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Browser automation with decision models

Choosing the next browser operation and target element from page state, with a small text model writing input only when needed. Covers web agents, scraping flows and browser testing.

120 public projects · page 4 of 4

  • Reproducible evaluation harness and field note for the Jev Ultrafast research browser, with QC-graded baseline and stress suites.

    ProjectresearchPython
  • Open 2B browser-agent decision model fine-tuned from MiniCPM5 that serves the System One protocol for jev-ultrafast.

    ProjectresearchPython
  • Pre-action gate and browser agent where rules decide first, then Jev or a local Jev-compatible model, emitting allow, confirm or block.

    ServiceresearchPython
  • jev-social★ 169

    Local social research agent: Jev picks each bounded Instagram, TikTok or LinkedIn step and socai CLI runs it in your Chrome.

    CLIbetaTypeScript
  • Browser extension and MCP server where Aside observes the page and Jev picks the next action from defined candidates.

    MCP serverbetaTypeScript
  • Python library for typed decisions with Jev or your own provider, adding validated distributions, batching, budgets, ranking and records.

    LibrarybetaPython
  • Playwright plus Jev core behind a typed SDK, persistent CLI and MCP server, with native operations needing no key and verifiable assertions.

    MCP serverbetaTypeScript
  • Library, CLI and MCP server where an LLM states each step's outcome and Jev decides element, action, value and done/blocked/irreversible.

    MCP serverbetaTypeScript
  • Reproducible bake-off of Playwright CLI alone, CLI plus Jev, and Playwright MCP on fuzzy browser goals, with honest results.

    MCP serverresearchPython
  • Zero-build local playground for Jev with browser-agent, intent routing and context-pruning presets, including a Playwright agent.

    AppbetaJavaScript
  • Evidence-driven frontend QA where Jev picks browser actions while code checks DOM, HTTP and database contracts.

    AppbetaPython
  • Browser agent that acts on one look at the page with one open-model call per action; Jev is an optional chooser backend.

    AppprototypePython
  • Coding-agent skill that drives Chrome over CDP to hunt for jobs on company sites, with Jev scoring every link and job posting.

    Agent skillprototypePython
  • OpenJev 1.7B-8B: open decision models distilled for general decisions and browser-agent steps, served behind /v1/systemone.

    ModelbetaPython
  • OpenJev on Hugging Face: open-weights decision model for text, web pages and screenshots with up to 52 options per forward pass.

    ServicebetaPython
  • Open 2B non-autoregressive decision model on Qwen3.5-2B for agent tool routing and DOM actions, with BF16, FP8 and INT8 weights.

    ModelresearchPython
  • 706K-parameter Jev-style option scorer that rates fill, check, click or skip for each form element in one parallel pass.

    ModelresearchPython
  • Open stack to synthesise decision data, train and calibrate a Qwen3.5-0.8B scorer, evaluate on Mind2Web and serve Jev-style.

    ServiceresearchPython
  • Open Apache-2.0 browser-agent decision model (Qwen3.5-35B-A3B fine-tune) that doubled Jev 1.13's task success in the same agent.

    ServiceresearchPython
  • Browser driver where Jev makes every decision and agent-browser performs every action, benchmarked against Claude Code on 10 tasks.

    BenchmarkbetaTypeScript
  • Jev-powered browser MCP server that makes each step in one parallel call and escalates to the driving LLM only when unsure.

    BenchmarkbetaTypeScript
  • Browser and macOS desktop agent for Pi where Jev picks each action from a structured text observation in a bounded loop.

    BenchmarkbetaTypeScript
  • Single-file, zero-dependency port of jev-ultrafast to Ego Lite: one typed-choice Jev request per browser step, with extra guardrails.

    BenchmarkprototypeJavaScript
  • Runs jev-browser entirely on a local Jev-style engine (Qwen2.5 1.5B decisions, 0.5B typing) on an RTX 2060 SUPER, with no cloud API.

    BenchmarkprototypePython, TypeScript
  • Browser-agent benchmark comparing WebMCP with screenshots, DOM and code execution, including a Jev + Mercury 2.5 configuration.

    Benchmarkresearch
  • Drives ego-browser pages with Jev: code builds the allowed actions, Jev picks one, and code acts and re-checks.

    Project
  • X preview of fast browser automation using Jev with OpenCode's browser CLI.

    Discussiondiscussion
  • X post claiming Playwright CLI with Jev choosing each step was 98% cheaper and twice as fast as the Playwright MCP.

    Discussiondiscussion
  • X post where the accessibility tree is the state, candidate actions are the options, Jev picks each step and Stagehand executes.

    Discussiondiscussion
  • X demo where Jev picks which candidate link to click on a page to move toward a goal.

    Discussiondiscussion