CMAT Reasoning Practice

\n {\n setTopic(e.target.value);\n clearState();\n }}\n className=\"w-full p-2 rounded bg-white dark:bg-gray-800 border border-gray-300 dark:border-gray-700\"\n >\n \n \n {topics.map((t) => (\n \n ))}\n \n

\n \n {\n setMode(\"regular\");\n clearState();\n }}\n />\n Regular Mode\n \n \n {\n setMode(\"exam\");\n clearState();\n }}\n />\n Exam Mode\n \n

\n {mode === \"exam\" && (\n

\n Number of questions:\n {\n setQuestionCount(parseInt(e.target.value));\n clearState();\n }}\n min=\"1\"\n max=\"20\"\n className=\"w-full p-2 rounded bg-white dark:bg-gray-800 border border-gray-300 dark:border-gray-700\"\n />\n

\n )}\n {mode === \"exam\" && !examQuestionsGenerated && (\n \n Generate Exam Questions\n \n )}\n {loading\n ? (\n

{loadingText}

\n )\n : currentQuestion\n ? (\n

{currentQuestion.question}

\n {currentQuestion.options.map((option, index) => (\n \n setSelectedOption(index.toString())}\n className=\"form-radio\"\n />\n {option}\n \n ))}\n

\n setUserLogic(e.target.value)}\n placeholder=\"Explain your logic here...\"\n className=\"w-full p-2 mt-4 rounded bg-white dark:bg-gray-800 border border-gray-300 dark:border-gray-700\"\n rows=\"4\"\n >\n \n \n {mode === \"regular\" ? \"Submit\" : progress < questionCount - 1 ? \"Next\" : \"Finish Exam\"}\n \n

\n )\n : null}\n {mode === \"regular\" && feedback && (\n

Correct Answer: {currentQuestion.options[currentQuestion.correctAnswer]}

Your Answer: {currentQuestion.options[parseInt(selectedOption)]}

Why the correct answer is correct:

{feedback.correctAnswerExplanation}

\n {selectedOption !== currentQuestion.correctAnswer.toString() && (\n <>\n

Analysis of your logic:

{feedback.userLogicAnalysis}

\n \n )}\n

Specific trick for this question type:

{feedback.specificTrick}

How this concept appears in CMAT:

{feedback.cmatApplication}

Rating of your approach:

{feedback.rating}/10

Exam Feedback

\n {examFeedback.map((feedback, index) => (\n

Question {index + 1}:

{examQuestions[index].question}

\n Correct Answer: {examQuestions[index].options[examQuestions[index].correctAnswer]}\n

Your Answer: {examQuestions[index].options[parseInt(examAnswers[index])]}

Feedback:

{feedback.feedback}

Quick Tip:

{feedback.quickTip}

\n ))}\n

Overall Performance

{examFeedback[examFeedback.length - 1].overallFeedback}

\n )}\n

Quick Tips

{tip}

\n \n Export Tips as PDF\n \n \n Share Insights\n \n

Progress: {progress + 1} / {mode === \"exam\" ? questionCount : \"∞\"}

\n );\n}\n\nfunction client() {\n createRoot(document.getElementById(\"root\")).render();\n}\n\nif (typeof document !== \"undefined\") {\n client();\n}\n\nexport default async function server(request: Request): Promise {\n const { OpenAI } = await import(\"npm:openai\");\n const { zodResponseFormat } = await import(\"npm:openai/helpers/zod\");\n const { z } = await import(\"npm:zod\");\n const openai = new OpenAI();\n\n const QuestionSchema = z.object({\n question: z.string(),\n options: z.array(z.string()),\n correctAnswer: z.number(),\n });\n\n const FeedbackSchema = z.object({\n correctAnswerExplanation: z.string(),\n userLogicAnalysis: z.string(),\n specificTrick: z.string(),\n cmatApplication: z.string(),\n rating: z.number(),\n nextTopic: z.string(),\n quickTip: z.string(),\n });\n\n const ExamFeedbackSchema = z.object({\n feedback: z.array(z.object({\n feedback: z.string(),\n quickTip: z.string(),\n })),\n overallFeedback: z.string(),\n strengths: z.array(z.string()),\n weaknesses: z.array(z.string()),\n practiceAreas: z.array(z.string()),\n quickTips: z.array(z.string()),\n });\n\n const ExamQuestionsSchema = z.object({\n questions: z.array(QuestionSchema),\n });\n\n if (request.method === \"POST\") {\n const {\n prompt,\n topic,\n selectedOption,\n userLogic,\n examAnswers,\n examLogic,\n questionCount,\n examQuestions,\n currentQuestion,\n } = await request.json();\n console.log(\"OpenAI API Request:\", { prompt, topic });\n\n try {\n let completion;\n if (request.url.includes(\"generate-question\")) {\n completion = await openai.beta.chat.completions.parse({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: \"You are a CMAT reasoning mentor generating questions.\" },\n { role: \"user\", content: prompt },\n ],\n response_format: zodResponseFormat(QuestionSchema, \"question\"),\n });\n } else if (request.url.includes(\"generate-exam-questions\")) {\n completion = await openai.beta.chat.completions.parse({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: \"You are a CMAT reasoning examiner generating exam questions.\" },\n { role: \"user\", content: prompt },\n ],\n response_format: zodResponseFormat(ExamQuestionsSchema, \"examQuestions\"),\n });\n } else if (request.url.includes(\"get-feedback\")) {\n completion = await openai.beta.chat.completions.parse({\n model: \"gpt-4o\",\n messages: [\n {\n role: \"system\",\n content:\n \"You are a CMAT reasoning mentor providing feedback. The user's first language is likely Gujarati, and their English may be weak. However, their logical reasoning skills are not affected by this language barrier. Provide clear, simple explanations.\",\n },\n { role: \"user\", content: prompt },\n ],\n response_format: zodResponseFormat(FeedbackSchema, \"feedback\"),\n });\n } else if (request.url.includes(\"get-exam-feedback\")) {\n completion = await openai.beta.chat.completions.parse({\n model: \"gpt-4o\",\n messages: [\n {\n role: \"system\",\n content:\n \"You are a CMAT reasoning examiner providing exam feedback. The user's first language is likely Gujarati, and their English may be weak. However, their logical reasoning skills are not affected by this language barrier. Provide clear, simple explanations and focus on logical reasoning rather than language proficiency.\",\n },\n { role: \"user\", content: prompt },\n ],\n response_format: zodResponseFormat(ExamFeedbackSchema, \"examFeedback\"),\n });\n } else {\n throw new Error(\"Invalid API endpoint\");\n }\n\n const response = completion.choices[0].message.parsed;\n console.log(\"OpenAI API Response:\", response);\n\n return new Response(JSON.stringify(response), {\n headers: { \"Content-Type\": \"application/json\" },\n });\n } catch (error) {\n console.error(\"Error in OpenAI API call:\", error);\n return new Response(JSON.stringify({ error: error.message }), {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n }\n\n return new Response(\n `\n \n \n \n \n \n CMAT Reasoning Practice\n \n \n \n \n \n

\n \n \n \n \n `,\n {\n headers: { \"Content-Type\": \"text/html\" },\n },\n );\n}","deleted","label",[99],"permalink","https://www.val.town/x/prashamtrivedi/reasoninghelper/code/main.tsx","extension","actionData","errors"]