| import requests | |
| import json | |
| def query_vectara(question, customer_id, api_key, corpus_key): | |
| """Queries the uploaded documents in Vectara API v2 using the correct query format.""" | |
| url = f"https://api.vectara.io/v2/corpora/{corpus_key}/query?query={question}" | |
| headers = { | |
| "x-api-key": api_key, | |
| "Accept": "application/json" | |
| } | |
| response = requests.get(url, headers=headers) | |
| return response.json() | |
| def process_queries(customer_id, api_key, corpus_key): | |
| """Runs all predefined queries on the uploaded documents.""" | |
| questions = [ | |
| "Based on uploaded documents, what are the top four challenges of the Fintech sector in Saudi Arabia? list them in bullet points.", | |
| "Based on uploaded documents, who are the top five leading companies in the Fintech sector in Saudi Arabia? list them in bullet points with brief information on each company.", | |
| "Based on uploaded documents, summarize Saudi Arabia's Fintech Strategy in five key points.", | |
| "Based on uploaded documents, describe STC Pay, its position in the market, and partners.", | |
| "Based on uploaded documents, what are the key differences between Fintech in Saudi vs UAE?", | |
| "Based on uploaded documents, summarize the Payment Services Provider Regulations (PSPR) in five bullet points." | |
| ] | |
| results = {} | |
| for question in questions: | |
| response = query_vectara(question, customer_id, api_key, corpus_key) | |
| results[question] = response | |
| return results | |