base on Browse the web with GPT-4V and Vimium # vimGPT Giving multimodal models an interface to play with. https://github.com/ishan0102/vimGPT/assets/47067154/467be2ac-7e8d-47de-af89-5bb6f51c1c31 ## Overview LLMs as a way to browse the web is being explored by numerous startups and open-source projects. With this project, I was interested in seeing if we could only use [GPT-4V](https://openai.com/research/gpt-4v-system-card)'s vision capabilities for web browsing. The issue with this is it's hard to determine what the model wants to click on without giving it the browser DOM as text. [Vimium](https://vimium.github.io/) is a Chrome extension that lets you navigate the web with only your keyboard. I thought it would be interesting to see if we could use Vimium to give the model a way to interact with the web. ## Usage Install Python requirements: ``` pip install -r requirements.txt ``` Download Vimium locally (have to load the extension manually when running Playwright): ``` ./setup.sh ``` Run the script: ``` python main.py ``` ## Voice Mode Voice Mode: Engage with the browser using voice commands. Simply say your objective, and watch vimGPT perform actions in real-time. ``` python main.py --voice ``` ## Ideas Feel free to collaborate with me on this, I have a number of ideas: - Use [Assistant API](https://platform.openai.com/docs/assistants/overview) once it's released for automatic context retrieval. The Assistant API will create a thread that we can add messages too, to keep the history of actions, but it doesn't support the Vision API yet. - Vimium fork for overlaying elements. A specialized version of Vimium that selectively overlays elements based on context could be useful, effectively pruning based on the user query. Might be worth testing if different sized boxes/colors help. - Use higher resolution images, as it seems to fail at low res. I noticed that below a certain threshold, the model wouldn't detect anything. This might be improved by using higher resolution images but that would require more tokens. - Fine-tune [LLaVa](https://github.com/haotian-liu/LLaVA) or [CogVLM](https://github.com/THUDM/CogVLM) to do this or [Fuyu-8B](https://www.adept.ai/blog/fuyu-8b). Could be faster/cheaper. CogVLM can accurately specify pixel coordinates which may be a good way to augment this. - Use JSON mode once it's released for Vision API. Currently the Vision API doesn't support JSON mode or function calling, so we have to rely on more primitive prompting methods. - Have the Vision API return general instructions, formalized by another call to the JSON mode version of the API. This is a workaround for the JSON mode issue but requires another LLM call, which is slower/more expensive. - Add speech-to-text with Whisper or another model to eliminate text input and make this more accessible. - Make this work for your own browser instead of spinning up an artificial one. I want to be able to order food with my credit card. - Provide the frames with and without Vimium enabled in case the model can't see what's under the yellow square. - Pass the Chrome accessibility tree in as input in addition to the image. This provides a layout of interactive elements that can be mapped to the Vimium bindings. - Have it write longer things based on the context of the page or return information to the user based on the query. Examples are replying to an email, summarizing a news article, etc. Visual question answering. - Make this a useful tool for blind people by adding voice mode and a key that creates an Assistant API for a given page. Something where you can "speak to an agent" about a page content in natural language. - Use Javascript to label DOM elements with colored boxes, similar to [this](https://x.com/DivGarg9/status/1659270501498523648?s=20). - Build a graph-based retry mechanism that makes sure we aren't falling into cycles, i.e. recursively clicking on the same element. ## Shoutouts - HackerNews: https://news.ycombinator.com/item?id=38200308 - VisualWebArena - Evaluating Multimodal Agents on Realistic Visual Web Tasks (page 9): https://arxiv.org/abs/2401.13649 - WIRED: https://www.wired.com/story/fast-forward-tested-next-gen-ai-assistant/ ## References - https://github.com/Globe-Engineer/globot - https://github.com/nat/natbot ", Assign "at most 3 tags" to the expected json: {"id":"4811","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"