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Custom model docs (#368)
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# PDFSearchTool
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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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@@ -33,3 +30,31 @@ tool = PDFSearchTool(pdf='path/to/your/document.pdf')
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## Arguments
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- `pdf`: **Optinal** The PDF path for the search. Can be provided at initialization or within the `run` method's arguments. If provided at initialization, the tool confines its search to the specified document.
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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 = PDFSearchTool(
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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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