browser-use / jev-ultrafast
git clone https://github.com/browser-use/jev-ultrafast.git
Fastest and cheapest web agent
+61
stars, 24h · #645
+~397
stars, 7 days · #547
+~1.7k
stars, 30 days · #492
24k
★ total · +2% this week
1.8k
forks · 205 open issues
Star history (as recorded here)
LanguagePython
LicenseMIT
Created2026-09-16 (1mo ago)
Last push23d ago
Watchers57
OwnerOrganization
Links
- GitHub: github.com/browser-use/jev-ultrafast
- Homepage: https://browser-use.com
- Releases · Issues · Hacker News mentions
README excerpt
# Jev Ultrafast ⚡ > [!IMPORTANT] > **The Browser Use Cloud waitlist is open.** Get early access to ultrafast browser agents in the cloud. > **Join the waitlist →** **A browser agent with a dynamic, indexed action space.** Give it one goal. TypeSafe's Jev picks an operation and an element. A small LLM writes text only when the operation is `TYPE_TEXT`. **Zürich → London on Google Flights in 7.1 seconds.** One natural-language goal, actual text generation, and loading waits included. Watch the MP4 · Measurements · Read the loop ## The action space Every observation produces a new element table: [code] The operations are `CLICK`, `TYPE_TEXT`, `SELECT`, `SCROLL_UP`, `SCROLL_DOWN`, `WAIT`, `DONE`, and `BLOCKED`. Only supported operations and targets are offered. [code] Target questions are speculative. If the operation is `CLICK`, only `click_target` can execute. Two decisions, **one network round trip**. Each target head contains only compatible elements. Native dropdown choices carry an observed element/option index. There are no site-specific action scripts or prepared field strings in the policy. The Flights example supplies a goal and independently verifies the outcome. The screenshot renderer adds labels afterward; it does not drive the browser. ## Try it [code] Open **http://127.0.0.1:8766** and click **Start demo → Run automatically**. The inspector shows numbered elements, operation probabilities, target probabilities, and executed actions. **Choose next** pauses before execution. Chrome connects through Browser Harness, installed by `uv sync`. Run `uv run browser-harness --doctor` if it needs connecting. Allow remote debugging in Chrome when prompted. `TEXT_MODEL_API_KEY` is an OpenRouter key in the example configuration. The current demo uses `inception/mercury-2.5` with reasoning disabled. Gemini, GLM, and DeepSeek can also use the OpenAI-compatible text helper; configure the appropriate model, endpoint, and reasoning setting. ## Use the library [code] Run with `uv run --env-file .env python your_script.py`. The same policy can run a different task: [code] `uv run --env-file .env python examples/flights.py --keep-open` performs the flight search, checks the actual route/date/results, and saves its trace. It does not select or book a flight. ## Why it moves - **One request per decision cycle.** Operation and target heads share the same observed state. - **No screenshots in the default agent loop.** Jev consumes structured state. The inspector opts into screenshots; the video uses a separate continuous screencast. - **One browser call per snapshot.** Read visible controls, their names, values, and text atomically. Keep references to the actual DOM nodes. - **Validate the selected target.** Clicks check the document, form values, target, and nearby context. Animation alone does not force another prediction. Resolve current geometry and reject covered controls before input. - **Wait for useful state.** After typing into a combobox, w