Merge branch 'main' into main

.dockerignore

@@ -0,0 +1 @@
+*

Dockerfile

@@ -0,0 +1,16 @@
+FROM python:3.13-alpine
+
+USER root
+
+# Runtime dependency
+RUN apk add --no-cache ffmpeg
+
+RUN pip install markitdown
+
+# Default USERID and GROUPID
+ARG USERID=10000
+ARG GROUPID=10000
+
+USER $USERID:$GROUPID
+
+ENTRYPOINT [ "markitdown" ]

README.md

@@ -59,24 +59,24 @@ You can pipe content to standard input by omitting the argument:
 cat path-to-file.pdf | markitdown
 ```
 
+You can also configure markitdown to use Large Language Models to describe images. To do so you must provide `llm_client` and `llm_model` parameters to MarkItDown object, according to your specific client.
 
-You can also configure markitdown to use Large Language Models to describe images. To do so you must provide `mlm_client` and `mlm_model` parameters to MarkItDown object, according to your specific client.
 
 ```python
 from markitdown import MarkItDown
 from openai import OpenAI
 
 client = OpenAI()
-md = MarkItDown(mlm_client=client, mlm_model="gpt-4o")
+md = MarkItDown(llm_client=client, llm_model="gpt-4o")
 result = md.convert("example.jpg")
 print(result.text_content)
 ```
 
-The prompt of describing images can be customized by providing `mlm_prompt` parameter.
+You can also use the project as Docker Image:
 
-```python
-# ...
-result = md.convert("example.jpg", mlm_prompt="Customized prompt")
+```sh
+docker build -t markitdown:latest .
+docker run --rm -i markitdown:latest < ~/your-file.pdf > output.md
 ```
 
 ## Contributing
@@ -95,15 +95,18 @@ contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additio
 
 ### Running Tests
 
-To run the tests for this project, use the following command:
+To run tests, install `hatch` using `pip` or other methods as described [here](https://hatch.pypa.io/dev/install).
 
 ```sh
+pip install hatch
 hatch shell
 hatch test
 ```
 
 ### Running Pre-commit Checks
 
+Please run the pre-commit checks before submitting a PR.
+
 ```sh
 pre-commit run --all-files
 ```

src/markitdown/_markitdown.py

@@ -793,7 +793,7 @@ class Mp3Converter(WavConverter):
 
 class ImageConverter(MediaConverter):
     """
-    Converts images to markdown via extraction of metadata (if `exiftool` is installed), OCR (if `easyocr` is installed), and description via a multimodal LLM (if an mlm_client is configured).
+    Converts images to markdown via extraction of metadata (if `exiftool` is installed), OCR (if `easyocr` is installed), and description via a multimodal LLM (if an llm_client is configured).
     """
 
     def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
@@ -823,17 +823,17 @@ class ImageConverter(MediaConverter):
                     md_content += f"{f}: {metadata[f]}\n"
 
         # Try describing the image with GPTV
-        mlm_client = kwargs.get("mlm_client")
-        mlm_model = kwargs.get("mlm_model")
-        if mlm_client is not None and mlm_model is not None:
+        llm_client = kwargs.get("llm_client")
+        llm_model = kwargs.get("llm_model")
+        if llm_client is not None and llm_model is not None:
             md_content += (
                 "\n# Description:\n"
-                + self._get_mlm_description(
+                + self._get_llm_description(
                     local_path,
                     extension,
-                    mlm_client,
-                    mlm_model,
-                    prompt=kwargs.get("mlm_prompt"),
+                    llm_client,
+                    llm_model,
+                    prompt=kwargs.get("llm_prompt"),
                 ).strip()
                 + "\n"
             )
@@ -843,11 +843,11 @@ class ImageConverter(MediaConverter):
             text_content=md_content,
         )
 
-    def _get_mlm_description(self, local_path, extension, client, model, prompt=None):
+    def _get_llm_description(self, local_path, extension, client, model, prompt=None):
         if prompt is None or prompt.strip() == "":
             prompt = "Write a detailed caption for this image."
 
-        sys.stderr.write(f"MLM Prompt:\n{prompt}\n")
+        sys.stderr.write(f"llm Prompt:\n{prompt}\n")
 
         data_uri = ""
         with open(local_path, "rb") as image_file:
@@ -1009,8 +1009,8 @@ class MarkItDown:
     def __init__(
         self,
         requests_session: Optional[requests.Session] = None,
-        mlm_client: Optional[Any] = None,
-        mlm_model: Optional[Any] = None,
+        llm_client: Optional[Any] = None,
+        llm_model: Optional[Any] = None,
         style_map: Optional[str] = None,
     ):
         if requests_session is None:
@@ -1018,8 +1018,8 @@ class MarkItDown:
         else:
             self._requests_session = requests_session
 
-        self._mlm_client = mlm_client
-        self._mlm_model = mlm_model
+        self._llm_client = llm_client
+        self._llm_model = llm_model
         self._style_map = style_map
 
         self._page_converters: List[DocumentConverter] = []
@@ -1190,11 +1190,12 @@ class MarkItDown:
                     _kwargs.update({"file_extension": ext})
 
                 # Copy any additional global options
-                if "mlm_client" not in _kwargs and self._mlm_client is not None:
-                    _kwargs["mlm_client"] = self._mlm_client
+                if "llm_client" not in _kwargs and self._llm_client is not None:
+                    _kwargs["llm_client"] = self._llm_client
+
+                if "llm_model" not in _kwargs and self._llm_model is not None:
+                    _kwargs["llm_model"] = self._llm_model
 
-                if "mlm_model" not in _kwargs and self._mlm_model is not None:
-                    _kwargs["mlm_model"] = self._mlm_model
                 # Add the list of converters for nested processing
                 _kwargs["_parent_converters"] = self._page_converters
 
@@ -1236,8 +1237,7 @@ class MarkItDown:
         if ext == "":
             return
         # if ext not in extensions:
-        if True:
-            extensions.append(ext)
+        extensions.append(ext)
 
     def _guess_ext_magic(self, path):
         """Use puremagic (a Python implementation of libmagic) to guess a file's extension based on the first few bytes."""