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Robodog

Project description

file: README.md

Robodog MCP File Service

Overview

Robodog is a lightweight, zero-install, command-line style generative AI client that integrates multiple providers (OpenAI, OpenRouter, LlamaAI, DeepSeek, Anthropic, Sarvam AI, Google Search API, and more) into a unified interface. Key capabilities include:

  • Access to cutting-edge models: o4-mini (200k context), gpt-4, gpt-4-turbo, dall-e-3, Llama3-70b, Claude Opus/Sonnet, Mistral, Sarvam-M, Gemma 3n, etc.
  • Massive context windows (up to 200k tokens) across different models.
  • Seamless chat history & knowledge management with stashes and snapshots.
  • File import/export (text, Markdown, code, PDF, images via OCR).
  • In-chat file inclusion from a local MCP server.
  • Built-in web search integration.
  • Image generation & OCR pipelines.
  • AI-driven web automation/testing via Playwright (/play).
  • Raw MCP operations (/mcp).
  • /todo feature: automate and track tasks defined in todo.md.
  • Accessible, retro “console” UI with customizable themes and responsive design.

Try Robodog


Configuration

Click the ⚙️ icon in the top-menu to open settings, or edit your YAML directly:

configs:
  providers:
    - provider: openAI
      baseUrl: "https://api.openai.com"
      apiKey: "<YOUR_OPENAI_KEY>"
    - provider: openRouter
      baseUrl: "https://openrouter.ai/api/v1"
      apiKey: "<YOUR_ROUTER_KEY>"
    - provider: searchAPI
      baseUrl: "https://google-search74.p.rapidapi.com"
      apiKey: "<YOUR_RAPIDAPI_KEY>"

  specialists:
    - specialist: nlp
      resume: natural language processing, content generation
    - specialist: gi
      resume: image generation from text
    - specialist: search
      resume: web search integration

  mcpServer:
    baseUrl: "http://localhost:2500"
    apiKey: "testtoken"

  models:
    - provider: openAI
      model: gpt-4
      stream: true
      specialist: nlp
      about: best for reasoning
    - provider: openAI
      model: o4-mini
      stream: true
      specialist: nlp
      about: 200k token context, advanced reasoning
    - provider: openAI
      model: dall-e-3
      stream: false
      specialist: gi
      about: image creation
    - provider: searchAPI
      model: search
      stream: false
      specialist: search
      about: web search results

Supported Models

OpenAI

  • gpt-4, gpt-4-turbo, gpt-3.5-turbo, gpt-3.5-turbo-16k, o4-mini, o1
  • dall-e-3

Others

  • LlamaAI: llama3-70b
  • Anthropic: Claude Opus 4, Claude Sonnet 4
  • DeepSeek R1
  • Mistral Medium 3, Devstral-Small
  • Sarvam-M
  • Google Gemma 3n E4B

Key Features

  • Multi-Provider Support: Switch between any configured provider or model on the fly (/model).
  • Chat & Knowledge: Separate panes for Chat History (💭) and Knowledge (📝)—both resizable.
  • Stash Management:
    • /stash <name> — save current chat+knowledge
    • /pop <name> — restore a stash
    • /list — list all stashes
  • File Import/Export:
    • /import <glob> — import files (.md, .js, .py, .pdf, images via OCR)
    • /export <file> — export chat+knowledge snapshot
  • MCP File Inclusion:
    • /include all
    • /include file=README.md
    • /include pattern=*.js|*.css recursive
    • /include dir=src pattern=*.py recursive
  • Raw MCP Operations:
    • /mcp OP [JSON] — e.g. /mcp LIST_FILES, /mcp READ_FILE {"path":"./foo.py"}
  • Web Fetch & Automation:
    • /curl [--no-headless] <url> [<url2>|<js>] — fetch pages or run JS
    • /play <instructions> — run AI-driven Playwright tests end-to-end
  • Web Search:
    • Use search model or click 🔎 to perform live web queries.
  • Image Generation & OCR: Ask questions to dall-e-3 or drop an image to extract text via OCR.
  • Interactive Console UI: Retro “pip-boy green” theme, responsive on desktop/mobile, accessible.
  • Performance & Size Indicators: Emoji feedback for processing speed and token usage.
  • Extensive Command Palette: /help lists all commands, indicators, and settings.
  • Todo Automation: Use /todo to execute tasks defined in todo.md across your project roots.

Usage Examples

1) AI-Driven Web Tests with /play

/play navigate to https://example.com, extract the page title, and verify it contains 'Example Domain'

2) Fetch & Scrape with /curl

/curl https://example.com

3) Include Local Files via MCP

/include pattern=*.js recursive fix bug in parser

4) Raw MCP Commands

/mcp LIST_FILES
/mcp READ_FILE {"path":"./src/cli.py"}

5) Switch Model on the Fly

/model o4-mini

6) Import & Export

/import **/*.md
/export conversation_snapshot.txt

/todo Feature

Robodog’s /todo command scans one or more todo.md files in your configured project roots, detects tasks marked [ ], transitions them to [~] (Doing) when started, and [x] (Done) when completed. Each task may include:

  • include: pattern or file specification to gather relevant knowledge
  • focus: file path where the AI will write or update content
  • Optional code fences below the task as initial context

You can have multiple todo.md files anywhere under your roots. /todo processes the earliest outstanding task, runs the AI with gathered knowledge, updates the focus file, stamps start/completion times, and advances to the next.

Robodog MCP File Service

Example todo.md File Formats

file: project1/todo.md

  • Revise API client
    • include: pattern=api/*.js recursive
    • focus: file=api/client.js
    // existing stub
    
  • Add unit tests
    • include: file=tests/template.spec.js
    • focus: file=tests/api.client.spec.js

file: project2/docs/todo.md

  • Update README
    • focus: file=README.md
  • Generate changelog
    • include: pattern=CHANGELOG*.md
    • focus: file=CHANGELOG.md

todo readme

  • readme
    • include: pattern=robodog.md|robodog.py|*todo.md recursive`
    • focus: file=c:\projects\robodog\robodogcli\temp\service.log
1. do not remove any content
2. add a new readme section for the /todo feature with examples of the todo.md files and how you can have as many as possible
3. give lots of exampkes of file formats

watch

  • change app prints in service logger.INFO
    • include: pattern=robodog.md|robodog.py recursive`
    • focus: file=c:\projects\robodog\robodogcli\robodog\cli3.py
do not remove any features.
give me full drop in code file

fix logging

  • ask: fix logging. change logging so that it gets log level through command line. change logger so that it takes log level from the command line param
    • include: pattern=robodog.md|robodog.py recursive`
    • focus: file=c:\projects\robodog\robodogcli\robodog\cli3.py
my knowledge

You can chain as many tasks and files as needed. Each can reside in different directories, and Robodog will locate all todo.md files automatically.

Configuration & Command Reference

See command palette in-app (/help) or the reference below:

/help             — show help  
/models           — list configured models  
/model <name>     — switch model  
/key <prov> <key> — set API key  
/import <glob>    — import files into knowledge  
/export <file>    — export snapshot  
/clear            — clear chat & knowledge  
/stash <name>     — stash state  
/pop <name>       — restore stash  
/list             — list stashes  
/temperature <n>  — set temperature  
/top_p <n>        — set top_p  
/max_tokens <n>   — set max_tokens  
/frequency_penalty <n> — set frequency_penalty  
/presence_penalty <n>  — set presence_penalty  
/stream           — enable streaming mode  
/rest             — disable streaming mode  
/folders <dirs>   — set MCP roots  
/include …        — include files via MCP  
/curl …           — fetch pages / run JS  
/play …           — AI-driven Playwright tests  
/mcp …            — invoke raw MCP operation  
/todo             — run next To Do task  

Build & Run

# Clone or unzip robodog
cd robodog
python build.py
open ./dist/robodog.html
npm install robodoglib  
npm install robodogcli  
npm install robodog  
pip install robodogcli  
pip show -f robodogcli  
python -m robodogcli.cli --help  
python -m playwright install

Enjoy Robodog AI—the future of fast, contextual, and extensible AI interaction!

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