{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.prompts.example_selector import MaxMarginalRelevanceExampleSelector\n",
    "from langchain.vectorstores import FAISS\n",
    "from langchain.embeddings import OpenAIEmbeddings\n",
    "from langchain.prompts import FewShotPromptTemplate, PromptTemplate\n",
    "from langchain.prompts.example_selector.ngram_overlap import NGramOverlapExampleSelector\n",
    "\n",
    "example_prompt = PromptTemplate(\n",
    "    input_variables=[\"input\", \"output\"],\n",
    "    template=\"Input: {input}\\nOutput: {output}\",\n",
    ")\n",
    "\n",
    "# These are a lot of examples of a pretend task of creating antonyms.\n",
    "examples = [\n",
    "    {\"input\": \"高兴\", \"output\": \"悲伤\"},\n",
    "    {\"input\": \"个子高\", \"output\": \"个子矮\"},\n",
    "    {\"input\": \"精力充沛\", \"output\": \"昏昏欲睡\"},\n",
    "    {\"input\": \"晴朗\", \"output\": \"阴暗的阴暗的\"},\n",
    "    {\"input\": \"多风\", \"output\": \"平静的\"},\n",
    "    {\"input\": \"经济下滑一路到底\", \"output\": \"业绩增长\"},\n",
    "    {\"input\": \"飞翔\", \"output\": \"天空\"},\n",
    "    {\"input\": \"教育\", \"output\": \"平静的\"},\n",
    "    {\"input\": \"小孩儿\", \"output\": \"平静的\"},\n",
    "    {\"input\": \"开心\", \"output\": \"平静的\"},\n",
    "    {\"input\": \"消防员\", \"output\": \"平静的\"},\n",
    "    {\"input\": \"程序员\", \"output\": \"平静的\"},\n",
    "    {\"input\": \"理财师\", \"output\": \"平静的\"},\n",
    "    {\"input\": \"学生\", \"output\": \"平静的\"},\n",
    "    {\"input\": \"计算机\", \"output\": \"平静的\"},\n",
    "    {\"input\": \"See Spot run.\", \"output\": \"Ver correr a Spot.\"},\n",
    "    {\"input\": \"My dog barks.\", \"output\": \"Mi perro ladra.\"},\n",
    "    {\"input\": \"Spot can run.\", \"output\": \"Spot puede correr.\"},\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "example_selector = MaxMarginalRelevanceExampleSelector.from_examples(\n",
    "    # This is the list of examples available to select from.\n",
    "    examples, \n",
    "    # This is the embedding class used to produce embeddings which are used to measure semantic similarity.\n",
    "    OpenAIEmbeddings(), \n",
    "    # This is the VectorStore class that is used to store the embeddings and do a similarity search over.\n",
    "    FAISS, \n",
    "    # This is the number of examples to produce.\n",
    "    k=2\n",
    ")\n",
    "mmr_prompt = FewShotPromptTemplate(\n",
    "    # We provide an ExampleSelector instead of examples.\n",
    "    example_selector=example_selector,\n",
    "    example_prompt=example_prompt,\n",
    "    prefix=\"Give the antonym of every input\",\n",
    "    suffix=\"Input: {adjective}\\nOutput:\", \n",
    "    input_variables=[\"adjective\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Give the antonym of every input\n",
      "\n",
      "Input: 理财师\n",
      "Output: 平静的\n",
      "\n",
      "Input: See Spot run.\n",
      "Output: Ver correr a Spot.\n",
      "\n",
      "Input: 投资\n",
      "Output:\n"
     ]
    }
   ],
   "source": [
    "# Input is a feeling, so should select the happy/sad example as the first one\n",
    "print(mmr_prompt.format(adjective=\"投资\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "example_selector = NGramOverlapExampleSelector(\n",
    "    # These are the examples it has available to choose from.\n",
    "    examples=examples, \n",
    "    # This is the PromptTemplate being used to format the examples.\n",
    "    example_prompt=example_prompt, \n",
    "    # This is the threshold, at which selector stops.\n",
    "    # It is set to -1.0 by default.\n",
    "    threshold=-1.0,\n",
    "    # For negative threshold:\n",
    "    # Selector sorts examples by ngram overlap score, and excludes none.\n",
    "    # For threshold greater than 1.0:\n",
    "    # Selector excludes all examples, and returns an empty list.\n",
    "    # For threshold equal to 0.0:\n",
    "    # Selector sorts examples by ngram overlap score,\n",
    "    # and excludes those with no ngram overlap with input.\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "dynamic_prompt = FewShotPromptTemplate(\n",
    "    # We provide an ExampleSelector instead of examples.\n",
    "    example_selector=example_selector,\n",
    "    example_prompt=example_prompt,\n",
    "    prefix=\"Give the Spanish translation of every input\",\n",
    "    suffix=\"Input: {sentence}\\nOutput:\", \n",
    "    input_variables=[\"sentence\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Give the Spanish translation of every input\n",
      "\n",
      "Input: See Spot run.\n",
      "Output: Ver correr a Spot.\n",
      "\n",
      "Input: Spot can run.\n",
      "Output: Spot puede correr.\n",
      "\n",
      "Input:  Spot run.\n",
      "Output:\n"
     ]
    }
   ],
   "source": [
    "# 没看懂有什么作用，0～1，\n",
    "example_selector.threshold=0\n",
    "print(dynamic_prompt.format(sentence=\" Spot run.\"))"
   ]
  }
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