567 lines
22 KiB
Python
567 lines
22 KiB
Python
"""Farm AI Assistant API views."""
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import json
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import logging
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from copy import deepcopy
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from django.db.models import Count
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from django.http import Http404
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from rest_framework import serializers, status
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from rest_framework.exceptions import ParseError
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from rest_framework.permissions import IsAuthenticated
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from rest_framework.response import Response
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from rest_framework.views import APIView
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from drf_spectacular.types import OpenApiTypes
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from drf_spectacular.utils import OpenApiParameter, extend_schema
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from config.swagger import status_response
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from external_api_adapter import request as external_api_request
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from external_api_adapter.exceptions import ExternalAPIRequestError
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from farm_hub.models import FarmHub
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from .mock_data import CONTEXT_RESPONSE_DATA
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from .models import Conversation, Message
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from .serializers import (
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ChatPostSerializer,
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ChatResponseDataSerializer,
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ConversationCreateSerializer,
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ConversationDeleteSerializer,
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ConversationMessagesSerializer,
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ConversationSummarySerializer,
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)
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logger = logging.getLogger(__name__)
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class FarmAccessMixin:
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@staticmethod
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def _get_farm(request, farm_uuid):
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if not farm_uuid:
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raise serializers.ValidationError({"farm_uuid": ["This field is required."]})
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return FarmAccessMixin._get_optional_farm(request, farm_uuid)
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@staticmethod
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def _get_optional_farm(request, farm_uuid):
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if not farm_uuid:
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return None
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try:
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return FarmHub.objects.get(farm_uuid=farm_uuid, owner=request.user)
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except FarmHub.DoesNotExist as exc:
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raise Http404("Farm not found") from exc
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@staticmethod
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def _farm_uuid_or_none(farm):
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return str(farm.farm_uuid) if farm else None
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class ContextView(FarmAccessMixin, APIView):
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permission_classes = [IsAuthenticated]
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@extend_schema(
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tags=["Farm AI Assistant"],
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parameters=[
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OpenApiParameter(name="farm_uuid", type=OpenApiTypes.UUID, location=OpenApiParameter.QUERY, required=False, default="11111111-1111-1111-1111-111111111111"),
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],
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responses={200: status_response("FarmAiAssistantContextResponse", data=serializers.JSONField())},
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)
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def get(self, request):
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farm = self._get_optional_farm(request, request.query_params.get("farm_uuid"))
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data = deepcopy(CONTEXT_RESPONSE_DATA)
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data["farm_uuid"] = self._farm_uuid_or_none(farm)
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return Response(
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{"status": "success", "data": data},
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status=status.HTTP_200_OK,
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)
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class ConversationAccessMixin(FarmAccessMixin):
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@staticmethod
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def _generate_conversation_title(query):
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normalized_query = (query or "").strip()
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if not normalized_query:
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return "Image"
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first_word = normalized_query.split()[0].strip()
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return (first_word or normalized_query or "New chat")[:255]
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@staticmethod
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def _get_conversation(request, conversation_id, farm_uuid=None):
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filters = {"uuid": conversation_id, "owner": request.user}
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if farm_uuid:
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filters["farm__farm_uuid"] = farm_uuid
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else:
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filters["farm__isnull"] = True
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try:
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return Conversation.objects.select_related("farm").get(**filters)
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except Conversation.DoesNotExist as exc:
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raise Http404("Conversation not found") from exc
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@staticmethod
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def _normalize_sections(raw_sections):
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if not isinstance(raw_sections, list):
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return []
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allowed_keys = {
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"type",
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"title",
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"content",
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"items",
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"icon",
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"primaryAction",
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"frequency",
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"amount",
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"timing",
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"validityPeriod",
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"expandableExplanation",
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}
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normalized_sections = []
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for section in raw_sections:
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if not isinstance(section, dict) or not section.get("type"):
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continue
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normalized_section = {}
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for key in allowed_keys:
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value = section.get(key)
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if value is None:
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continue
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if key == "items":
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if not isinstance(value, list):
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continue
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normalized_section[key] = [str(item) for item in value]
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continue
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normalized_section[key] = str(value) if key != "type" else value
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normalized_sections.append(normalized_section)
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return normalized_sections
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def _get_or_create_conversation(self, request, validated):
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conversation_id = validated.get("conversation_id")
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farm = self._get_optional_farm(request, validated.get("farm_uuid"))
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if conversation_id:
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conversation = self._get_conversation(
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request,
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conversation_id,
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farm.farm_uuid if farm else None,
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)
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return conversation
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return Conversation.objects.create(
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owner=request.user,
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farm=farm,
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title=self._generate_conversation_title(validated.get("query", "")),
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farm_context={},
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)
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@staticmethod
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def _serialize_history_messages(history):
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normalized_history = []
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for item in history or []:
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if not isinstance(item, dict):
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continue
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role = str(item.get("role") or "").strip()
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content = str(item.get("content") or item.get("message") or "").strip()
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if not role and not content:
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continue
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normalized_item = {}
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if role:
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normalized_item["role"] = role
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if content:
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normalized_item["content"] = content
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if item.get("sections") is not None:
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normalized_item["sections"] = item.get("sections")
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normalized_history.append(normalized_item)
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return normalized_history
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@staticmethod
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def _build_adapter_payload(request, validated, conversation):
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payload = {
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"farm_uuid": str(conversation.farm.farm_uuid) if conversation.farm else "",
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"query": validated.get("query", ""),
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"history": ConversationAccessMixin._serialize_history_messages(validated.get("history", [])),
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"image_urls": validated.get("image_urls", []),
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"images": validated.get("images", []),
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"conversation_id": str(conversation.uuid),
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"user_id": request.user.id,
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}
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return payload
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@staticmethod
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def _attach_uploaded_files(payload, uploaded_images):
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if not uploaded_images:
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return payload
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files = []
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for uploaded_image in uploaded_images:
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files.append(
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(
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"images",
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(
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uploaded_image.name,
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uploaded_image,
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getattr(uploaded_image, "content_type", "application/octet-stream"),
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),
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)
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)
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multipart_payload = dict(payload)
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multipart_payload["history"] = json.dumps(payload.get("history", []), ensure_ascii=False)
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multipart_payload["image_urls"] = json.dumps(payload.get("image_urls", []), ensure_ascii=False)
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multipart_payload["__files__"] = files
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return multipart_payload
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@staticmethod
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def _parse_json_array(value):
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if not isinstance(value, str):
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return None
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try:
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parsed = json.loads(value)
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except (TypeError, ValueError):
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return None
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return parsed if isinstance(parsed, list) else None
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def _collect_uploaded_images(self, request):
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uploaded_images = []
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single_image = request.FILES.get("image")
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if single_image is not None:
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uploaded_images.append(single_image)
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uploaded_images.extend(request.FILES.getlist("images"))
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return uploaded_images
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def _merge_history(self, validated, conversation):
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provided_history = validated.get("history", [])
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if provided_history:
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return self._serialize_history_messages(provided_history)
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existing_messages = conversation.messages.order_by("created_at")
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return [
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{
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"role": message.role,
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"content": message.content,
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**({"sections": message.raw_response.get("sections", [])} if message.role == Message.ROLE_ASSISTANT else {}),
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}
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for message in existing_messages
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if message.content or (message.role == Message.ROLE_ASSISTANT and message.raw_response.get("sections"))
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]
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def _prepare_chat_input(self, request):
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mutable_data = request.data.copy()
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for field_name in ("message", "content", "title", "farm_context"):
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if field_name in mutable_data:
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mutable_data.pop(field_name)
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if "history" in mutable_data:
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parsed_history = self._parse_json_array(mutable_data.get("history"))
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if parsed_history is not None:
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mutable_data["history"] = parsed_history
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if "image_urls" in mutable_data and isinstance(mutable_data.get("image_urls"), str):
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parsed_urls = self._parse_json_array(mutable_data.get("image_urls"))
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if parsed_urls is not None:
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mutable_data.setlist("image_urls", parsed_urls) if hasattr(mutable_data, "setlist") else mutable_data.__setitem__("image_urls", parsed_urls)
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if "images" in mutable_data and isinstance(mutable_data.get("images"), str):
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parsed_images = self._parse_json_array(mutable_data.get("images"))
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if parsed_images is not None:
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mutable_data.setlist("images", parsed_images) if hasattr(mutable_data, "setlist") else mutable_data.__setitem__("images", parsed_images)
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return mutable_data
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def _extract_assistant_payload(self, adapter_data, conversation):
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payload_source = adapter_data
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if isinstance(adapter_data, dict) and isinstance(adapter_data.get("data"), dict):
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payload_source = adapter_data["data"]
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logger.warning(
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"Farm AI assistant parsing response: conversation_id=%s adapter_type=%s adapter_keys=%s payload_source_type=%s payload_source_keys=%s",
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str(conversation.uuid),
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type(adapter_data).__name__,
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sorted(adapter_data.keys()) if isinstance(adapter_data, dict) else None,
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type(payload_source).__name__,
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sorted(payload_source.keys()) if isinstance(payload_source, dict) else None,
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)
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content = ""
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sections = []
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if isinstance(payload_source, dict):
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content = payload_source.get("content") or ""
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sections = self._normalize_sections(payload_source.get("sections"))
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logger.warning(
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"Farm AI assistant payload_source parsed: conversation_id=%s raw_content_present=%s raw_sections_type=%s normalized_sections_count=%s",
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str(conversation.uuid),
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bool(content),
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type(payload_source.get("sections")).__name__ if payload_source.get("sections") is not None else None,
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len(sections),
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)
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logger.warning("%s %s", isinstance(payload_source, dict), not sections and isinstance(adapter_data, dict))
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if not sections and isinstance(adapter_data, dict):
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sections = self._normalize_sections(adapter_data.get("sections"))
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logger.warning(
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"Farm AI assistant root-level sections fallback: conversation_id=%s raw_sections_type=%s normalized_sections_count=%s",
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str(conversation.uuid),
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type(adapter_data.get("sections")).__name__ if adapter_data.get("sections") is not None else None,
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len(sections),
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)
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if not content and isinstance(adapter_data, dict):
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content = adapter_data.get("body") or adapter_data.get("content") or ""
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logger.warning(
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"Farm AI assistant content fallback: conversation_id=%s body_present=%s content_present=%s final_content_present=%s",
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str(conversation.uuid),
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bool(adapter_data.get("body")),
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bool(adapter_data.get("content")),
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bool(content),
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)
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if isinstance(adapter_data, dict) and adapter_data.get("result") is not None:
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logger.warning(
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"Farm AI assistant unparsed result detected: conversation_id=%s result_type=%s result_keys=%s",
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str(conversation.uuid),
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type(adapter_data.get("result")).__name__,
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sorted(adapter_data["result"].keys()) if isinstance(adapter_data.get("result"), dict) else None,
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)
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logger.warning(
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"Farm AI assistant final parsed payload: conversation_id=%s content_length=%s sections_count=%s",
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str(conversation.uuid),
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len(content or ""),
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len(sections),
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)
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return {
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"message_id": "",
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"conversation_id": str(conversation.uuid),
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"farm_uuid": self._farm_uuid_or_none(conversation.farm),
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"content": content,
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"sections": sections,
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}
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@staticmethod
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def _serialize_chat_message(message):
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raw_response = message.raw_response if isinstance(message.raw_response, dict) else {}
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sections = raw_response.get("sections") if message.role == Message.ROLE_ASSISTANT else []
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return {
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"message_id": str(message.uuid),
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"conversation_id": str(message.conversation.uuid),
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"farm_uuid": ConversationAccessMixin._farm_uuid_or_none(message.farm),
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"role": message.role,
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"content": message.content,
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"sections": ConversationAccessMixin._normalize_sections(sections),
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"images": message.images if isinstance(message.images, list) else [],
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"created_at": message.created_at,
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}
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class ChatListCreateView(ConversationAccessMixin, APIView):
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permission_classes = [IsAuthenticated]
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@extend_schema(
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tags=["Farm AI Assistant"],
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parameters=[
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OpenApiParameter(name="farm_uuid", type=OpenApiTypes.UUID, location=OpenApiParameter.QUERY, required=False, default="11111111-1111-1111-1111-111111111111"),
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],
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responses={200: status_response("FarmAiAssistantConversationListResponse", data=ConversationSummarySerializer(many=True))},
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)
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def get(self, request):
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farm = self._get_optional_farm(request, request.query_params.get("farm_uuid"))
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conversations = (
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Conversation.objects.filter(owner=request.user, farm=farm)
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.annotate(message_count=Count("messages"))
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.order_by("-updated_at", "-created_at")
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)
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serializer = ConversationSummarySerializer(conversations, many=True)
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return Response({"status": "success", "data": serializer.data}, status=status.HTTP_200_OK)
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@extend_schema(
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tags=["Farm AI Assistant"],
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request=ConversationCreateSerializer,
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responses={201: status_response("FarmAiAssistantConversationCreateResponse", data=ConversationSummarySerializer())},
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)
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def post(self, request):
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serializer = ConversationCreateSerializer(data=request.data)
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serializer.is_valid(raise_exception=True)
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validated = serializer.validated_data
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farm = self._get_optional_farm(request, validated.get("farm_uuid"))
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conversation = Conversation.objects.create(
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owner=request.user,
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farm=farm,
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title=validated.get("title", "").strip() or "New chat",
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farm_context=validated.get("farm_context") or {},
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)
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response_serializer = ConversationSummarySerializer(
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{
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"uuid": conversation.uuid,
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"farm": farm,
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"message_count": 0,
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}
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)
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return Response({"status": "success", "data": response_serializer.data}, status=status.HTTP_201_CREATED)
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class ChatMessagesView(ConversationAccessMixin, APIView):
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permission_classes = [IsAuthenticated]
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@extend_schema(
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tags=["Farm AI Assistant"],
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parameters=[
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OpenApiParameter(name="conversation_id", type=OpenApiTypes.UUID, location=OpenApiParameter.PATH),
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OpenApiParameter(name="farm_uuid", type=OpenApiTypes.UUID, location=OpenApiParameter.QUERY, required=False, default="11111111-1111-1111-1111-111111111111"),
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],
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responses={200: status_response("FarmAiAssistantMessageListResponse", data=ConversationMessagesSerializer())},
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)
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def get(self, request, conversation_id):
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farm = self._get_optional_farm(request, request.query_params.get("farm_uuid"))
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conversation = self._get_conversation(request, conversation_id, farm.farm_uuid if farm else None)
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messages = conversation.messages.select_related("farm").all()
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serialized_messages = [self._serialize_chat_message(message) for message in messages]
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return Response(
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{
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"status": "success",
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"data": {
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"conversation_id": str(conversation.uuid),
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"farm_uuid": self._farm_uuid_or_none(farm),
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"messages": serialized_messages,
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},
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},
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status=status.HTTP_200_OK,
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)
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class ChatDetailView(ConversationAccessMixin, APIView):
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permission_classes = [IsAuthenticated]
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@extend_schema(
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tags=["Farm AI Assistant"],
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parameters=[
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OpenApiParameter(name="conversation_id", type=OpenApiTypes.UUID, location=OpenApiParameter.PATH),
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OpenApiParameter(name="farm_uuid", type=OpenApiTypes.UUID, location=OpenApiParameter.QUERY, required=False, default="11111111-1111-1111-1111-111111111111"),
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],
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responses={200: status_response("FarmAiAssistantConversationDeleteResponse", data=ConversationDeleteSerializer())},
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)
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def delete(self, request, conversation_id):
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farm = self._get_optional_farm(request, request.query_params.get("farm_uuid"))
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conversation = self._get_conversation(request, conversation_id, farm.farm_uuid if farm else None)
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deleted_conversation_id = str(conversation.uuid)
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deleted_farm_uuid = self._farm_uuid_or_none(conversation.farm)
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conversation.delete()
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return Response(
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{
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"status": "success",
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"data": {
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"conversation_id": deleted_conversation_id,
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"farm_uuid": deleted_farm_uuid,
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},
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},
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status=status.HTTP_200_OK,
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)
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class ChatView(ConversationAccessMixin, APIView):
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permission_classes = [IsAuthenticated]
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@extend_schema(
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tags=["Farm AI Assistant"],
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request=ChatPostSerializer,
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responses={200: status_response("FarmAiAssistantChatResponse", data=ChatResponseDataSerializer())},
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)
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def post(self, request):
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try:
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chat_input = self._prepare_chat_input(request)
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except ParseError:
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return Response(
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{
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"status": "error",
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"data": {
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"message": "Invalid JSON body. Use valid JSON and remove extra trailing characters.",
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},
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},
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status=status.HTTP_400_BAD_REQUEST,
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)
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serializer = ChatPostSerializer(data=chat_input)
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serializer.is_valid(raise_exception=True)
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validated = serializer.validated_data
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conversation = self._get_or_create_conversation(request, validated)
|
|
history = self._merge_history(validated, conversation)
|
|
uploaded_images = self._collect_uploaded_images(request)
|
|
|
|
user_message = Message.objects.create(
|
|
conversation=conversation,
|
|
farm=conversation.farm,
|
|
role=Message.ROLE_USER,
|
|
content=validated.get("query", ""),
|
|
images=validated.get("image_urls", []) + validated.get("images", []),
|
|
raw_response={
|
|
"farm_uuid": self._farm_uuid_or_none(conversation.farm),
|
|
"history": history,
|
|
},
|
|
)
|
|
|
|
adapter_payload = self._build_adapter_payload(request, validated, conversation)
|
|
adapter_payload["history"] = history
|
|
adapter_payload = self._attach_uploaded_files(adapter_payload, uploaded_images)
|
|
|
|
try:
|
|
adapter_response = external_api_request(
|
|
"ai",
|
|
"/api/rag/chat/",
|
|
method="POST",
|
|
payload=adapter_payload,
|
|
)
|
|
logger.warning(
|
|
"Farm AI assistant adapter response received: conversation_id=%s status_code=%s response_type=%s response_keys=%s",
|
|
str(conversation.uuid),
|
|
adapter_response.status_code,
|
|
type(adapter_response.data).__name__,
|
|
adapter_response
|
|
)
|
|
if adapter_response.status_code >= 400:
|
|
return Response(
|
|
{
|
|
"status": "error",
|
|
"data": adapter_response.data,
|
|
},
|
|
status=adapter_response.status_code,
|
|
)
|
|
assistant_payload = self._extract_assistant_payload(adapter_response.data, conversation)
|
|
response_status_code = adapter_response.status_code
|
|
except ExternalAPIRequestError as exc:
|
|
return Response(
|
|
{
|
|
"status": "error",
|
|
"data": {
|
|
"message": str(exc) or "External AI service is unavailable.",
|
|
},
|
|
},
|
|
status=status.HTTP_503_SERVICE_UNAVAILABLE,
|
|
)
|
|
|
|
assistant_message = Message.objects.create(
|
|
conversation=conversation,
|
|
farm=conversation.farm,
|
|
role=Message.ROLE_ASSISTANT,
|
|
content=assistant_payload.get("content", ""),
|
|
raw_response={},
|
|
)
|
|
assistant_payload["message_id"] = str(assistant_message.uuid)
|
|
assistant_message.raw_response = assistant_payload
|
|
assistant_message.save(update_fields=["raw_response"])
|
|
|
|
if not conversation.title:
|
|
conversation.title = self._generate_conversation_title(validated.get("query", ""))
|
|
conversation.save(update_fields=["title", "updated_at"])
|
|
else:
|
|
conversation.save(update_fields=["updated_at"])
|
|
|
|
return Response(
|
|
{
|
|
"status": "success",
|
|
"data": assistant_payload,
|
|
},
|
|
status=response_status_code,
|
|
)
|