| import os | |
| import openai | |
| import json, csv | |
| def results_agent(query, context): | |
| system_prompt = """ | |
| You are an academic advisor helping students (user role) find classes for the next semester, based only on rag responses that are provided to you as context. | |
| Relay information in a succinct way, relaying relevant information to classes or simply saying that you weren't able to find similar classes. | |
| Based on the context provided, respond to the user's query in a natural way as if you are a person. | |
| Only recommend ~2 or 3 classes when they are provided in RAG responses, otherwise, respond appropriately that you don't have good recommendations. | |
| """ | |
| response = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=[ | |
| {"role": "system", "content": system_prompt}, | |
| {"role": "user", "content": "User's query:" + query + "Additional Context (RAG responses and chat history):" + context} | |
| ] | |
| ) | |
| return response["choices"][0]["message"]["content"] | |