> For the complete documentation index, see [llms.txt](https://docs.myshell.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.myshell.ai/create/pro-config-mode/example/function-calling-example.md). # Function Calling Example > ### [ ]()Reference > > > > In this section, we will provide an example of advanced usage of function calling, and we hope this can serve as a good starting point for you to write your own Pro Config. ````json { "type": "automata", "id": "studymate_bot", "initial": "home_page_state", "inputs": {}, "outputs": {}, "context": { "general_purpose_widget_id":"", "advanced_task_widget_id":"", "memory":"{{[]}}", "note_topic":"", "user_given_note_topic":null, "number_of_questions":"", "difficulty_level":"", "questions_string_sample": "{\"question\": \"Which of the following statements is not correct? \\n A. The execution of an Automata starts from the `initial` state. \\n B. An Automata can contain multiple AtomicStates. \\n C. Each AtomicState must define both inputs and outputs. \\n D. We can define transitions in either Automata or AtomicState.\", \"answer\": \"C\", \"explanation\": \"Both inputs and outputs in an AtomicState are optional.\"}", "questions_string_sample_another": "{\"question\": \"You are building an AutomicState, please choose the correct order of execution: \\n A. inputs -> tasks -> outputs -> render \\n B. render -> inputs -> tasks -> outputs. \\n C. tasks -> inputs -> outputs -> render. \\n D. render -> tasks -> inputs -> outputs\", \"answer\": \"A\", \"explanation\": \"The correct order is `inputs -> tasks -> outputs -> render`. Please refer to `Expressions and Variables`\"}, {\"question\": \"Which of the following expressions is not correct (assume all the variables exist)? \\n A. context.variable \\n B. variable \\n C. variable1 + variable2 \\n D. np.array(variable)\", \"answer\": \"D\", \"explanation\": \"Our expression supports JavaScript grammar.\"}", "questions": "", "question_idx": "", "chosen_answer": "", "correct_answer": "", "correct_count": "", "google_search_raw_result":"", "json_regex":"{{\"\\[.*?\\]\"}}", "json_flags":"s", "json_match":"" }, "transitions": { "go_home": "home_page_state", "submit_note":"submit_note_state", "prequiz":"pre_quiz_page", "get_quiz":"quiz_page_state", "continue": "continue_state" }, "states": { "home_page_state": { "inputs": { "intro_message": { "type": "text", "user_input": false, "default_value": "Hi, this is your studymate chatbot" }, "general_purpose_widget_id": { "type": "text", "user_input": false, "default_value": "1744214024104448000", "description": "widget id for the main widget(LLM)" }, "advanced_task_widget_id": { "type": "text", "user_input": false, "default_value": "1744214047475109888", "description": "widget id for the advanced tasks widget(LLM)" }, "topic":{ "type": "text", "user_input": true, "default_value": "{{context.note_topic}}" } }, "outputs": { "context.general_purpose_widget_id": "{{general_purpose_widget_id}}", "context.advanced_task_widget_id": "{{advanced_task_widget_id}}", "context.user_given_note_topic":"{{topic}}", "context.note_topic":"{{topic}}", "context.question_idx": "{{0}}", "context.correct_count": "{{0}}", "context.json_match":"{{new RegExp(context.json_regex, context.json_flags)}}" }, "render": { "text": "Welcome to the Study Mate Chatbot, continue by pasting your note", "buttons": [ { "content": "🏠Home", "description": "Go to back to 🏠Home", "on_click": "go_home" }, { "content": "Take Quiz", "description": "Skip submitting note and take quiz on {{topic}}", "on_click": "prequiz" } ] }, "transitions": { "CHAT": "submit_note_state" } }, "submit_note_state":{ "inputs": { "user_note":{ "type": "IM", "user_input": true } }, "tasks": [ { "name": "generate_reply", "module_type": "AnyWidgetModule", "module_config": { "widget_id": "{{context.general_purpose_widget_id}}", "system_prompt": "You are a summary-giving machine, summarising notes given and also giving main key points.", "user_prompt": "{{user_note}}", "output_name": "reply" } }, { "name": "generate_topic", "module_type": "AnyWidgetModule", "module_config": { "widget_id": "{{context.general_purpose_widget_id}}", "system_prompt": "You are a summary-giving encyclopedia, identify the topic of the given note.", "user_prompt": "{{user_note}}", "output_name": "note_topic" } }, { "name": "generate_voice", "module_type": "AnyWidgetModule", "module_config": { "content": "{{reply}}", "widget_id": "1743159010695057408", "output_name": "reply_voice" } } ], "outputs": { "context.note_topic":"{{note_topic}}", "context.google_search_raw_result":"{{google_search_raw_result}}" }, "render": { "text": "{{reply}}", "audio": "{{reply_voice}}", "buttons": [ { "content": "Quiz", "description": "Attempt quiz on {{context.note_topic??note_topic}}", "on_click": "prequiz" } ] } }, "pre_quiz_page":{ "inputs": { "difficulty_level":{ "type": "text", "choices": ["easy","medium","hard"], "default_value": "medium", "description": "Choose the difficulty level for your quiz", "user_input": true }, "number_of_questions":{ "type": "text", "default_value": "10", "description": "Enter the number of questions you want to attempt in this quiz", "user_input": true } }, "tasks": [ { "name": "generate_multiple_choice_question", "module_type": "AnyWidgetModule", "module_config": { "widget_id": "{{context.advanced_task_widget_id}}", "system_prompt": "You are my question bank, generating dynamic {{difficulty_level}} level questions based on the topic provided, you will generate a question with several choices (as mcq test) and output it in JSON format. the format is `{'question': 'here is the question', 'choices': ['A. xxxxxxxxxxxx', 'B. xxxxxxxxx', 'C. xxxxxxxxxxx', 'D. xxxxxxxxxx'], 'answer': '? (from ABCD)', 'explanation': 'why we choose ? (from ABCD) as answer, explain it.'}`", "user_prompt": "generate a four choice questions under the topic:{{context.user_given_note_topic??context.note_topic}}. The output should be a JSON format.", "function_description": "Generate a multiple-choice question. Output: JSON format question. containing question, choices, answer and explanation", "function_name": "GenerateMCQ", "function_parameters": [ { "type": "string", "name":"question", "description": "the question" }, { "type": "array", "name":"choices", "items": { "type": "string" }, "description": "the choices, must contain 4 choices, format should be A. xxx, B. xxx, C. xxx, D.xxx" }, { "type": "string", "name":"answer", "description": "the answer, must chosen from A/B/C/D" }, { "type": "string", "name":"explanation", "description": "the explanation" } ], "output_name": "llm_generated_question" } } ], "outputs": { "context.number_of_questions":"{{number_of_questions}}", "context.difficulty_level":"{{difficulty_level}}", "context.questions":"{{llm_generated_question.mcqtest}}" }, "render": { "text": "```json\n{{JSON.stringify(context.questions, null, 2)}}\n```", "buttons": [ { "content": "Start Quiz", "description": "Start untimed quiz {{context.questions}}", "on_click":"get_quiz" } ] } }, "quiz_page_state": { "outputs": { "context.correct_answer": "{{context.questions[context.question_idx]['answer']}}" }, "render": { "text": "{{context.question_idx + 1}}. {{context.questions[context.question_idx]['question']}}", "buttons": [ { "content": "A.", "description": "Choose A.", "on_click": { "event": "check_answer", "payload": { "button_id": "A" } } }, { "content": "B.", "description": "Choose B.", "on_click": { "event": "check_answer", "payload": { "button_id": "B" } } }, { "content": "C.", "description": "Choose C.", "on_click": { "event": "check_answer", "payload": { "button_id": "C" } } }, { "content": "D.", "description": "Choose D.", "on_click": { "event": "check_answer", "payload": { "button_id": "D" } } } ], } "transitions": { "check_answer": { "target": "analyze_answer_state", "target_inputs":{ "button_id":"{{button_id}}" } } } }, "analyze_answer_state": { "inputs": { "button_id": { "type": "text", "user_input": false } }, "outputs": { "context.chosen_answer": "{{button_id}}", "context.is_correct": "{{button_id == context.correct_answer}}" }, "render": { "text": "Check answer state." }, "transitions": { "ALWAYS": [ { "target": "correct_answer_state", "condition": "{{context.is_correct}}" }, { "target": "wrong_answer_state", "condition": "{{true}}" } ] } }, "correct_answer_state": { "outputs": { "context.question_idx": "{{(context.question_idx + 1) % context.questions.length}}", "context.correct_count": "{{context.correct_count + 1}}" }, "render": { "text": "Congratulations! You have chosen the correct answer {{context.correct_answer}}", "buttons": [ { "content": "Continue", "description": "continue", "on_click": "continue" } ] } }, "wrong_answer_state": { "outputs": { "context.question_idx": "{{(context.question_idx + 1) % context.questions.length}}" }, "render": { "text": "Oh No! The chosen answer is {{context.chosen_answer}}, while the correct one is {{context.correct_answer}}.", "buttons": [ { "content": "Continue", "description": "continue", "on_click": "continue" } ] } }, "continue_state": { "render": { "text": "Click to Next Question" }, "transitions": { "ALWAYS": [ { "target": "quiz_page_state", "condition": "{{context.question_idx > 0}}" }, { "target": "finish_state", "condition": "{{context.correct_count == context.questions.length}}" }, { "target": "review_state", "condition": "{{true}}" } ] } }, "finish_state": { "render": { "text": "Congratulations you scored {{context.correct_count}}/{{context.questions.length}}", "buttons": [ { "content": "🏠Home", "description": "Back to Home", "on_click": "go_home" } ] } }, "review_state": { "outputs": { "context.memory": "{{[]}}" }, "render": { "text": "{{context.intro_message}}" } } } } ```` The above example is from a bot called StudyMate made by a participant of Pro Config Learning Lab. In this app, the user can input any topic and choose a difficulty level, and some quizzes can be dynamically generated accordingly. The core to parse the results into structured quizes are achieved using function-calling as: ```json "tasks": [ { "name": "generate_multiple_choice_question", "module_type": "AnyWidgetModule", "module_config": { "widget_id": "{{context.advanced_task_widget_id}}", "system_prompt": "You are my question bank, generating dynamic {{difficulty_level}} level questions based on the topic provided, you will generate a question with several choices (as mcq test) and output it in JSON format. the format is `{'question': 'here is the question', 'choices': ['A. xxxxxxxxxxxx', 'B. xxxxxxxxx', 'C. xxxxxxxxxxx', 'D. xxxxxxxxxx'], 'answer': '? (from ABCD)', 'explanation': 'why we choose ? (from ABCD) as answer, explain it.'}`", "user_prompt": "generate a four choice questions under the topic:{{context.user_given_note_topic??context.note_topic}}. The output should be a JSON format.", "function_description": "Generate a multiple-choice question. Output: JSON format question. containing question, choices, answer and explanation", "function_name": "GenerateMCQ", "function_parameters": [ { "type": "string", "name":"question", "description": "the question" }, { "type": "array", "name":"choices", "items": { "type": "string" }, "description": "the choices, must contain 4 choices, format should be A. xxx, B. xxx, C. xxx, D.xxx" }, { "type": "string", "name":"answer", "description": "the answer, must chosen from A/B/C/D" }, { "type": "string", "name":"explanation", "description": "the explanation" } ], "output_name": "llm_generated_question" } } ], ``` In the above example, we aim to generate the question, choices, answer and explanation, and the type of them are `string` `array` `string` `string` accordingly. We can adopt the OpenAI schema like above to define the desired structure recursively.