10ce065d9e
* feat(openai): use max_completion_tokens & reasoning_effort params * feat(openai): use developer prompt for reasoning models * docs: update openai config in readme * refactor: follow lua style quotes * fix(azure): rename max_tokens to max_completion_tokens * refactor(azure): remove duplicate field * refactor: update types * refactor(azure): update type
44 lines
2.2 KiB
Markdown
44 lines
2.2 KiB
Markdown
Cursor planning mode
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====================
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Because avante.nvim has always used Aider’s method for planning applying, but its prompts are very picky with models and require ones like claude-3.5-sonnet or gpt-4o to work properly.
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Therefore, I have adopted Cursor’s method to implement planning applying, which should work on most models. If you encounter issues with your current model, I highly recommend switching to cursor planning mode to resolve them.
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For details on the implementation, please refer to: [🚀 Introducing Fast Apply - Replicate Cursor's Instant Apply model](https://www.reddit.com/r/LocalLLaMA/comments/1ga25gj/introducing_fast_apply_replicate_cursors_instant/)
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~~So you need to first run the `FastApply` model mentioned above:~~
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~~```bash~~
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ollama pull hf.co/Kortix/FastApply-7B-v1.0_GGUF:Q4_K_M
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~~```~~
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An interesting fact is that I found the `FastApply` model mentioned above doesn't work well. First, it's too slow, and second, it's not accurate for processing long code file. It often includes `// ... existing code ...` comments in the generated final code, resulting in incorrect code generation.
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The best model I found for applying is `llama-3.3-70b-versatile` on [Groq](https://console.groq.com/playground), it's both fast and accurate, it's perfect!
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Then enable it in avante.nvim:
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```lua
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{
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--- ... existing configurations
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provider = 'claude', -- In this example, use Claude for planning, but you can also use any provider you want.
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cursor_applying_provider = 'groq', -- In this example, use Groq for applying, but you can also use any provider you want.
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behaviour = {
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--- ... existing behaviours
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enable_cursor_planning_mode = true, -- enable cursor planning mode!
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},
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vendors = {
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--- ... existing vendors
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groq = { -- define groq provider
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__inherited_from = 'openai',
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api_key_name = 'GROQ_API_KEY',
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endpoint = 'https://api.groq.com/openai/v1/',
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model = 'llama-3.3-70b-versatile',
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max_completion_tokens = 32768, -- remember to increase this value, otherwise it will stop generating halfway
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},
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},
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--- ... existing configurations
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}
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```
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