{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d581e8a1",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'RunnableRetry' object has no attribute 'with_fallback'",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mAttributeError\u001b[39m                            Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[22]\u001b[39m\u001b[32m, line 23\u001b[39m\n\u001b[32m     19\u001b[39m     stop_after_attempt= \u001b[32m3\u001b[39m\n\u001b[32m     20\u001b[39m )\n\u001b[32m     21\u001b[39m llm2_with_retry = llm2.with_retry(stop_after_attempt=\u001b[32m3\u001b[39m)\n\u001b[32m     22\u001b[39m \n\u001b[32m---> \u001b[39m\u001b[32m23\u001b[39m runner = llm_with_retry.with_fallback(llm2_with_retry)\n\u001b[32m     24\u001b[39m \n\u001b[32m     25\u001b[39m \u001b[38;5;66;03m#Create a prompt template\u001b[39;00m\n\u001b[32m     26\u001b[39m prompt = ChatPromptTemplate.from_template(\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/Projects/longchain/first_chain/lib/python3.14/site-packages/pydantic/main.py:1042\u001b[39m, in \u001b[36mBaseModel.__getattr__\u001b[39m\u001b[34m(self, item)\u001b[39m\n\u001b[32m   1039\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msuper\u001b[39m().\u001b[34m__getattribute__\u001b[39m(item)  \u001b[38;5;66;03m# Raises AttributeError if appropriate\u001b[39;00m\n\u001b[32m   1040\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m   1041\u001b[39m     \u001b[38;5;66;03m# this is the current error\u001b[39;00m\n\u001b[32m-> \u001b[39m\u001b[32m1042\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(\u001b[33mf\u001b[39m\u001b[33m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(\u001b[38;5;28mself\u001b[39m).\u001b[34m__name__\u001b[39m\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[33m object has no attribute \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mitem\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[33m'\u001b[39m)\n",
      "\u001b[31mAttributeError\u001b[39m: 'RunnableRetry' object has no attribute 'with_fallback'"
     ]
    }
   ],
   "source": [
    "from langchain_ollama import ChatOllama\n",
    "from langchain_core.prompts import ChatPromptTemplate\n",
    "from langchain_core.caches import InMemoryCache \n",
    "from langchain_core.globals import set_llm_cache\n",
    "\n",
    "set_llm_cache(InMemoryCache())\n",
    "\n",
    "#Initialize the language model\n",
    "llm = ChatOllama(\n",
    "    model=\"gemma4:12b-mlx\",\n",
    "    base_url=\"http://mini2.dorceus.local:11434\"\n",
    ")\n",
    "llm2 = ChatOllama(\n",
    "    model=\"qwen3.5:35b-mlx\",\n",
    "    base_url=\"http://studio1.dorceus.local:11434\"\n",
    ")\n",
    "\n",
    "llm_with_retry = llm.with_retry(\n",
    "    stop_after_attempt= 3\n",
    ")\n",
    "llm2_with_retry = llm2.with_retry(stop_after_attempt=3)\n",
    "\n",
    "runner = llm_with_retry.with_fallbacks([llm2_with_retry])\n",
    "\n",
    "#Create a prompt template\n",
    "prompt = ChatPromptTemplate.from_template(\n",
    "    \"Write a brief, engaging paragraph about {topic}\"\n",
    ")\n",
    "\n",
    "prompt2  = ChatPromptTemplate.from_template(\n",
    "    \"Summarize the following in one sentence : {paragraph}\"\n",
    ")\n",
    "\n",
    "prompt3 = ChatPromptTemplate.from_template(\n",
    "    \"Suggest some side dished that goes with the following food description : {food_description}\"\n",
    ")\n",
    "\n",
    "#Create the chain \n",
    "# chain = prompt | llm\n",
    "# chain2 = prompt2 | llm2\n",
    "# chain3 = prompt3 | llm2 \n",
    "\n",
    "#sequential chain\n",
    "# seq_chain = (\n",
    "#     {\n",
    "#         \"paragraph\" : prompt,\n",
    "#         \"food_description\" : prompt2\n",
    "#     }\n",
    "#     | prompt2 \n",
    "#     | prompt3 \n",
    "#     | llm2\n",
    "# )\n",
    "\n",
    "seq_chain = (\n",
    "    prompt\n",
    "    | (lambda message : {\"paragraph\" : message.content})\n",
    "    | prompt2 \n",
    "    | (lambda message : {\"food_description\" : message.content})\n",
    "    | prompt3 \n",
    "    | runner\n",
    ")\n",
    "\n",
    "for i in range(1,5) :\n",
    "    response = chain.invoke(\n",
    "        {\"topic\": \"adobong baboy\"}\n",
    "    )\n",
    "    #print(response.content)\n",
    "\n",
    "print(\"DONE\")\n",
    "\n",
    "#Run the chain\n",
    "# result = chain.invoke({\"topic\": \"adobong baboy\"})\n",
    "# result2 = chain2.invoke({\"topic\": result.content})\n",
    "# result3 = chain3.invoke({\"food_description\" : result2.content})\n",
    "# print(result.content)\n",
    "# print(result2.content)\n",
    "# print(result3.content)\n",
    "\n"
   ]
  }
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