Skip to content

[Sweep Rules] Added error handling and logging in summarize.py #21

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
sweep-ai-deprecated wants to merge 1 commit into
base: master
Choose a base branch
from
Open

[Sweep Rules] Added error handling and logging in summarize.py #21

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
43 changes: 24 additions & 19 deletions aicord/core/ai/summarize.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,7 +1,8 @@
from __future__ import annotations

import logging
import os
import logging
logging.basicConfig(level=logging.INFO)

from langchain.schema import (
Document,
Expand Down Expand Up @@ -38,21 +39,25 @@
"""
question_prompt = PromptTemplate.from_template(question_template)

openai_api_key = os.environ['OPENAI_TOKEN']
model_name = "gpt-4-1106-preview"
llm = ChatOpenAI(temperature=0, openai_api_key=openai_api_key, model_name=model_name)
embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)
text_splitter = CharacterTextSplitter.from_tiktoken_encoder(
model_name=model_name,
# chunk_size=1000,
# chunk_overlap=200,
)
chain = load_summarize_chain(
llm,
chain_type="stuff",
prompt=question_prompt,
# chain_type="refine",
# question_prompt=question_prompt,
# refine_prompt=refine_prompt,
verbose=True,
)
try:
openai_api_key = os.environ['OPENAI_TOKEN']
model_name = "gpt-4-1106-preview"
llm = ChatOpenAI(temperature=0, openai_api_key=openai_api_key, model_name=model_name)
embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)
text_splitter = CharacterTextSplitter.from_tiktoken_encoder(
model_name=model_name,
# chunk_size=1000,
# chunk_overlap=200,
)
chain = load_summarize_chain(
llm,
chain_type="stuff",
prompt=question_prompt,
# chain_type="refine",
# question_prompt=question_prompt,
# refine_prompt=refine_prompt,
verbose=True,
)
except Exception as e:
logging.error(f"Error occurred while setting up the model: {str(e)}")
raise