Merge branch 'main' into delete-documents-feature

cli/magic-config.ts

@@ -630,7 +630,10 @@ async function processCreateOptions(options: any): Promise<void> {
           options.kendraExternal.length > 0) ||
         false,
       skip(): boolean {
-        return !(this as any).state.answers.enableRag;
+        if (!(this as any).state.answers.enableRag){
+          return true;
+        }
+        return !(this as any).state.answers.ragsToEnable.includes("kendra");
       },
     },
   ];

lib/aws-genai-llm-chatbot-stack.ts

@@ -357,7 +357,7 @@ export class AwsGenAILLMChatbotStack extends cdk.Stack {
         NagSuppressions.addResourceSuppressionsByPath(
           this,
           [
-            `/${this.stackName}/RagEngines/KendraRetrieval/CreateAuroraWorkspace/CreateKendraWorkspace/Role/DefaultPolicy/Resource`,
+            `/${this.stackName}/RagEngines/KendraRetrieval/CreateKendraWorkspace/CreateKendraWorkspace/Role/DefaultPolicy/Resource`,
           ],
           [
             {

lib/model-interfaces/langchain/README.md

@@ -2,13 +2,12 @@
 
 You can find examples of model adapters in [functions/request-handler/adapters/](./functions/request-handler/adapters/)
 
-
 1. Create your own adapter under [functions/request-handler/adapters/](./functions/request-handler/adapters/).
 
 ```python
 import os
 
-from langchain.chat_models import ChatOpenAI
+from langchain_community.chat_models import ChatOpenAI
 
 from ..base import ModelAdapter
 from ..registry import registry
@@ -29,7 +28,7 @@ class GPTAdapter(ModelAdapter):
 
     # (OPTIONAL) 3.If you need to override the default prompt, override the get_prompt and get_qa_prompt methods.
     # The get_qa_prompt is only used when RAG is enabled.
-    # If not you can remove this and leverage the get_prompt and get_qa_prompts from the base adapater.
+    # If not you can remove this and leverage the get_prompt and get_qa_prompts from the base adapter.
     # must return a PromptTemplate
     def get_prompt(self):
         template = """The following is a friendly conversation between a human and an AI. If the AI does not know the answer to a question, it truthfully says it does not know.
@@ -69,8 +68,8 @@ registry.register(r"^openai*", GPTAdapter)
 ```
 
 2. Make sure the `__init__.py` files are updated so that your adapter is correctly imported.
-   - Example model adapter [__init__.py](./functions/request-handler/adapters/openai/gpt.py)
-   - Adapters [__init__.py](./functions/request-handler/adapters/__init__.py)
+   - Example model adapter [**init**.py](./functions/request-handler/adapters/openai/gpt.py)
+   - Adapters [**init**.py](./functions/request-handler/adapters/__init__.py)
 
 Ensure the registry regex
 

lib/model-interfaces/langchain/functions/request-handler/adapters/azureopenai/azuregpt.py

@@ -1,5 +1,5 @@
 import os
-from langchain.chat_models import AzureChatOpenAI
+from langchain_community.chat_models import AzureChatOpenAI
 from langchain.prompts.prompt import PromptTemplate
 
 from ..base import ModelAdapter
@@ -26,14 +26,18 @@ def get_llm(self, model_kwargs={}):
 
         return AzureChatOpenAI(
             openai_api_base=os.environ.get(f"AZURE_OPENAI_API_BASE__{self.model_id}"),
-            deployment_name=os.environ.get(f"AZURE_OPENAI_API_DEPLOYMENT_NAME__{self.model_id}"),
+            deployment_name=os.environ.get(
+                f"AZURE_OPENAI_API_DEPLOYMENT_NAME__{self.model_id}"
+            ),
             openai_api_key=os.environ.get(f"AZURE_OPENAI_API_KEY__{self.model_id}"),
             openai_api_type=os.environ.get(f"AZURE_OPENAI_API_TYPE__{self.model_id}"),
-            openai_api_version=os.environ.get(f"AZURE_OPENAI_API_VERSION__{self.model_id}"),
-            callbacks=[self.callback_handler], **params
+            openai_api_version=os.environ.get(
+                f"AZURE_OPENAI_API_VERSION__{self.model_id}"
+            ),
+            callbacks=[self.callback_handler],
+            **params,
         )
 
 
-
 # Register the adapter
 registry.register(r"^azure.openai*", AzureGptAdapter)

lib/model-interfaces/langchain/functions/request-handler/adapters/bedrock/ai21_j2.py

@@ -1,5 +1,5 @@
 import genai_core.clients
-from langchain.llms import Bedrock
+from langchain_community.llms import Bedrock
 from langchain.prompts.prompt import PromptTemplate
 
 from ..base import ModelAdapter

lib/model-interfaces/langchain/functions/request-handler/adapters/bedrock/claude.py

@@ -1,6 +1,6 @@
 import genai_core.clients
 
-# from langchain.llms import Bedrock
+# from langchain_community.llms import Bedrock
 from langchain.prompts.prompt import PromptTemplate
 
 from .base import Bedrock

lib/model-interfaces/langchain/functions/request-handler/adapters/bedrock/cohere.py

@@ -1,6 +1,6 @@
 import genai_core.clients
 
-from langchain.llms import Bedrock
+from langchain_community.llms import Bedrock
 from langchain.prompts.prompt import PromptTemplate
 
 from ..base import ModelAdapter

lib/model-interfaces/langchain/functions/request-handler/adapters/bedrock/llama2_chat.py

@@ -1,6 +1,6 @@
 import genai_core.clients
 
-# from langchain.llms import Bedrock (pending https://github.com/langchain-ai/langchain/issues/13316)
+# from langchain_community.llms import Bedrock (pending https://github.com/langchain-ai/langchain/issues/13316)
 from .base import Bedrock
 
 from langchain.prompts.prompt import PromptTemplate

lib/model-interfaces/langchain/functions/request-handler/adapters/bedrock/titan.py

@@ -1,7 +1,7 @@
 import genai_core.clients
 from langchain.prompts.prompt import PromptTemplate
 
-from langchain.llms import Bedrock
+from langchain_community.llms import Bedrock
 
 from ..base import ModelAdapter
 from genai_core.registry import registry

lib/model-interfaces/langchain/functions/request-handler/adapters/openai/gpt.py

@@ -1,5 +1,5 @@
 import os
-from langchain.chat_models import ChatOpenAI
+from langchain_community.chat_models import ChatOpenAI
 from ..base import ModelAdapter
 from genai_core.registry import registry
 

lib/rag-engines/kendra-retrieval/index.ts

@@ -27,7 +27,7 @@ export class KendraRetrieval extends Construct {
 
     const createWorkflow = new CreateKendraWorkspace(
       this,
-      "CreateAuroraWorkspace",
+      "CreateKendraWorkspace",
       {
         config: props.config,
         shared: props.shared,

lib/shared/layers/common/requirements.txt

@@ -1,10 +1,11 @@
 aws_xray_sdk==2.12.1
-boto3==1.34.1
+boto3==1.34.98
 numpy==1.26.0
 cfnresponse==1.1.2
 aws_requests_auth==0.4.3
 requests-aws4auth==1.2.3
-langchain==0.1.5
+langchain==0.1.17
+langchain-community==0.0.36
 opensearch-py==2.4.2
 psycopg2-binary==2.9.7
 pgvector==0.2.2

lib/shared/layers/python-sdk/python/genai_core/models.py

@@ -45,13 +45,14 @@ def list_openai_models():
             "streaming": True,
             "inputModalities": [Modality.TEXT.value],
             "outputModalities": [Modality.TEXT.value],
-            "interface": ModelInterface.LANGCHIAN.value,
+            "interface": ModelInterface.LANGCHAIN.value,
             "ragSupported": True,
         }
         for model in models.data
         if model["id"].startswith("gpt")
     ]
 
+
 def list_azure_openai_models():
     # azure openai model are listed, comma separated in AZURE_OPENAI_MODELS variable in external API secret
     models = genai_core.parameters.get_external_api_key("AZURE_OPENAI_MODELS") or ""
@@ -63,12 +64,13 @@ def list_azure_openai_models():
             "streaming": True,
             "inputModalities": [Modality.TEXT.value],
             "outputModalities": [Modality.TEXT.value],
-            "interface": ModelInterface.LANGCHIAN.value,
+            "interface": ModelInterface.LANGCHAIN.value,
             "ragSupported": True,
         }
-        for model in models.split(',')
+        for model in models.split(",")
     ]
 
+
 def list_bedrock_models():
     try:
         bedrock = genai_core.clients.get_bedrock_client(service_name="bedrock")
@@ -93,7 +95,7 @@ def list_bedrock_models():
                 "streaming": model.get("responseStreamingSupported", False),
                 "inputModalities": model["inputModalities"],
                 "outputModalities": model["outputModalities"],
-                "interface": ModelInterface.LANGCHIAN.value,
+                "interface": ModelInterface.LANGCHAIN.value,
                 "ragSupported": True,
             }
             for model in bedrock_models
@@ -126,7 +128,7 @@ def list_bedrock_finetuned_models():
                 "streaming": model.get("responseStreamingSupported", False),
                 "inputModalities": model["inputModalities"],
                 "outputModalities": model["outputModalities"],
-                "interface": ModelInterface.LANGCHIAN.value,
+                "interface": ModelInterface.LANGCHAIN.value,
                 "ragSupported": True,
             }
             for model in bedrock_custom_models

lib/shared/layers/python-sdk/python/genai_core/types.py

@@ -53,7 +53,7 @@ class ModelStatus(Enum):
 
 
 class ModelInterface(Enum):
-    LANGCHIAN = "langchain"
+    LANGCHAIN = "langchain"
     IDEFICS = "idefics"
 
 
@@ -77,8 +77,9 @@ class ChatbotMessageType(Enum):
     Human = "human"
     AI = "ai"
 
+
 class Task(Enum):
     STORE = "store"
     RETRIEVE = "retrieve"
     SEARCH_QUERY = "search_query"
-    SEARCH_DOCUMENT = "search_document"
+    SEARCH_DOCUMENT = "search_document"

lib/shared/shared-asset-bundler.ts

@@ -50,7 +50,6 @@ export class SharedAssetBundler extends Construct {
   }
 
   bundleWithAsset(assetPath: string): Asset {
-    console.log(`Bundling asset ${assetPath}`);
     const asset = new aws_s3_assets.Asset(
       this,
       md5hash(assetPath).slice(0, 6),