fix(QDrant): Resolve bug in document search functionality (langflow-ai#2518)

* Update Qdrant.py

fixed embeddings and distance_func for search_documents issue langflow-ai#2517

* [autofix.ci] apply automated fixes

* fixed documents link

* update params Qdrant

* Update Qdrant.py

* Update Qdrant.py

* Update Qdrant.py

* [autofix.ci] apply automated fixes

* Update args

* [autofix.ci] apply automated fixes

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: Gabriel Luiz Freitas Almeida <[email protected]>

Author: 3 people

src/backend/base/langflow/components/vectorstores/Qdrant.py

@@ -1,7 +1,6 @@
 from typing import List
 
 from langchain_community.vectorstores import Qdrant
-
 from langflow.base.vectorstores.model import LCVectorStoreComponent
 from langflow.helpers.data import docs_to_data
 from langflow.io import (
@@ -13,15 +12,14 @@
     DataInput,
     MultilineInput,
 )
-
 from langflow.schema import Data
+from langchain.embeddings.base import Embeddings  # Certifique-se de que esta importação está correta
 
 
 class QdrantVectorStoreComponent(LCVectorStoreComponent):
     display_name = "Qdrant"
     description = "Qdrant Vector Store with search capabilities"
     documentation = "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/qdrant"
-    name = "Qdrant"
     icon = "Qdrant"
 
     inputs = [
@@ -66,19 +64,18 @@ def _build_qdrant(self) -> Qdrant:
         qdrant_kwargs = {
             "collection_name": self.collection_name,
             "content_payload_key": self.content_payload_key,
-            "distance_func": self.distance_func,
             "metadata_payload_key": self.metadata_payload_key,
         }
 
         server_kwargs = {
-            "host": self.host,
-            "port": self.port,
-            "grpc_port": self.grpc_port,
+            "host": self.host if self.host else None,
+            "port": int(self.port),  # Garantir que port seja um inteiro
+            "grpc_port": int(self.grpc_port),  # Garantir que grpc_port seja um inteiro
             "api_key": self.api_key,
             "prefix": self.prefix,
-            "timeout": self.timeout,
-            "path": self.path,
-            "url": self.url,
+            "timeout": int(self.timeout) if self.timeout else None,  # Garantir que timeout seja um inteiro
+            "path": self.path if self.path else None,
+            "url": self.url if self.url else None,
         }
 
         server_kwargs = {k: v for k, v in server_kwargs.items() if v is not None}
@@ -90,13 +87,17 @@ def _build_qdrant(self) -> Qdrant:
             else:
                 documents.append(_input)
 
+        embedding = self.embedding
+        if not isinstance(embedding, Embeddings):
+            raise ValueError("Invalid embedding object")
+
         if documents:
-            qdrant = Qdrant.from_documents(documents, embedding=self.embedding, **qdrant_kwargs)
+            qdrant = Qdrant.from_documents(documents, embeddings=embedding, **qdrant_kwargs)
         else:
             from qdrant_client import QdrantClient
 
             client = QdrantClient(**server_kwargs)
-            qdrant = Qdrant(embedding_function=self.embedding.embed_query, client=client, **qdrant_kwargs)
+            qdrant = Qdrant(embeddings=embedding, client=client, **qdrant_kwargs)
 
         return qdrant