diff --git a/litellm/llms/bedrock/files/transformation.py b/litellm/llms/bedrock/files/transformation.py index fdcbe1a8242..20ec233808d 100644 --- a/litellm/llms/bedrock/files/transformation.py +++ b/litellm/llms/bedrock/files/transformation.py @@ -202,52 +202,84 @@ def map_openai_params( return optional_params + # Providers whose InvokeModel body uses the Converse API format + # (messages + inferenceConfig + image blocks). Nova is the primary + # example; add others here as they adopt the same schema. + CONVERSE_INVOKE_PROVIDERS = ("nova",) + def _map_openai_to_bedrock_params( self, openai_request_body: Dict[str, Any], provider: Optional[str] = None, ) -> Dict[str, Any]: """ - Transform OpenAI request body to Bedrock-compatible modelInput parameters using existing transformation logic + Transform OpenAI request body to Bedrock-compatible modelInput + parameters using existing transformation logic. + + Routes to the correct per-provider transformation so that the + resulting dict matches the InvokeModel body that Bedrock expects + for batch inference. """ from litellm.types.utils import LlmProviders + _model = openai_request_body.get("model", "") messages = openai_request_body.get("messages", []) - - # Use existing Anthropic transformation logic for Anthropic models + optional_params = { + k: v + for k, v in openai_request_body.items() + if k not in ["model", "messages"] + } + + # --- Anthropic: use existing AmazonAnthropicClaudeConfig --- if provider == LlmProviders.ANTHROPIC: from litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformation import ( AmazonAnthropicClaudeConfig, ) - - anthropic_config = AmazonAnthropicClaudeConfig() - - # Extract optional params (everything except model and messages) - optional_params = {k: v for k, v in openai_request_body.items() if k not in ["model", "messages"]} - mapped_params = anthropic_config.map_openai_params( + + config = AmazonAnthropicClaudeConfig() + mapped_params = config.map_openai_params( non_default_params={}, optional_params=optional_params, model=_model, - drop_params=False + drop_params=False, ) - - # Transform using existing Anthropic logic - bedrock_params = anthropic_config.transform_request( + return config.transform_request( model=_model, messages=messages, optional_params=mapped_params, litellm_params={}, - headers={} + headers={}, ) - return bedrock_params - else: - # For other providers, use basic mapping - bedrock_params = { - "messages": messages, - **{k: v for k, v in openai_request_body.items() if k not in ["model", "messages"]} - } - return bedrock_params + # --- Converse API providers (e.g. Nova): use AmazonConverseConfig + # to correctly convert image_url blocks to Bedrock image format + # and wrap inference params inside inferenceConfig. --- + if provider in self.CONVERSE_INVOKE_PROVIDERS: + from litellm.llms.bedrock.chat.converse_transformation import ( + AmazonConverseConfig, + ) + + config = AmazonConverseConfig() + mapped_params = config.map_openai_params( + non_default_params=optional_params, + optional_params={}, + model=_model, + drop_params=False, + ) + return config.transform_request( + model=_model, + messages=messages, + optional_params=mapped_params, + litellm_params={}, + headers={}, + ) + + # --- All other providers: passthrough (OpenAI-compatible models + # like openai.gpt-oss-*, qwen, deepseek, etc.) --- + return { + "messages": messages, + **optional_params, + } def _transform_openai_jsonl_content_to_bedrock_jsonl_content( self, openai_jsonl_content: List[Dict[str, Any]] diff --git a/tests/test_litellm/llms/bedrock/files/expected_bedrock_batch_completions.jsonl b/tests/test_litellm/llms/bedrock/files/expected_bedrock_batch_completions.jsonl index c58963bb1de..8bb35ba95d7 100644 --- a/tests/test_litellm/llms/bedrock/files/expected_bedrock_batch_completions.jsonl +++ b/tests/test_litellm/llms/bedrock/files/expected_bedrock_batch_completions.jsonl @@ -1,2 +1,2 @@ -{"recordId": "request-1", "modelInput": {"messages": [{"role": "user", "content": [{"type": "text", "text": "Hello world!"}]}], "max_tokens": 10, "system": [{"type": "text", "text": "You are a helpful assistant."}], "anthropic_version": "bedrock-2023-05-31"}} -{"recordId": "request-2", "modelInput": {"messages": [{"role": "user", "content": [{"type": "text", "text": "Hello world!"}]}], "max_tokens": 10, "system": [{"type": "text", "text": "You are an unhelpful assistant."}], "anthropic_version": "bedrock-2023-05-31"}} +{"recordId": "request-1", "modelInput": {"messages": [{"role": "user", "content": [{"type": "text", "text": "Hello world!"}]}], "max_tokens": 10, "system": [{"type": "text", "text": "You are a helpful assistant."}], "anthropic_version": "bedrock-2023-05-31", "anthropic_beta": []}} +{"recordId": "request-2", "modelInput": {"messages": [{"role": "user", "content": [{"type": "text", "text": "Hello world!"}]}], "max_tokens": 10, "system": [{"type": "text", "text": "You are an unhelpful assistant."}], "anthropic_version": "bedrock-2023-05-31", "anthropic_beta": []}} diff --git a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py index 06e72539088..88cac84e438 100644 --- a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py +++ b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py @@ -88,3 +88,223 @@ def test_transform_openai_jsonl_content_to_bedrock_jsonl_content(self): print(f"\n=== Expected output written to: {expected_output_path} ===") + def test_nova_text_only_uses_converse_format(self): + """ + Test that Nova models produce Converse API format in batch modelInput. + + Verifies that: + - max_tokens is wrapped inside inferenceConfig.maxTokens + - messages use Converse content block format + - No raw OpenAI keys (max_tokens, temperature) at the top level + """ + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + config = BedrockFilesConfig() + + openai_jsonl_content = [ + { + "custom_id": "nova-text-1", + "method": "POST", + "url": "/v1/chat/completions", + "body": { + "model": "us.amazon.nova-pro-v1:0", + "messages": [ + {"role": "user", "content": "What is the capital of France?"} + ], + "max_tokens": 50, + "temperature": 0.7, + }, + } + ] + + result = config._transform_openai_jsonl_content_to_bedrock_jsonl_content( + openai_jsonl_content + ) + + assert len(result) == 1 + record = result[0] + assert record["recordId"] == "nova-text-1" + + model_input = record["modelInput"] + + # Must have inferenceConfig with maxTokens, NOT top-level max_tokens + assert "inferenceConfig" in model_input, ( + "Nova modelInput must contain inferenceConfig" + ) + assert model_input["inferenceConfig"]["maxTokens"] == 50 + assert model_input["inferenceConfig"]["temperature"] == 0.7 + assert "max_tokens" not in model_input, ( + "max_tokens must NOT be at the top level for Nova" + ) + assert "temperature" not in model_input, ( + "temperature must NOT be at the top level for Nova" + ) + + # Must have messages + assert "messages" in model_input + + def test_nova_image_content_uses_converse_image_blocks(self): + """ + Test that image_url content blocks are converted to Bedrock Converse + image format for Nova models in batch. + + Verifies that: + - image_url blocks are converted to {"image": {"format": ..., "source": {"bytes": ...}}} + - text blocks are converted to {"text": "..."} + - No raw OpenAI image_url type remains + """ + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + config = BedrockFilesConfig() + + # 1x1 transparent PNG + img_b64 = ( + "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR4" + "2mP8z8BQDwADhQGAWjR9awAAAABJRU5ErkJggg==" + ) + + openai_jsonl_content = [ + { + "custom_id": "nova-img-1", + "method": "POST", + "url": "/v1/chat/completions", + "body": { + "model": "us.amazon.nova-pro-v1:0", + "messages": [ + { + "role": "user", + "content": [ + {"type": "text", "text": "Describe this image."}, + { + "type": "image_url", + "image_url": { + "url": "data:image/png;base64," + img_b64 + }, + }, + ], + } + ], + "max_tokens": 100, + }, + } + ] + + result = config._transform_openai_jsonl_content_to_bedrock_jsonl_content( + openai_jsonl_content + ) + + assert len(result) == 1 + model_input = result[0]["modelInput"] + + # Check inferenceConfig + assert "inferenceConfig" in model_input + assert model_input["inferenceConfig"]["maxTokens"] == 100 + assert "max_tokens" not in model_input + + # Check messages structure + messages = model_input["messages"] + assert len(messages) == 1 + content_blocks = messages[0]["content"] + + # Should have text block and image block in Converse format + has_text = False + has_image = False + for block in content_blocks: + if "text" in block: + has_text = True + if "image" in block: + has_image = True + # Verify Converse image format + assert "format" in block["image"], ( + "Image block must have format field" + ) + assert "source" in block["image"], ( + "Image block must have source field" + ) + assert "bytes" in block["image"]["source"], ( + "Image source must have bytes field" + ) + # Must NOT have OpenAI-style image_url + assert "image_url" not in block, ( + "image_url must not appear in Converse format" + ) + assert block.get("type") != "image_url", ( + "type=image_url must not appear in Converse format" + ) + + assert has_text, "Should have a text content block" + assert has_image, "Should have an image content block" + + def test_anthropic_still_works_after_nova_fix(self): + """ + Regression test: ensure Anthropic models are still correctly + transformed after the Converse API provider changes. + """ + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + config = BedrockFilesConfig() + + openai_jsonl_content = [ + { + "custom_id": "claude-1", + "method": "POST", + "url": "/v1/chat/completions", + "body": { + "model": "us.anthropic.claude-3-5-sonnet-20240620-v1:0", + "messages": [ + {"role": "system", "content": "You are helpful."}, + {"role": "user", "content": "Hello!"}, + ], + "max_tokens": 10, + }, + } + ] + + result = config._transform_openai_jsonl_content_to_bedrock_jsonl_content( + openai_jsonl_content + ) + + assert len(result) == 1 + model_input = result[0]["modelInput"] + + # Anthropic should have anthropic_version + assert "anthropic_version" in model_input + assert "messages" in model_input + assert "max_tokens" in model_input + + def test_openai_passthrough_still_works(self): + """ + Regression test: ensure OpenAI-compatible models (e.g. gpt-oss) + still use passthrough format. + """ + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + config = BedrockFilesConfig() + + openai_jsonl_content = [ + { + "custom_id": "openai-1", + "method": "POST", + "url": "/v1/chat/completions", + "body": { + "model": "openai.gpt-oss-120b-1:0", + "messages": [ + {"role": "user", "content": "Hello!"}, + ], + "max_tokens": 10, + }, + } + ] + + result = config._transform_openai_jsonl_content_to_bedrock_jsonl_content( + openai_jsonl_content + ) + + assert len(result) == 1 + model_input = result[0]["modelInput"] + + # OpenAI-compatible should use passthrough: max_tokens at top level + assert "messages" in model_input + assert "max_tokens" in model_input + assert model_input["max_tokens"] == 10 +