Spaces:
Runtime error
Runtime error
File size: 4,924 Bytes
7f46a81 f26592e 7f46a81 6541511 7f46a81 f26592e 7f46a81 6541511 b4ea488 6541511 b4ea488 6541511 5fc81fd 7f46a81 b4ea488 f26592e 5cebf82 7f46a81 b4ea488 7f46a81 7ff5239 6541511 7f46a81 6541511 7f46a81 39e2176 ee0fd94 5cebf82 7f46a81 f26592e 7f46a81 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 |
import requests
import json
import re
from urllib.parse import quote
def extract_between_tags(text, start_tag, end_tag):
start_index = text.find(start_tag)
end_index = text.find(end_tag, start_index)
return text[start_index+len(start_tag):end_index-len(end_tag)]
class VectaraQuery():
def __init__(self, api_key: str, customer_id: int, corpus_ids: list):
self.customer_id = customer_id
self.corpus_ids = corpus_ids
self.api_key = api_key
self.conv_id = None
def submit_query(self, query_str: str):
corpora_key_list = [{
'customer_id': str(self.customer_id), 'corpus_id': str(corpus_id), 'lexical_interpolation_config': {'lambda': 0.025}
} for corpus_id in self.corpus_ids
]
endpoint = f"https://api.vectara.io/v1/query"
start_tag = "%START_SNIPPET%"
end_tag = "%END_SNIPPET%"
headers = {
"Content-Type": "application/json",
"Accept": "application/json",
"customer-id": str(self.customer_id),
"x-api-key": self.api_key,
"grpc-timeout": "60S"
}
body = {
'query': [
{
'query': query_str,
'start': 0,
'numResults': 50,
'corpusKey': corpora_key_list,
'context_config': {
'sentences_before': 2,
'sentences_after': 2,
'start_tag': start_tag,
'end_tag': end_tag,
},
'rerankingConfig':
{
'rerankerId': 272725718,
'mmrConfig': {
'diversityBias': 0.3
}
},
'summary': [
{
'responseLang': 'eng',
'maxSummarizedResults': 5,
'summarizerPromptName': 'vectara-experimental-summary-ext-2023-12-11-sml',
'chat': {
'store': True,
'conversationId': self.conv_id
},
'debug': True,
}
]
}
]
}
response = requests.post(endpoint, data=json.dumps(body), verify=True, headers=headers)
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 in my brain. Please try again later."
res = response.json()
top_k = 10
summary = res['responseSet'][0]['summary'][0]['text']
responses = res['responseSet'][0]['response'][:top_k]
docs = res['responseSet'][0]['document']
chat = res['responseSet'][0]['summary'][0]['chat']
if chat['status'] != None:
st_code = chat['status']
print(f"Chat query failed with code {st_code}")
if st_code == 'RESOURCE_EXHAUSTED':
self.conv_id = None
return 'Sorry, Vectara chat turns exceeds plan limit.'
return 'Sorry, something went wrong in my brain. Please try again later.'
self.conv_id = res['responseSet'][0]['summary'][0]['chat']['conversationId']
pattern = r'\[\d{1,2}\]'
matches = [match.span() for match in re.finditer(pattern, summary)]
# figure out unique list of references
refs = []
for match in matches:
start, end = match
response_num = int(summary[start+1:end-1])
doc_num = responses[response_num-1]['documentIndex']
metadata = {item['name']: item['value'] for item in docs[doc_num]['metadata']}
text = extract_between_tags(responses[response_num-1]['text'], start_tag, end_tag)
url = f"{metadata['url']}#:~:text={quote(text)}"
if url not in refs:
refs.append(url)
# replace references with markdown links
refs_dict = {url:(inx+1) for inx,url in enumerate(refs)}
for match in reversed(matches):
start, end = match
response_num = int(summary[start+1:end-1])
doc_num = responses[response_num-1]['documentIndex']
metadata = {item['name']: item['value'] for item in docs[doc_num]['metadata']}
text = extract_between_tags(responses[response_num-1]['text'], start_tag, end_tag)
url = f"{metadata['url']}#:~:text={quote(text)}"
citation_inx = refs_dict[url]
summary = summary[:start] + f'[\[{citation_inx}\]]({url})' + summary[end:]
return summary
|