Jotflow

Chat with local (and remote) LLMs right inside VS Code — LM Studio style. Bring your own models and keys, keep every conversation as a versionable file, and use tools, embedded model management and neural text‑to‑speech without leaving the editor.

Why Jotflow

• 🔒 Local‑first & private — runs against your own LLM (LM Studio, Ollama…), your keys live in VS Code SecretStorage, the managed server binds to 127.0.0.1, and there is no telemetry.
• 🧩 Five backends, one UI — OpenAI‑compatible, Ollama, OpenRouter, Google Gemini and Anthropic Claude, switchable per conversation.
• 📄 Conversations as files — each chat is a human‑readable .chat (config + history) you can diff, version and share.
• 🦙 Models, batteries included — manage an embedded Ollama and browse/download models from the Ollama library (default) or Hugging Face GGUF repos, without installing anything.
• 🔧 Agentic tools — workspace filesystem + MCP servers (function calling) on every backend.
• 🗣️ Read aloud — system voices or self‑contained neural Piper TTS.

Features

Sidebar — Engines · Models · Voices · Dictionary, with a .chat open	Chat with the Reasoning & Tools panels
Per‑conversation settings (⚙) — backend, model, sampling, read‑aloud	Jotflow settings in VS Code

• 💬 Streaming responses, token by token, with a Stop button and auto‑save after each turn.
• 🧠 Reasoning / thinking panel for models that expose it.
• 📊 Markdown + Mermaid in chat bubbles: ```mermaid blocks render as diagrams with a GitHub‑style viewer — pan pad, zoom (pinch / Ctrl·⌘+wheel), fullscreen and copy‑as‑image. The library is lazy‑loaded only when a chat contains a diagram.
• 🦙 Embedded Ollama + model explorer (Ollama library by default, Hugging Face GGUF optional via jotflow.models.source): capability badges, quantization options and downloads with progress (shows size and free disk space first; retry/cancel).
• 🔧 Tools (function calling): native workspace filesystem + MCP servers — agentic loop.
• 🗣️ Read aloud (TTS): system voices (Web Speech) or neural Piper (local, managed daemon).
• 🔎 Find & replace in chat (Ctrl/Cmd+F find · Ctrl/Cmd+H replace), 🔍 zoom (Alt/Option + wheel), 🌳 fork, 🕓 compare versions, ♻️ regenerate / continue / merge / edit / delete messages.
• 🖼️ Attachments (images & documents) and image generation — image‑output models like Gemini flash‑image ("nano‑banana") render their images inline (copy / save to disk).
• 📎 @file mentions in the composer: type @, pick a workspace file, insert its full path.
• 🧾 Export to standalone HTML / PDF.
• 🧮 Context management: auto‑summarize when context fills up, or send only the last N messages — both shown visually in the chat.
• 🌍 6 languages (UI, spell‑check and TTS): English, Spanish, Portuguese, French, German, Italian — switchable live, with a personal spell‑check dictionary per language.

Backends

Configure any of these per conversation (in the ⚙ panel) or as the default in Settings:

Quick start

1. Install Jotflow from the Marketplace.
2. Command palette (Cmd/Ctrl+Shift+P) → “Jotflow: New chat” → choose where to save the .chat file.
3. Pick a backend in the ⚙ panel and start chatting.

Have LM Studio (local server enabled) or Ollama running first — or use a hosted backend (OpenRouter / Gemini / Anthropic) with an API key.

API keys are best stored securely: run “Jotflow: Set API Key (secure)” to keep them in VS Code SecretStorage instead of plain settings.

Local models (embedded Ollama)

Jotflow can manage its own Ollama server without you installing anything:

• The Jotflow sidebar groups everything into sections: Engines (Ollama / Piper, with run/stop/install), Models (local models + downloads), Voices and Dictionary.
• The ＋ button opens an LM Studio‑style explorer. By default it browses the Ollama library; set jotflow.models.source to huggingface to search GGUF repos on Hugging Face instead. It shows capability badges, quantization options and downloads with progress, and renders each model's README (with its benchmarks table) and headline Context / Size.
• Cloud models (e.g. gemma4:cloud, kimi-k2.7-code:cloud) are flagged ☁ and offer Register (pulls a tiny stub, no weights) so you can pick them in chat — inference runs on Ollama Cloud. Set an Ollama API key via “Jotflow: Set API Key” (or jotflow.ollama.apiKey).
• On first use it downloads the Ollama binary (SHA256‑verified, fail‑closed) into your global storage; the server runs only on 127.0.0.1. Configure under Settings → Jotflow → Ollama.

.chat files

Each conversation is a .chat file (human‑readable JSON) storing the inference config + full history. Opening it shows the chat UI; everything is persisted in the file, so it is git‑versionable. A .chat may reference its system prompt from an external .md file (systemPromptFile, confined to the .chat's directory).

Tools (function calling)

With Tools on (⚙, available on every backend), the model can call tools in an agentic loop:

• Workspace filesystem & helpers (native, no setup): fs_list, fs_read, fs_write, fs_glob, fs_search, plus editor_context, web_fetch and get_datetime. File tools are confined to the workspace folder (resolved + realpath‑checked against symlink escape).
• MCP servers: define them in a .mcp/ folder (one *.json per server) or a .mcp.json at the workspace root. Each server's tools are exposed as server__tool.

The loop runs up to jotflow.tools.maxIterations rounds per turn (default 8; 0 = unlimited, ending only when the model stops requesting tools or you press Stop).

MCP servers and fs_write only run in a trusted workspace. Enabling Tools (⚙) in an untrusted folder prompts you to Manage Trust up front, so tools don't fail mid-turn.

Privacy

• Your API keys can be stored in VS Code SecretStorage (not plain settings).
• The managed Ollama server and the Piper TTS daemon bind to 127.0.0.1 only.
• No telemetry — Jotflow does not phone home. Network traffic goes only to the LLM backend you configure and, on demand, to Hugging Face / PyPI to download models and the TTS engine.

Configuration

Settings under Settings → Jotflow:

Third‑party components & licenses

Jotflow is MIT licensed. It bundles or downloads third‑party components under their own terms:

The neural TTS engine (Piper) is GPL and is fetched on demand from PyPI; it is not shipped inside the extension package.

Changelog

See CHANGELOG.md for the release history. 2.1.2 bundles the extension host with esbuild for a smaller, faster package. 2.1.1 is a security hardening pass that clears all GitHub CodeQL alerts (DOM-allowlist HTML sanitizer, Blob-URL images, etc.). 2.1.0 makes the model explorer source configurable (Ollama library by default, Hugging Face optional), adds Ollama cloud models (register + API key) and richer detail pages (README + Context/Size). 2.0.0 is the rebrand from Parley to Jotflow (no functional change; the major bump reflects the new identity and extension ID). The preceding quality passes against BEST-PRACTICES.md still apply: 1.6.0 / 1.6.1 closed a security + reliability audit, and 1.6.2 is a best-practices conformance pass over every source file (module sizes, linting, test coverage) with no behavior change.

Contributing

See ARCHITECTURE.md for a tour of the codebase (extension host ↔ webviews, providers, the agentic loop, local engines, i18n and security) with diagrams. Development conventions are in BEST-PRACTICES.md.

License

Released under the MIT License.