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chore: a few documentation enhancements for main README and FAQs

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Cole Medin
2024-12-18 07:01:58 -06:00
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FAQ.md
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# bolt.diy
## Recommended Models for bolt.diy
For the best experience with bolt.diy, we recommend using the following models:
- **Claude 3.5 Sonnet (old)**: Best overall coder, providing excellent results across all use cases
- **Gemini 2.0 Flash**: Exceptional speed while maintaining good performance
- **GPT-4o**: Strong alternative to Claude 3.5 Sonnet with comparable capabilities
- **DeepSeekCoder V2 236b**: Best open source model (available through OpenRouter, DeepSeek API, or self-hosted)
- **Qwen 2.5 Coder 32b**: Best model for self-hosting with reasonable hardware requirements
**Note**: Models with less than 7b parameters typically lack the capability to properly interact with bolt!
## FAQ
### 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.
### How to add a LLM:
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.
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!
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!
### Everything works but the results are bad
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!
### Received structured exception #0xc0000005: access violation
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)
### How to add an LLM:
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.
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!
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.