fix: send images to Mistral as base64 vision chunks instead of placeholders

The text provider now includes reference_images alongside inputs when
building prompts. Image files are sent as base64 data URLs via
ImageURLChunk for actual multimodal vision support, replacing the
previous [Attached image: ...] placeholder text.

bulkgen/providers/text.py

@@ -2,6 +2,8 @@
 
 from __future__ import annotations
 
+import base64
+import mimetypes
 from pathlib import Path
 from typing import override
 
@@ -11,6 +13,13 @@ from bulkgen.config import IMAGE_EXTENSIONS, TargetConfig
 from bulkgen.providers import Provider
 
 
+def _image_to_data_url(path: Path) -> str:
+    """Read an image file and return a ``data:`` URL with base64-encoded content."""
+    mime = mimetypes.guess_type(path.name)[0] or "image/png"
+    b64 = base64.b64encode(path.read_bytes()).decode("ascii")
+    return f"data:{mime};base64,{b64}"
+
+
 class TextProvider(Provider):
     """Generates text via the Mistral API."""
 
@@ -30,26 +39,26 @@ class TextProvider(Provider):
     ) -> None:
         output_path = project_dir / target_name
 
-        content_parts: list[str] = [resolved_prompt]
+        all_input_names = list(target_config.inputs) + list(
+            target_config.reference_images
+        )
 
-        for input_name in target_config.inputs:
-            input_path = project_dir / input_name
-            suffix = input_path.suffix.lower()
+        has_images = any(
+            (project_dir / name).suffix.lower() in IMAGE_EXTENSIONS
+            for name in all_input_names
+        )
 
-            if suffix in IMAGE_EXTENSIONS:
-                content_parts.append(f"\n[Attached image: {input_name}]")
-            else:
-                file_content = input_path.read_text()
-                content_parts.append(
-                    f"\n--- Contents of {input_name} ---\n{file_content}"
-                )
-
-        full_prompt = "\n".join(content_parts)
+        if has_images:
+            message = _build_multimodal_message(
+                resolved_prompt, all_input_names, project_dir
+            )
+        else:
+            message = _build_text_message(resolved_prompt, all_input_names, project_dir)
 
         async with Mistral(api_key=self._api_key) as client:
             response = await client.chat.complete_async(
                 model=resolved_model,
-                messages=[models.UserMessage(content=full_prompt)],
+                messages=[message],
             )
 
         if not response.choices:
@@ -63,3 +72,42 @@ class TextProvider(Provider):
 
         text = content if isinstance(content, str) else str(content)
         _ = output_path.write_text(text)
+
+
+def _build_text_message(
+    prompt: str,
+    input_names: list[str],
+    project_dir: Path,
+) -> models.UserMessage:
+    """Build a plain-text message (no images)."""
+    parts: list[str] = [prompt]
+    for name in input_names:
+        file_content = (project_dir / name).read_text()
+        parts.append(f"\n--- Contents of {name} ---\n{file_content}")
+    return models.UserMessage(content="\n".join(parts))
+
+
+def _build_multimodal_message(
+    prompt: str,
+    input_names: list[str],
+    project_dir: Path,
+) -> models.UserMessage:
+    """Build a multimodal message with text and image chunks."""
+    chunks: list[models.TextChunk | models.ImageURLChunk] = [
+        models.TextChunk(text=prompt),
+    ]
+
+    for name in input_names:
+        input_path = project_dir / name
+        suffix = input_path.suffix.lower()
+
+        if suffix in IMAGE_EXTENSIONS:
+            data_url = _image_to_data_url(input_path)
+            chunks.append(models.ImageURLChunk(image_url=models.ImageURL(url=data_url)))
+        else:
+            file_content = input_path.read_text()
+            chunks.append(
+                models.TextChunk(text=f"\n--- Contents of {name} ---\n{file_content}")
+            )
+
+    return models.UserMessage(content=chunks)  # pyright: ignore[reportArgumentType]