Fix passing inline images to vision models

- Fix regression: Inline images were not getting passed to the AI
  models since #992
- Format inline images passed to Gemini models correctly
- Format inline images passed to Anthropic models correctly

Verified vision working with inline and url images for OpenAI,
Anthropic and Gemini models.

Resolves #1112

src/khoj/processor/conversation/anthropic/utils.py

@@ -15,6 +15,7 @@ from tenacity import (
 from khoj.processor.conversation.utils import (
     ThreadedGenerator,
     commit_conversation_trace,
+    get_image_from_base64,
     get_image_from_url,
 )
 from khoj.utils.helpers import (
@@ -232,7 +233,11 @@ def format_messages_for_anthropic(messages: list[ChatMessage], system_prompt=Non
                 if part["type"] == "text":
                     content.append({"type": "text", "text": part["text"]})
                 elif part["type"] == "image_url":
-                    image = get_image_from_url(part["image_url"]["url"], type="b64")
+                    image_data = part["image_url"]["url"]
+                    if image_data.startswith("http"):
+                        image = get_image_from_url(image_data, type="b64")
+                    else:
+                        image = get_image_from_base64(image_data, type="b64")
                     # Prefix each image with text block enumerating the image number
                     # This helps the model reference the image in its response. Recommended by Anthropic
                     content.extend(

src/khoj/processor/conversation/google/utils.py

@@ -18,6 +18,7 @@ from tenacity import (
 from khoj.processor.conversation.utils import (
     ThreadedGenerator,
     commit_conversation_trace,
+    get_image_from_base64,
     get_image_from_url,
 )
 from khoj.utils.helpers import (
@@ -245,7 +246,11 @@ def format_messages_for_gemini(
             message_content = []
             for item in sorted(message.content, key=lambda x: 0 if x["type"] == "image_url" else 1):
                 if item["type"] == "image_url":
-                    image = get_image_from_url(item["image_url"]["url"], type="bytes")
+                    image_data = item["image_url"]["url"]
+                    if image_data.startswith("http"):
+                        image = get_image_from_url(image_data, type="bytes")
+                    else:
+                        image = get_image_from_base64(image_data, type="bytes")
                     message_content += [gtypes.Part.from_bytes(data=image.content, mime_type=image.type)]
                 else:
                     message_content += [gtypes.Part.from_text(text=item.get("text", ""))]

src/khoj/processor/conversation/utils.py

@@ -345,7 +345,6 @@ def construct_structured_message(
             constructed_messages.append({"type": "text", "text": attached_file_context})
         if vision_enabled and images:
             for image in images:
-                if image.startswith("https://"):
                 constructed_messages.append({"type": "image_url", "image_url": {"url": image}})
         return constructed_messages
 
@@ -664,6 +663,23 @@ class ImageWithType:
     type: str
 
 
+def get_image_from_base64(image: str, type="b64"):
+    # Extract image type and base64 data from inline image data
+    image_base64 = image.split(",", 1)[1]
+    image_type = image.split(";", 1)[0].split(":", 1)[1]
+
+    # Convert image to desired format
+    if type == "b64":
+        return ImageWithType(content=image_base64, type=image_type)
+    elif type == "pil":
+        image_data = base64.b64decode(image_base64)
+        image_pil = PIL.Image.open(BytesIO(image_data))
+        return ImageWithType(content=image_pil, type=image_type)
+    elif type == "bytes":
+        image_data = base64.b64decode(image_base64)
+        return ImageWithType(content=image_data, type=image_type)
+
+
 def get_image_from_url(image_url: str, type="pil"):
     try:
         response = requests.get(image_url)

src/khoj/routers/api_chat.py

@@ -675,7 +675,9 @@ async def chat(
                 image_bytes = base64.b64decode(base64_data)
                 webp_image_bytes = convert_image_to_webp(image_bytes)
                 uploaded_image = upload_user_image_to_bucket(webp_image_bytes, request.user.object.id)
-                if uploaded_image:
+                if not uploaded_image:
+                    base64_webp_image = base64.b64encode(webp_image_bytes).decode("utf-8")
+                    uploaded_image = f"data:image/webp;base64,{base64_webp_image}"
                 uploaded_images.append(uploaded_image)
 
         query_files: Dict[str, str] = {}