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Custom model docs (#368)
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# GitHubSearchTool
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!!! note "Depend on OpenAI"
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All RAG tools at the moment can only use openAI to generate embeddings, we are working on adding support for other providers.
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!!! note "Experimental"
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We are still working on improving tools, so there might be unexpected behavior or changes in the future.
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@@ -40,3 +37,31 @@ tool = GitHubSearchTool(
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## Arguments
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- `github_repo` : The URL of the GitHub repository where the search will be conducted. This is a mandatory field and specifies the target repository for your search.
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- `content_types` : Specifies the types of content to include in your search. You must provide a list of content types from the following options: `code` for searching within the code, `repo` for searching within the repository's general information, `pr` for searching within pull requests, and `issue` for searching within issues. This field is mandatory and allows tailoring the search to specific content types within the GitHub repository.
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## Custom model and embeddings
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By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
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```python
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tool = GitHubSearchTool(
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config=dict(
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llm=dict(
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provider="ollama", # or google, openai, anthropic, llama2, ...
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config=dict(
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model="llama2",
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# temperature=0.5,
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# top_p=1,
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# stream=true,
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),
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),
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embedder=dict(
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provider="google",
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config=dict(
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model="models/embedding-001",
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task_type="retrieval_document",
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# title="Embeddings",
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),
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),
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)
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)
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```
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