diff --git a/.nojekyll b/.nojekyll new file mode 100644 index 000000000..e69de29bb diff --git a/404.html b/404.html new file mode 100644 index 000000000..dff23c597 --- /dev/null +++ b/404.html @@ -0,0 +1,439 @@ + + + +
+ + + + + + + + + + + + + + +The DEFAULT_NUM_CTX
environment variable can be used to limit the maximum number of context values used by the qwen2.5-coder model. For example, to limit the context to 24576 values (which uses 32GB of VRAM), set DEFAULT_NUM_CTX=24576
in your .env.local
file.
First off, thank you for considering contributing to Bolt.new! This fork aims to expand the capabilities of the original project by integrating multiple LLM providers and enhancing functionality. Every contribution helps make Bolt.new a better tool for developers worldwide.
+This project and everyone participating in it is governed by our Code of Conduct. By participating, you are expected to uphold this code. Please report unacceptable behavior to the project maintainers.
+We're looking for dedicated contributors to help maintain and grow this project. If you're interested in becoming a core contributor, please fill out our Contributor Application Form.
+Clone the repository: +
+Install dependencies: +
+Set up environment variables:
+.env.example
to .env.local
Optionally set debug level: +
+Optionally set context size: +
+Some Example Context Values for the qwen2.5-coder:32b models are.
+Important: Never commit your .env.local
file to version control. It's already included in .gitignore.
Note: You will need Google Chrome Canary to run this locally if you use Chrome! It's an easy install and a good browser for web development anyway.
+Run the test suite with:
+ +To deploy the application to Cloudflare Pages:
+ +Make sure you have the necessary permissions and Wrangler is correctly configured for your Cloudflare account.
+This guide outlines various methods for building and deploying the application using Docker.
+NPM scripts are provided for convenient building:
+ +You can use Docker's target feature to specify the build environment:
+# Development build
+docker build . --target bolt-ai-development
+
+# Production build
+docker build . --target bolt-ai-production
+
Use Docker Compose profiles to manage different environments:
+# Development environment
+docker-compose --profile development up
+
+# Production environment
+docker-compose --profile production up
+
After building using any of the methods above, run the container with:
+# Development
+docker run -p 5173:5173 --env-file .env.local bolt-ai:development
+
+# Production
+docker run -p 5173:5173 --env-file .env.local bolt-ai:production
+
Coolify provides a straightforward deployment process:
+The docker-compose.yaml
configuration is compatible with VS Code dev containers:
Ensure you have the appropriate .env.local
file configured before running the containers. This file should contain:
+- API keys
+- Environment-specific configurations
+- Other required environment variables
.env.local
Be specific about your stack: If you want to use specific frameworks or libraries (like Astro, Tailwind, ShadCN, or any other popular JavaScript framework), mention them in your initial prompt to ensure Bolt scaffolds the project accordingly.
+Use the enhance prompt icon: Before sending your prompt, try clicking the 'enhance' icon to have the AI model help you refine your prompt, then edit the results before submitting.
+Scaffold the basics first, then add features: Make sure the basic structure of your application is in place before diving into more advanced functionality. This helps oTToDev understand the foundation of your project and ensure everything is wired up right before building out more advanced functionality.
+Batch simple instructions: Save time by combining simple instructions into one message. For example, you can ask oTToDev to change the color scheme, add mobile responsiveness, and restart the dev server, all in one go saving you time and reducing API credit consumption significantly.
+Please check out our dedicated page for contributing to oTToDev here!
+More news coming on this coming early next month - stay tuned!
+Lot more updates to this roadmap coming soon!
+oTToDev was started simply to showcase how to edit an open source project and to do something cool with local LLMs on my (@ColeMedin) YouTube channel! However, it quickly +grew into a massive community project that I am working hard to keep up with the demand of by forming a team of maintainers and getting as many people involved as I can. +That effort is going well and all of our maintainers are ABSOLUTE rockstars, but it still takes time to organize everything so we can efficiently get through all +the issues and PRs. But rest assured, we are working hard and even working on some partnerships behind the scenes to really help this project take off!
+As much as the gap is quickly closing between open source and massive close source models, you’re still going to get the best results with the very large models like GPT-4o, Claude 3.5 Sonnet, and DeepSeek Coder V2 236b. This is one of the big tasks we have at hand - figuring out how to prompt better, use agents, and improve the platform as a whole to make it work better for even the smaller local LLMs!
+If you see this error within oTToDev, that is just the application telling you there is a problem at a high level, and this could mean a number of different things. To find the actual error, please check BOTH the terminal where you started the application (with Docker or pnpm) and the developer console in the browser. For most browsers, you can access the developer console by pressing F12 or right clicking anywhere in the browser and selecting “Inspect”. Then go to the “console” tab in the top right.
+We have seen this error a couple times and for some reason just restarting the Docker container has fixed it. This seems to be Ollama specific. Another thing to try is try to run oTToDev with Docker or pnpm, whichever you didn’t run first. We are still on the hunt for why this happens once and a while!
+We promise you that we are constantly testing new PRs coming into oTToDev and the preview is core functionality, so the application is not broken! When you get a blank preview or don’t get a preview, this is generally because the LLM hallucinated bad code or incorrect commands. We are working on making this more transparent so it is obvious. Sometimes the error will appear in developer console too so check that as well.
+This goes to the point above about how local LLMs are getting very powerful but you still are going to see better (sometimes much better) results with the largest LLMs like GPT-4o, Claude 3.5 Sonnet, and DeepSeek Coder V2 236b. If you are using smaller LLMs like Qwen-2.5-Coder, consider it more experimental and educational at this point. It can build smaller applications really well, which is super impressive for a local LLM, but for larger scale applications you want to use the larger LLMs still!
+ + + + + + + + + + + + + +