mirror of
https://github.com/hwchase17/langchain.git
synced 2025-05-10 01:26:29 +00:00
753353411f
- [ ] **PR title**: "Fix list handling in Clova embeddings example documentation" - Description: Fixes a bug in the Clova Embeddings example documentation where document_text was incorrectly wrapped in an additional list. - Rationale The embed_documents method expects a list, but the previous example wrapped document_text in an unnecessary additional list, causing an error. The updated example correctly passes document_text directly to the method, ensuring it functions as intended.
87 lines
1.9 KiB
Plaintext
87 lines
1.9 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"# Clova Embeddings\n",
|
|
"[Clova](https://api.ncloud-docs.com/docs/ai-naver-clovastudio-summary) offers an embeddings service\n",
|
|
"\n",
|
|
"This example goes over how to use LangChain to interact with Clova inference for text embedding.\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import os\n",
|
|
"\n",
|
|
"os.environ[\"CLOVA_EMB_API_KEY\"] = \"\"\n",
|
|
"os.environ[\"CLOVA_EMB_APIGW_API_KEY\"] = \"\"\n",
|
|
"os.environ[\"CLOVA_EMB_APP_ID\"] = \"\""
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"from langchain_community.embeddings import ClovaEmbeddings"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"embeddings = ClovaEmbeddings()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"query_text = \"This is a test query.\"\n",
|
|
"query_result = embeddings.embed_query(query_text)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"document_text = [\"This is a test doc1.\", \"This is a test doc2.\"]\n",
|
|
"document_result = embeddings.embed_documents(document_text)"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.9.1"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
}
|