{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello\n"
     ]
    }
   ],
   "source": [
    "print(\"hello\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tamizh/miniconda3/envs/movies-app/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n",
      "DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): huggingface.co:443\n",
      "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /meta-llama/Meta-Llama-3.1-8B-Instruct/resolve/main/tokenizer_config.json HTTP/11\" 200 0\n",
      "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /meta-llama/Meta-Llama-3.1-8B-Instruct/resolve/main/config.json HTTP/11\" 200 0\n",
      "DEBUG:bitsandbytes.cextension:Loading bitsandbytes native library from: /home/tamizh/miniconda3/envs/movies-app/lib/python3.11/site-packages/bitsandbytes/libbitsandbytes_cuda121.so\n",
      "INFO:accelerate.utils.modeling:We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk).\n",
      "Loading checkpoint shards: 100%|██████████| 4/4 [00:07<00:00,  1.81s/it]\n",
      "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /meta-llama/Meta-Llama-3.1-8B-Instruct/resolve/main/generation_config.json HTTP/11\" 200 0\n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "import json\n",
    "\n",
    "from functions import *\n",
    "from transformers import pipeline\n",
    "from tools import tools\n",
    "\n",
    "import functions\n",
    "import torch\n",
    "from transformers import (\n",
    "    AutoModelForCausalLM,\n",
    "    AutoTokenizer,\n",
    "    BitsAndBytesConfig\n",
    ")\n",
    "\n",
    "from transformers import AutoTokenizer, AutoModelForCausalLM\n",
    "\n",
    "quantization_config = BitsAndBytesConfig(\n",
    "    load_in_8bit=True,\n",
    "    load_in_4bit=False,\n",
    "    bnb_4bit_quant_type=\"nf4\",\n",
    "    bnb_4bit_compute_dtype=torch.bfloat16\n",
    ")\n",
    "\n",
    "model_id = \"meta-llama/Meta-Llama-3.1-8B-Instruct\"\n",
    "tokenizer = AutoTokenizer.from_pretrained(model_id)\n",
    "model = AutoModelForCausalLM.from_pretrained(model_id, \n",
    "                                             device_map=\"auto\", \n",
    "                                             quantization_config=quantization_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_reasoning_chain(query):\n",
    "    user_message = f\"\"\"\n",
    "    Given the user query: \"{query}\"\n",
    "    Generate a multi-step reasoning chain to answer the query. Include steps for using available tools if necessary.\n",
    "    \"\"\"\n",
    "\n",
    "    messages = [\n",
    "        {\"role\": \"system\", \"content\": \"You are a movie search assistant bot who uses TMDB to help users find movies. Think step by step and identify the sequence of function calls that will help to answer.\"},\n",
    "        {\"role\": \"user\", \"content\": user_message},\n",
    "    ]\n",
    "\n",
    "    tokenized_chat = tokenizer.apply_chat_template(\n",
    "        messages, tools=tools, add_generation_prompt=False, tokenize=True, return_tensors=\"pt\")\n",
    "\n",
    "\n",
    "    outputs = model.generate(tokenized_chat, max_new_tokens=128)\n",
    "    # return tokenizer.batch_decode(outputs[:, tokenized_chat.shape[1]:])[0]\n",
    "    return tokenizer.batch_decode(outputs)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{{- bos_token }}\n",
      "{%- if custom_tools is defined %}\n",
      "    {%- set tools = custom_tools %}\n",
      "{%- endif %}\n",
      "{%- if not tools_in_user_message is defined %}\n",
      "    {%- set tools_in_user_message = true %}\n",
      "{%- endif %}\n",
      "{%- if not date_string is defined %}\n",
      "    {%- set date_string = \"26 Jul 2024\" %}\n",
      "{%- endif %}\n",
      "{%- if not tools is defined %}\n",
      "    {%- set tools = none %}\n",
      "{%- endif %}\n",
      "\n",
      "{#- This block extracts the system message, so we can slot it into the right place. #}\n",
      "{%- if messages[0]['role'] == 'system' %}\n",
      "    {%- set system_message = messages[0]['content']|trim %}\n",
      "    {%- set messages = messages[1:] %}\n",
      "{%- else %}\n",
      "    {%- set system_message = \"\" %}\n",
      "{%- endif %}\n",
      "\n",
      "{#- System message + builtin tools #}\n",
      "{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n",
      "{%- if builtin_tools is defined or tools is not none %}\n",
      "    {{- \"Environment: ipython\\n\" }}\n",
      "{%- endif %}\n",
      "{%- if builtin_tools is defined %}\n",
      "    {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n",
      "{%- endif %}\n",
      "{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n",
      "{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n",
      "{%- if tools is not none and not tools_in_user_message %}\n",
      "    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n",
      "    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n",
      "    {{- \"Do not use variables.\\n\\n\" }}\n",
      "    {%- for t in tools %}\n",
      "        {{- t | tojson(indent=4) }}\n",
      "        {{- \"\\n\\n\" }}\n",
      "    {%- endfor %}\n",
      "{%- endif %}\n",
      "{{- system_message }}\n",
      "{{- \"<|eot_id|>\" }}\n",
      "\n",
      "{#- Custom tools are passed in a user message with some extra guidance #}\n",
      "{%- if tools_in_user_message and not tools is none %}\n",
      "    {#- Extract the first user message so we can plug it in here #}\n",
      "    {%- if messages | length != 0 %}\n",
      "        {%- set first_user_message = messages[0]['content']|trim %}\n",
      "        {%- set messages = messages[1:] %}\n",
      "    {%- else %}\n",
      "        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n",
      "{%- endif %}\n",
      "    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n",
      "    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n",
      "    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n",
      "    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n",
      "    {{- \"Do not use variables.\\n\\n\" }}\n",
      "    {%- for t in tools %}\n",
      "        {{- t | tojson(indent=4) }}\n",
      "        {{- \"\\n\\n\" }}\n",
      "    {%- endfor %}\n",
      "    {{- first_user_message + \"<|eot_id|>\"}}\n",
      "{%- endif %}\n",
      "\n",
      "{%- for message in messages %}\n",
      "    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n",
      "        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n",
      "    {%- elif 'tool_calls' in message %}\n",
      "        {%- if not message.tool_calls|length == 1 %}\n",
      "            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n",
      "        {%- endif %}\n",
      "        {%- set tool_call = message.tool_calls[0].function %}\n",
      "        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n",
      "            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n",
      "            {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n",
      "            {%- for arg_name, arg_val in tool_call.arguments | items %}\n",
      "                {{- arg_name + '=\"' + arg_val + '\"' }}\n",
      "                {%- if not loop.last %}\n",
      "                    {{- \", \" }}\n",
      "                {%- endif %}\n",
      "                {%- endfor %}\n",
      "            {{- \")\" }}\n",
      "        {%- else  %}\n",
      "            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n",
      "            {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n",
      "            {{- '\"parameters\": ' }}\n",
      "            {{- tool_call.arguments | tojson }}\n",
      "            {{- \"}\" }}\n",
      "        {%- endif %}\n",
      "        {%- if builtin_tools is defined %}\n",
      "            {#- This means we're in ipython mode #}\n",
      "            {{- \"<|eom_id|>\" }}\n",
      "        {%- else %}\n",
      "            {{- \"<|eot_id|>\" }}\n",
      "        {%- endif %}\n",
      "    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n",
      "        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n",
      "        {%- if message.content is mapping or message.content is iterable %}\n",
      "            {{- message.content | tojson }}\n",
      "        {%- else %}\n",
      "            {{- message.content }}\n",
      "        {%- endif %}\n",
      "        {{- \"<|eot_id|>\" }}\n",
      "    {%- endif %}\n",
      "{%- endfor %}\n",
      "{%- if add_generation_prompt %}\n",
      "    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n",
      "{%- endif %}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(tokenizer.chat_template)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'type': 'function',\n",
       "  'function': {'name': 'search_person',\n",
       "   'description': 'Search for people in the entertainment industry.',\n",
       "   'parameters': {'type': 'object',\n",
       "    'properties': {'query': {'type': 'string',\n",
       "      'description': 'The search query for the person'},\n",
       "     'include_adult': {'type': 'boolean',\n",
       "      'description': 'Include adult (pornography) content in the results',\n",
       "      'default': False},\n",
       "     'language': {'type': 'string',\n",
       "      'description': 'Language for the search results',\n",
       "      'default': 'en-US'},\n",
       "     'page': {'type': 'integer',\n",
       "      'description': 'Page number of results',\n",
       "      'default': 1}},\n",
       "    'required': ['query']}}},\n",
       " {'type': 'function',\n",
       "  'function': {'name': 'get_person_details',\n",
       "   'description': 'Get detailed information about a specific person.',\n",
       "   'parameters': {'type': 'object',\n",
       "    'properties': {'person_id': {'type': 'integer',\n",
       "      'description': 'The ID of the person to get details for'},\n",
       "     'language': {'type': 'string',\n",
       "      'description': 'Language for the person details',\n",
       "      'default': 'en-US'},\n",
       "     'append_to_response': {'type': 'string',\n",
       "      'description': \"Comma-separated list of additional details to append to the response (e.g., 'images,credits')\"}},\n",
       "    'required': ['person_id']}}}]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tools = [\n",
    "    {'type': 'function', 'function': {'name': 'search_person'}},\n",
    "    {'type': 'function', 'function': {'name': 'get_person_details'}} \n",
    "]\n",
    "\n",
    "messages = [\n",
    "        {\"role\": \"system\", \"content\": \"You are a movie search assistant bot who uses TMDB to help users find movies. Think step by step and identify the sequence of function calls that will help to answer.\"},\n",
    "        {\"role\": \"user\", \"content\": \"\"\"Generate a multi-step reasoning chain to answer the query. Include steps for using available tools if necessary.\n",
    "        Reasoning chain:\n",
    "        \"\"\"},\n",
    "        {\"role\": \"assistant\", \"content\": \"Model response\"},\n",
    "    ]\n",
    "\n",
    "\n",
    "expected_rendered_text = \"\"\"\n",
    "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n",
    "\n",
    "Environment: ipython\n",
    "Cutting Knowledge Date: December 2023\n",
    "Today Date: 26 Jul 2024\n",
    "\n",
    "You are a movie search assistant bot who uses TMDB to help users find movies. Think step by step and identify the sequence of function calls that will help to answer.<|eot_id|>\n",
    "<|start_header_id|>user<|end_header_id|>\n",
    "Generate a multi-step reasoning chain to answer the query. Include steps for using available tools if necessary.\n",
    "<|eot_id|>\n",
    "<|start_header_id|>assistant<|end_header_id|>model_response<|eot_id|>\n",
    "<|start_header_id|>user<|end_header_id|>\n",
    "Given the following functions, please respond with a JSON for a function call with its proper arguments that best answers the given prompt.\n",
    "\n",
    "Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.Do not use variables.\n",
    "\n",
    "{\n",
    "    \"type\": \"function\",\n",
    "    \"function\": {\n",
    "        \"name\": \"discover_movie\"}\n",
    "}\n",
    "\n",
    "{\n",
    "    \"type\": \"function\",\n",
    "    \"function\": {\n",
    "        \"name\": \"get_person_details\"}\n",
    "}\n",
    "\"\"\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n",
      "\n",
      "Environment: ipython\n",
      "Cutting Knowledge Date: December 2023\n",
      "Today Date: 26 Jul 2024\n",
      "\n",
      "You are a movie search assistant bot who uses TMDB to help users find movies. Think step by step and identify the sequence of function calls that will help to answer.<|eot_id|><|start_header_id|>user<|end_header_id|>\n",
      "\n",
      "Given the following functions, please respond with a JSON for a function call with its proper arguments that best answers the given prompt.\n",
      "\n",
      "Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.Do not use variables.\n",
      "\n",
      "{\n",
      "    \"type\": \"function\",\n",
      "    \"function\": {\n",
      "        \"name\": \"discover_movie\",\n",
      "        \"description\": \"Find movies using over 30 filters and sort options\",\n",
      "        \"parameters\": {\n",
      "            \"type\": \"object\",\n",
      "            \"properties\": {\n",
      "                \"region\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"ISO 3166-1 code to filter release dates\"\n",
      "                },\n",
      "                \"sort_by\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"Sort the results\"\n",
      "                },\n",
      "                \"release_date.gte\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"Filter and only include movies that have a release date (looking at all release dates) that is greater or equal to the specified value\"\n",
      "                },\n",
      "                \"release_date.lte\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"Filter and only include movies that have a release date (looking at all release dates) that is less than or equal to the specified value\"\n",
      "                },\n",
      "                \"with_release_type\": {\n",
      "                    \"type\": \"integer\",\n",
      "                    \"description\": \"Specify a comma (AND) or pipe (OR) separated value to filter release types\"\n",
      "                },\n",
      "                \"year\": {\n",
      "                    \"type\": \"integer\",\n",
      "                    \"description\": \"Filter the results to only include movies that have a release year that equals the specified value\"\n",
      "                },\n",
      "                \"with_cast\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"A comma separated list of person ID's to filter the results with\"\n",
      "                },\n",
      "                \"with_crew\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"A comma separated list of person ID's to filter the results with\"\n",
      "                },\n",
      "                \"with_people\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"A comma separated list of person ID's to filter the results with\"\n",
      "                },\n",
      "                \"with_companies\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"A comma separated list of production company ID's to filter the results with\"\n",
      "                },\n",
      "                \"with_genres\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"A comma separated list of genre ID's to filter the results with\"\n",
      "                },\n",
      "                \"without_genres\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"A comma separated list of genre ID's to exclude from the results\"\n",
      "                },\n",
      "                \"with_keywords\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"A comma separated list of keyword ID's to filter the results with\"\n",
      "                },\n",
      "                \"without_keywords\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"A comma separated list of keyword ID's to exclude from the results\"\n",
      "                }\n",
      "            },\n",
      "            \"required\": []\n",
      "        }\n",
      "    }\n",
      "}\n",
      "\n",
      "{\n",
      "    \"type\": \"function\",\n",
      "    \"function\": {\n",
      "        \"name\": \"get_movie_details\",\n",
      "        \"description\": \"Get the top level details of a movie by ID\",\n",
      "        \"parameters\": {\n",
      "            \"type\": \"object\",\n",
      "            \"properties\": {\n",
      "                \"movie_id\": {\n",
      "                    \"type\": \"integer\",\n",
      "                    \"description\": \"The ID of the movie to get details for\"\n",
      "                },\n",
      "                \"append_to_response\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"Comma-separated list of sub requests to append to the response\"\n",
      "                }\n",
      "            },\n",
      "            \"required\": [\n",
      "                \"movie_id\"\n",
      "            ]\n",
      "        }\n",
      "    }\n",
      "}\n",
      "\n",
      "{\n",
      "    \"type\": \"function\",\n",
      "    \"function\": {\n",
      "        \"name\": \"search_person\",\n",
      "        \"description\": \"Search for people in the entertainment industry.\",\n",
      "        \"parameters\": {\n",
      "            \"type\": \"object\",\n",
      "            \"properties\": {\n",
      "                \"query\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"The search query for the person\"\n",
      "                },\n",
      "                \"include_adult\": {\n",
      "                    \"type\": \"boolean\",\n",
      "                    \"description\": \"Include adult (pornography) content in the results\",\n",
      "                    \"default\": false\n",
      "                },\n",
      "                \"language\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"Language for the search results\",\n",
      "                    \"default\": \"en-US\"\n",
      "                },\n",
      "                \"page\": {\n",
      "                    \"type\": \"integer\",\n",
      "                    \"description\": \"Page number of results\",\n",
      "                    \"default\": 1\n",
      "                }\n",
      "            },\n",
      "            \"required\": [\n",
      "                \"query\"\n",
      "            ]\n",
      "        }\n",
      "    }\n",
      "}\n",
      "\n",
      "{\n",
      "    \"type\": \"function\",\n",
      "    \"function\": {\n",
      "        \"name\": \"get_person_details\",\n",
      "        \"description\": \"Get detailed information about a specific person.\",\n",
      "        \"parameters\": {\n",
      "            \"type\": \"object\",\n",
      "            \"properties\": {\n",
      "                \"person_id\": {\n",
      "                    \"type\": \"integer\",\n",
      "                    \"description\": \"The ID of the person to get details for\"\n",
      "                },\n",
      "                \"language\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"Language for the person details\",\n",
      "                    \"default\": \"en-US\"\n",
      "                },\n",
      "                \"append_to_response\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"Comma-separated list of additional details to append to the response (e.g., 'images,credits')\"\n",
      "                }\n",
      "            },\n",
      "            \"required\": [\n",
      "                \"person_id\"\n",
      "            ]\n",
      "        }\n",
      "    }\n",
      "}\n",
      "\n",
      "{\n",
      "    \"type\": \"function\",\n",
      "    \"function\": {\n",
      "        \"name\": \"get_movie_genres\",\n",
      "        \"description\": \"Get the list of official genres for movies.\",\n",
      "        \"parameters\": {\n",
      "            \"type\": \"object\",\n",
      "            \"properties\": {\n",
      "                \"language\": {\n",
      "                    \"type\": \"string\",\n",
      "                    \"description\": \"Language for the genre names\",\n",
      "                    \"default\": \"en-US\"\n",
      "                }\n",
      "            }\n",
      "        }\n",
      "    }\n",
      "}\n",
      "\n",
      "Given the user query: \"What are the genres of the movie 'The Dark Knight'?\"\n",
      "    Generate a multi-step reasoning chain to answer the query. Include steps for using available tools if necessary.<|eot_id|>\n"
     ]
    }
   ],
   "source": [
    "import textwrap\n",
    "\n",
    "\n",
    "query = \"What are the genres of the movie 'The Dark Knight'?\"\n",
    "\n",
    "user_message = f\"\"\"\n",
    "    Given the user query: \"{query}\"\n",
    "    Generate a multi-step reasoning chain to answer the query. Include steps for using available tools if necessary.\n",
    "    \"\"\"\n",
    "messages = [\n",
    "        {\"role\": \"system\", \"content\": \"You are a movie search assistant bot who uses TMDB to help users find movies. Think step by step and identify the sequence of function calls that will help to answer.\"},\n",
    "        {\"role\": \"user\", \"content\": user_message},\n",
    "    ]\n",
    "\n",
    "chat = tokenizer.apply_chat_template(\n",
    "        messages, tools=tools, \n",
    "        add_generation_prompt=False, \n",
    "        tools_in_user_message=True,\n",
    "        tokenize=False, \n",
    "        return_tensors=\"pt\")\n",
    "print(chat)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = generate_reasoning_chain(\"What are the genres of the movie 'The Dark Knight'?\")\n",
    "print(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "<|begin_of_text|>\n",
    "<|start_header_id|>system<|end_header_id|>          {{ system_prompt }}<|eot_id|>\n",
    "<|start_header_id|>user<|end_header_id|>            {{ user_message_1 }}<|eot_id|>\n",
    "<|start_header_id|>assistant<|end_header_id|>       <|python_tag|>{{ model_tool_call_1 }}<|eom_id|>\n",
    "<|start_header_id|>ipython<|end_header_id|>         {{ tool_response }}<|eot_id|>\n",
    "<|start_header_id|>assistant<|end_header_id|>       {{ model_response_based_on_tool_response }}<|eot_id|>\n",
    "\"\"\"\n",
    "print(response)"
   ]
  }
 ],
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   "language": "python",
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    "name": "ipython",
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