Add support to parse Openai function call input and results format to mistral_rubra format. TODO: need to clean up prints after testing.

examples/server/python-parser.hpp

@@ -39,7 +39,7 @@ static void parseFunctionCalls(const TSNode& node, std::vector<json>& calls, con
     if (strcmp(type, "call") == 0) {
         
         json call = {
-            {"id", calls.size()},
+            {"id", std::to_string(calls.size())},
             {"name", ""},
             {"args", json::array()},
             {"kwargs", json::object()}

examples/server/utils.hpp

@@ -10,6 +10,7 @@
 #include <vector>
 #include <sstream>
 #include <random>
+#include <unordered_map>
 
 #define DEFAULT_OAICOMPAT_MODEL "gpt-3.5-turbo-0613"
 
@@ -491,19 +492,123 @@ static json oaicompat_completion_params_parse(
     //    function_str = default_tool_formatter(body["functions"]);
        function_str = rubra_format_function_call_str(body["functions"]);
     }
-
+    printf("\n=============Formatting Input from OPENAI format...============\n");
     if (function_str != "") {
         const std::vector<json> expand_messages = [&]() {
-            std::vector<json> temp_vec = body["messages"];
+            // std::vector<json> temp_vec = body["messages"];
-            if (body["messages"][0]["role"] == "system") {
+            // if (body["messages"][0]["role"] == "system") {
-                std::string old_content = temp_vec[0]["content"];
+            //     std::string old_content = temp_vec[0]["content"];
-                temp_vec[0]["content"] = old_content + "\n" + function_str;
+            //     temp_vec[0]["content"] = old_content + "\n" + function_str;
+            // }
+            // else {
+            //     json function_call;
+            //     function_call["role"] = "system";
+            //     function_call["content"] = "You are a helpful assistant.\n" + function_str;
+            //     temp_vec.push_back(function_call);
+            // }
+            std::vector<json> temp_vec;
+            std::unordered_map<std::string, std::string> func_observation_map;
+            for (size_t i = 0; i < body["messages"].size(); ++i) {
+                printf("body[\"messages\"][%d][\"role\"] = %s\n", i, body["messages"][i]["role"].get<std::string>().c_str());
+                printf("Message: %s\n", body["messages"][i].dump().c_str());
+                printf("%d\n", body["messages"][i].contains("tool_calls"));
+
+                if (body["messages"][i]["role"] != "tool" and func_observation_map.size() > 0) {
+                    // insert the observation from the tool call before the next message
+                    std::string observation_str = "";
+                    for (const auto& [key, value] : func_observation_map) {
+                        if (observation_str != "") {
+                            observation_str += ", ";
+                        }
+                        observation_str += value;
+                    }
+                    observation_str = std::string("<<observation>>") + "[" + observation_str + "]";
+                    json observation_call;
+                    observation_call["role"] = "observation";
+                    observation_call["content"] = observation_str;
+                    temp_vec.push_back(observation_call);
+                    func_observation_map.clear();
+                }
+
+                if (i == 0){
+                    if (body["messages"][0]["role"] == "system") {
+                        std::string old_content = body["messages"][0]["content"];
+                        json function_call;
+                        function_call["role"] = "system";
+                        function_call["content"] = old_content + "\n" + function_str;
+                        temp_vec.push_back(function_call);
+                    }
+                    else { // insert a system message of tool definition before the first message
+                        json function_call;
+                        function_call["role"] = "system";
+                        function_call["content"] = "You are a helpful assistant.\n" + function_str;
+                        temp_vec.push_back(function_call);
+                        temp_vec.push_back(body["messages"][0]);
+                    }
+                }
+                // else if (body["messages"][i]["role"] == "assistant" and (body["messages"][i]["content"].is_null() or body["messages"][i]["content"]=="") and !body["messages"][i]["tool_calls"].is_null() and !body["messages"][i]["tool_calls"].empty()){
+                else if (body["messages"][i]["role"] == "assistant" and body["messages"][i].contains("tool_calls")){
+                    printf("Tool call detected\n");
+                    // convert OpenAI function call format to Rubra format
+                    std::string tool_call_str = "";
+                    printf("Tool calls: %s\n", body["messages"][i]["tool_calls"].dump().c_str());
+                    for (const auto & tool_call : body["messages"][i]["tool_calls"]) {
+                        printf("Tool call id: %s\n", tool_call["id"].get<std::string>().c_str());
+                        std::string func_str = "";
+                        func_observation_map[tool_call["id"].get<std::string>()] = ""; // initialize with empty value and later should be updated with the actual value from "tool_call" role message
+                        json args = json::parse(tool_call["function"]["arguments"].get<std::string>()); // TODO: catch the exceptions 
+                        for (auto& arg : args.items()) {
+                            if (func_str != "") {
+                                func_str += ", ";
+                            }
+                            func_str += arg.key() + "=" + arg.value().dump();
+                        }
+                        func_str = tool_call["function"]["name"].get<std::string>() + "(" + func_str + ")";
+                        if (tool_call_str != "") {
+                            tool_call_str += ", ";
+                        }
+                        tool_call_str += func_str;
+                    }
+                    tool_call_str = std::string("<<functions>>") + "[" + tool_call_str + "]";
+                    printf("Tool call string: %s\n", tool_call_str.c_str());
+
+                    json function_call;
+                    function_call["role"] = "function";
+                    function_call["content"] = tool_call_str;
+                    temp_vec.push_back(function_call);
+                }
+                else if (body["messages"][i]["role"] == "tool") {
+                    printf("Observation detected\n");
+                    printf(body["messages"][i].dump().c_str());
+                    std::string tool_call_id = body["messages"][i]["tool_call_id"].get<std::string>();
+                    if (func_observation_map.find(tool_call_id) != func_observation_map.end()) {
+                        func_observation_map[tool_call_id] = body["messages"][i]["content"].get<std::string>();
+                    } else {
+                        LOG_ERROR("Tool call id not found in the map", {{"tool_call_id", tool_call_id}});
+                        // TODO: the input is not valid in this case, should return an error
+                    }
+
+                }
+                else {
+                    temp_vec.push_back(body["messages"][i]);
+                }
+                
             }
-            else {
+            if (func_observation_map.size() > 0) {
-                json function_call;
+                // insert the observation from the tool call before the next message
-                function_call["role"] = "system";
+                std::string observation_str = "";
-                function_call["content"] = "You are a helpful assistant.\n" + function_str;
+                for (const auto& [key, value] : func_observation_map) {
-                temp_vec.push_back(function_call);
+                    if (observation_str != "") {
+                        observation_str += ", ";
+                    }
+                    observation_str += value;
+                }
+                observation_str = std::string("<<observation>>") + "[" + observation_str + "]";
+                json observation_call;
+                observation_call["role"] = "observation";
+                observation_call["content"] = observation_str;
+                temp_vec.push_back(observation_call);
+                func_observation_map.clear();
             }
             return temp_vec;
         }();

llama.cpp

@@ -14518,7 +14518,6 @@ static int32_t llama_chat_apply_template_internal(
         // construct the prompt
         bool is_inside_turn = true; // skip BOS at the beginning
         // ss << "[INST] ";
-        
         for (auto message : chat) {
             std::string content = strip_message ? trim(message->content) : message->content;
             std::string role(message->role);
@@ -14537,7 +14536,7 @@ static int32_t llama_chat_apply_template_internal(
                 ss << "[INST]" << content << " [/INST]";
             } else {
                 ss << (space_around_response ? " " : "") << content << (space_around_response ? " " : "") << "</s>";
-                is_inside_turn = false;
+                // is_inside_turn = false;
             }
         }
         // llama2 templates seem to not care about "add_generation_prompt"

test_llamacpp.ipynb

@@ -1,5 +1,82 @@
 {
  "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run_completion(chat_method, user_query):\n",
+    "    print(chat_method)\n",
+    "    system_prompt = \"You are a helpful assistant.\"\n",
+    "    functions = [\n",
+    "      {\n",
+    "          \"type\": \"function\",\n",
+    "        \"function\": {\n",
+    "          \"name\": \"getCurrentWeather\",\n",
+    "          \"description\": \"Get the weather in location\",\n",
+    "          \"parameters\": {\n",
+    "            \"type\": \"object\",\n",
+    "            \"properties\": {\n",
+    "              \"location\": {\"type\": \"string\", \"description\": \"The city and state e.g. San Francisco, CA\"},\n",
+    "              \"unit\": {\"type\": \"string\", \"enum\": [\"c\", \"f\"]}\n",
+    "            },\n",
+    "            \"required\": [\"location\"]\n",
+    "          }\n",
+    "        }\n",
+    "      },\n",
+    "      {    \"type\": \"function\",\n",
+    "        \"function\":\n",
+    "        {\n",
+    "            \"name\": \"orderUmbrella\",\n",
+    "            \"description\": \"Do this to help user to order an umbrella online\", \n",
+    "            \"parameters\": {\n",
+    "                \"type\": \"object\",\n",
+    "                \"properties\": {\n",
+    "                    \"number_to_buy\": {\n",
+    "                        \"type\": \"integer\",\n",
+    "                        \"description\": \"the amount of umbrellas to buy\"\n",
+    "                    }\n",
+    "                },\n",
+    "                \"required\": [\n",
+    "                    \"number_to_buy\"\n",
+    "                ]\n",
+    "            }\n",
+    "        }},\n",
+    "    ]\n",
+    "    # functions = [{\"type\": \"function\",\"function\":{\"name\":\"calculate_distance\",\"description\":\"Calculate the distance between two locations\",\"parameters\":{\"type\":\"object\",\"properties\":{\"origin\":{\"type\":\"string\",\"description\":\"The starting location\"},\"destination\":{\"type\":\"string\",\"description\":\"The destination location\"},\"mode\":{\"type\":\"string\",\"description\":\"The mode of transportation\"}},\"required\":[\"origin\",\"destination\",\"mode\"]}}},{\"type\": \"function\",\"function\":{\"name\":\"generate_password\",\"description\":\"Generate a random password\",\"parameters\":{\"type\":\"object\",\"properties\":{\"length\":{\"type\":\"integer\",\"description\":\"The length of the password\"}},\"required\":[\"length\"]}}}]\n",
+    "\n",
+    "    msgs = [{\"role\": \"system\", \"content\":system_prompt} ,{\"role\": \"user\", \"content\": user_query}]\n",
+    "\n",
+    "    res = chat_method(user_query, \"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
+    "    print(f\"First Response:\")\n",
+    "    for tool_call in res.message.tool_calls:\n",
+    "        print(f\"Tool Call: {tool_call.id}, {tool_call.function}\")\n",
+    "    assistant_message = res.message\n",
+    "    tool_calls = []\n",
+    "    for tool_call in assistant_message.tool_calls:\n",
+    "        tool_calls.append( {\n",
+    "                            \"id\": tool_call.id,\n",
+    "                            \"function\": {\"name\": tool_call.function.name,\n",
+    "                                        \"arguments\": tool_call.function.arguments},\n",
+    "                            \"type\": \"function\",\n",
+    "                        })\n",
+    "    msgs.append({\"role\": \"assistant\",  \"tool_calls\": tool_calls})\n",
+    "    \n",
+    "    for i, tool_call in enumerate(assistant_message.tool_calls):\n",
+    "        if tool_call.function.name == \"getCurrentWeather\":\n",
+    "            msgs.append({\"role\": \"tool\", \"tool_call_id\": str(assistant_message.tool_calls[i].id), \"name\": assistant_message.tool_calls[i].function.name, \"content\": f\"temprature is {i * 50} degree\"})\n",
+    "        else:\n",
+    "            msgs.append({\"role\": \"tool\", \"tool_call_id\": str(assistant_message.tool_calls[i].id), \"name\": assistant_message.tool_calls[i].function.name, \"content\": f\"Order placed.\"})\n",
+    "        \n",
+    "\n",
+    "    print(\"Print before second response...\")\n",
+    "    res_next = chat_method(user_query, \"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
+    "    for m in msgs:\n",
+    "        print(m)\n",
+    "    print(f\"Second Response: {res_next.message}\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -9,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17,8 +94,8 @@
     "\n",
     "\n",
     "def get_oai_response(prompt, model, functions, msgs):\n",
-    "  openai.api_key = \"sk-\"\n",
+    "  openai.api_key = \"sk-\" ## Add your API key here\n",
-    "  # openai.base_url = \"http://localhost:8019/v1/\"\n",
+    "  openai.base_url = \"https://api.openai.com/v1/\"\n",
     "  \n",
     "  try:\n",
     "    completion = openai.chat.completions.create(\n",
@@ -38,66 +115,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, role='assistant', function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_NVPCmdRCtY9lO7sVhOFRPS6R', function=Function(arguments='{\"location\":\"Boston, MA\",\"unit\":\"f\"}', name='getCurrentWeather'), type='function')]))\n"
+      "<function get_oai_response at 0x10b9c93f0>\n",
+      "First Response:\n",
+      "Tool Call: call_FYLEpX5CVo2dqSyNupcgtFak, Function(arguments='{\"number_to_buy\":2}', name='orderUmbrella')\n",
+      "Print before second response...\n",
+      "{'role': 'system', 'content': 'You are a helpful assistant.'}\n",
+      "{'role': 'user', 'content': 'order 2 umbrellas'}\n",
+      "{'role': 'assistant', 'tool_calls': [{'id': 'call_FYLEpX5CVo2dqSyNupcgtFak', 'function': {'name': 'orderUmbrella', 'arguments': '{\"number_to_buy\":2}'}, 'type': 'function'}]}\n",
+      "{'role': 'tool', 'tool_call_id': 'call_FYLEpX5CVo2dqSyNupcgtFak', 'name': 'orderUmbrella', 'content': 'Order placed.'}\n",
+      "Second Response: ChatCompletionMessage(content=\"I've placed the order for 2 umbrellas for you. Is there anything else I can help with?\", role='assistant', function_call=None, tool_calls=None)\n"
      ]
     }
    ],
    "source": [
-    "system_prompt = \"You are a helpful assistant.\"\n",
+    "# user_query = \"What is the distance between San Francisco and Cupertino by car and by air\"\n",
-    "functions = [\n",
+    "# user_query = \"weather in boston as well as cupertino?\"\n",
-    "   {\n",
+    "user_query = \"order 2 umbrellas\"\n",
-    "      \"type\": \"function\",\n",
+    "run_completion(get_oai_response, user_query)"
-    "    \"function\": {\n",
-    "      \"name\": \"getCurrentWeather\",\n",
-    "      \"description\": \"Get the weather in location\",\n",
-    "      \"parameters\": {\n",
-    "        \"type\": \"object\",\n",
-    "        \"properties\": {\n",
-    "          \"location\": {\"type\": \"string\", \"description\": \"The city and state e.g. San Francisco, CA\"},\n",
-    "          \"unit\": {\"type\": \"string\", \"enum\": [\"c\", \"f\"]}\n",
-    "        },\n",
-    "        \"required\": [\"location\"]\n",
-    "      }\n",
-    "    }\n",
-    "  },\n",
-    "   {    \"type\": \"function\",\n",
-    "     \"function\":\n",
-    "    {\n",
-    "        \"name\": \"orderUmbrella\",\n",
-    "        \"description\": \"Do this to help user to order an umbrella online\", \n",
-    "        \"parameters\": {\n",
-    "            \"type\": \"object\",\n",
-    "            \"properties\": {\n",
-    "                \"brand_name\": {\n",
-    "                    \"type\": \"string\",\n",
-    "                    \"description\": \"The name of the umbrella brand\"\n",
-    "                }\n",
-    "            },\n",
-    "            \"required\": [\n",
-    "                \"brand_name\"\n",
-    "            ]\n",
-    "        }\n",
-    "    }},\n",
-    "]\n",
-    "\n",
-    "\n",
-    "user_query = \"check the weather in boston\"\n",
-    "# msgs = [{\"role\": \"system\", \"content\":system_prompt} ,{\"role\": \"user\", \"content\": user_query}, {\"role\": \"function\", \"content\": '<<functions>>[getCurrentWeather(location=\"Boston)]'}, {\"role\": \"observation\", \"content\": \"<<observation>>72 f, rainy.\"}\n",
-    "#         ,\n",
-    "#         {\"role\": \"assistant\", \"content\": \"The current weather in Boston is 72 degrees Fahrenheit and it's raining. Would you like to order an umbrella?\"},\n",
-    "#          {\"role\": \"user\", \"content\": \"yes pls\"},\n",
-    "#         ]\n",
-    "msgs = [{\"role\": \"system\", \"content\":system_prompt} ,{\"role\": \"user\", \"content\": user_query}]\n",
-    "\n",
-    "res = get_oai_response(user_query, \"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
-    "print(res)"
    ]
   },
   {
@@ -109,17 +150,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 72,
    "metadata": {},
-   "outputs": [
+   "outputs": [],
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content=None, role='assistant', function_call=None, tool_calls=[ChatCompletionMessageToolCall(id=0, function=[Function(arguments='{\"location\":\"Boston\",\"unit\":\"c\"}', name='getCurrentWeather')], type='function')]))\n"
-     ]
-    }
-   ],
    "source": [
     "import openai\n",
     "\n",
@@ -135,62 +168,40 @@
     "      messages=msgs,\n",
     "      tools=functions,\n",
     "      tool_choice=\"auto\",\n",
-    "      # functions=functions,\n",
-    "      # function_call=\"auto\",\n",
     "      stream=False,\n",
     "    )\n",
     "    return completion.choices[0]\n",
     "  except Exception as e:\n",
     "    print(e, model, prompt)\n",
-    "\n",
+    "\n"
-    "system_prompt = \"You are a helpful assistant.\"\n",
+   ]
-    "functions = [\n",
+  },
-    "   {\n",
+  {
-    "      \"type\": \"function\",\n",
+   "cell_type": "code",
-    "    \"function\": {\n",
+   "execution_count": 73,
-    "      \"name\": \"getCurrentWeather\",\n",
+   "metadata": {},
-    "      \"description\": \"Get the weather in location\",\n",
+   "outputs": [
-    "      \"parameters\": {\n",
+    {
-    "        \"type\": \"object\",\n",
+     "name": "stdout",
-    "        \"properties\": {\n",
+     "output_type": "stream",
-    "          \"location\": {\"type\": \"string\", \"description\": \"The city and state e.g. San Francisco, CA\"},\n",
+     "text": [
-    "          \"unit\": {\"type\": \"string\", \"enum\": [\"c\", \"f\"]}\n",
+      "<function get_mistral_rubra_response at 0x10b9cac20>\n",
-    "        },\n",
+      "First Response:\n",
-    "        \"required\": [\"location\"]\n",
+      "Tool Call: 0, Function(arguments='{\"number_to_buy\":\"2\"}', name='orderUmbrella')\n",
-    "      }\n",
+      "Print before second response...\n",
-    "    }\n",
+      "{'role': 'system', 'content': 'You are a helpful assistant.'}\n",
-    "  },\n",
+      "{'role': 'user', 'content': 'order 2 umbrellas'}\n",
-    "   {    \"type\": \"function\",\n",
+      "{'role': 'assistant', 'tool_calls': [{'id': '0', 'function': {'name': 'orderUmbrella', 'arguments': '{\"number_to_buy\":\"2\"}'}, 'type': 'function'}]}\n",
-    "     \"function\":\n",
+      "{'role': 'tool', 'tool_call_id': '0', 'name': 'orderUmbrella', 'content': 'Order placed.'}\n",
-    "    {\n",
+      "Second Response: ChatCompletionMessage(content=' Your order for 2 umbrellas has been placed.', role='assistant', function_call=None, tool_calls=None)\n"
-    "        \"name\": \"orderUmbrella\",\n",
+     ]
-    "        \"description\": \"Do this to help user to order an umbrella online\", \n",
+    }
-    "        \"parameters\": {\n",
+   ],
-    "            \"type\": \"object\",\n",
+   "source": [
-    "            \"properties\": {\n",
+    "# user_query = \"generate a password of length 10 and another of length 20\" \n",
-    "                \"brand_name\": {\n",
+    "# user_query = \"what's the weather in Boston and Cupertino?\"\n",
-    "                    \"type\": \"string\",\n",
+    "user_query = \"order 2 umbrellas\"\n",
-    "                    \"description\": \"The name of the umbrella brand\"\n",
+    "run_completion(get_mistral_rubra_response, user_query)"
-    "                }\n",
-    "            },\n",
-    "            \"required\": [\n",
-    "                \"brand_name\"\n",
-    "            ]\n",
-    "        }\n",
-    "    }},\n",
-    "]\n",
-    "\n",
-    "\n",
-    "user_query = \"check the weather in boston\"\n",
-    "# msgs = [{\"role\": \"system\", \"content\":system_prompt} ,{\"role\": \"user\", \"content\": user_query}, {\"role\": \"function\", \"content\": '<<functions>>[getCurrentWeather(location=\"Boston)]'}, {\"role\": \"observation\", \"content\": \"<<observation>>72 f, rainy.\"}\n",
-    "#         ,\n",
-    "#         {\"role\": \"assistant\", \"content\": \"The current weather in Boston is 72 degrees Fahrenheit and it's raining. Would you like to order an umbrella?\"},\n",
-    "#          {\"role\": \"user\", \"content\": \"yes pls\"},\n",
-    "#         ]\n",
-    "msgs = [{\"role\": \"system\", \"content\":system_prompt} ,{\"role\": \"user\", \"content\": user_query}]\n",
-    "\n",
-    "res = get_mistral_rubra_response(user_query, \"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
-    "print(res)"
    ]
   },
   {
@@ -202,15 +213,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      " <<functions>>[get_stock_fundermentals(symbol=\"TSLA\")]\n",
+      "None\n"
-      "<<functions>>[get_stock_fundermentals(symbol=\"GOOG\")]\n"
      ]
     }
    ],
@@ -268,7 +278,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [
     {
@@ -286,8 +296,8 @@
      "traceback": [
       "Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
       "\u001b[0m  File \u001b[1;32m~/.pyenv/versions/3.10.12/envs/py310/lib/python3.10/site-packages/IPython/core/interactiveshell.py:3548\u001b[0m in \u001b[1;35mrun_code\u001b[0m\n    exec(code_obj, self.user_global_ns, self.user_ns)\u001b[0m\n",
-      "\u001b[0m  Cell \u001b[1;32mIn[19], line 40\u001b[0m\n    result_dict = parse_function_call(function_call.strip())\u001b[0m\n",
+      "\u001b[0m  Cell \u001b[1;32mIn[47], line 40\u001b[0m\n    result_dict = parse_function_call(function_call.strip())\u001b[0m\n",
-      "\u001b[0m  Cell \u001b[1;32mIn[19], line 22\u001b[0m in \u001b[1;35mparse_function_call\u001b[0m\n    parsed_value = ast.literal_eval(value)\u001b[0m\n",
+      "\u001b[0m  Cell \u001b[1;32mIn[47], line 22\u001b[0m in \u001b[1;35mparse_function_call\u001b[0m\n    parsed_value = ast.literal_eval(value)\u001b[0m\n",
       "\u001b[0m  File \u001b[1;32m~/.pyenv/versions/3.10.12/lib/python3.10/ast.py:64\u001b[0m in \u001b[1;35mliteral_eval\u001b[0m\n    node_or_string = parse(node_or_string.lstrip(\" \\t\"), mode='eval')\u001b[0m\n",
       "\u001b[0;36m  File \u001b[0;32m~/.pyenv/versions/3.10.12/lib/python3.10/ast.py:50\u001b[0;36m in \u001b[0;35mparse\u001b[0;36m\n\u001b[0;31m    return compile(source, filename, mode, flags,\u001b[0;36m\n",
       "\u001b[0;36m  File \u001b[0;32m<unknown>:1\u001b[0;36m\u001b[0m\n\u001b[0;31m    'Boston\u001b[0m\n\u001b[0m    ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m unterminated string literal (detected at line 1)\n"
@@ -344,7 +354,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -389,7 +399,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -455,26 +465,6 @@
     "\n",
     "print(functions)\n"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "46"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "\n"
-   ]
   }
  ],
  "metadata": {