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@ -41,6 +41,8 @@ class VectorDBQA(Chain, BaseModel):
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"""Return the source documents."""
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"""Return the source documents."""
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search_kwargs: Dict[str, Any] = Field(default_factory=dict)
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search_kwargs: Dict[str, Any] = Field(default_factory=dict)
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"""Extra search args."""
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"""Extra search args."""
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search_type: str = "similarity"
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"""Search type to use over vectorstore. `similarity` or `mmr`."""
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class Config:
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class Config:
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"""Configuration for this pydantic object."""
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"""Configuration for this pydantic object."""
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@ -90,6 +92,15 @@ class VectorDBQA(Chain, BaseModel):
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values["combine_documents_chain"] = combine_documents_chain
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values["combine_documents_chain"] = combine_documents_chain
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return values
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return values
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@root_validator()
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def validate_search_type(cls, values: Dict) -> Dict:
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"""Validate search type."""
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if "search_type" in values:
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search_type = values["search_type"]
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if search_type not in ("similarity", "mmr"):
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raise ValueError(f"search_type of {search_type} not allowed.")
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return values
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@classmethod
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@classmethod
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def from_llm(
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def from_llm(
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cls, llm: BaseLLM, prompt: PromptTemplate = PROMPT, **kwargs: Any
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cls, llm: BaseLLM, prompt: PromptTemplate = PROMPT, **kwargs: Any
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@ -129,9 +140,16 @@ class VectorDBQA(Chain, BaseModel):
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"""
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"""
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question = inputs[self.input_key]
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question = inputs[self.input_key]
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if self.search_type == "similarity":
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docs = self.vectorstore.similarity_search(
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docs = self.vectorstore.similarity_search(
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question, k=self.k, **self.search_kwargs
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question, k=self.k, **self.search_kwargs
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)
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)
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elif self.search_type == "mmr":
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docs = self.vectorstore.max_marginal_relevance_search(
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question, k=self.k, **self.search_kwargs
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)
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else:
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raise ValueError(f"search_type of {self.search_type} not allowed.")
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answer, _ = self.combine_documents_chain.combine_docs(docs, question=question)
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answer, _ = self.combine_documents_chain.combine_docs(docs, question=question)
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if self.return_source_documents:
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if self.return_source_documents:
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