chore-refactor_askAI

apiserver/plane/app/urls/__init__.py

@@ -1,3 +1,4 @@
+from .ai import urlpatterns as ai_urls
 from .analytic import urlpatterns as analytic_urls
 from .api import urlpatterns as api_urls
 from .asset import urlpatterns as asset_urls
@@ -19,6 +20,7 @@ from .webhook import urlpatterns as webhook_urls
 from .workspace import urlpatterns as workspace_urls
 
 urlpatterns = [
+    *ai_urls,
     *analytic_urls,
     *asset_urls,
     *cycle_urls,

apiserver/plane/app/urls/ai.py

@@ -0,0 +1,12 @@
+from django.urls import path
+
+
+from plane.app.views import AskAIEndpoint
+
+urlpatterns = [
+    path(
+        "workspaces/<str:slug>/ask-AI/",
+        AskAIEndpoint.as_view(),
+        name="askAI",
+    ),
+]

apiserver/plane/app/urls/external.py

@@ -2,23 +2,11 @@ from django.urls import path
 
 
 from plane.app.views import UnsplashEndpoint
-from plane.app.views import GPTIntegrationEndpoint, WorkspaceGPTIntegrationEndpoint
-
 
 urlpatterns = [
     path(
         "unsplash/",
         UnsplashEndpoint.as_view(),
         name="unsplash",
-    ),
-    path(
-        "workspaces/<str:slug>/projects/<uuid:project_id>/ai-assistant/",
-        GPTIntegrationEndpoint.as_view(),
-        name="importer",
-    ),
-   path(
-        "workspaces/<str:slug>/ai-assistant/",
-        WorkspaceGPTIntegrationEndpoint.as_view(),
-        name="importer",
-    ),
+    )
 ]

apiserver/plane/app/views/__init__.py

@@ -191,12 +191,10 @@ from .page.version import PageVersionEndpoint
 from .search.base import GlobalSearchEndpoint
 from .search.issue import IssueSearchEndpoint
 
+from .external.base import UnsplashEndpoint
+
+from .ai.base import AskAIEndpoint
 
-from .external.base import (
-    GPTIntegrationEndpoint,
-    UnsplashEndpoint,
-    WorkspaceGPTIntegrationEndpoint,
-)
 from .estimate.base import (
     ProjectEstimatePointEndpoint,
     BulkEstimatePointEndpoint,

apiserver/plane/app/views/ai/base.py

@@ -0,0 +1,109 @@
+# Python imports
+import os
+from enum import Enum
+
+
+# Third party imports
+from openai import OpenAI
+from rest_framework.response import Response
+from rest_framework import status
+
+# Django imports
+
+# Module imports
+from ..base import BaseAPIView
+from plane.app.permissions import (
+    WorkspaceEntityPermission,
+)
+from plane.license.utils.instance_value import get_configuration_value
+
+
+class Task(Enum):
+    ASK_AI = "ASK_AI"
+
+
+class AskAIEndpoint(BaseAPIView):
+    permission_classes = [
+        WorkspaceEntityPermission,
+    ]
+
+    def get_system_prompt(self, task):
+        if task == Task.ASK_AI.value:
+            return (
+                True,
+                """
+                You are an advanced AI assistant designed to provide optimal responses by integrating given context with your broad knowledge base. Your primary objectives are:
+
+                1. Thoroughly analyze and understand the provided context, which may include context, specific questions, code snippets, or any relevant information.
+                2. Treat the given context as a critical input, using it to inform and guide your response.
+                3. Leverage your extensive knowledge to complement and enhance your understanding of the context and to provide comprehensive, accurate answers.
+                4. Seamlessly blend insights from the given context with your general knowledge, ensuring a cohesive and informative response.
+                5. Adapt your response style and depth based on the nature of the context and the question asked.
+                6. When dealing with code or technical context, provide explanations or solutions that are directly relevant and technically sound.
+                7. Maintain clarity and conciseness in your responses while ensuring they are complete and informative.
+                8. Use appropriate HTML tags for formatting only when it enhances readability or structure of the response.
+                9. Respect privacy and avoid sensationalism when addressing sensitive topics.
+
+                Your goal is to deliver the most relevant, accurate, and helpful response possible, considering both the provided content and your broader understanding.
+                """,
+            )
+        else:
+            return False, {
+                "error": "Invalid task. Please provide a correct task name."
+            }
+
+    def post(self, request, slug):
+        task = request.data.get("task", "ASK_AI")
+        context = request.data.get("text_input", "")
+        user_prompt = request.data.get("query", "")
+
+        if not context or not user_prompt:
+            return Response(
+                {"error": "Query and Text input are required"},
+                status=status.HTTP_400_BAD_REQUEST,
+            )
+
+        OPENAI_API_KEY, GPT_ENGINE = get_configuration_value(
+            [
+                {
+                    "key": "OPENAI_API_KEY",
+                    "default": os.environ.get("OPENAI_API_KEY", None),
+                },
+                {
+                    "key": "GPT_ENGINE",
+                    "default": os.environ.get("GPT_ENGINE", "gpt-3.5-turbo"),
+                },
+            ]
+        )
+
+        if not OPENAI_API_KEY or not GPT_ENGINE:
+            return Response(
+                {"error": "OpenAI API key and engine are required"},
+                status=status.HTTP_400_BAD_REQUEST,
+            )
+
+        client = OpenAI(api_key=OPENAI_API_KEY)
+
+        processed, system_prompt = self.get_system_prompt(task)
+        if not processed:
+            return Response(system_prompt, status=status.HTTP_400_BAD_REQUEST)
+
+        try:
+            completion = client.chat.completions.create(
+                model=GPT_ENGINE,
+                messages=[
+                    {"role": "system", "content": system_prompt},
+                    {
+                        "role": "user",
+                        "content": f"Context:\n\n{context}\n\nQuestion: {user_prompt}",
+                    },
+                ],
+                temperature=0.1,
+            )
+            response = completion.choices[0].message.content.strip()
+            return Response({"response": response}, status=status.HTTP_200_OK)
+        except Exception as e:
+            return Response(
+                {"error": f"An error occurred: {str(e)}"},
+                status=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            )

apiserver/plane/app/views/external/base.py

@@ -2,8 +2,8 @@
 import requests
 import os
 
+
 # Third party imports
-from openai import OpenAI
 from rest_framework.response import Response
 from rest_framework import status
 
@@ -11,136 +11,9 @@ from rest_framework import status
 
 # Module imports
 from ..base import BaseAPIView
-from plane.app.permissions import ProjectEntityPermission, WorkspaceEntityPermission
-from plane.db.models import Workspace, Project
-from plane.app.serializers import (
-    ProjectLiteSerializer,
-    WorkspaceLiteSerializer,
-)
 from plane.license.utils.instance_value import get_configuration_value
 
 
-class GPTIntegrationEndpoint(BaseAPIView):
-    permission_classes = [
-        ProjectEntityPermission,
-    ]
-
-    def post(self, request, slug, project_id):
-        OPENAI_API_KEY, GPT_ENGINE = get_configuration_value(
-            [
-                {
-                    "key": "OPENAI_API_KEY",
-                    "default": os.environ.get("OPENAI_API_KEY", None),
-                },
-                {
-                    "key": "GPT_ENGINE",
-                    "default": os.environ.get("GPT_ENGINE", "gpt-3.5-turbo"),
-                },
-            ]
-        )
-
-        # Get the configuration value
-        # Check the keys
-        if not OPENAI_API_KEY or not 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
-
-        client = OpenAI(
-            api_key=OPENAI_API_KEY,
-        )
-
-        response = client.chat.completions.create(
-            model=GPT_ENGINE,
-            messages=[{"role": "user", "content": final_text}],
-        )
-
-        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,
-        )
-
-
-class WorkspaceGPTIntegrationEndpoint(BaseAPIView):
-    permission_classes = [
-        WorkspaceEntityPermission,
-    ]
-
-    def post(self, request, slug):
-        OPENAI_API_KEY, GPT_ENGINE = get_configuration_value(
-            [
-                {
-                    "key": "OPENAI_API_KEY",
-                    "default": os.environ.get("OPENAI_API_KEY", None),
-                },
-                {
-                    "key": "GPT_ENGINE",
-                    "default": os.environ.get("GPT_ENGINE", "gpt-3.5-turbo"),
-                },
-            ]
-        )
-
-        # Get the configuration value
-        # Check the keys
-        if not OPENAI_API_KEY or not 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
-
-        client = OpenAI(
-            api_key=OPENAI_API_KEY,
-        )
-
-        response = client.chat.completions.create(
-            model=GPT_ENGINE,
-            messages=[{"role": "user", "content": final_text}],
-        )
-
-        text = response.choices[0].message.content.strip()
-        text_html = text.replace("\n", "<br/>")
-        return Response(
-            {
-                "response": text,
-                "response_html": text_html,
-            },
-            status=status.HTTP_200_OK,
-        )
-
-
 class UnsplashEndpoint(BaseAPIView):
     def get(self, request):
         (UNSPLASH_ACCESS_KEY,) = get_configuration_value(