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Usage.md
12
Usage.md
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- [Working with GitHub App](#working-with-github-app)
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- [Working with GitHub App](#working-with-github-app)
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- [Working with GitHub Action](#working-with-github-action)
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- [Working with GitHub Action](#working-with-github-action)
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- [Changing a model](#changing-a-model)
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- [Changing a model](#changing-a-model)
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- [Working with large PRs](#working-with-large-prs)
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- [Appendix - additional configurations walkthrough](#appendix---additional-configurations-walkthrough)
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- [Appendix - additional configurations walkthrough](#appendix---additional-configurations-walkthrough)
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### Introduction
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### Introduction
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Also review the [AiHandler](pr_agent/algo/ai_handler.py) file for instruction how to set keys for other models.
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Also review the [AiHandler](pr_agent/algo/ai_handler.py) file for instruction how to set keys for other models.
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### Working with large PRs
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The default mode of CodiumAI is to have a single call per tool, using GPT-4, which has a token limit of 8000 tokens.
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This mode provide a very good speed-quality-cost tradeoff, and can handle most PRs successfully.
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When the PR is above the token limit, it employs a [PR Compression strategy](./PR_COMPRESSION.md).
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However, for very large PRs, or in case you want to emphasize quality over speed and cost, there are 2 possible solutions:
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1) [use a model](#changing-a-model) with larger context, like GPT-32K, or claude-100K. This solution will be applicable for all the tools
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2) For the `/improve` tool, there is an ['extended' mode](./docs/IMPROVE.md) (`/improve --extended`),
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which divides the PR to chunks, and process each chunk separately, so regardless of the model, no compression will be done (but for large PRs, multiple calls may occur)
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### Appendix - additional configurations walkthrough
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### Appendix - additional configurations walkthrough
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