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Bedrock Wrapper is an npm package that simplifies the integration of existing OpenAI-compatible API objects with AWS Bedrock's serverless inference LLMs.","maintainers":[{"name":"jparkerweb","email":"jparkerweb@gmail.com"}],"readme":"# ๐Ÿชจ Bedrock Wrapper\r\n\r\nBedrock Wrapper is an npm package that simplifies the integration of existing OpenAI-compatible API objects with AWS Bedrock's serverless inference LLMs. Follow the steps below to integrate into your own application, or alternativly use the ๐Ÿ”€ [Bedrock Proxy Endpoint](https://github.com/jparkerweb/bedrock-proxy-endpoint) project to spin up your own custom OpenAI server endpoint for even easier inference (using the standard `baseUrl`, and `apiKey` params).\r\n\r\n![bedrock-wrapper](https://raw.githubusercontent.com/jparkerweb/bedrock-wrapper/refs/heads/main/docs/bedrock-wrapper.jpg)\r\n\r\n---\r\n\r\n### Maintained by\r\n\r\n \"eQuill\r\n\r\n\r\n---\r\n\r\n### Install\r\n\r\n- install package: `npm install bedrock-wrapper`\r\n\r\n---\r\n\r\n### Usage\r\n\r\n1. import `bedrockWrapper` \r\n ```javascript\r\n import { bedrockWrapper } from \"bedrock-wrapper\";\r\n ```\r\n\r\n2. create an `awsCreds` object and fill in your AWS credentials \r\n ```javascript\r\n const awsCreds = {\r\n region: AWS_REGION,\r\n accessKeyId: AWS_ACCESS_KEY_ID,\r\n secretAccessKey: AWS_SECRET_ACCESS_KEY,\r\n };\r\n ```\r\n\r\n3. clone your openai chat completions object into `openaiChatCompletionsCreateObject` or create a new one and edit the values \r\n ```javascript\r\n const openaiChatCompletionsCreateObject = {\r\n \"messages\": messages,\r\n \"model\": \"Claude-4-5-Sonnet\",\r\n \"max_tokens\": LLM_MAX_GEN_TOKENS,\r\n \"stream\": true,\r\n \"temperature\": LLM_TEMPERATURE,\r\n \"stop_sequences\": [\"STOP\", \"END\"], // Optional: sequences that will stop generation\r\n };\r\n ```\r\n\r\n the `messages` variable should be in openai's role/content format (not all models support system prompts)\r\n ```javascript\r\n messages = [\r\n {\r\n role: \"system\",\r\n content: \"You are a helpful AI assistant that follows instructions extremely well. Answer the user questions accurately. Think step by step before answering the question. You will get a $100 tip if you provide the correct answer.\",\r\n },\r\n {\r\n role: \"user\",\r\n content: \"Describe why openai api standard used by lots of serverless LLM api providers is better than aws bedrock invoke api offered by aws bedrock. Limit your response to five sentences.\",\r\n },\r\n {\r\n role: \"assistant\",\r\n content: \"\",\r\n },\r\n ]\r\n ```\r\n\r\n ***the `model` value should be the corresponding `modelName` value in the `bedrock_models` section below (see Supported Models below)***\r\n\r\n4. call the `bedrockWrapper` function and pass in the previously defined `awsCreds` and `openaiChatCompletionsCreateObject` objects \r\n ```javascript\r\n // create a variable to hold the complete response\r\n let completeResponse = \"\";\r\n // invoke the streamed bedrock api response\r\n for await (const chunk of bedrockWrapper(awsCreds, openaiChatCompletionsCreateObject)) {\r\n completeResponse += chunk;\r\n // ---------------------------------------------------\r\n // -- each chunk is streamed as it is received here --\r\n // ---------------------------------------------------\r\n process.stdout.write(chunk); // โ‡  do stuff with the streamed chunk\r\n }\r\n // console.log(`\\n\\completeResponse:\\n${completeResponse}\\n`); // โ‡  optional do stuff with the complete response returned from the API reguardless of stream or not\r\n ```\r\n\r\n if calling the unstreamed version you can call bedrockWrapper like this \r\n ```javascript\r\n // create a variable to hold the complete response\r\n let completeResponse = \"\";\r\n if (!openaiChatCompletionsCreateObject.stream){ // invoke the unstreamed bedrock api response\r\n const response = await bedrockWrapper(awsCreds, openaiChatCompletionsCreateObject);\r\n for await (const data of response) {\r\n completeResponse += data;\r\n }\r\n // ----------------------------------------------------\r\n // -- unstreamed complete response is available here --\r\n // ----------------------------------------------------\r\n console.log(`\\n\\completeResponse:\\n${completeResponse}\\n`); // โ‡  do stuff with the complete response\r\n }\r\n\r\n5. **NEW: Using the Converse API (optional)**\r\n \r\n You can now optionally use AWS Bedrock's Converse API instead of the Invoke API by passing `useConverseAPI: true` in the options parameter:\r\n ```javascript\r\n // Use the Converse API for unified request/response format across all models\r\n for await (const chunk of bedrockWrapper(awsCreds, openaiChatCompletionsCreateObject, { useConverseAPI: true })) {\r\n completeResponse += chunk;\r\n process.stdout.write(chunk);\r\n }\r\n ```\r\n \r\n The Converse API provides:\r\n - **Consistent API**: Single request/response format across all models\r\n - **Simplified conversation management**: Better handling of multi-turn conversations\r\n - **System prompts**: Cleaner separation of system instructions\r\n - **Tool use support**: Native support for function calling (where supported)\r\n - **Unified multimodal**: Consistent handling of text and image inputs\r\n\r\n **Note**: Some models only support the Converse API and will automatically use it regardless of the `useConverseAPI` flag:\r\n - DeepSeek-V3.1\r\n\r\n---\r\n\r\n### Supported Models\r\n\r\n| modelName | AWS Model Id | Image |\r\n|----------------------------|-------------------------------------------------|-------|\r\n| Claude-3-5-Haiku | us.anthropic.claude-3-5-haiku-20241022-v1:0 | โŒ |\r\n| Claude-3-5-Sonnet | us.anthropic.claude-3-5-sonnet-20240620-v1:0 | โœ… |\r\n| Claude-3-5-Sonnet-v2 | us.anthropic.claude-3-5-sonnet-20241022-v2:0 | โœ… |\r\n| Claude-3-7-Sonnet | us.anthropic.claude-3-7-sonnet-20250219-v1:0 | โœ… |\r\n| Claude-3-7-Sonnet-Thinking | us.anthropic.claude-3-7-sonnet-20250219-v1:0 | โœ… |\r\n| Claude-3-Haiku | us.anthropic.claude-3-haiku-20240307-v1:0 | โœ… |\r\n| Claude-4-Opus | us.anthropic.claude-opus-4-20250514-v1:0 | โœ… |\r\n| Claude-4-Opus-Thinking | us.anthropic.claude-opus-4-20250514-v1:0 | โœ… |\r\n| Claude-4-Sonnet | us.anthropic.claude-sonnet-4-20250514-v1:0 | โœ… |\r\n| Claude-4-Sonnet-Thinking | us.anthropic.claude-sonnet-4-20250514-v1:0 | โœ… |\r\n| Claude-4-1-Opus | us.anthropic.claude-opus-4-1-20250805-v1:0 | โœ… |\r\n| Claude-4-1-Opus-Thinking | us.anthropic.claude-opus-4-1-20250805-v1:0 | โœ… |\r\n| Claude-4-5-Haiku | global.anthropic.claude-haiku-4-5-20251001-v1:0 | โœ… |\r\n| Claude-4-5-Haiku-Thinking | global.anthropic.claude-haiku-4-5-20251001-v1:0 | โœ… |\r\n| Claude-4-5-Opus | global.anthropic.claude-opus-4-5-20251101-v1:0 | โœ… |\r\n| Claude-4-5-Opus-Thinking | global.anthropic.claude-opus-4-5-20251101-v1:0 | โœ… |\r\n| Claude-4-5-Sonnet | us.anthropic.claude-sonnet-4-5-20250929-v1:0 | โœ… |\r\n| Claude-4-5-Sonnet-Thinking | us.anthropic.claude-sonnet-4-5-20250929-v1:0 | โœ… |\r\n| Claude-Opus-4-6 | us.anthropic.claude-opus-4-6-v1 | โœ… |\r\n| Claude-Sonnet-4-6 | us.anthropic.claude-sonnet-4-6 | โœ… |\r\n| DeepSeek-R1 | us.deepseek.r1-v1:0 | โŒ |\r\n| DeepSeek-V3.1 | deepseek.v3-v1:0 | โŒ |\r\n| Gemma-3-4b | google.gemma-3-4b-it | โœ… |\r\n| Gemma-3-12b | google.gemma-3-12b-it | โœ… |\r\n| Gemma-3-27b | google.gemma-3-27b-it | โœ… |\r\n| GPT-OSS-120B | openai.gpt-oss-120b-1:0 | โŒ |\r\n| GPT-OSS-120B-Thinking | openai.gpt-oss-120b-1:0 | โŒ |\r\n| GPT-OSS-20B | openai.gpt-oss-20b-1:0 | โŒ |\r\n| GPT-OSS-20B-Thinking | openai.gpt-oss-20b-1:0 | โŒ |\r\n| Kimi-K2 | moonshot.kimi-k2-thinking | โŒ |\r\n| Kimi-K2-Thinking | moonshot.kimi-k2-thinking | โŒ |\r\n| Llama-3-8b | meta.llama3-8b-instruct-v1:0 | โŒ |\r\n| Llama-3-70b | meta.llama3-70b-instruct-v1:0 | โŒ |\r\n| Llama-3-1-8b | us.meta.llama3-1-8b-instruct-v1:0 | โŒ |\r\n| Llama-3-1-70b | us.meta.llama3-1-70b-instruct-v1:0 | โŒ |\r\n| Llama-3-1-405b | meta.llama3-1-405b-instruct-v1:0 | โŒ |\r\n| Llama-3-2-1b | us.meta.llama3-2-1b-instruct-v1:0 | โŒ |\r\n| Llama-3-2-3b | us.meta.llama3-2-3b-instruct-v1:0 | โŒ |\r\n| Llama-3-2-11b | us.meta.llama3-2-11b-instruct-v1:0 | โŒ |\r\n| Llama-3-2-90b | us.meta.llama3-2-90b-instruct-v1:0 | โŒ |\r\n| Llama-3-3-70b | us.meta.llama3-3-70b-instruct-v1:0 | โŒ |\r\n| Llama-4-Scout-17b | us.meta.llama4-scout-17b-instruct-v1:0 | โœ… |\r\n| Llama-4-Maverick-17b | us.meta.llama4-maverick-17b-instruct-v1:0 | โœ… |\r\n| Magistral-Small-2509 | mistral.magistral-small-2509 | โŒ |\r\n| MiniMax-M2 | minimax.minimax-m2 | โŒ |\r\n| Ministral-3-3b | mistral.ministral-3-3b-instruct | โœ… |\r\n| Ministral-3-8b | mistral.ministral-3-8b-instruct | โœ… |\r\n| Ministral-3-14b | mistral.ministral-3-14b-instruct | โœ… |\r\n| Mistral-7b | mistral.mistral-7b-instruct-v0:2 | โŒ |\r\n| Mistral-Large | mistral.mistral-large-2402-v1:0 | โŒ |\r\n| Mistral-Large-3 | mistral.mistral-large-3-675b-instruct | โœ… |\r\n| Mixtral-8x7b | mistral.mixtral-8x7b-instruct-v0:1 | โŒ |\r\n| Nova-2-Lite | us.amazon.nova-2-lite-v1:0 | โœ… |\r\n| Nova-Micro | us.amazon.nova-micro-v1:0 | โŒ |\r\n| Nova-Lite | us.amazon.nova-lite-v1:0 | โœ… |\r\n| Nova-Pro | us.amazon.nova-pro-v1:0 | โœ… |\r\n| Qwen3-32B | qwen.qwen3-32b-v1:0 | โŒ |\r\n| Qwen3-235B-A22B-2507 | qwen.qwen3-235b-a22b-2507-v1:0 | โŒ |\r\n| Qwen3-Coder-30B-A3B | qwen.qwen3-coder-30b-a3b-v1:0 | โŒ |\r\n| Qwen3-Coder-480B-A35B | qwen.qwen3-coder-480b-a35b-v1:0 | โŒ |\r\n| Qwen3-Next-80B-A3B | qwen.qwen3-next-80b-a3b | โŒ |\r\n\r\nTo return the list progrmatically you can import and call `listBedrockWrapperSupportedModels`: \r\n```javascript\r\nimport { listBedrockWrapperSupportedModels } from 'bedrock-wrapper';\r\nconsole.log(`\\nsupported models:\\n${JSON.stringify(await listBedrockWrapperSupportedModels())}\\n`);\r\n```\r\n\r\nAdditional Bedrock model support can be added. \r\nPlease modify the `bedrock_models.js` file and submit a PR ๐Ÿ† or create an Issue.\r\n\r\n---\r\n\r\n### Thinking Models\r\n\r\nSome models support extended reasoning capabilities through \"thinking mode\". These models include:\r\n- **Claude models**: Claude-4-5-Opus-Thinking, Claude-4-1-Opus-Thinking, Claude-4-Opus-Thinking, Claude-4-5-Sonnet-Thinking, Claude-4-5-Haiku-Thinking, Claude-4-Sonnet-Thinking, Claude-3-7-Sonnet-Thinking\r\n- **GPT-OSS models**: GPT-OSS-120B-Thinking, GPT-OSS-20B-Thinking\r\n- **Kimi models**: Kimi-K2-Thinking (preserves reasoning tags in output)\r\n\r\nTo use thinking mode and see the model's reasoning process, set `include_thinking_data: true` in your request:\r\n\r\n```javascript\r\nconst openaiChatCompletionsCreateObject = {\r\n \"messages\": messages,\r\n \"model\": \"Claude-4-5-Sonnet-Thinking\",\r\n \"max_tokens\": 4000,\r\n \"stream\": true,\r\n \"temperature\": 1.0, // Thinking models require temperature of 1.0\r\n \"include_thinking_data\": true // Enable thinking output\r\n};\r\n\r\nlet completeResponse = \"\";\r\nfor await (const chunk of bedrockWrapper(awsCreds, openaiChatCompletionsCreateObject)) {\r\n completeResponse += chunk;\r\n process.stdout.write(chunk); // Shows both thinking and response\r\n}\r\n```\r\n\r\n**Features:**\r\n- Thinking content appears in `...` tags for Claude models\r\n- Thinking content appears in `...` tags for GPT-OSS models\r\n- Temperature is automatically set to 1.0 for optimal thinking performance\r\n- Budget tokens are automatically calculated based on max_tokens\r\n\r\n---\r\n\r\n### Image Support\r\n\r\nFor models with image support (Claude 4+ series including Claude Opus 4.6, Claude Sonnet 4.6, Claude 4.5 Opus, Claude 4.5 Sonnet, Claude 4.5 Haiku, Claude 3.7 Sonnet, Claude 3.5 Sonnet, Claude 3 Haiku, Nova Pro, Nova Lite, Nova 2 Lite, Mistral Large 3, Ministral 3 series, Gemma 3 series, and Llama 4 series), you can include images in your messages using the following format (not all models support system prompts):\r\n\r\n```javascript\r\nmessages = [\r\n {\r\n role: \"system\",\r\n content: \"You are a helpful AI assistant that can analyze images.\",\r\n },\r\n {\r\n role: \"user\",\r\n content: [\r\n { type: \"text\", text: \"What's in this image?\" },\r\n { \r\n type: \"image_url\", \r\n image_url: {\r\n url: \"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEA...\" // base64 encoded image\r\n }\r\n }\r\n ]\r\n }\r\n]\r\n```\r\n\r\nYou can also use a direct URL to an image instead of base64 encoding:\r\n\r\n```javascript\r\nmessages = [\r\n {\r\n role: \"user\",\r\n content: [\r\n { type: \"text\", text: \"Describe this image in detail.\" },\r\n { \r\n type: \"image_url\", \r\n image_url: {\r\n url: \"https://example.com/path/to/image.jpg\" // direct URL to image\r\n }\r\n }\r\n ]\r\n }\r\n]\r\n```\r\n\r\nYou can include multiple images in a single message by adding more image_url objects to the content array.\r\n\r\n---\r\n\r\n### Stop Sequences\r\n\r\nStop sequences are custom text sequences that cause the model to stop generating text. This is useful for controlling where the model stops its response.\r\n\r\n```javascript\r\nconst openaiChatCompletionsCreateObject = {\r\n \"messages\": messages,\r\n \"model\": \"Claude-3-5-Sonnet\",\r\n \"max_tokens\": 100,\r\n \"stop_sequences\": [\"STOP\", \"END\", \"\\n\\n\"], // Array of stop sequences\r\n // OR use single string format:\r\n // \"stop\": \"STOP\"\r\n};\r\n```\r\n\r\n**Model Support:**\r\n- โœ… **Claude models**: Fully supported (up to 8,191 sequences)\r\n- โœ… **Nova models**: Fully supported (up to 4 sequences)\r\n- โœ… **GPT-OSS models**: Fully supported\r\n- โœ… **Mistral models**: Fully supported (up to 10 sequences)\r\n- โœ… **Qwen models**: Fully supported\r\n- โœ… **Gemma models**: Fully supported\r\n- โœ… **Kimi models**: Fully supported\r\n- โœ… **MiniMax models**: Fully supported\r\n- โŒ **Llama models**: Not supported (AWS Bedrock limitation)\r\n\r\n**Features:**\r\n- Compatible with OpenAI's `stop` parameter (single string or array)\r\n- Also accepts `stop_sequences` parameter for explicit usage\r\n- Automatic conversion between string and array formats\r\n- Model-specific parameter mapping handled automatically\r\n\r\n**Example Usage:**\r\n```javascript\r\n// Stop generation when model tries to output \"7\"\r\nconst result = await bedrockWrapper(awsCreds, {\r\n messages: [{ role: \"user\", content: \"Count from 1 to 10\" }],\r\n model: \"Claude-3-5-Sonnet\", // Use Claude, Nova, Mistral, or Qwen models\r\n stop_sequences: [\"7\"]\r\n});\r\n// Response: \"1, 2, 3, 4, 5, 6,\" (stops before \"7\")\r\n\r\n// Note: Llama models will ignore stop sequences due to AWS Bedrock limitations\r\n```\r\n\r\n---\r\n\r\n### Parameter Restrictions\r\n\r\nSome AWS Bedrock models have specific parameter restrictions that are automatically handled by the wrapper:\r\n\r\n#### Claude 4+ Models (Temperature/Top-P Mutual Exclusion)\r\n\r\n**Affected Models:**\r\n- Claude-Opus-4-6\r\n- Claude-Sonnet-4-6\r\n- Claude-4-5-Opus & Claude-4-5-Opus-Thinking\r\n- Claude-4-5-Sonnet & Claude-4-5-Sonnet-Thinking\r\n- Claude-4-5-Haiku & Claude-4-5-Haiku-Thinking\r\n- Claude-4-Sonnet & Claude-4-Sonnet-Thinking\r\n- Claude-4-Opus & Claude-4-Opus-Thinking\r\n- Claude-4-1-Opus & Claude-4-1-Opus-Thinking\r\n\r\n---\r\n\r\n### ๐Ÿงช Testing\r\n\r\nThe package includes comprehensive test suites to verify functionality:\r\n\r\n```bash\r\n# Test all models with the Both APIs (Comparison)\r\nnpm run test\r\n\r\n# Test all models with the Invoke API\r\nnpm run test:invoke\r\n\r\n# Test all models with the Converse API\r\nnpm run test:converse\r\n\r\n# Test vision/multimodal capabilities with Both APIs (Comparison)\r\nnpm run test-vision\r\n\r\n# Test vision/multimodal capabilities with Invoke API\r\nnpm run test-vision:invoke\r\n\r\n# Test vision/multimodal capabilities with Converse API\r\nnpm run test-vision:converse\r\n\r\n# Test stop sequences functionality with Both APIs (Comparison)\r\nnpm run test-stop\r\n\r\n# Test stop sequences functionality with Invoke API\r\nnpm run test-stop:invoke\r\n\r\n# Test stop sequences functionality with Converse API\r\nnpm run test-stop:converse\r\n\r\n# Test Converse API specifically\r\nnpm run test-converse\r\n\r\n# Run all test suites\r\nnpm run test:all\r\n\r\n# Interactive testing\r\nnpm run interactive\r\n```\r\n\r\n---\r\n\r\n### ๐Ÿ“ข P.S.\r\n\r\nIn case you missed it at the beginning of this doc, for an even easier setup, use the ๐Ÿ”€ [Bedrock Proxy Endpoint](https://github.com/jparkerweb/bedrock-proxy-endpoint) project to spin up your own custom OpenAI server endpoint (using the standard `baseUrl`, and `apiKey` params).\r\n\r\n![bedrock-proxy-endpoing](./docs/bedrock-proxy-endpoint.jpg)\r\n\r\n---\r\n\r\n### ๐Ÿ“š References\r\n\r\n- [AWS Meta Llama Models User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-meta.html)\r\n- [AWS Mistral Models User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-mistral.html)\r\n- [OpenAI API](https://platform.openai.com/docs/api-reference/chat/create)\r\n- [AWS Bedrock](https://aws.amazon.com/bedrock/)\r\n- [AWS SDK for JavaScript](https://aws.amazon.com/sdk-for-javascript/)\r\n\r\n---\r\n\r\nPlease consider sending me a tip to support my work ๐Ÿ˜€\r\n# [๐Ÿต tip me here](https://ko-fi.com/jparkerweb)\r\n","readmeFilename":"README.md"}