AIEngineeringW1V2 / app /services /summarize.py
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added AI plugin for sentiment and summarize endpoints
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from __future__ import annotations
import os
from typing import Any
from openai import OpenAI
from dotenv import load_dotenv
_DEFAULT_MODEL = "gpt-4.1-mini"
def _extract_text_from_response(response: Any) -> str:
"""Extract assistant text from OpenAI responses API output."""
output = getattr(response, "output", None) or []
chunks: list[str] = []
for item in output:
if getattr(item, "type", None) != "message":
continue
for content_part in getattr(item, "content", None) or []:
if getattr(content_part, "type", None) == "output_text":
text = getattr(content_part, "text", "")
if text:
chunks.append(text)
return "\n".join(chunks).strip()
def _get_summary(text: str, max_length: int) -> str:
"""Generate concise summary text with an OpenAI model."""
load_dotenv()
api_key = os.getenv("OPENAI_API_KEY")
if not api_key:
raise RuntimeError("OPENAI_API_KEY is not set")
model = os.getenv("OPENAI_MODEL", _DEFAULT_MODEL)
client = OpenAI(api_key=api_key)
response = client.responses.create(
model=model,
temperature=0,
input=[
{
"role": "system",
"content": (
"You are a concise summarization assistant. "
"Return only the summary text with no preamble."
),
},
{
"role": "user",
"content": (
f"Summarize the text entered in JSON in under {max_length} words. "
"Return only the summary, no extra commentary.\n\n"
f"Text:\n{text}"
),
},
],
)
summary = _extract_text_from_response(response)
if not summary:
raise RuntimeError("No summary text returned from model")
return summary