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Copy file name to clipboardExpand all lines: FAQ.md
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# bolt.diy
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## Recommended Models for bolt.diy
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For the best experience with bolt.diy, we recommend using the following models:
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-**Claude 3.5 Sonnet (old)**: Best overall coder, providing excellent results across all use cases
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-**Gemini 2.0 Flash**: Exceptional speed while maintaining good performance
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-**GPT-4o**: Strong alternative to Claude 3.5 Sonnet with comparable capabilities
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-**DeepSeekCoder V2 236b**: Best open source model (available through OpenRouter, DeepSeek API, or self-hosted)
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-**Qwen 2.5 Coder 32b**: Best model for self-hosting with reasonable hardware requirements
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**Note**: Models with less than 7b parameters typically lack the capability to properly interact with bolt!
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## FAQ
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### How do I get the best results with bolt.diy?
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We promise you that we are constantly testing new PRs coming into bolt.diy 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.
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### How to add a LLM:
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### Everything works but the results are bad
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To make new LLMs available to use in this version of bolt.new, head on over to `app/utils/constants.ts`and find the constant MODEL_LIST. Each element in this array is an object that has the model ID for the name (get this from the provider's API documentation), a label for the frontend model dropdown, and the provider.
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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!
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By default, Anthropic, OpenAI, Groq, and Ollama are implemented as providers, but the YouTube video for this repo covers how to extend this to work with more providers if you wish!
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### Received structured exception #0xc0000005: access violation
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When you add a new model to the MODEL_LIST array, it will immediately be available to use when you run the app locally or reload it. For Ollama models, make sure you have the model installed already before trying to use it here!
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If you are getting this, you are probably on Windows. The fix is generally to update the [Visual C++ Redistributable](https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170)
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### Everything works but the results are bad
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### How to add an LLM:
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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!
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To make new LLMs available to use in this version of bolt.new, head on over to `app/utils/constants.ts` and find the constant MODEL_LIST. Each element in this array is an object that has the model ID for the name (get this from the provider's API documentation), a label for the frontend model dropdown, and the provider.
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By default, many providers are already implemented, but the YouTube video for this repo covers how to extend this to work with more providers if you wish!
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When you add a new model to the MODEL_LIST array, it will immediately be available to use when you run the app locally or reload it.
Copy file name to clipboardExpand all lines: README.md
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[](https://bolt.diy)
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# bolt.diy (Previously oTToDev)
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[](https://bolt.diy)
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Welcome to bolt.diy, the official open source version of Bolt.new (previously known as oTToDev and bolt.new ANY LLM), which allows you to choose the LLM that you use for each prompt! Currently, you can use OpenAI, Anthropic, Ollama, OpenRouter, Gemini, LMStudio, Mistral, xAI, HuggingFace, DeepSeek, or Groq models - and it is easily extended to use any other model supported by the Vercel AI SDK! See the instructions below for running this locally and extending it to include more models.
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Check the [bolt.diy Docs](https://stackblitz-labs.github.io/bolt.diy/) for more information. This documentation is still being updated after the transfer.
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Check the [bolt.diy Docs](https://stackblitz-labs.github.io/bolt.diy/) for more information.
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We have also launched an experimental agent called the "bolt.diy Expert" that can answer common questions about bolt.diy. Find it here on the [oTTomator Live Agent Studio](https://studio.ottomator.ai/).
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bolt.diy was originally started by [Cole Medin](https://www.youtube.com/@ColeMedin) but has quickly grown into a massive community effort to build the BEST open source AI coding assistant!
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## Join the community for bolt.diy!
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## Table of Contents
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-[Join the Community](#join-the-community)
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-[Requested Additions](#requested-additions)
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-[Features](#features)
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-[Setup](#setup)
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-[Run the Application](#run-the-application)
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-[Available Scripts](#available-scripts)
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-[Contributing](#contributing)
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-[Roadmap](#roadmap)
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-[FAQ](#faq)
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## Join the community
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https://thinktank.ottomator.ai
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[Join the bolt.diy community here, in the thinktank on ottomator.ai!](https://thinktank.ottomator.ai)
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## Requested Additions - Feel Free to Contribute!
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## Requested Additions
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- ✅ OpenRouter Integration (@coleam00)
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- ✅ Gemini Integration (@jonathands)
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- ⬜ Perplexity Integration
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- ⬜ Vertex AI Integration
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## bolt.diy Features
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## Features
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-**AI-powered full-stack web development** directly in your browser.
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-**Support for multiple LLMs** with an extensible architecture to integrate additional models.
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-**Download projects as ZIP** for easy portability.
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-**Integration-ready Docker support** for a hassle-free setup.
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## Setup bolt.diy
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## Setup
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If you're new to installing software from GitHub, don't worry! If you encounter any issues, feel free to submit an "issue" using the provided links or improve this documentation by forking the repository, editing the instructions, and submitting a pull request. The following instruction will help you get the stable branch up and running on your local machine in no time.
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## FAQ
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For answers to common questions, visit our [FAQ Page](FAQ.md).
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For answers to common questions, issues, and to see a list of recommended models, visit our [FAQ Page](FAQ.md).
These providers are experimental and allow you to run AI models locally or connect to your own infrastructure. They require additional setup but offer more flexibility.
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