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elastic · Jan 25, 2024 · 58cb37c · 58cb37c
1 parent a05ed9b
commit 58cb37c
Showing 1 changed file with 12 additions and 11 deletions.
diff --git a/notebooks/integrations/gemini/qa-langchain-gemini-elasticsearch.ipynb b/notebooks/integrations/gemini/qa-langchain-gemini-elasticsearch.ipynb
@@ -5,9 +5,9 @@
    "id": "2a3143e8-3949-4ecc-905c-8333a43c9c87",
    "metadata": {},
    "source": [
-    "# Question Answering using Gemini, Langchain & Elasticsearch \n",
+    "# Question Answering using Gemini, Langchain & Elasticsearch\n",
     "\n",
-    "This tutorial demonstrates how to use the [Gemini API](https://ai.google.dev/docs) to create [embeddings](https://ai.google.dev/docs/embeddings_guide) and store them in Elasticsearch. We will learn how to connect Gemini to private data stored in Elasticsearch and build question/answer capabilities over it using [LangChain](https://python.langchain.com/docs/get_started/introduction)."
+    "This tutorial demonstrates how to use the [Gemini API](https://ai.google.dev/docs) to create [embeddings](https://ai.google.dev/docs/embeddings_guide) and store them in Elasticsearch. We will learn how to connect Gemini to private data stored in Elasticsearch and build question/answer capabilities over it using [LangChian](https://python.langchain.com/docs/get_started/introduction)."
    ]
   },
   {
@@ -60,13 +60,14 @@
     "from getpass import getpass\n",
     "from urllib.request import urlopen\n",
     "\n",
-    "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
-    "from langchain.schema.runnable import RunnablePassthrough\n",
-    "from langchain.text_splitter import CharacterTextSplitter\n",
+    "from elasticsearch import Elasticsearch, helpers\n",
     "from langchain.vectorstores import ElasticsearchStore\n",
+    "from langchain.text_splitter import CharacterTextSplitter\n",
+    "from langchain_google_genai import GoogleGenerativeAIEmbeddings\n",
     "from langchain_google_genai import ChatGoogleGenerativeAI\n",
-    "from langchain_google_genai import GoogleGenerativeAIEmbeddings",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.schema.output_parser import StrOutputParser\n",
+    "from langchain.schema.runnable import RunnablePassthrough"
    ]
   },
   {
@@ -165,7 +166,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "embedding = GoogleGenerativeAIEmbeddings(\n",
+    "query_embedding = GoogleGenerativeAIEmbeddings(\n",
     "    model=\"models/embedding-001\", task_type=\"retrieval_document\"\n",
     ")\n",
     "\n",
@@ -174,7 +175,7 @@
     "    es_cloud_id=ELASTIC_CLOUD_ID,\n",
     "    es_api_key=ELASTIC_API_KEY,\n",
     "    index_name=elastic_index_name,\n",
-    "    embedding=embedding\n",
+    "    embedding=query_embedding\n",
     ")"
    ]
   },
@@ -193,14 +194,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "embedding = GoogleGenerativeAIEmbeddings(\n",
+    "query_embedding = GoogleGenerativeAIEmbeddings(\n",
     "    model=\"models/embedding-001\", task_type=\"retrieval_query\"\n",
     ")\n",
     "\n",
     "es = ElasticsearchStore(\n",
     "    es_cloud_id=ELASTIC_CLOUD_ID,\n",
     "    es_api_key=ELASTIC_API_KEY,\n",
-    "    embedding=embedding,\n",
+    "    embedding=query_embedding,\n",
     "    index_name=elastic_index_name\n",
     ")\n",
     "\n",