mirror of
https://github.com/hwchase17/langchain.git
synced 2025-10-01 08:35:56 +00:00
Thank you for contributing to LangChain! Checklist: - **PR title**: docs: add & update docs for Oracle Cloud Infrastructure (OCI) integrations - **Description**: adding and updating documentation for two integrations - OCI Generative AI & OCI Data Science (1) adding integration page for OCI Generative AI embeddings (@baskaryan request, docs/docs/integrations/text_embedding/oci_generative_ai.ipynb) (2) updating integration page for OCI Generative AI llms (docs/docs/integrations/llms/oci_generative_ai.ipynb) (3) adding platform documentation for OCI (@baskaryan request, docs/docs/integrations/platforms/oci.mdx). this combines the integrations of OCI Generative AI & OCI Data Science (4) if possible, requesting to be added to 'Featured Community Providers' so supplying a modified docs/docs/integrations/platforms/index.mdx to reflect the addition - **Issue:** none - **Dependencies:** no new dependencies - **Twitter handle:** --------- Co-authored-by: MING KANG <ming.kang@oracle.com>
141 lines
4.0 KiB
Plaintext
Executable File
141 lines
4.0 KiB
Plaintext
Executable File
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Oracle Cloud Infrastructure Generative AI"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Oracle Cloud Infrastructure (OCI) Generative AI is a fully managed service that provides a set of state-of-the-art, customizable large language models (LLMs), that cover a wide range of use cases, and which are available through a single API.\n",
|
|
"Using the OCI Generative AI service you can access ready-to-use pretrained models, or create and host your own fine-tuned custom models based on your own data on dedicated AI clusters. Detailed documentation of the service and API is available __[here](https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm)__ and __[here](https://docs.oracle.com/en-us/iaas/api/#/en/generative-ai/20231130/)__.\n",
|
|
"\n",
|
|
"This notebook explains how to use OCI's Genrative AI models with LangChain."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Prerequisite\n",
|
|
"We will need to install the oci sdk"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"!pip install -U oci"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### OCI Generative AI API endpoint \n",
|
|
"https://inference.generativeai.us-chicago-1.oci.oraclecloud.com"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Authentication\n",
|
|
"The authentication methods supported for this langchain integration are:\n",
|
|
"\n",
|
|
"1. API Key\n",
|
|
"2. Session token\n",
|
|
"3. Instance principal\n",
|
|
"4. Resource principal \n",
|
|
"\n",
|
|
"These follows the standard SDK authentication methods detailed __[here](https://docs.oracle.com/en-us/iaas/Content/API/Concepts/sdk_authentication_methods.htm)__.\n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Usage"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"from langchain_community.embeddings import OCIGenAIEmbeddings\n",
|
|
"\n",
|
|
"# use default authN method API-key\n",
|
|
"embeddings = OCIGenAIEmbeddings(\n",
|
|
" model_id=\"MY_EMBEDDING_MODEL\",\n",
|
|
" service_endpoint=\"https://inference.generativeai.us-chicago-1.oci.oraclecloud.com\",\n",
|
|
" compartment_id=\"MY_OCID\",\n",
|
|
")\n",
|
|
"\n",
|
|
"\n",
|
|
"query = \"This is a query in English.\"\n",
|
|
"response = embeddings.embed_query(query)\n",
|
|
"print(response)\n",
|
|
"\n",
|
|
"documents = [\"This is a sample document\", \"and here is another one\"]\n",
|
|
"response = embeddings.embed_documents(documents)\n",
|
|
"print(response)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Use Session Token to authN\n",
|
|
"embeddings = OCIGenAIEmbeddings(\n",
|
|
" model_id=\"MY_EMBEDDING_MODEL\",\n",
|
|
" service_endpoint=\"https://inference.generativeai.us-chicago-1.oci.oraclecloud.com\",\n",
|
|
" compartment_id=\"MY_OCID\",\n",
|
|
" auth_type=\"SECURITY_TOKEN\",\n",
|
|
" auth_profile=\"MY_PROFILE\", # replace with your profile name\n",
|
|
")\n",
|
|
"\n",
|
|
"\n",
|
|
"query = \"This is a sample query\"\n",
|
|
"response = embeddings.embed_query(query)\n",
|
|
"print(response)\n",
|
|
"\n",
|
|
"documents = [\"This is a sample document\", \"and here is another one\"]\n",
|
|
"response = embeddings.embed_documents(documents)\n",
|
|
"print(response)"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "oci_langchain",
|
|
"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": "3.8.9"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|