[New feature] Add support for Amazon Bedrock, Amazon Kendra (#1053)

src/backend/langflow/components/llms/AmazonBedrock.py

@@ -0,0 +1,48 @@
+from typing import Optional
+from langflow import CustomComponent
+from langchain.llms.bedrock import Bedrock
+from langchain.llms.base import BaseLLM
+
+
+class AmazonBedrockComponent(CustomComponent):
+    display_name: str = "Amazon Bedrock"
+    description: str = "LLM model from Amazon Bedrock."
+
+    def build_config(self):
+        return {
+            "model_id": {
+                "display_name": "Model Id",
+                "options": [
+                    "ai21.j2-grande-instruct",
+                    "ai21.j2-jumbo-instruct",
+                    "ai21.j2-mid",
+                    "ai21.j2-mid-v1",
+                    "ai21.j2-ultra",
+                    "ai21.j2-ultra-v1",
+                    "anthropic.claude-instant-v1",
+                    "anthropic.claude-v1",
+                    "anthropic.claude-v2",
+                    "cohere.command-text-v14",
+                ],
+            },
+            "credentials_profile_name": {"display_name": "Credentials Profile Name"},
+            "streaming": {
+                "display_name": "Streaming",
+                "field_type": "bool"
+            },
+            "code": {"show": False},
+        }
+
+    def build(
+        self,
+        model_id: str = "anthropic.claude-instant-v1",
+        credentials_profile_name: Optional[str] = None,
+    ) -> BaseLLM:
+        try:
+            output = Bedrock(
+                credentials_profile_name=credentials_profile_name,
+                model_id=model_id,
+            )  # type: ignore
+        except Exception as e:
+            raise ValueError("Could not connect to AmazonBedrock API.") from e
+        return output

src/backend/langflow/components/retrievers/AmazonKendra.py

@@ -0,0 +1,47 @@
+from typing import Optional
+from langflow import CustomComponent
+from langchain.retrievers import AmazonKendraRetriever
+from langchain.schema import BaseRetriever
+
+
+class AmazonKendraRetrieverComponent(CustomComponent):
+    display_name: str = "Amazon Kendra Retriever"
+    description: str = "Retriever that uses the Amazon Kendra API."
+
+    def build_config(self):
+        return {
+            "index_id": {"display_name": "Index ID"},
+            "region_name": {"display_name": "Region Name"},
+            "credentials_profile_name": {"display_name": "Credentials Profile Name"},
+            "attribute_filter": {
+                "display_name": "Attribute Filter",
+                "field_type": "code",
+            },
+            "top_k": {"display_name": "Top K", "field_type": "int"},
+            "user_context": {
+                "display_name": "User Context",
+                "field_type": "code",
+            },
+            "code": {"show": False},
+        }
+
+    def build(
+        self,
+        index_id: str,
+        top_k: int = 3,
+        region_name: Optional[str] = None,
+        credentials_profile_name: Optional[str] = None,
+        attribute_filter: Optional[dict] = None,
+        user_context: Optional[dict] = None,
+    ) -> BaseRetriever:
+        try:
+            output = AmazonKendraRetriever(
+                index_id=index_id,
+                top_k=top_k,
+                region_name=region_name,
+                credentials_profile_name=credentials_profile_name,
+                attribute_filter=attribute_filter,
+                user_context=user_context)  # type: ignore
+        except Exception as e:
+            raise ValueError("Could not connect to AmazonKendra API.") from e
+        return output