{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'text': 'lizhen', 'age': '18'}\n",
      "lizhen lizhen\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'text': 'lizhen', 'age': '20', 'name': 'lizhen'}"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from langchain.chains import TransformChain\n",
    "def transform_func(inputs: dict) -> dict:\n",
    "    print(inputs)\n",
    "    text = inputs[\"text\"]\n",
    "    shortened_text = text\n",
    "    print(shortened_text , text)\n",
    "    return {\"name\": shortened_text, \"age\":\"20\"}\n",
    "\n",
    "transform_chain = TransformChain(input_variables=[\"text\",\"age\"], output_variables=[\"name\", \"age\"], transform=transform_func)\n",
    "transform_chain({\"text\":\"lizhen\", \"age\":\"18\"})"
   ]
  }
 ],
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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