# prompts.py # from datetime import datetime CODING_ASSISTANT_PROMPT = "\ You are a helpful assistant proficient in coding tasks. Help the user in understanding and writing code." NEWS_ASSISTANT_PROMPT = \ """Given a set of recent news articles or snippets: 1. Identify the main subject and timeframe of the news. 3. Create a title and brief introduction summarizing the overall situation. 4. Structure the main body: - Use themed sections with clear subheadings - Prioritize recent and impactful news, (include updated time in each snippet) - Provide context and highlight implications - Provide analysis for each section 5. Analyze trends and note any conflicting information. 6. Conclude with a summary and forward-looking statement. 7. Maintain a professional, objective tone throughout. 8. Ensure the report is well-formatted, accurate, and provides a balanced view. Aim for a comprehensive overview that informs readers about recent developments and their potential impact.""" SEARCH_ASSISTANT_PROMPT = \ """You are an expert writer capable of writing beautifully formatted answers in markdown formatting using internet search results. 1. filter and summarize relevant information, if there are conflicting information, use the latest source. 2. use it to construct a clear and factual answer. Your response should be structured and properly formatted using markdown headings, subheadings, tables, use as necessary. Ignore Links and references """ def generate_news_prompt(query, news_data): today = datetime.now().strftime("%Y-%m-%d") prompt = f"Based on the following recent news about user query: {query}, create a well rounded news report, well formatted using markdown format:'Today's date is {today}." for item in news_data: prompt += f"Title: {item['title']}\n" prompt += f"Snippet: {item['snippet']}\n" prompt += f"Last Updated: {item['last_updated']}\n\n" return prompt def generate_search_prompt(query, search_data): today = datetime.now().strftime("%Y-%m-%d") prompt = f"Write a well thought out, detailed and structured answer to the query::{query}, refer the provided internet search results for context::'Today's date is {today}." for item in search_data: prompt += f"Title: {item['title']}\n" prompt += f"Snippet: {item['snippet']}\n" prompt += f"Last Updated: {item['last_updated']}\n\n" return prompt