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community[minor]: Add SparkLLM to community (langchain-ai#17702)
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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"# SparkLLM\n", | ||
"[SparkLLM](https://xinghuo.xfyun.cn/spark) is a large-scale cognitive model independently developed by iFLYTEK.\n", | ||
"It has cross-domain knowledge and language understanding ability by learning a large amount of texts, codes and images.\n", | ||
"It can understand and perform tasks based on natural dialogue." | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"## Prerequisite\n", | ||
"- 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", | ||
"metadata": {}, | ||
"source": [ | ||
"## Use SparkLLM" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 1, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"import os\n", | ||
"\n", | ||
"os.environ[\"IFLYTEK_SPARK_APP_ID\"] = \"app_id\"\n", | ||
"os.environ[\"IFLYTEK_SPARK_API_KEY\"] = \"api_key\"\n", | ||
"os.environ[\"IFLYTEK_SPARK_API_SECRET\"] = \"api_secret\"" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 2, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"name": "stderr", | ||
"output_type": "stream", | ||
"text": [ | ||
"/Users/liugddx/code/langchain/libs/core/langchain_core/_api/deprecation.py:117: LangChainDeprecationWarning: The function `__call__` was deprecated in LangChain 0.1.7 and will be removed in 0.2.0. Use invoke instead.\n", | ||
" warn_deprecated(\n" | ||
] | ||
}, | ||
{ | ||
"name": "stdout", | ||
"output_type": "stream", | ||
"text": [ | ||
"My name is iFLYTEK Spark. How can I assist you today?\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"from langchain_community.llms import SparkLLM\n", | ||
"\n", | ||
"# Load the model\n", | ||
"llm = SparkLLM()\n", | ||
"\n", | ||
"res = llm(\"What's your name?\")\n", | ||
"print(res)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 9, | ||
"metadata": { | ||
"ExecuteTime": { | ||
"end_time": "2024-02-18T13:04:29.305856Z", | ||
"start_time": "2024-02-18T13:04:28.085715Z" | ||
} | ||
}, | ||
"outputs": [ | ||
{ | ||
"data": { | ||
"text/plain": "LLMResult(generations=[[Generation(text='Hello! How can I assist you today?')]], llm_output=None, run=[RunInfo(run_id=UUID('d8cdcd41-a698-4cbf-a28d-e74f9cd2037b'))])" | ||
}, | ||
"execution_count": 9, | ||
"metadata": {}, | ||
"output_type": "execute_result" | ||
} | ||
], | ||
"source": [ | ||
"res = llm.generate(prompts=[\"hello!\"])\n", | ||
"res" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 8, | ||
"metadata": { | ||
"ExecuteTime": { | ||
"end_time": "2024-02-18T13:05:44.640035Z", | ||
"start_time": "2024-02-18T13:05:43.244126Z" | ||
} | ||
}, | ||
"outputs": [ | ||
{ | ||
"name": "stdout", | ||
"output_type": "stream", | ||
"text": [ | ||
"Hello! How can I assist you today?\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"for res in llm.stream(\"foo:\"):\n", | ||
" print(res)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": { | ||
"collapsed": false | ||
}, | ||
"outputs": [], | ||
"source": [] | ||
} | ||
], | ||
"metadata": { | ||
"kernelspec": { | ||
"display_name": "Python 3 (ipykernel)", | ||
"language": "python", | ||
"name": "python3" | ||
}, | ||
"language_info": { | ||
"name": "python" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 2 | ||
} |
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