Add GPT4Vision Image loader (#1089)
Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>
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@@ -126,7 +126,6 @@ class QdrantDB(BaseVectorDB):
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documents: List[str],
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metadatas: List[object],
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ids: List[str],
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skip_embedding: bool,
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**kwargs: Optional[Dict[str, any]],
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):
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"""add data in vector database
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@@ -138,12 +137,8 @@ class QdrantDB(BaseVectorDB):
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:type metadatas: List[object]
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:param ids: ids of docs
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:type ids: List[str]
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:param skip_embedding: A boolean flag indicating if the embedding for the documents to be added is to be
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generated or not
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:type skip_embedding: bool
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"""
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if not skip_embedding:
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embeddings = self.embedder.embedding_fn(documents)
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embeddings = self.embedder.embedding_fn(documents)
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payloads = []
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qdrant_ids = []
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@@ -167,7 +162,6 @@ class QdrantDB(BaseVectorDB):
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input_query: List[str],
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n_results: int,
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where: Dict[str, any],
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skip_embedding: bool,
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citations: bool = False,
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**kwargs: Optional[Dict[str, Any]],
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) -> Union[List[Tuple[str, Dict]], List[str]]:
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@@ -179,20 +173,13 @@ class QdrantDB(BaseVectorDB):
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:type n_results: int
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:param where: Optional. to filter data
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:type where: Dict[str, any]
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:param skip_embedding: A boolean flag indicating if the embedding for the documents to be added is to be
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generated or not
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:type skip_embedding: bool
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:param citations: we use citations boolean param to return context along with the answer.
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:type citations: bool, default is False.
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:return: The content of the document that matched your query,
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along with url of the source and doc_id (if citations flag is true)
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:rtype: List[str], if citations=False, otherwise List[Tuple[str, str, str]]
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"""
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if not skip_embedding:
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query_vector = self.embedder.embedding_fn([input_query])[0]
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else:
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query_vector = input_query
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query_vector = self.embedder.embedding_fn([input_query])[0]
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keys = set(where.keys() if where is not None else set())
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qdrant_must_filters = []
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