--- title: "Generating image descriptions using Claude | Nutrient Python SDK" canonical_url: "https://www.nutrient.io/guides/python/extraction/describe-image-with-claude/" md_url: "https://www.nutrient.io/guides/python/extraction/describe-image-with-claude.md" last_updated: "2026-06-10T13:06:33.240Z" description: "Generate accessible image descriptions using Claude AI with Nutrient Python SDK." --- # Generating image descriptions using Claude Use image description to generate alt text and visual summaries from images. Common use cases include: - Accessibility workflows for screen readers - Digital asset cataloging - Document enrichment for scanned reports - E-learning content description - Archive and metadata generation This guide uses Claude as the VLM provider through Nutrient Vision API. [Download sample](https://www.nutrient.io/downloads/samples/python/describe-image-with-claude.zip) ## How Nutrient helps Nutrient Python SDK handles provider configuration, request handling, and response parsing. The SDK handles: - API authentication and endpoint configuration - Image encoding and multimodal request payloads - Model settings such as temperature and token limits - Vision API failures and rate-limit handling ## Complete implementation This example generates an image description using Claude: ```python from nutrient_sdk import Document, Vision from nutrient_sdk import VlmProvider ``` ## Configuring the Claude provider Open the image in a [context manager](https://docs.python.org/3/reference/datamodel.html#context-managers) and configure Claude as the provider. In this sample: - `vision_settings.provider = VlmProvider.CLAUDE` selects Claude. - `claude_api_settings.api_key` sets the Anthropic API key. - Input can be PNG, JPEG, GIF, BMP, or TIFF. ```python with Document.open("input_photo.png") as document: # Configure Claude as the VLM provider document.settings.vision_settings.provider = VlmProvider.CLAUDE # Set the Claude API key document.settings.claude_api_settings.api_key = "CLAUDE_API_KEY" ``` ## Creating a vision instance and generating the description Create a vision instance and call `describe()` to generate text. In this sample: - `Vision.set(document)` binds processing to the opened image. - `vision.describe()` returns a description string. - The SDK handles encoding, request construction, and response parsing. ```python vision = Vision.set(document) description = vision.describe() ``` ## Outputting the description Print the description for review, or store it in your application. Common destinations include: - Database fields - JSON output files - HTML `alt` attributes ```python print("Image description:") print(description) ``` ## Understanding the output `describe()` returns natural language text for accessibility and content understanding. Claude descriptions are typically: - **Concise** — Focused on key subjects and details, often one to three sentences - **Accessible** — Suitable for users who rely on screen readers - **Accurate** — Based on visible content only - **Contextual** — Include relevant relationships and scene context Use this output for accessibility metadata, image search, and document workflows. ## Claude API settings The Claude provider uses these `claude_api_settings` properties: - `api_endpoint` — The Claude API endpoint (default: `https://api.anthropic.com/v1/`). - `api_key` — Your Anthropic API key for authentication. - `model` — The model identifier to use (default: `claude-sonnet-4-5`). - `temperature` — Controls response creativity (0.0 = deterministic, 1.0 = creative). - `max_tokens` — Maximum tokens in the response (default: 16384). ## Error handling The SDK raises `NutrientException` when vision operations fail. Common failure scenarios include: - The input image can’t be read due to path, permission, or format issues - The Claude API key is missing or invalid - The Claude API is unavailable - Rate limits are exceeded - Network requests fail before reaching the API - Image data is too large or corrupted In production code: - Catch `NutrientException`. - Return a clear error message. - Log failure details for debugging. - Add retry logic for transient API failures. ## Conclusion Use this workflow to generate image descriptions with Claude: 1. Open the image file using a [context manager](https://docs.python.org/3/reference/datamodel.html#context-managers) for automatic resource cleanup. 2. The SDK supports multiple image formats, including PNG, JPEG, GIF, BMP, and TIFF. 3. Access the vision settings with `document.settings.vision_settings.provider` to configure the VLM provider. 4. Set the provider to Claude with the property assignment `VlmProvider.CLAUDE` instead of alternatives like OpenAI or local models. 5. Access Claude-specific settings with `document.settings.claude_api_settings` for API configuration. 6. Set the Anthropic API key with property assignment using credentials obtained from the Anthropic Console. 7. Claude API settings control endpoint URLs, model selection (default: claude-sonnet-4-5), temperature, and max tokens. 8. Create a vision instance with `Vision.set()` bound to the document with configured provider settings. 9. Generate the description with `vision.describe()`, which sends the image to Claude’s vision endpoint and returns natural language text. 10. The SDK encodes image data, constructs multimodal API requests, and parses responses automatically. 11. Generated descriptions are concise (1–3 sentences), accessible (WCAG-compliant alt text), accurate (observable details only), and contextual. 12. Print or save the description for use in accessibility systems, content management, or cataloging workflows. 13. Handle `NutrientException` for vision processing failures, including authentication errors, API failures, and rate limits. 14. The context manager ensures proper resource cleanup when processing completes or exceptions occur. For related image workflows, refer to the [Python SDK guides](https://www.nutrient.io/guides/python.md). Download [this ready-to-use sample package](https://www.nutrient.io/downloads/samples/python/describe-image-with-claude.zip) to explore Claude-based image description. --- ## Related pages - [Nutrient Python SDK extraction guides](/guides/python/extraction.md) - [Generating image descriptions using OpenAI](/guides/python/extraction/describe-image-with-openai.md) - [Applying OCR to a PDF document](/guides/python/extraction/apply-ocr-to-pdf.md) - [Applying OCR to a PDF page](/guides/python/extraction/apply-ocr-to-pdf-page.md) - [Extracting data from images using ICR](/guides/python/extraction/extract-data-from-image-icr.md) - [Extracting data from images using vision language models](/guides/python/extraction/extract-data-from-image-vlm.md) - [Extracting text from PDF documents](/guides/python/extraction/pdf-to-text.md) - [Extracting structured JSON data from PDF documents](/guides/python/extraction/json-data-extraction.md) - [Extracting text from multilingual images](/guides/python/extraction/read-text-from-image-multi-language.md) - [Extracting text from images](/guides/python/extraction/read-text-from-image.md) - [Labeling form fields with a vision language model](/guides/python/extraction/label-form-fields-with-vlm.md) - [Speeding up first ICR operation by predownloading models](/guides/python/extraction/speed-up-first-icr-by-downloading-requirements.md) - [Extracting form fields from images](/guides/python/extraction/extract-form-fields-from-image.md) - [Extracting structured data from documents](/guides/python/extraction/extract-structured-data.md) - [Generating image descriptions using local AI](/guides/python/extraction/describe-image-with-local-ai.md) - [Extracting data from images using OCR](/guides/python/extraction/extract-data-from-image-ocr.md)