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## Summary - `CvModel["Bedrock"]` was absent from `rag/llm/cv_model.py`, causing `model_instance()` to return `None` when a Bedrock model was used as a PDF parser — even after correct model resolution. - This PR adds `BedrockCV`, enabling Bedrock vision models (e.g. `amazon.nova-pro-v1:0`, `anthropic.claude-3-5-sonnet`) to be used as PDF parsers. ## What problem does this PR solve? When a Bedrock model is selected as the PDF parser in a knowledge base, ingestion failed with: ``` 'LiteLLMBase' object has no attribute 'describe_with_prompt' ``` The root cause: `LiteLLMBase` (the Bedrock chat implementation) was the only registered handler for the Bedrock factory. It does not implement `describe_with_prompt`. `CvModel` had no Bedrock entry, so `model_instance()` returned `None` for `image2text` requests. ## Type of change - [x] New Feature (non-breaking change which adds functionality) ## Changes **`rag/llm/cv_model.py`** Adds `BedrockCV(Base)` with `_FACTORY_NAME = "Bedrock"`: - Uses `litellm.completion` with the `bedrock/` prefix (consistent with `LiteLLMBase`) - Parses AWS credentials from the JSON key assembled by `add_llm` (`auth_mode`, `bedrock_ak`, `bedrock_sk`, `bedrock_region`, `aws_role_arn`) - Supports three auth modes: `access_key_secret`, `iam_role` (via STS `assume_role`), and default credential chain (IRSA, instance profile) - Implements `describe_with_prompt` and `describe` ## Test plan - [ ] Configure a Bedrock vision model (e.g. `amazon.nova-pro-v1:0`) with valid AWS credentials - [ ] Select it as PDF parser in a knowledge base - [ ] Verify ingestion of a PDF document completes without errors - [ ] Verify `CvModel["Bedrock"]` resolves to `BedrockCV` 🤖 Generated with [Claude Code](https://claude.ai/claude-code) --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>