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This commit is contained in:
mrT23
2023-09-06 09:12:25 +03:00
parent dcd8196b94
commit bc95cf5b8e
3 changed files with 25 additions and 15 deletions
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19
pr_agent/tools/pr_similar_issue.py
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@ -132,7 +132,7 @@ class PRSimilarIssue:
header = issue.title
body = issue.body
number = issue.number
if get_settings().pinecone.skip_comments:
if get_settings().pr_similar_issue.skip_comments:
comments = []
else:
comments = list(issue.get_comments())
@ -151,11 +151,12 @@ class PRSimilarIssue:
counter = 0
for issue in issues_list:
if issue.pull_request:
continue
counter += 1
if counter % 100 == 0:
logging.info(f"Scanned {counter} issues")
if counter >= self.max_issues_to_scan:
logging.info(f"Scanned {self.max_issues_to_scan} issues, stopping")
break
@ -179,7 +180,7 @@ class PRSimilarIssue:
for j, comment in enumerate(comments):
comment_body = comment.body
num_words_comment = len(comment_body.split())
if num_words_comment < 10:
if num_words_comment < 10 or not isinstance(comment_body, str):
continue
if len(issue_str) < 8000 or \
@ -199,8 +200,14 @@ class PRSimilarIssue:
logging.info('Embedding...')
openai.api_key = get_settings().openai.key
list_to_encode = list(df["text"].values)
res = openai.Embedding.create(input=list_to_encode, engine=MODEL)
embeds = [record['embedding'] for record in res['data']]
try:
res = openai.Embedding.create(input=list_to_encode, engine=MODEL)
embeds = [record['embedding'] for record in res['data']]
except:
embeds = []
for i, text in enumerate(list_to_encode):
res = openai.Embedding.create(input=[text], engine=MODEL)
embeds.append(res['data'][0]['embedding'])
df["values"] = embeds
meta = DatasetMetadata.empty()
meta.dense_model.dimension = len(embeds[0])
@ -210,7 +217,7 @@ class PRSimilarIssue:
api_key = get_settings().pinecone.api_key
environment = get_settings().pinecone.environment
if not upsert:
logging.info('Creating index...')
logging.info('Creating index from scratch...')
ds.to_pinecone_index(self.index_name, api_key=api_key, environment=environment)
else:
logging.info('Upserting index...')