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import requests
import json
import re
class VectaraQuery():
def __init__(self, api_key: str, customer_id: str, corpus_id: str, prompt_name: str = None):
self.customer_id = customer_id
self.corpus_id = corpus_id
self.api_key = api_key
self.prompt_name = prompt_name if prompt_name else "vectara-experimental-summary-ext-2023-12-11-large"
self.conv_id = None
def get_body(self, user_response: str):
corpora_key_list = [{
'customer_id': self.customer_id, 'corpus_id': self.corpus_id, 'lexical_interpolation_config': {'lambda': 0.025}
}]
user_response = user_response.replace('"', '\\"') # Escape double quotes
prompt = f'''
[
{{
"role": "system",
"content": "You are an assistant that provides information about drink names based on a given corpus."
}},
{{
"role": "user",
"content": "{user_response}"
}}
]
'''
return {
'query': [
{
'query': user_response,
'start': 0,
'numResults': 10,
'corpusKey': corpora_key_list,
'context_config': {
'sentences_before': 2,
'sentences_after': 2,
'start_tag': "%START_SNIPPET%",
'end_tag': "%END_SNIPPET%",
}
}
]
}
def get_headers(self):
return {
"Content-Type": "application/json",
"Accept": "application/json",
"customer-id": self.customer_id,
"x-api-key": self.api_key,
"grpc-timeout": "60S"
}
def submit_query(self, query_str: str):
endpoint = f"https://api.vectara.io/v1/stream-query"
body = self.get_body(query_str)
response = requests.post(endpoint, data=json.dumps(body), verify=True, headers=self.get_headers(), stream=True)
if response.status_code != 200:
print(f"Query failed with code {response.status_code}, reason {response.reason}, text {response.text}")
return "Sorry, something went wrong. Please try again later."
chunks = []
accumulated_text = "" # Initialize text accumulation
pattern_max_length = 50 # Example heuristic
for line in response.iter_lines():
if line: # filter out keep-alive new lines
data = json.loads(line.decode('utf-8'))
res = data['result']
response_set = res['responseSet']
if response_set:
for result in response_set:
text = result['text']
# Extract relevant information from the text
reason = re.search(r"Reason Why it Can't be Used: (.*?)\n", text).group(1)
alternative = re.search(r"Alternative: (.*?)\n", text).group(1)
notes = re.search(r"Notes: (.*?)\n", text).group(1)
response = f"Reason: {reason}\nAlternative: {alternative}\nNotes: {notes}"
return response
return "No relevant information found."
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