python-rag-application.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fce99756-68ec-4530-b7ed-4a8a61561abc",
   "metadata": {},
   "outputs": [],
   "source": [
    "Using LangChain to Prompts Templates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0e5aacb4-ed5b-4146-9124-f8d19f36ec5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"LangChain is an open-source, decentralized, and modular framework for building blockchain-based data management systems.\\n\\nHere's a breakdown of the key components:\\n\\n1. **Blockchain**: LangChain uses blockchain technology as its foundation, allowing for secure, transparent, and tamper-proof data storage.\\n2. **Decentralized Data Management**: LangChain enables the creation of decentralized data management systems, where data is stored on multiple nodes across the network, ensuring high availability and fault tolerance.\\n3. **Modular Architecture**: The framework is designed with a modular architecture, allowing developers to build custom applications by composing existing components.\\n\\nLangChain's primary focus areas include:\\n\\n1. **Decentralized Data Storage**: LangChain enables the creation of decentralized storage solutions, such as decentralized file systems and data lakes.\\n2. **Data Management Orchestration**: The framework provides tools for managing and orchestrating data across multiple nodes and blockchain networks.\\n3. **Interoperability**: LangChain aims to enable seamless interaction between different blockchain networks and data storage solutions.\\n\\nOverall, LangChain has the potential to revolutionize the way we store, manage, and interact with data on blockchain platforms.\""
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from langchain_core.prompts import ChatPromptTemplate\n",
    "from langchain_ollama.llms import OllamaLLM\n",
    "\n",
    "template = \"\"\"Question: {question}\n",
    "\n",
    "Answer: Let's think step by step.\"\"\"\n",
    "\n",
    "prompt = ChatPromptTemplate .from_template(template)\n",
    "\n",
    "model = OllamaLLM(model=\"llama3.2\")\n",
    "\n",
    "chain = prompt | model\n",
    "\n",
    "chain.invoke({\"question\": \"What is LangChain?\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "540f47cf-c92d-491b-b310-2fe6e8083205",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "expected str, got list",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[13], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m chat_template \u001b[38;5;241m=\u001b[39m \u001b[43mChatPromptTemplate\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_template\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m      2\u001b[0m \u001b[43m    \u001b[49m\u001b[43m[\u001b[49m\n\u001b[0;32m      3\u001b[0m \u001b[43m        \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msystem\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mYou are a helpful assistance that gives one line definition of the word asked by user\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m      4\u001b[0m \u001b[43m        \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mhuman\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{user_input}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m      5\u001b[0m \u001b[43m    \u001b[49m\u001b[43m]\u001b[49m\n\u001b[0;32m      6\u001b[0m \u001b[43m)\u001b[49m\n\u001b[0;32m      9\u001b[0m messages \u001b[38;5;241m=\u001b[39m chat_template\u001b[38;5;241m.\u001b[39mformat_message(user_input\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTranslucent\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m     10\u001b[0m messages\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\langchain_core\\prompts\\chat.py:1120\u001b[0m, in \u001b[0;36mChatPromptTemplate.from_template\u001b[1;34m(cls, template, **kwargs)\u001b[0m\n\u001b[0;32m   1106\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[0;32m   1107\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfrom_template\u001b[39m(\u001b[38;5;28mcls\u001b[39m, template: \u001b[38;5;28mstr\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ChatPromptTemplate:\n\u001b[0;32m   1108\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Create a chat prompt template from a template string.\u001b[39;00m\n\u001b[0;32m   1109\u001b[0m \n\u001b[0;32m   1110\u001b[0m \u001b[38;5;124;03m    Creates a chat template consisting of a single message assumed to be from\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1118\u001b[0m \u001b[38;5;124;03m        A new instance of this class.\u001b[39;00m\n\u001b[0;32m   1119\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m-> 1120\u001b[0m     prompt_template \u001b[38;5;241m=\u001b[39m \u001b[43mPromptTemplate\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_template\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtemplate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1121\u001b[0m     message \u001b[38;5;241m=\u001b[39m HumanMessagePromptTemplate(prompt\u001b[38;5;241m=\u001b[39mprompt_template)\n\u001b[0;32m   1122\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39mfrom_messages([message])\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\langchain_core\\prompts\\prompt.py:286\u001b[0m, in \u001b[0;36mPromptTemplate.from_template\u001b[1;34m(cls, template, template_format, partial_variables, **kwargs)\u001b[0m\n\u001b[0;32m    246\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[0;32m    247\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfrom_template\u001b[39m(\n\u001b[0;32m    248\u001b[0m     \u001b[38;5;28mcls\u001b[39m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    253\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[0;32m    254\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m PromptTemplate:\n\u001b[0;32m    255\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Load a prompt template from a template.\u001b[39;00m\n\u001b[0;32m    256\u001b[0m \n\u001b[0;32m    257\u001b[0m \u001b[38;5;124;03m    *Security warning*:\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    283\u001b[0m \u001b[38;5;124;03m        The prompt template loaded from the template.\u001b[39;00m\n\u001b[0;32m    284\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m--> 286\u001b[0m     input_variables \u001b[38;5;241m=\u001b[39m \u001b[43mget_template_variables\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtemplate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtemplate_format\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    287\u001b[0m     _partial_variables \u001b[38;5;241m=\u001b[39m partial_variables \u001b[38;5;129;01mor\u001b[39;00m {}\n\u001b[0;32m    289\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m _partial_variables:\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\langchain_core\\prompts\\string.py:255\u001b[0m, in \u001b[0;36mget_template_variables\u001b[1;34m(template, template_format)\u001b[0m\n\u001b[0;32m    252\u001b[0m     input_variables \u001b[38;5;241m=\u001b[39m _get_jinja2_variables_from_template(template)\n\u001b[0;32m    253\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m template_format \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mf-string\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m    254\u001b[0m     input_variables \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m--> 255\u001b[0m         v \u001b[38;5;28;01mfor\u001b[39;00m _, v, _, _ \u001b[38;5;129;01min\u001b[39;00m \u001b[43mFormatter\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparse\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtemplate\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mif\u001b[39;00m v \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m    256\u001b[0m     }\n\u001b[0;32m    257\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m template_format \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmustache\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m    258\u001b[0m     input_variables \u001b[38;5;241m=\u001b[39m mustache_template_vars(template)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\string.py:288\u001b[0m, in \u001b[0;36mFormatter.parse\u001b[1;34m(self, format_string)\u001b[0m\n\u001b[0;32m    287\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mparse\u001b[39m(\u001b[38;5;28mself\u001b[39m, format_string):\n\u001b[1;32m--> 288\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m _string\u001b[38;5;241m.\u001b[39mformatter_parser(format_string)\n",
      "\u001b[1;31mTypeError\u001b[0m: expected str, got list"
     ]
    }
   ],
   "source": [
    "from langchain_core.prompts import ChatPromptTemplate\n",
    "\n",
    "chat_template = ChatPromptTemplate.from_template(\n",
    "    [\n",
    "        (\"system\", 'You are a helpful assistance that gives one line definition of the word asked by user'),\n",
    "        (\"human\", \"{user_input}\"),\n",
    "    ]\n",
    ")\n",
    "\n",
    "\n",
    "messages = chat_template.format_message(user_input=\"Translucent\")\n",
    "messages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f564de96-a84c-46f2-94f7-b5d95b5cd9b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_ollama import ChatOllama\n",
    "llm = ChatOllama(\n",
    "    model=\"llama3.2\",\n",
    "    temprature=0"
   ]
  }
 ],
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