Add support to parse Openai function call input and results format to mistral_rubra format. TODO: need to clean up prints after testing.
This commit is contained in:
Yingbei
parent
79fd89a62b
commit
784fa90cbe
4 changed files with 249 additions and 155 deletions
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@ -39,7 +39,7 @@ static void parseFunctionCalls(const TSNode& node, std::vector<json>& calls, con
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if (strcmp(type, "call") == 0) {
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json call = {
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{"id", calls.size()},
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{"id", std::to_string(calls.size())},
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{"name", ""},
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{"args", json::array()},
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{"kwargs", json::object()}
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@ -10,6 +10,7 @@
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#include <vector>
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#include <sstream>
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#include <random>
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#include <unordered_map>
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#define DEFAULT_OAICOMPAT_MODEL "gpt-3.5-turbo-0613"
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@ -491,19 +492,123 @@ static json oaicompat_completion_params_parse(
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// function_str = default_tool_formatter(body["functions"]);
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function_str = rubra_format_function_call_str(body["functions"]);
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}
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printf("\n=============Formatting Input from OPENAI format...============\n");
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if (function_str != "") {
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const std::vector<json> expand_messages = [&]() {
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std::vector<json> temp_vec = body["messages"];
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if (body["messages"][0]["role"] == "system") {
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std::string old_content = temp_vec[0]["content"];
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temp_vec[0]["content"] = old_content + "\n" + function_str;
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// std::vector<json> temp_vec = body["messages"];
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// if (body["messages"][0]["role"] == "system") {
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// std::string old_content = temp_vec[0]["content"];
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// temp_vec[0]["content"] = old_content + "\n" + function_str;
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// }
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// else {
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// json function_call;
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// function_call["role"] = "system";
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// function_call["content"] = "You are a helpful assistant.\n" + function_str;
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// temp_vec.push_back(function_call);
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// }
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std::vector<json> temp_vec;
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std::unordered_map<std::string, std::string> func_observation_map;
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for (size_t i = 0; i < body["messages"].size(); ++i) {
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printf("body[\"messages\"][%d][\"role\"] = %s\n", i, body["messages"][i]["role"].get<std::string>().c_str());
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printf("Message: %s\n", body["messages"][i].dump().c_str());
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printf("%d\n", body["messages"][i].contains("tool_calls"));
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if (body["messages"][i]["role"] != "tool" and func_observation_map.size() > 0) {
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// insert the observation from the tool call before the next message
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std::string observation_str = "";
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for (const auto& [key, value] : func_observation_map) {
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if (observation_str != "") {
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observation_str += ", ";
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}
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observation_str += value;
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}
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observation_str = std::string("<<observation>>") + "[" + observation_str + "]";
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json observation_call;
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observation_call["role"] = "observation";
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observation_call["content"] = observation_str;
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temp_vec.push_back(observation_call);
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func_observation_map.clear();
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}
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if (i == 0){
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if (body["messages"][0]["role"] == "system") {
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std::string old_content = body["messages"][0]["content"];
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json function_call;
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function_call["role"] = "system";
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function_call["content"] = old_content + "\n" + function_str;
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temp_vec.push_back(function_call);
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}
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else { // insert a system message of tool definition before the first message
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json function_call;
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function_call["role"] = "system";
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function_call["content"] = "You are a helpful assistant.\n" + function_str;
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temp_vec.push_back(function_call);
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temp_vec.push_back(body["messages"][0]);
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}
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}
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// 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()){
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else if (body["messages"][i]["role"] == "assistant" and body["messages"][i].contains("tool_calls")){
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printf("Tool call detected\n");
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// convert OpenAI function call format to Rubra format
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std::string tool_call_str = "";
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printf("Tool calls: %s\n", body["messages"][i]["tool_calls"].dump().c_str());
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for (const auto & tool_call : body["messages"][i]["tool_calls"]) {
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printf("Tool call id: %s\n", tool_call["id"].get<std::string>().c_str());
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std::string func_str = "";
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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
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json args = json::parse(tool_call["function"]["arguments"].get<std::string>()); // TODO: catch the exceptions
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for (auto& arg : args.items()) {
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if (func_str != "") {
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func_str += ", ";
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}
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func_str += arg.key() + "=" + arg.value().dump();
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}
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func_str = tool_call["function"]["name"].get<std::string>() + "(" + func_str + ")";
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if (tool_call_str != "") {
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tool_call_str += ", ";
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}
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tool_call_str += func_str;
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}
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tool_call_str = std::string("<<functions>>") + "[" + tool_call_str + "]";
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printf("Tool call string: %s\n", tool_call_str.c_str());
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json function_call;
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function_call["role"] = "function";
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function_call["content"] = tool_call_str;
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temp_vec.push_back(function_call);
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}
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else if (body["messages"][i]["role"] == "tool") {
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printf("Observation detected\n");
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printf(body["messages"][i].dump().c_str());
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std::string tool_call_id = body["messages"][i]["tool_call_id"].get<std::string>();
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if (func_observation_map.find(tool_call_id) != func_observation_map.end()) {
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func_observation_map[tool_call_id] = body["messages"][i]["content"].get<std::string>();
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} else {
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LOG_ERROR("Tool call id not found in the map", {{"tool_call_id", tool_call_id}});
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// TODO: the input is not valid in this case, should return an error
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}
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}
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else {
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temp_vec.push_back(body["messages"][i]);
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}
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}
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else {
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json function_call;
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function_call["role"] = "system";
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function_call["content"] = "You are a helpful assistant.\n" + function_str;
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temp_vec.push_back(function_call);
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if (func_observation_map.size() > 0) {
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// insert the observation from the tool call before the next message
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std::string observation_str = "";
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for (const auto& [key, value] : func_observation_map) {
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if (observation_str != "") {
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observation_str += ", ";
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}
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observation_str += value;
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}
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observation_str = std::string("<<observation>>") + "[" + observation_str + "]";
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json observation_call;
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observation_call["role"] = "observation";
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observation_call["content"] = observation_str;
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temp_vec.push_back(observation_call);
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func_observation_map.clear();
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}
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return temp_vec;
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}();
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@ -14518,7 +14518,6 @@ static int32_t llama_chat_apply_template_internal(
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// construct the prompt
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bool is_inside_turn = true; // skip BOS at the beginning
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// ss << "[INST] ";
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for (auto message : chat) {
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std::string content = strip_message ? trim(message->content) : message->content;
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std::string role(message->role);
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@ -14537,7 +14536,7 @@ static int32_t llama_chat_apply_template_internal(
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ss << "[INST]" << content << " [/INST]";
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} else {
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ss << (space_around_response ? " " : "") << content << (space_around_response ? " " : "") << "</s>";
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is_inside_turn = false;
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// is_inside_turn = false;
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}
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}
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// llama2 templates seem to not care about "add_generation_prompt"
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@ -1,5 +1,82 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 69,
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"metadata": {},
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"outputs": [],
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"source": [
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"def run_completion(chat_method, user_query):\n",
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" print(chat_method)\n",
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" system_prompt = \"You are a helpful assistant.\"\n",
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" functions = [\n",
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" {\n",
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" \"type\": \"function\",\n",
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" \"function\": {\n",
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" \"name\": \"getCurrentWeather\",\n",
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" \"description\": \"Get the weather in location\",\n",
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" \"parameters\": {\n",
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" \"type\": \"object\",\n",
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" \"properties\": {\n",
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" \"location\": {\"type\": \"string\", \"description\": \"The city and state e.g. San Francisco, CA\"},\n",
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" \"unit\": {\"type\": \"string\", \"enum\": [\"c\", \"f\"]}\n",
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" },\n",
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" \"required\": [\"location\"]\n",
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" }\n",
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" }\n",
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" },\n",
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" { \"type\": \"function\",\n",
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" \"function\":\n",
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" {\n",
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" \"name\": \"orderUmbrella\",\n",
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" \"description\": \"Do this to help user to order an umbrella online\", \n",
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" \"parameters\": {\n",
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" \"type\": \"object\",\n",
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" \"properties\": {\n",
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" \"number_to_buy\": {\n",
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" \"type\": \"integer\",\n",
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" \"description\": \"the amount of umbrellas to buy\"\n",
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" }\n",
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" },\n",
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" \"required\": [\n",
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" \"number_to_buy\"\n",
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" ]\n",
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" }\n",
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" }},\n",
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" ]\n",
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" # 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",
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"\n",
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" msgs = [{\"role\": \"system\", \"content\":system_prompt} ,{\"role\": \"user\", \"content\": user_query}]\n",
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"\n",
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" res = chat_method(user_query, \"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
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" print(f\"First Response:\")\n",
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" for tool_call in res.message.tool_calls:\n",
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" print(f\"Tool Call: {tool_call.id}, {tool_call.function}\")\n",
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" assistant_message = res.message\n",
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" tool_calls = []\n",
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" for tool_call in assistant_message.tool_calls:\n",
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" tool_calls.append( {\n",
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" \"id\": tool_call.id,\n",
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" \"function\": {\"name\": tool_call.function.name,\n",
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" \"arguments\": tool_call.function.arguments},\n",
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" \"type\": \"function\",\n",
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" })\n",
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" msgs.append({\"role\": \"assistant\", \"tool_calls\": tool_calls})\n",
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" \n",
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" for i, tool_call in enumerate(assistant_message.tool_calls):\n",
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" if tool_call.function.name == \"getCurrentWeather\":\n",
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" 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",
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" else:\n",
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" 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",
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" \n",
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"\n",
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" print(\"Print before second response...\")\n",
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" res_next = chat_method(user_query, \"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
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" for m in msgs:\n",
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" print(m)\n",
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" print(f\"Second Response: {res_next.message}\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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@ -9,7 +86,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 70,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -17,8 +94,8 @@
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"\n",
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"\n",
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"def get_oai_response(prompt, model, functions, msgs):\n",
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" openai.api_key = \"sk-\"\n",
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" # openai.base_url = \"http://localhost:8019/v1/\"\n",
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" openai.api_key = \"sk-\" ## Add your API key here\n",
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" openai.base_url = \"https://api.openai.com/v1/\"\n",
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" \n",
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" try:\n",
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" completion = openai.chat.completions.create(\n",
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@ -38,66 +115,30 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 71,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"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"
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"<function get_oai_response at 0x10b9c93f0>\n",
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"First Response:\n",
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"Tool Call: call_FYLEpX5CVo2dqSyNupcgtFak, Function(arguments='{\"number_to_buy\":2}', name='orderUmbrella')\n",
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"Print before second response...\n",
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"{'role': 'system', 'content': 'You are a helpful assistant.'}\n",
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"{'role': 'user', 'content': 'order 2 umbrellas'}\n",
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"{'role': 'assistant', 'tool_calls': [{'id': 'call_FYLEpX5CVo2dqSyNupcgtFak', 'function': {'name': 'orderUmbrella', 'arguments': '{\"number_to_buy\":2}'}, 'type': 'function'}]}\n",
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"{'role': 'tool', 'tool_call_id': 'call_FYLEpX5CVo2dqSyNupcgtFak', 'name': 'orderUmbrella', 'content': 'Order placed.'}\n",
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"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"
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]
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}
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],
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"source": [
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"system_prompt = \"You are a helpful assistant.\"\n",
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"functions = [\n",
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" {\n",
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" \"type\": \"function\",\n",
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" \"function\": {\n",
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" \"name\": \"getCurrentWeather\",\n",
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" \"description\": \"Get the weather in location\",\n",
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" \"parameters\": {\n",
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" \"type\": \"object\",\n",
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" \"properties\": {\n",
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" \"location\": {\"type\": \"string\", \"description\": \"The city and state e.g. San Francisco, CA\"},\n",
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" \"unit\": {\"type\": \"string\", \"enum\": [\"c\", \"f\"]}\n",
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" },\n",
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" \"required\": [\"location\"]\n",
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" }\n",
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" }\n",
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" },\n",
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" { \"type\": \"function\",\n",
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" \"function\":\n",
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" {\n",
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" \"name\": \"orderUmbrella\",\n",
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" \"description\": \"Do this to help user to order an umbrella online\", \n",
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" \"parameters\": {\n",
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" \"type\": \"object\",\n",
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" \"properties\": {\n",
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" \"brand_name\": {\n",
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" \"type\": \"string\",\n",
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" \"description\": \"The name of the umbrella brand\"\n",
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" }\n",
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" },\n",
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" \"required\": [\n",
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" \"brand_name\"\n",
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" ]\n",
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" }\n",
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" }},\n",
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"]\n",
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"\n",
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"\n",
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"user_query = \"check the weather in boston\"\n",
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"# 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",
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"# ,\n",
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"# {\"role\": \"assistant\", \"content\": \"The current weather in Boston is 72 degrees Fahrenheit and it's raining. Would you like to order an umbrella?\"},\n",
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"# {\"role\": \"user\", \"content\": \"yes pls\"},\n",
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"# ]\n",
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"msgs = [{\"role\": \"system\", \"content\":system_prompt} ,{\"role\": \"user\", \"content\": user_query}]\n",
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"\n",
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"res = get_oai_response(user_query, \"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
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"print(res)"
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"# user_query = \"What is the distance between San Francisco and Cupertino by car and by air\"\n",
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"# user_query = \"weather in boston as well as cupertino?\"\n",
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"user_query = \"order 2 umbrellas\"\n",
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"run_completion(get_oai_response, user_query)"
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]
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},
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{
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@ -109,17 +150,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 72,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"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"
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]
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}
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||||
],
|
||||
"outputs": [],
|
||||
"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",
|
||||
"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",
|
||||
" \"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_mistral_rubra_response(user_query, \"gpt-4-0125-preview\", functions=functions, msgs=msgs)\n",
|
||||
"print(res)"
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 73,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"<function get_mistral_rubra_response at 0x10b9cac20>\n",
|
||||
"First Response:\n",
|
||||
"Tool Call: 0, 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': '0', 'function': {'name': 'orderUmbrella', 'arguments': '{\"number_to_buy\":\"2\"}'}, 'type': 'function'}]}\n",
|
||||
"{'role': 'tool', 'tool_call_id': '0', 'name': 'orderUmbrella', 'content': 'Order placed.'}\n",
|
||||
"Second Response: ChatCompletionMessage(content=' Your order for 2 umbrellas has been placed.', role='assistant', function_call=None, tool_calls=None)\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# user_query = \"generate a password of length 10 and another of length 20\" \n",
|
||||
"# user_query = \"what's the weather in Boston and Cupertino?\"\n",
|
||||
"user_query = \"order 2 umbrellas\"\n",
|
||||
"run_completion(get_mistral_rubra_response, user_query)"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -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",
|
||||
"<<functions>>[get_stock_fundermentals(symbol=\"GOOG\")]\n"
|
||||
"None\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[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 40\u001b[0m\n result_dict = parse_function_call(function_call.strip())\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": {
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue