Python: Bedrock Runtime document understanding examples

.doc_gen/metadata/bedrock-runtime_metadata.yaml

@@ -1522,6 +1522,109 @@ bedrock-runtime_InvokeModelWithResponseStream_TitanTextEmbeddings:
   services:
     bedrock-runtime: {InvokeModel}
 
+# Document understanding
+bedrock-runtime_DocumentUnderstanding_AmazonNova:
+  title: Send and process a document with Amazon Nova on &BR;
+  title_abbrev: "Document understanding"
+  synopsis: send and process a document with Amazon Nova on &BR;.
+  category: Amazon Nova
+  languages:
+    Python:
+      versions:
+        - sdk_version: 3
+          github: python/example_code/bedrock-runtime
+          excerpts:
+            - description: Send and process a document with Amazon Nova on &BR;.
+              snippet_tags:
+                - python.example_code.bedrock-runtime.DocumentUnderstanding_AmazonNovaText
+  services:
+    bedrock-runtime: {Converse}
+
+bedrock-runtime_DocumentUnderstanding_AnthropicClaude:
+  title: Send and process a document with Anthropic Claude on &BR;
+  title_abbrev: "Document understanding"
+  synopsis: send and process a document with Anthropic Claude on &BR;.
+  category: Anthropic Claude
+  languages:
+    Python:
+      versions:
+        - sdk_version: 3
+          github: python/example_code/bedrock-runtime
+          excerpts:
+            - description: Send and process a document with Anthropic Claude on &BR;.
+              snippet_tags:
+                - python.example_code.bedrock-runtime.DocumentUnderstanding_AnthropicClaude
+  services:
+    bedrock-runtime: {Converse}
+
+bedrock-runtime_DocumentUnderstanding_CohereCommand:
+  title: Send and process a document with Cohere Command models on &BR;
+  title_abbrev: "Document understanding"
+  synopsis: send and process a document with Cohere Command models on &BR;.
+  category: Cohere Command
+  languages:
+    Python:
+      versions:
+        - sdk_version: 3
+          github: python/example_code/bedrock-runtime
+          excerpts:
+            - description: Send and process a document with Cohere Command models on &BR;.
+              snippet_tags:
+                - python.example_code.bedrock-runtime.DocumentUnderstanding_CohereCommand
+  services:
+    bedrock-runtime: {Converse}
+
+bedrock-runtime_DocumentUnderstanding_DeepSeek:
+  title: Send and process a document with DeepSeek on &BR;
+  title_abbrev: "Document understanding"
+  synopsis: send and process a document with DeepSeek on &BR;.
+  category: DeepSeek
+  languages:
+    Python:
+      versions:
+        - sdk_version: 3
+          github: python/example_code/bedrock-runtime
+          excerpts:
+            - description: Send and process a document with DeepSeek on &BR;.
+              snippet_tags:
+                - python.example_code.bedrock-runtime.DocumentUnderstanding_DeepSeek
+  services:
+    bedrock-runtime: {Converse}
+
+bedrock-runtime_DocumentUnderstanding_MetaLlama:
+  title: Send and process a document with Llama on &BR;
+  title_abbrev: "Document understanding"
+  synopsis: send and process a document with Llama on &BR;.
+  category: Meta Llama
+  languages:
+    Python:
+      versions:
+        - sdk_version: 3
+          github: python/example_code/bedrock-runtime
+          excerpts:
+            - description: Send and process a document with Llama on &BR;.
+              snippet_tags:
+                - python.example_code.bedrock-runtime.DocumentUnderstanding_MetaLlama
+  services:
+    bedrock-runtime: {Converse}
+
+bedrock-runtime_DocumentUnderstanding_Mistral:
+  title: Send and process a document with Mistral models on &BR;
+  title_abbrev: "Document understanding"
+  synopsis: send and process a document with Mistral models on &BR;.
+  category: Mistral AI
+  languages:
+    Python:
+      versions:
+        - sdk_version: 3
+          github: python/example_code/bedrock-runtime
+          excerpts:
+            - description: Send and process a document with Mistral models on &BR;.
+              snippet_tags:
+                - python.example_code.bedrock-runtime.DocumentUnderstanding_Mistral
+  services:
+    bedrock-runtime: {Converse}
+
 # Tool use scenarios
 bedrock-runtime_Scenario_ToolUseDemo_AmazonNova:
   title: "A tool use demo illustrating how to connect AI models on &BR; with a custom tool or API"

python/example_code/bedrock-runtime/README.md

@@ -60,6 +60,7 @@ functions within the same service.
 
 - [Converse](models/amazon_nova/amazon_nova_text/converse.py#L4)
 - [ConverseStream](models/amazon_nova/amazon_nova_text/converse_stream.py#L4)
+- [Document understanding](models/amazon_nova/amazon_nova_text/document_understanding.py#L4)
 
 ### Amazon Nova Canvas
 
@@ -88,6 +89,7 @@ functions within the same service.
 
 - [Converse](models/anthropic_claude/converse.py#L4)
 - [ConverseStream](models/anthropic_claude/converse_stream.py#L4)
+- [Document understanding](models/anthropic_claude/document_understanding.py#L4)
 - [InvokeModel](models/anthropic_claude/invoke_model.py#L4)
 - [InvokeModelWithResponseStream](models/anthropic_claude/invoke_model_with_response_stream.py#L4)
 - [Scenario: Tool use with the Converse API](cross-model-scenarios/tool_use_demo/tool_use_demo.py)
@@ -96,23 +98,30 @@ functions within the same service.
 
 - [Converse](models/cohere_command/converse.py#L4)
 - [ConverseStream](models/cohere_command/converse_stream.py#L4)
+- [Document understanding](models/cohere_command/document_understanding.py#L4)
 - [InvokeModel: Command R and R+](models/cohere_command/command_r_invoke_model.py#L4)
 - [InvokeModel: Command and Command Light](models/cohere_command/command_invoke_model.py#L4)
 - [InvokeModelWithResponseStream: Command R and R+](models/cohere_command/command_r_invoke_model_with_response_stream.py#L4)
 - [InvokeModelWithResponseStream: Command and Command Light](models/cohere_command/command_invoke_model_with_response_stream.py#L4)
 - [Scenario: Tool use with the Converse API](cross-model-scenarios/tool_use_demo/tool_use_demo.py)
 
+### DeepSeek
+
+- [Document understanding](models/deepseek/document_understanding.py#L4)
+
 ### Meta Llama
 
 - [Converse](models/meta_llama/converse.py#L4)
 - [ConverseStream](models/meta_llama/converse_stream.py#L4)
+- [Document understanding](models/meta_llama/document_understanding.py#L4)
 - [InvokeModel](models/meta_llama/llama3_invoke_model.py#L4)
 - [InvokeModelWithResponseStream](models/meta_llama/llama3_invoke_model_with_response_stream.py#L4)
 
 ### Mistral AI
 
 - [Converse](models/mistral_ai/converse.py#L4)
 - [ConverseStream](models/mistral_ai/converse_stream.py#L4)
+- [Document understanding](models/mistral_ai/document_understanding.py#L4)
 - [InvokeModel](models/mistral_ai/invoke_model.py#L4)
 - [InvokeModelWithResponseStream](models/mistral_ai/invoke_model_with_response_stream.py#L4)
 

python/example_code/bedrock-runtime/models/amazon_nova/amazon_nova_text/document_understanding.py

@@ -0,0 +1,54 @@
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+# snippet-start:[python.example_code.bedrock-runtime.DocumentUnderstanding_AmazonNovaText]
+# Send and process a document with Amazon Nova on Amazon Bedrock.
+
+import boto3
+from botocore.exceptions import ClientError
+
+# Create a Bedrock Runtime client in the AWS Region you want to use.
+client = boto3.client("bedrock-runtime", region_name="us-east-1")
+
+# Set the model ID, e.g. Amazon Nova Lite.
+model_id = "amazon.nova-lite-v1:0"
+
+# Load the document
+with open("example-data/amazon-nova-service-cards.pdf", "rb") as file:
+    document_bytes = file.read()
+
+# Start a conversation with a user message and the document
+conversation = [
+    {
+        "role": "user",
+        "content": [
+            {"text": "Briefly compare the models described in this document"},
+            {
+                "document": {
+                    # Available formats: html, md, pdf, doc/docx, xls/xlsx, csv, and txt
+                    "format": "pdf",
+                    "name": "Amazon Nova Service Cards",
+                    "source": {"bytes": document_bytes},
+                }
+            },
+        ],
+    }
+]
+
+try:
+    # Send the message to the model, using a basic inference configuration.
+    response = client.converse(
+        modelId=model_id,
+        messages=conversation,
+        inferenceConfig={"maxTokens": 500, "temperature": 0.3},
+    )
+
+    # Extract and print the response text.
+    response_text = response["output"]["message"]["content"][0]["text"]
+    print(response_text)
+
+except (ClientError, Exception) as e:
+    print(f"ERROR: Can't invoke '{model_id}'. Reason: {e}")
+    exit(1)
+
+# snippet-end:[python.example_code.bedrock-runtime.DocumentUnderstanding_AmazonNovaText]

python/example_code/bedrock-runtime/models/anthropic_claude/document_understanding.py

@@ -0,0 +1,54 @@
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+# snippet-start:[python.example_code.bedrock-runtime.DocumentUnderstanding_AnthropicClaude]
+# Send and process a document with Anthropic Claude on Amazon Bedrock.
+
+import boto3
+from botocore.exceptions import ClientError
+
+# Create a Bedrock Runtime client in the AWS Region you want to use.
+client = boto3.client("bedrock-runtime", region_name="us-east-1")
+
+# Set the model ID, e.g. Claude 3 Haiku.
+model_id = "anthropic.claude-3-haiku-20240307-v1:0"
+
+# Load the document
+with open("example-data/amazon-nova-service-cards.pdf", "rb") as file:
+    document_bytes = file.read()
+
+# Start a conversation with a user message and the document
+conversation = [
+    {
+        "role": "user",
+        "content": [
+            {"text": "Briefly compare the models described in this document"},
+            {
+                "document": {
+                    # Available formats: html, md, pdf, doc/docx, xls/xlsx, csv, and txt
+                    "format": "pdf",
+                    "name": "Amazon Nova Service Cards",
+                    "source": {"bytes": document_bytes},
+                }
+            },
+        ],
+    }
+]
+
+try:
+    # Send the message to the model, using a basic inference configuration.
+    response = client.converse(
+        modelId=model_id,
+        messages=conversation,
+        inferenceConfig={"maxTokens": 500, "temperature": 0.3},
+    )
+
+    # Extract and print the response text.
+    response_text = response["output"]["message"]["content"][0]["text"]
+    print(response_text)
+
+except (ClientError, Exception) as e:
+    print(f"ERROR: Can't invoke '{model_id}'. Reason: {e}")
+    exit(1)
+
+# snippet-end:[python.example_code.bedrock-runtime.DocumentUnderstanding_AnthropicClaude]

python/example_code/bedrock-runtime/models/cohere_command/document_understanding.py

@@ -0,0 +1,54 @@
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+# snippet-start:[python.example_code.bedrock-runtime.DocumentUnderstanding_CohereCommand]
+# Send and process a document with Cohere Command models on Amazon Bedrock.
+
+import boto3
+from botocore.exceptions import ClientError
+
+# Create a Bedrock Runtime client in the AWS Region you want to use.
+client = boto3.client("bedrock-runtime", region_name="us-east-1")
+
+# Set the model ID, e.g. Command R+.
+model_id = "cohere.command-r-plus-v1:0"
+
+# Load the document
+with open("example-data/amazon-nova-service-cards.pdf", "rb") as file:
+    document_bytes = file.read()
+
+# Start a conversation with a user message and the document
+conversation = [
+    {
+        "role": "user",
+        "content": [
+            {"text": "Briefly compare the models described in this document"},
+            {
+                "document": {
+                    # Available formats: html, md, pdf, doc/docx, xls/xlsx, csv, and txt
+                    "format": "pdf",
+                    "name": "Amazon Nova Service Cards",
+                    "source": {"bytes": document_bytes},
+                }
+            },
+        ],
+    }
+]
+
+try:
+    # Send the message to the model, using a basic inference configuration.
+    response = client.converse(
+        modelId=model_id,
+        messages=conversation,
+        inferenceConfig={"maxTokens": 500, "temperature": 0.3},
+    )
+
+    # Extract and print the response text.
+    response_text = response["output"]["message"]["content"][0]["text"]
+    print(response_text)
+
+except (ClientError, Exception) as e:
+    print(f"ERROR: Can't invoke '{model_id}'. Reason: {e}")
+    exit(1)
+
+# snippet-end:[python.example_code.bedrock-runtime.DocumentUnderstanding_CohereCommand]

python/example_code/bedrock-runtime/models/deepseek/document_understanding.py

@@ -0,0 +1,62 @@
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+# snippet-start:[python.example_code.bedrock-runtime.DocumentUnderstanding_DeepSeek]
+# Send and process a document with DeepSeek on Amazon Bedrock.
+
+import boto3
+from botocore.exceptions import ClientError
+
+# Create a Bedrock Runtime client in the AWS Region you want to use.
+client = boto3.client("bedrock-runtime", region_name="us-east-1")
+
+# Set the model ID, e.g. DeepSeek-R1
+model_id = "us.deepseek.r1-v1:0"
+
+# Load the document
+with open("example-data/amazon-nova-service-cards.pdf", "rb") as file:
+    document_bytes = file.read()
+
+# Start a conversation with a user message and the document
+conversation = [
+    {
+        "role": "user",
+        "content": [
+            {"text": "Briefly compare the models described in this document"},
+            {
+                "document": {
+                    # Available formats: html, md, pdf, doc/docx, xls/xlsx, csv, and txt
+                    "format": "pdf",
+                    "name": "Amazon Nova Service Cards",
+                    "source": {"bytes": document_bytes},
+                }
+            },
+        ],
+    }
+]
+
+try:
+    # Send the message to the model, using a basic inference configuration.
+    response = client.converse(
+        modelId=model_id,
+        messages=conversation,
+        inferenceConfig={"maxTokens": 2000, "temperature": 0.3},
+    )
+
+    # Extract and print the reasoning and response text.
+    reasoning, response_text = "", ""
+    for item in response["output"]["message"]["content"]:
+        for key, value in item.items():
+            if key == "reasoningContent":
+                reasoning = value["reasoningText"]["text"]
+            elif key == "text":
+                response_text = value
+
+    print(f"\nReasoning:\n{reasoning}")
+    print(f"\nResponse:\n{response_text}")
+
+except (ClientError, Exception) as e:
+    print(f"ERROR: Can't invoke '{model_id}'. Reason: {e}")
+    exit(1)
+
+# snippet-end:[python.example_code.bedrock-runtime.DocumentUnderstanding_DeepSeek]