plane/apiserver/plane/api/views/gpt.py
2023-09-05 13:11:31 +05:30

76 lines
2.5 KiB
Python

# Python imports
import requests
# Third party imports
from rest_framework.response import Response
from rest_framework import status
import openai
from sentry_sdk import capture_exception
# Django imports
from django.conf import settings
# Module imports
from .base import BaseAPIView
from plane.api.permissions import ProjectEntityPermission
from plane.db.models import Workspace, Project
from plane.api.serializers import ProjectLiteSerializer, WorkspaceLiteSerializer
class GPTIntegrationEndpoint(BaseAPIView):
permission_classes = [
ProjectEntityPermission,
]
def post(self, request, slug, project_id):
try:
if not settings.OPENAI_API_KEY or not settings.GPT_ENGINE:
return Response(
{"error": "OpenAI API key and engine is required"},
status=status.HTTP_400_BAD_REQUEST,
)
prompt = request.data.get("prompt", False)
task = request.data.get("task", False)
if not task:
return Response(
{"error": "Task is required"}, status=status.HTTP_400_BAD_REQUEST
)
final_text = task + "\n" + prompt
openai.api_key = settings.OPENAI_API_KEY
response = openai.ChatCompletion.create(
model=settings.GPT_ENGINE,
messages=[{"role": "user", "content": final_text}],
temperature=0.7,
max_tokens=1024,
)
workspace = Workspace.objects.get(slug=slug)
project = Project.objects.get(pk=project_id)
text = response.choices[0].message.content.strip()
text_html = text.replace("\n", "<br/>")
return Response(
{
"response": text,
"response_html": text_html,
"project_detail": ProjectLiteSerializer(project).data,
"workspace_detail": WorkspaceLiteSerializer(workspace).data,
},
status=status.HTTP_200_OK,
)
except (Workspace.DoesNotExist, Project.DoesNotExist) as e:
return Response(
{"error": "Workspace or Project Does not exist"},
status=status.HTTP_400_BAD_REQUEST,
)
except Exception as e:
capture_exception(e)
return Response(
{"error": "Something went wrong please try again later"},
status=status.HTTP_400_BAD_REQUEST,
)