{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bdede0af",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ollama\n",
    "\n",
    "model = \"llama3\"\n",
    "messages = [\n",
    "    {\"role\": \"user\", \"content\": \"Testing ollama type 5 random words\"}\n",
    "]\n",
    "\n",
    "response = ollama.chat(model=model, messages=messages)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "81b38610",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A fun challenge!\n",
      "\n",
      "Here are 5 random words, type 5:\n",
      "\n",
      "1. Fjord\n",
      "2. Quiche\n",
      "3. Ninja\n",
      "4. Galaxy\n",
      "5. Pocket\n"
     ]
    }
   ],
   "source": [
    "print(response[\"message\"][\"content\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "066f73af",
   "metadata": {},
   "outputs": [],
   "source": [
    "model2 = \"bk_test\"\n",
    "\n",
    "response2 = ollama.chat(model=model2, messages=messages)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4a75aff1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Arre yaar, lemme check dat out! *tapping on computer* Okay, here are 5 random words:\n",
      "\n",
      "1. **Mango**\n",
      "2. **Pyjamas**\n",
      "3. **Chai**\n",
      "4. **Bollywood**\n",
      "5. **Diwali**\n",
      "\n",
      "How's dat, yaar?\n"
     ]
    }
   ],
   "source": [
    "print(response2[\"message\"][\"content\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c8c310d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_llava = \"llava\"\n",
    "messages_llava = [\n",
    "    {\n",
    "        \"role\": \"user\",\n",
    "        \"content\": \"Explain the code in this image\",\n",
    "        \"images\": [\n",
    "            \"image4.png\"\n",
    "        ]\n",
    "    }\n",
    "]\n",
    "response_llava = ollama.chat(model=model_llava, messages=messages_llava)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "de949fdd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The image shows a computer screen with a Python script open in a text editor. The script appears to be a code snippet that is printing out a list of strings in a specific order. Here's the code:\n",
      "\n",
      "```python\n",
      "for i in range(len(my_list)):\n",
      "    print(\"Word {} in {}\".format(i, my_list[i]))\n",
      "```\n",
      "\n",
      "This code is using a `for` loop to iterate through the elements of a list called `my_list`. The loop variable `i` is used to keep track of the current index in the loop. For each iteration, the code prints out a formatted string using the `print` function. The string format is `\"Word {} in {}\".format(i, my_list[i])`.\n",
      "\n",
      "The `format` method is used to replace placeholders in the string with the actual values. The placeholder `{}` is replaced with the value of `i` and the second placeholder `{}` is replaced with the value of `my_list[i]`. This results in the string `\"Word {} in {}\".format(i, my_list[i])` being replaced with `\"Word i in my_list[i]\"` for each iteration.\n",
      "\n",
      "The `range` function is used to generate a sequence of numbers from 0 to the length of `my_list - 1`. This allows the loop to iterate through all elements of the list.\n",
      "\n",
      "The output of the script would be a list of words, each word followed by its position within the list. The output would look something like this:\n",
      "\n",
      "```\n",
      "Word 0 in my_list[0]\n",
      "Word 1 in my_list[1]\n",
      "Word 2 in my_list[2]\n",
      "...\n",
      "Word n in my_list[n]\n",
      "```\n",
      "\n",
      "where `my_list` is the list being iterated over and `n` is the length of the list. \n"
     ]
    }
   ],
   "source": [
    "print(response_llava[\"message\"][\"content\"])"
   ]
  }
 ],
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