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langchain/docs/versioned_docs/version-0.2.x/integrations/chat/sparkllm.ipynb
Jacob Lee aff771923a Jacob/new docs (#20570)
Use docusaurus versioning with a callout, merged master as well

@hwchase17 @baskaryan

---------

Signed-off-by: Weichen Xu <weichen.xu@databricks.com>
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2024-04-18 11:10:55 -07:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "3ddface67cd10a87",
"metadata": {
"collapsed": false
},
"source": [
"# SparkLLM Chat\n",
"\n",
"SparkLLM chat models API by iFlyTek. For more information, see [iFlyTek Open Platform](https://www.xfyun.cn/)."
]
},
{
"cell_type": "markdown",
"id": "b895d98989d4de01",
"metadata": {},
"source": [
"## Basic use"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "43daa39972d4c533",
"metadata": {
"ExecuteTime": {
"end_time": "2024-02-17T07:55:44.526904Z",
"start_time": "2024-02-17T07:55:43.166698Z"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": "AIMessage(content='Hello! How can I help you today?')"
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\"\"\"For basic init and call\"\"\"\n",
"from langchain_community.chat_models import ChatSparkLLM\n",
"from langchain_core.messages import HumanMessage\n",
"\n",
"chat = ChatSparkLLM(\n",
" spark_app_id=\"<app_id>\", spark_api_key=\"<api_key>\", spark_api_secret=\"<api_secret>\"\n",
")\n",
"message = HumanMessage(content=\"Hello\")\n",
"chat([message])"
]
},
{
"cell_type": "markdown",
"id": "df755f4c5689510",
"metadata": {
"collapsed": false
},
"source": [
"- Get SparkLLM's app_id, api_key and api_secret from [iFlyTek SparkLLM API Console](https://console.xfyun.cn/services/bm3) (for more info, see [iFlyTek SparkLLM Intro](https://xinghuo.xfyun.cn/sparkapi) ), then set environment variables `IFLYTEK_SPARK_APP_ID`, `IFLYTEK_SPARK_API_KEY` and `IFLYTEK_SPARK_API_SECRET` or pass parameters when creating `ChatSparkLLM` as the demo above."
]
},
{
"cell_type": "markdown",
"id": "984e32ee47bc6772",
"metadata": {
"collapsed": false
},
"source": [
"## For ChatSparkLLM with Streaming"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "7dc162bd65fec08f",
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello! How can I help you today?"
]
}
],
"source": [
"chat = ChatSparkLLM(\n",
" spark_app_id=\"<app_id>\",\n",
" spark_api_key=\"<api_key>\",\n",
" spark_api_secret=\"<api_secret>\",\n",
" streaming=True,\n",
")\n",
"for chunk in chat.stream(\"Hello!\"):\n",
" print(chunk.content, end=\"\")"
]
},
{
"cell_type": "markdown",
"id": "566c85e0",
"metadata": {},
"source": [
"## For v2"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3103ebdf",
"metadata": {},
"outputs": [],
"source": [
"\"\"\"For basic init and call\"\"\"\n",
"from langchain_community.chat_models import ChatSparkLLM\n",
"from langchain_core.messages import HumanMessage\n",
"\n",
"chat = ChatSparkLLM(\n",
" spark_app_id=\"<app_id>\",\n",
" spark_api_key=\"<api_key>\",\n",
" spark_api_secret=\"<api_secret>\",\n",
" spark_api_url=\"wss://spark-api.xf-yun.com/v2.1/chat\",\n",
" spark_llm_domain=\"generalv2\",\n",
")\n",
"message = HumanMessage(content=\"Hello\")\n",
"chat([message])"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}