Add VLM picture description support for image handling

docs/configuration/processing.md

@@ -36,6 +36,13 @@ processing:
     # Image settings
     images_scale: 2.0                        # Image scale factor
     generate_picture_images: false           # Include embedded images in output
+
+    # VLM picture description (optional)
+    picture_description:
+      enabled: false                         # Enable VLM image descriptions
+      model:
+        provider: ollama
+        name: ministral-3
 ```
 
 ### Conversion Options
@@ -81,6 +88,70 @@ conversion_options:
 - **images_scale**: Scale factor for extracted images. Higher values = better quality but larger size. Typical range: 1.0-3.0.
 - **generate_picture_images**: When `true`, embedded images (figures, diagrams) are included as base64-encoded data in the document. When `false` (default), images are excluded to reduce chunk size and avoid context bloat.
 
+#### Picture Description (VLM)
+
+Use a Vision Language Model (VLM) to automatically describe images in documents. Descriptions become searchable text, improving RAG retrieval for visual content.
+
+```yaml
+conversion_options:
+  picture_description:
+    enabled: true                  # Enable VLM picture description
+    model:
+      provider: ollama             # ollama, openai, or custom
+      name: ministral-3            # VLM model name
+    prompt: "Describe this image in detail. Be precise and concise."
+    timeout: 90                    # Request timeout in seconds
+    max_tokens: 200                # Maximum tokens in response
+```
+
+**Configuration options:**
+
+- **enabled**: When `true`, each embedded image is sent to a VLM for description. Requires `generate_picture_images` to be `true` (automatically enabled).
+- **model**: Standard model configuration
+  - `provider`: `ollama` (default), `openai`, or use `base_url` for custom endpoints
+  - `name`: Model name (e.g., `ministral-3`, `granite3.2-vision`, `gpt-4-vision`)
+  - `base_url`: Optional custom API endpoint for vLLM, LM Studio, etc.
+- **prompt**: Instruction for the VLM when describing images
+- **timeout**: Request timeout in seconds
+- **max_tokens**: Maximum tokens in the VLM response
+
+**Using with Ollama:**
+
+```yaml
+conversion_options:
+  picture_description:
+    enabled: true
+    model:
+      provider: ollama
+      name: ministral-3
+```
+
+Requires Ollama running with a vision-capable model:
+
+```bash
+ollama pull ministral-3
+ollama serve
+```
+
+**Using with vLLM or custom endpoints:**
+
+```yaml
+conversion_options:
+  picture_description:
+    enabled: true
+    model:
+      provider: openai           # Use OpenAI-compatible API format
+      name: granite-vision
+      base_url: http://my-vllm-server:8000
+```
+
+**How it works:**
+
+1. During PDF conversion, docling extracts embedded images
+2. Each image is sent to the configured VLM for description
+3. Descriptions are added as annotations on the image
+4. When exported to markdown, descriptions appear as searchable text
+
 ### Local vs Remote Processing
 
 **Local processing** (default):

haiku_rag_slim/haiku/rag/config/models.py

@@ -96,6 +96,21 @@ class ResearchConfig(BaseModel):
     max_concurrency: int = 1
 
 
+class PictureDescriptionConfig(BaseModel):
+    """Configuration for VLM-based picture description."""
+
+    enabled: bool = False
+    model: ModelConfig = Field(
+        default_factory=lambda: ModelConfig(
+            provider="ollama",
+            name="ministral-3",
+        )
+    )
+    prompt: str = "Describe this image in detail. Be precise and concise."
+    timeout: int = 90
+    max_tokens: int = 200
+
+
 class ConversionOptions(BaseModel):
     """Options for document conversion."""
 
@@ -113,6 +128,11 @@ class ConversionOptions(BaseModel):
     images_scale: float = 2.0
     generate_picture_images: bool = False
 
+    # VLM picture description
+    picture_description: PictureDescriptionConfig = Field(
+        default_factory=PictureDescriptionConfig
+    )
+
 
 class ProcessingConfig(BaseModel):
     chunk_size: int = 256

haiku_rag_slim/haiku/rag/converters/docling_local.py

@@ -11,6 +11,8 @@ from haiku.rag.converters.text_utils import TextFileHandler
 if TYPE_CHECKING:
     from docling_core.types.doc.document import DoclingDocument
 
+    from haiku.rag.config.models import ModelConfig
+
 
 class DoclingLocalConverter(DocumentConverter):
     """Converter that uses local docling for document conversion.
@@ -54,6 +56,21 @@ class DoclingLocalConverter(DocumentConverter):
         """Return list of file extensions supported by this converter."""
         return self.docling_extensions + TextFileHandler.text_extensions
 
+    def _get_vlm_api_url(self, model: "ModelConfig") -> str:
+        """Construct VLM API URL from model config."""
+        if model.base_url:
+            base = model.base_url.rstrip("/")
+            return f"{base}/v1/chat/completions"
+
+        if model.provider == "ollama":
+            base = self.config.providers.ollama.base_url.rstrip("/")
+            return f"{base}/v1/chat/completions"
+
+        if model.provider == "openai":
+            return "https://api.openai.com/v1/chat/completions"
+
+        raise ValueError(f"Unsupported VLM provider: {model.provider}")
+
     def _sync_convert_docling_file(self, path: Path) -> "DoclingDocument":
         """Synchronous conversion of docling-supported files."""
         from docling.backend.docling_parse_backend import DoclingParseDocumentBackend
@@ -61,6 +78,7 @@ class DoclingLocalConverter(DocumentConverter):
         from docling.datamodel.pipeline_options import (
             OcrAutoOptions,
             PdfPipelineOptions,
+            PictureDescriptionApiOptions,
             TableFormerMode,
             TableStructureOptions,
         )
@@ -73,13 +91,14 @@ class DoclingLocalConverter(DocumentConverter):
         )
 
         opts = self.config.processing.conversion_options
+        pic_desc = opts.picture_description
 
         pipeline_options = PdfPipelineOptions(
             do_ocr=opts.do_ocr,
             do_table_structure=opts.do_table_structure,
             images_scale=opts.images_scale,
             generate_page_images=True,
-            generate_picture_images=opts.generate_picture_images,
+            generate_picture_images=opts.generate_picture_images or pic_desc.enabled,
             table_structure_options=TableStructureOptions(
                 do_cell_matching=opts.table_cell_matching,
                 mode=(
@@ -92,6 +111,21 @@ class DoclingLocalConverter(DocumentConverter):
                 force_full_page_ocr=opts.force_ocr,
                 lang=opts.ocr_lang if opts.ocr_lang else [],
             ),
+            do_picture_description=pic_desc.enabled,
+        )
+
+        if pic_desc.enabled:
+            from pydantic import AnyUrl
+
+            pipeline_options.enable_remote_services = True
+            pipeline_options.picture_description_options = PictureDescriptionApiOptions(
+                url=AnyUrl(self._get_vlm_api_url(pic_desc.model)),
+                params=dict(
+                    model=pic_desc.model.name,
+                    max_completion_tokens=pic_desc.max_tokens,
+                ),
+                prompt=pic_desc.prompt,
+                timeout=pic_desc.timeout,
             )
 
         format_options = cast(

tests/test_converters.py

@@ -308,6 +308,74 @@ class TestDoclingLocalConverter:
                 "Pictures should have image data when generate_picture_images=True"
             )
 
+    def test_get_vlm_api_url_with_ollama(self, config):
+        """Test VLM API URL construction for Ollama provider."""
+        converter = DoclingLocalConverter(config)
+        from haiku.rag.config.models import ModelConfig
+
+        model = ModelConfig(provider="ollama", name="ministral-3")
+        url = converter._get_vlm_api_url(model)
+        assert url == "http://localhost:11434/v1/chat/completions"
+
+    def test_get_vlm_api_url_with_custom_base_url(self, config):
+        """Test VLM API URL construction with custom base_url."""
+        converter = DoclingLocalConverter(config)
+        from haiku.rag.config.models import ModelConfig
+
+        model = ModelConfig(
+            provider="openai", name="gpt-4-vision", base_url="http://my-vllm:8000"
+        )
+        url = converter._get_vlm_api_url(model)
+        assert url == "http://my-vllm:8000/v1/chat/completions"
+
+    def test_get_vlm_api_url_with_openai(self, config):
+        """Test VLM API URL construction for OpenAI provider."""
+        converter = DoclingLocalConverter(config)
+        from haiku.rag.config.models import ModelConfig
+
+        model = ModelConfig(provider="openai", name="gpt-4-vision")
+        url = converter._get_vlm_api_url(model)
+        assert url == "https://api.openai.com/v1/chat/completions"
+
+    def test_get_vlm_api_url_unsupported_provider(self, config):
+        """Test VLM API URL construction raises error for unsupported provider."""
+        converter = DoclingLocalConverter(config)
+        from haiku.rag.config.models import ModelConfig
+
+        model = ModelConfig(provider="unsupported", name="test")
+        with pytest.raises(ValueError, match="Unsupported VLM provider"):
+            converter._get_vlm_api_url(model)
+
+    def test_picture_description_config_defaults(self, config):
+        """Test that picture description config has correct defaults."""
+        assert config.processing.conversion_options.picture_description.enabled is False
+        assert (
+            config.processing.conversion_options.picture_description.model.provider
+            == "ollama"
+        )
+        assert (
+            config.processing.conversion_options.picture_description.model.name
+            == "ministral-3"
+        )
+        assert config.processing.conversion_options.picture_description.timeout == 90
+        assert (
+            config.processing.conversion_options.picture_description.max_tokens == 200
+        )
+
+    def test_picture_description_config_applied(self, config):
+        """Test that picture description config is applied to converter."""
+        config.processing.conversion_options.picture_description.enabled = True
+        config.processing.conversion_options.picture_description.prompt = (
+            "Custom prompt for testing."
+        )
+        config.processing.conversion_options.picture_description.timeout = 120
+        converter = DoclingLocalConverter(config)
+
+        pic_desc = converter.config.processing.conversion_options.picture_description
+        assert pic_desc.enabled is True
+        assert pic_desc.prompt == "Custom prompt for testing."
+        assert pic_desc.timeout == 120
+
 
 class TestDoclingServeConverter:
     """Tests for DoclingServeConverter (mocked)."""