feat: Add SelfQueryRetrieverComponent to langflow retrievers

src/backend/base/langflow/components/retrievers/SelfQueryRetriever.py

@@ -0,0 +1,39 @@
+# from langflow.field_typing import Data
+from langchain.chains.query_constructor.base import AttributeInfo
+from langchain.retrievers.self_query.base import SelfQueryRetriever
+from langchain_core.vectorstores import VectorStore
+
+from langflow.custom import CustomComponent
+from langflow.field_typing import BaseLanguageModel
+from langflow.schema import Record
+from langflow.schema.message import Message
+
+
+class SelfQueryRetrieverComponent(CustomComponent):
+    display_name: str = "Self Query Retriever"
+    description: str = "Retriever that uses a vector store and an LLM to generate the vector store queries."
+    icon = "LangChain"
+
+    def build(
+        self,
+        query: Message,
+        vectorstore: VectorStore,
+        metadata_field_info: list[AttributeInfo],
+        document_content_description: str,
+        llm: BaseLanguageModel,
+    ) -> Record:
+        metadata_field_info = [i[0] for i in metadata_field_info]
+
+        self_query_retriever = SelfQueryRetriever.from_llm(
+            llm,
+            vectorstore,
+            document_content_description,
+            metadata_field_info,
+            enable_limit=True,
+        )
+
+        input_text = query.text
+        documents = self_query_retriever.invoke(input=input_text)
+        records = [Record.from_document(document) for document in documents]
+        self.status = records
+        return records