From 6e0afd87c30bcafe828958cbbda2a47ea86d31e4 Mon Sep 17 00:00:00 2001
From: Atharva J <me.atharvajadhav@gmail.com>
Date: Sun, 12 Nov 2023 01:18:41 +0530
Subject: [PATCH] minor - removal of extra imports

---
 .../retrievers/VectaraSelfQueryRetriever.py         | 13 ++++---------
 .../langflow/components/vectorstores/Vectara.py     |  4 ----
 2 files changed, 4 insertions(+), 13 deletions(-)

diff --git a/src/backend/langflow/components/retrievers/VectaraSelfQueryRetriever.py b/src/backend/langflow/components/retrievers/VectaraSelfQueryRetriever.py
index 0055e6ff2..34c9707f3 100644
--- a/src/backend/langflow/components/retrievers/VectaraSelfQueryRetriever.py
+++ b/src/backend/langflow/components/retrievers/VectaraSelfQueryRetriever.py
@@ -1,17 +1,11 @@
-from typing import Optional, Union, List
+from typing import Optional, List
 from langflow import CustomComponent
 import json
-import lark
-from langchain.vectorstores import Vectara
-from langchain.schema import Document
-# from langchain.vectorstores.base import VectorStore
 from langchain.schema import BaseRetriever
-from langchain.embeddings.base import Embeddings
 from langchain.schema.vectorstore import VectorStore
 from langchain.base_language import BaseLanguageModel
 from langchain.retrievers.self_query.base import SelfQueryRetriever
 from langchain.chains.query_constructor.base import AttributeInfo
-from langchain.embeddings import FakeEmbeddings
 
 
 class VectaraComponent(CustomComponent):
@@ -31,13 +25,14 @@ class VectaraComponent(CustomComponent):
             "display_name": "LLM", 
             "info": "For self query retriever"
             },
-        'document_content_description':{
+        "document_content_description":{
             "display_name": "Document Content Description", 
             "info": "For self query retriever",
             },
         "metadata_field_info": {
             "display_name": "Metadata Field Info", 
-            "info": "Check json format in documentation for self query retriever",
+            "info": "Check dictionary format in documentation for self query retriever",
+            "info": "Each metadata field is a json string containing additional search metadata. Example input: {\"name\":\"speech\",\"description\":\"what name of the speech\",\"type\":\"string or list[string]\"}. The keys should remain constant",
             },
     }
 
diff --git a/src/backend/langflow/components/vectorstores/Vectara.py b/src/backend/langflow/components/vectorstores/Vectara.py
index 1a40e94f1..b8b2f1021 100644
--- a/src/backend/langflow/components/vectorstores/Vectara.py
+++ b/src/backend/langflow/components/vectorstores/Vectara.py
@@ -7,11 +7,7 @@ from langchain.vectorstores import Vectara
 from langchain.schema import Document
 from langchain.vectorstores.base import VectorStore
 from langchain.schema import BaseRetriever
-from langchain.embeddings.base import Embeddings
 from langchain.schema.vectorstore import VectorStore
-from langchain.base_language import BaseLanguageModel
-from langchain.retrievers.self_query.base import SelfQueryRetriever
-from langchain.chains.query_constructor.base import AttributeInfo
 from langchain.embeddings import FakeEmbeddings