Add image upload and vision analysis to Ask Simba chat

Users can now attach images in the web chat for Simba to analyze using
Ollama's gemma3 vision model. Images are stored in Garage (S3-compatible)
and displayed in chat history.

Also fixes aerich migration config by extracting TORTOISE_CONFIG into a
standalone config/db.py module, removing the stale aerich_config.py, and
adding missing MODELS_STATE to migration 3.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

blueprints/conversation/__init__.py

@@ -1,13 +1,19 @@
 import datetime
 import json
+import logging
+import uuid
 
-from quart import Blueprint, jsonify, make_response, request
+from quart import Blueprint, Response, jsonify, make_response, request
 from quart_jwt_extended import (
     get_jwt_identity,
     jwt_refresh_token_required,
 )
 
 import blueprints.users.models
+from utils.image_process import analyze_user_image
+from utils.image_upload import ImageValidationError, process_image
+from utils.s3_client import get_image as s3_get_image
+from utils.s3_client import upload_image as s3_upload_image
 
 from .agents import main_agent
 from .logic import (
@@ -29,7 +35,9 @@ conversation_blueprint = Blueprint(
 _SYSTEM_PROMPT = SIMBA_SYSTEM_PROMPT
 
 
-def _build_messages_payload(conversation, query_text: str) -> list:
+def _build_messages_payload(
+    conversation, query_text: str, image_description: str | None = None
+) -> list:
     recent_messages = (
         conversation.messages[-10:]
         if len(conversation.messages) > 10
@@ -38,8 +46,19 @@ def _build_messages_payload(conversation, query_text: str) -> list:
     messages_payload = [{"role": "system", "content": _SYSTEM_PROMPT}]
     for msg in recent_messages[:-1]:  # Exclude the message we just added
         role = "user" if msg.speaker == "user" else "assistant"
-        messages_payload.append({"role": role, "content": msg.text})
-    messages_payload.append({"role": "user", "content": query_text})
+        text = msg.text
+        if msg.image_key and role == "user":
+            text = f"[User sent an image]\n{text}"
+        messages_payload.append({"role": role, "content": text})
+
+    # Build the current user message with optional image description
+    if image_description:
+        content = f"[Image analysis: {image_description}]"
+        if query_text:
+            content = f"{query_text}\n\n{content}"
+    else:
+        content = query_text
+    messages_payload.append({"role": "user", "content": content})
     return messages_payload
 
 
@@ -74,6 +93,58 @@ async def query():
     return jsonify({"response": message})
 
 
+@conversation_blueprint.post("/upload-image")
+@jwt_refresh_token_required
+async def upload_image():
+    current_user_uuid = get_jwt_identity()
+    await blueprints.users.models.User.get(id=current_user_uuid)
+
+    files = await request.files
+    form = await request.form
+    file = files.get("file")
+    conversation_id = form.get("conversation_id")
+
+    if not file or not conversation_id:
+        return jsonify({"error": "file and conversation_id are required"}), 400
+
+    file_bytes = file.read()
+    content_type = file.content_type or "image/jpeg"
+
+    try:
+        processed_bytes, output_content_type = process_image(file_bytes, content_type)
+    except ImageValidationError as e:
+        return jsonify({"error": str(e)}), 400
+
+    ext = output_content_type.split("/")[-1]
+    if ext == "jpeg":
+        ext = "jpg"
+    key = f"conversations/{conversation_id}/{uuid.uuid4()}.{ext}"
+
+    await s3_upload_image(processed_bytes, key, output_content_type)
+
+    return jsonify(
+        {
+            "image_key": key,
+            "image_url": f"/api/conversation/image/{key}",
+        }
+    )
+
+
+@conversation_blueprint.get("/image/<path:image_key>")
+@jwt_refresh_token_required
+async def serve_image(image_key: str):
+    try:
+        image_bytes, content_type = await s3_get_image(image_key)
+    except Exception:
+        return jsonify({"error": "Image not found"}), 404
+
+    return Response(
+        image_bytes,
+        content_type=content_type,
+        headers={"Cache-Control": "private, max-age=3600"},
+    )
+
+
 @conversation_blueprint.post("/stream-query")
 @jwt_refresh_token_required
 async def stream_query():
@@ -82,16 +153,31 @@ async def stream_query():
     data = await request.get_json()
     query_text = data.get("query")
     conversation_id = data.get("conversation_id")
+    image_key = data.get("image_key")
     conversation = await get_conversation_by_id(conversation_id)
     await conversation.fetch_related("messages")
     await add_message_to_conversation(
         conversation=conversation,
-        message=query_text,
+        message=query_text or "",
         speaker="user",
         user=user,
+        image_key=image_key,
     )
 
-    messages_payload = _build_messages_payload(conversation, query_text)
+    # If an image was uploaded, analyze it with the vision model
+    image_description = None
+    if image_key:
+        try:
+            image_bytes, _ = await s3_get_image(image_key)
+            image_description = await analyze_user_image(image_bytes)
+            logging.info(f"Image analysis complete for {image_key}")
+        except Exception as e:
+            logging.error(f"Failed to analyze image: {e}")
+            image_description = "[Image could not be analyzed]"
+
+    messages_payload = _build_messages_payload(
+        conversation, query_text or "", image_description
+    )
     payload = {"messages": messages_payload}
 
     async def event_generator():
@@ -160,6 +246,7 @@ async def get_conversation(conversation_id: str):
                 "text": msg.text,
                 "speaker": msg.speaker.value,
                 "created_at": msg.created_at.isoformat(),
+                "image_key": msg.image_key,
             }
         )
     name = conversation.name