add prompts

llms_semantic_similarity.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 100,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 101,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 102,
    "metadata": {},
    "outputs": [
     {
@@ -72,7 +72,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 103,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -81,7 +81,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 104,
    "metadata": {},
    "outputs": [
     {
@@ -108,23 +108,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 105,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'\\n作业帮回答：除法'"
+       "'？\\n很晴朗，非常适合出去活动。'"
       ]
      },
-     "execution_count": 81,
+     "execution_count": 105,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "llm = OpenAI(temperature=0)\n",
-    "llm(prompt.format(input=\"66/2=34\"))"
+    "llm(prompt.format(input=\"天气怎么样\"))"
    ]
   }
  ],

prompt_load.ipynb

@@ -0,0 +1,35 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.prompts import load_prompt"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "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": "3.10.10"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

prompt_partial_template.ipynb.ipynb

@@ -0,0 +1,151 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.prompts import PromptTemplate\n",
+    "from datetime import datetime"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'lizhen : 18'"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "prompt_template = PromptTemplate(template=\"{name} : {age}\", input_variables=[\"name\", \"age\"])\n",
+    "partial_prompt_template = prompt_template.partial(name=\"lizhen\")\n",
+    "partial_prompt_template.format(age=\"18\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "foobaz\n"
+     ]
+    }
+   ],
+   "source": [
+    "prompt = PromptTemplate(template=\"{foo}{bar}\", input_variables=[\"bar\"], partial_variables={\"foo\": \"foo\"})\n",
+    "print(prompt.format(bar=\"baz\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'lizhen : 18'"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "prompt1 = PromptTemplate(template=\"{name} : {age}\", input_variables=[\"age\"], partial_variables={\"name\": \"lizhen\"})\n",
+    "prompt1.format(age=\"18\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def _get_time():\n",
+    "    now = datetime.now()\n",
+    "    return now.strftime(\"%Y/%m/%d %H:%M:%S\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2023/04/21 17:46:37, 北京气温多少？'"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "date_prompt = PromptTemplate(template=\"{date}, {city}气温多少？\",input_variables=[\"date\",\"city\"])\n",
+    "date_partial_prompt = date_prompt.partial(date=_get_time)\n",
+    "date_partial_prompt.format(city=\"北京\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2023/04/21 17:48:50, 天津气温多少？'"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "date_prompt1 = PromptTemplate(template=\"{date}, {city}气温多少？\", input_variables=[\"city\"], partial_variables={\"date\": _get_time})\n",
+    "date_prompt1.format(city=\"天津\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "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": "3.10.10"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}