From 971deba8da82c6e15fa7cafacf3aab3b78a124c8 Mon Sep 17 00:00:00 2001
From: 72004 <syahra2014@gmail.com>
Date: Sat, 15 Aug 2026 00:14:01 +0500
Subject: [PATCH] Refactor ImageConverter to reuse llm_caption

---
 .../markitdown/converters/_image_converter.py | 60 +------------------
 1 file changed, 3 insertions(+), 57 deletions(-)

diff --git a/packages/markitdown/src/markitdown/converters/_image_converter.py b/packages/markitdown/src/markitdown/converters/_image_converter.py
index dd8fbac61c..b68b5afc47 100644
--- a/packages/markitdown/src/markitdown/converters/_image_converter.py
+++ b/packages/markitdown/src/markitdown/converters/_image_converter.py
@@ -1,7 +1,6 @@
-from typing import BinaryIO, Any, Union
-import base64
-import mimetypes
+from typing import BinaryIO, Any
 from ._exiftool import exiftool_metadata
+from ._llm_caption import llm_caption
 from .._base_converter import DocumentConverter, DocumentConverterResult
 from .._stream_info import StreamInfo
 
@@ -69,7 +68,7 @@ def convert(
         llm_client = kwargs.get("llm_client")
         llm_model = kwargs.get("llm_model")
         if llm_client is not None and llm_model is not None:
-            llm_description = self._get_llm_description(
+            llm_description = llm_caption(
                 file_stream,
                 stream_info,
                 client=llm_client,
@@ -83,56 +82,3 @@ def convert(
         return DocumentConverterResult(
             markdown=md_content,
         )
-
-    def _get_llm_description(
-        self,
-        file_stream: BinaryIO,
-        stream_info: StreamInfo,
-        *,
-        client,
-        model,
-        prompt=None,
-    ) -> Union[None, str]:
-        if prompt is None or prompt.strip() == "":
-            prompt = "Write a detailed caption for this image."
-
-        # Get the content type
-        content_type = stream_info.mimetype
-        if not content_type:
-            content_type, _ = mimetypes.guess_type(
-                "_dummy" + (stream_info.extension or "")
-            )
-        if not content_type:
-            content_type = "application/octet-stream"
-
-        # Convert to base64
-        cur_pos = file_stream.tell()
-        try:
-            base64_image = base64.b64encode(file_stream.read()).decode("utf-8")
-        except Exception as e:
-            return None
-        finally:
-            file_stream.seek(cur_pos)
-
-        # Prepare the data-uri
-        data_uri = f"data:{content_type};base64,{base64_image}"
-
-        # Prepare the OpenAI API request
-        messages = [
-            {
-                "role": "user",
-                "content": [
-                    {"type": "text", "text": prompt},
-                    {
-                        "type": "image_url",
-                        "image_url": {
-                            "url": data_uri,
-                        },
-                    },
-                ],
-            }
-        ]
-
-        # Call the OpenAI API
-        response = client.chat.completions.create(model=model, messages=messages)
-        return response.choices[0].message.content