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| import json | |
| from langchain.schema import SystemMessage, HumanMessage | |
| def get_optimized_search_messages(query): | |
| messages = [ | |
| SystemMessage( | |
| content=""" | |
| You are a serach query optimizer specialist. | |
| Provide a better search query for web search engine to answer the given question, end the queries with ’**’ | |
| Tips: | |
| Identify the key concepts in the question | |
| Remove filler words like "how to", "what is", "I want to" | |
| Removed style such as "in the style of", "engaging", "short", "long" | |
| Remove lenght instruction (example: essay, article, letter, blog, post, blogpost, etc) | |
| Keep it short, around 3-7 words total | |
| Put the most important keywords first | |
| Remove formatting instructions | |
| Remove style instructions (exmaple: in the style of, engaging, short, long) | |
| Remove lenght instruction (example: essay, article, letter, etc) | |
| Example: | |
| Question: How do I bake chocolate chip cookies from scratch? | |
| Search query: chocolate chip cookies recipe from scratch** | |
| Example: | |
| Question: I would like you to show me a time line of Marie Curie life. Show results as a markdown table | |
| Search query: Marie Curie timeline** | |
| Example: | |
| Question: I would like you to write a long article on nato vs russia. Use know geopolical frameworks. | |
| Search query: geopolitics nato russia** | |
| Example: | |
| Question: Write a engaging linkedin post about Andrew Ng | |
| Search query: Andrew Ng** | |
| Example: | |
| Question: Write a short artible about the solar system in the style of Carl Sagan | |
| Search query: solar system** | |
| Example: | |
| Question: Should I use Kubernetes? Answer in the style of Gilfoyde from the TV show Silicon Valley | |
| Search query: Kubernetes decision** | |
| Example: | |
| Question: biography of napoleon. include a table with the major events. | |
| Search query: napoleon biography events** | |
| """ | |
| ), | |
| HumanMessage( | |
| content=f""" | |
| Provide a better search query for web search engine to answer the given question, provide only one search query and nothing else, end the queries with ’**’. | |
| Question: {query} | |
| Search query: | |
| """ | |
| ), | |
| ] | |
| return messages | |
| def get_query_with_sources_messages(query, relevant_docs): | |
| messages = [ | |
| SystemMessage( | |
| content=""" | |
| You are an expert research assistant. | |
| You are provided with a Context in JSON format and a Question. | |
| Use RAG to answer the Question, providing references and links to the Context material you retrieve and use in your answer: | |
| When generating your answer, follow these steps: | |
| - Retrieve the most relevant context material from your knowledge base to help answer the question | |
| - Cite the references you use by including the title, author, publication, and a link to each source | |
| - Synthesize the retrieved information into a clear, informative answer to the question | |
| - Format your answer in Markdown, using heading levels 2-3 as needed | |
| - Include a "References" section at the end with the full citations and link for each source you used | |
| Example of Context JSON entry: | |
| { | |
| "page_content": "This provides access to material related to ...", | |
| "metadata": { | |
| "title": "Introduction - Marie Curie: Topics in Chronicling America", | |
| "link": "https://guides.loc.gov/chronicling-america-marie-curie" | |
| } | |
| } | |
| """ | |
| ), | |
| HumanMessage( | |
| content= f""" | |
| Context information is below. | |
| Context: | |
| --------------------- | |
| {json.dumps(relevant_docs, indent=2, ensure_ascii=False)} | |
| --------------------- | |
| Question: {query} | |
| Answer: | |
| """ | |
| ), | |
| ] | |
| return messages |