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feat: add AWS Bedrock support for codebase indexing
- Add bedrock as a new EmbedderProvider type
- Add AWS Bedrock embedding model profiles (titan-embed-text models)
- Create BedrockEmbedder class with support for Titan and Cohere models
- Add Bedrock configuration support to config manager and interfaces
- Update service factory to create BedrockEmbedder instances
- Add comprehensive tests for BedrockEmbedder
- Add localization strings for Bedrock support
Closes#8658
"unknownErrorDeletingPoints": "Unknown error deleting points for {{filePath}}",
@@ -48,6 +54,7 @@
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"geminiConfigMissing": "Gemini configuration missing for embedder creation",
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"mistralConfigMissing": "Mistral configuration missing for embedder creation",
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"vercelAiGatewayConfigMissing": "Vercel AI Gateway configuration missing for embedder creation",
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"bedrockConfigMissing": "AWS Bedrock configuration missing for embedder creation",
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"invalidEmbedderType": "Invalid embedder type configured: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "Could not determine vector dimension for model '{{modelId}}' with provider '{{provider}}'. Please ensure the 'Embedding Dimension' is correctly set in the OpenAI-Compatible provider settings.",
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"vectorDimensionNotDetermined": "Could not determine vector dimension for model '{{modelId}}' with provider '{{provider}}'. Check model profiles or configuration.",
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