point baseUrl at an internal Ollama instance and you're done
    You want an AI tool that fits into CI/CD scripts --json output, stdin support, non-zero exit codes on errors
    You want to contribute to an AI tool without fighting vendor APIs The hard parts (streaming, tool-calling, config) are already built cleanly

    Quick Start

    Prerequisites

    • Node.js 20+
    • Ollama running locally (ollama serve)
    • A pulled model: ollama pull llama3.2

    Install

    # Global install (once published to npm)
    npm install -g jam-cli
    
    # Or run from source
    git clone https://github.com/sunilp/jam-cli.git
    cd jam-cli
    npm install
    npm run build
    npm link          # makes `jam` available globally

    Verify

    jam doctor        # checks Node version, config, provider connectivity, ripgrep
    jam auth login    # validates connection to Ollama

    Commands

    jam ask

    One-shot question. Streams the response to stdout.

    jam ask "What is the difference between TCP and UDP?"
    
    # From stdin
    echo "Explain recursion in one paragraph" | jam ask
    
    # From a file
    jam ask --file prompt.txt
    
    # JSON output (full response + token usage)
    jam ask "What is 2+2?" --json
    
    # Override model
    jam ask "Hello" --model codellama
    
    # Use a named profile
    jam ask "Hello" --profile work

    Options:

    Flag Description
    --file <path> Read prompt from file
    --system <prompt> Override system prompt
    --json Machine-readable JSON output
    --model <id> Override model for this request
    --provider <name> Override provider
    --base-url <url> Override provider base URL
    --profile <name> Use a named config profile
    --no-color Strip ANSI colors from output

    jam chat

    Interactive multi-turn chat REPL (Ink/React TUI).

    jam chat                         # new session
    jam chat --name "auth refactor"  # named session
    jam chat --resume <sessionId>    # resume a previous session

    Keyboard shortcuts inside chat:

    Key Action
    Enter Submit message
    Ctrl-C (once) Interrupt current generation
    Ctrl-C (twice) Exit chat

    Sessions are saved automatically to ~/.local/share/jam/sessions/ (macOS: ~/Library/Application Support/jam/sessions/).


    jam explain

    Read one or more files and ask the model to explain them.

    jam explain src/auth/middleware.ts
    jam explain src/api/routes.ts src/api/handlers.ts
    jam explain src/utils/retry.ts --json

    Search the codebase using ripgrep (falls back to JS if rg is not installed).

    jam search "TODO"                          # plain search, prints results
    jam search "useEffect" --glob "*.tsx"      # filter by file type
    jam search "createServer" --ask            # pipe results to AI for explanation
    jam search "error handling" --max-results 50

    Options:

    Flag Description
    --glob <pattern> Limit to files matching this glob (e.g. *.ts)
    --max-results <n> Max results (default: 20)
    --ask Send results to AI for analysis
    --json JSON output (with --ask)

    jam diff

    Run git diff and optionally review it with AI.

    jam diff                    # review working tree changes
    jam diff --staged           # review staged changes (ready to commit)
    jam diff --path src/api/    # limit to a specific directory
    jam diff --no-review        # just print the raw diff, no AI
    jam diff --staged --json    # JSON output

    jam patch

    Ask the AI to generate a unified diff patch, validate it, and optionally apply it.

    jam patch "Add input validation to the login function"
    jam patch "Fix the off-by-one error in pagination" --file src/api/paginate.ts
    jam patch "Add JSDoc comments to all public methods" --dry   # generate only, don't apply
    jam patch "Remove unused imports" --yes                      # auto-confirm apply

    Flow:

    1. Collects context (git status, current diff, specified files)
    2. Prompts the model for a unified diff
    3. Validates with git apply --check
    4. Shows the patch preview
    5. Asks for confirmation (unless --yes)
    6. Applies with git apply

    jam run

    Agentic task workflow — the model can call tools in a loop to accomplish a goal.

    jam run "Find all TODO comments and summarize them"
    jam run "Check git status and explain what's changed"
    jam run "Read src/config.ts and identify any security issues"

    Available tools (model-callable):

    Tool Type Description
    read_file Read Read file contents
    list_dir Read List directory contents
    search_text Read Search codebase with ripgrep
    git_status Read Get git status
    git_diff Read Get git diff
    write_file Write Write to a file (prompts for confirmation)
    apply_patch Write Apply a unified diff (prompts for confirmation)

    Write tools require confirmation unless toolPolicy is set to allowlist in config.


    jam auth

    jam auth login    # validate connectivity to the current provider
    jam auth logout   # remove stored credentials from keychain

    jam config

    jam config show            # print merged effective config as JSON
    jam config init            # create .jam/config.json in the current directory
    jam config init --global   # create ~/.config/jam/config.json

    jam models list

    jam models list            # list models available from the current provider
    jam models list --provider ollama --base-url http://localhost:11434

    jam history

    jam history list           # list all saved chat sessions
    jam history show <id>      # show all messages in a session (first 8 chars of ID work)

    jam completion install

    jam completion install                    # auto-detects shell
    jam completion install --shell bash       # bash completion script
    jam completion install --shell zsh        # zsh completion script

    Follow the printed instructions to add the completion to your shell.


    jam doctor

    Run system diagnostics:

    jam doctor

    Checks:

    • Node.js version (≥ 20)
    • Config file is valid
    • Provider connectivity (Ollama reachable)
    • ripgrep availability (optional, JS fallback used if absent)
    • keytar availability (optional, env vars used if absent)

    Configuration

    Config File Locations

    Jam merges config in priority order (highest wins):

    1. CLI flags
    2. .jam/config.json  or  .jamrc  (repo-level)
    3. ~/.config/jam/config.json     (user-level)
    4. Built-in defaults

    Config Schema

    {
      "defaultProfile": "default",
      "profiles": {
        "default": {
          "provider": "ollama",
          "model": "llama3.2",
          "baseUrl": "http://localhost:11434",
          "temperature": 0.7,
          "maxTokens": 4096,
          "systemPrompt": "You are a helpful coding assistant."
        },
        "fast": {
          "provider": "ollama",
          "model": "qwen2.5-coder:1.5b",
          "baseUrl": "http://localhost:11434"
        }
      },
      "toolPolicy": "ask_every_time",
      "toolAllowlist": [],
      "historyEnabled": true,
      "logLevel": "warn",
      "redactPatterns": ["sk-[a-z0-9]+", "Bearer\\s+\\S+"]
    }

    Config Fields

    Field Type Default Description
    defaultProfile string "default" Active profile name
    profiles object see below Named provider/model configurations
    toolPolicy ask_every_time | allowlist | never ask_every_time How write tools require confirmation
    toolAllowlist string[] [] Tools that never prompt (when policy is allowlist)
    historyEnabled boolean true Save chat sessions to disk
    logLevel silent | error | warn | info | debug warn Log verbosity
    redactPatterns string[] [] Regex patterns redacted from logs

    Profile Fields

    Field Type Description
    provider string Provider name (ollama)
    model string Model ID (e.g. llama3.2, codellama)
    baseUrl string Provider API base URL
    apiKey string API key (prefer keychain or env vars)
    temperature number Sampling temperature (0–2)
    maxTokens number Max tokens in response
    systemPrompt string Default system prompt

    Initialize Config

    # Repo-level (committed to version control)
    jam config init
    
    # User-level (applies everywhere)
    jam config init --global

    Using Profiles

    # Use a specific profile
    jam ask "Hello" --profile fast
    
    # Switch default in config
    echo '{"defaultProfile": "fast"}' > .jamrc

    Environment Variables

    Variable Description
    JAM_API_KEY API key fallback (if keytar unavailable)
    JAM_BASE_URL Override provider base URL

    Development

    npm run dev -- ask "What is 2+2?"   # run from source with tsx
    npm run build                         # compile TypeScript to dist/
    npm run typecheck                     # tsc --noEmit
    npm run lint                          # ESLint
    npm test                              # Vitest unit tests
    npm run test:watch                    # watch mode
    npm run test:coverage                 # coverage report

    Project Structure

    src/
    ├── index.ts              # CLI entry point (commander, lazy imports)
    ├── commands/             # One file per command
    │   ├── ask.ts            # jam ask
    │   ├── chat.ts           # jam chat
    │   ├── run.ts            # jam run (agentic loop)
    │   ├── explain.ts        # jam explain
    │   ├── search.ts         # jam search
    │   ├── diff.ts           # jam diff
    │   ├── patch.ts          # jam patch
    │   ├── auth.ts           # jam auth
    │   ├── config.ts         # jam config
    │   ├── models.ts         # jam models
    │   ├── history.ts        # jam history
    │   ├── completion.ts     # jam completion
    │   └── doctor.ts         # jam doctor
    ├── providers/            # LLM adapter layer
    │   ├── base.ts           # ProviderAdapter interface
    │   ├── ollama.ts         # Ollama adapter (NDJSON streaming)
    │   └── factory.ts        # createProvider()
    ├── tools/                # Model-callable local tools
    │   ├── types.ts          # ToolDefinition, ToolResult interfaces
    │   ├── registry.ts       # ToolRegistry + permission enforcement
    │   ├── read_file.ts
    │   ├── list_dir.ts
    │   ├── search_text.ts
    │   ├── git_diff.ts
    │   ├── git_status.ts
    │   ├── apply_patch.ts
    │   └── write_file.ts
    ├── config/               # Config loading and schema
    │   ├── schema.ts         # Zod schema
    │   ├── defaults.ts       # Built-in defaults
    │   └── loader.ts         # cosmiconfig + deep merge
    ├── storage/
    │   └── history.ts        # Chat session persistence (JSON files)
    ├── ui/
    │   ├── chat.tsx          # Ink chat REPL (React TUI)
    │   └── renderer.ts       # Markdown + streaming renderer
    └── utils/
        ├── errors.ts         # JamError class
        ├── stream.ts         # withRetry, collectStream
        ├── logger.ts         # Logger (stderr, redaction)
        ├── secrets.ts        # keytar + env fallback
        └── workspace.ts      # Git root detection

    Adding a New Provider

    1. Implement ProviderAdapter from src/providers/base.ts:
    import type { ProviderAdapter, ProviderInfo, CompletionRequest, StreamChunk } from './base.js';
    
    export class MyProvider implements ProviderAdapter {
      readonly info: ProviderInfo = { name: 'myprovider', supportsStreaming: true };
    
      async validateCredentials(): Promise<void> { /* ... */ }
      async listModels(): Promise<string[]> { /* ... */ }
      async *streamCompletion(request: CompletionRequest): AsyncIterable<StreamChunk> { /* ... */ }
    }
    1. Register in src/providers/factory.ts:
    if (provider === 'myprovider') {
      const { MyProvider } = await import('./myprovider.js');
      return new MyProvider({ apiKey: profile.apiKey });
    }
    1. Use: jam ask "Hello" --provider myprovider

    Contributing

    Jam is intentionally built to be easy to extend. The architecture is layered, each concern is isolated, and the three main contribution surfaces — providers, tools, and commands — each have a clean interface to implement.

    You don't need to understand the whole codebase to contribute. A new provider is one file. A new tool is one file. The patterns are already established and documented.

    1. Fork the repository
    2. Create your feature branch (git checkout -b feat/amazing-feature)
    3. Commit your changes (git commit -m 'feat: add amazing feature')
    4. Push to the branch (git push origin feat/amazing-feature)
    5. Open a Pull Request

    Please read our Contributing Guide for details on our code of conduct, development workflow, and pull request process.

    Good First Issues

    Look for issues labeled good first issue — these are great starting points for new contributors.

    What the Codebase Looks Like

    • Strict TypeScript throughout — no any, no guessing what a function does
    • Tests colocated with sourcefoo.tsfoo.test.ts, using Vitest
    • One file per concern — each command, provider, and tool is self-contained
    • Zod schema validation — config is validated at load time, not at runtime when it's too late
    • Conventional Commits — the git log tells the story of the project

    If you can read TypeScript, you can contribute to Jam.


    Community


    Security Policy

    We take security seriously. If you discover a vulnerability, please do not open a public issue. Instead, follow the responsible disclosure process in our Security Policy.


    Roadmap

    • OpenAI / Azure OpenAI provider
    • Anthropic Claude provider
    • Groq provider
    • jam commit — AI-generated commit messages
    • jam review — PR review workflow
    • Plugin system for custom tools
    • Token usage tracking and budgets
    • Web UI companion

    Acknowledgments

    Built with these excellent open source projects:


    License

    MIT License — Copyright (c) 2026-present Sunil Prakash. All rights reserved.

    See LICENSE for the full license text.


    Made with ❤️ by Sunil Prakash

    If you find Jam useful, consider giving it a ⭐ on GitHub — it helps others discover the project!