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Refactor ImageConverter to reuse llm_caption helper #2302

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Refactor ImageConverter to reuse llm_caption helper #2302

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60 changes: 3 additions & 57 deletions packages/markitdown/src/markitdown/converters/_image_converter.py
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Original file line number Diff line number Diff line change
@@ -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

Expand Down Expand Up @@ -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,
Expand All @@ -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