[Feature] Add support for AWS Bedrock LLM (#1189)

Co-authored-by: Deven Patel <deven298@yahoo.com>

embedchain/factory.py

@@ -21,6 +21,7 @@ class LlmFactory:
         "openai": "embedchain.llm.openai.OpenAILlm",
         "vertexai": "embedchain.llm.vertex_ai.VertexAILlm",
         "google": "embedchain.llm.google.GoogleLlm",
+        "aws_bedrock": "embedchain.llm.aws_bedrock.AWSBedrockLlm",
         "mistralai": "embedchain.llm.mistralai.MistralAILlm",
     }
     provider_to_config_class = {

embedchain/llm/aws_bedrock.py

@@ -0,0 +1,48 @@
+from typing import Optional
+
+from langchain.llms import Bedrock
+
+from embedchain.config import BaseLlmConfig
+from embedchain.helpers.json_serializable import register_deserializable
+from embedchain.llm.base import BaseLlm
+
+
+@register_deserializable
+class AWSBedrockLlm(BaseLlm):
+    def __init__(self, config: Optional[BaseLlmConfig] = None):
+        super().__init__(config)
+
+    def get_llm_model_answer(self, prompt) -> str:
+        response = self._get_answer(prompt, self.config)
+        return response
+
+    def _get_answer(self, prompt: str, config: BaseLlmConfig) -> str:
+        try:
+            import boto3
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "The required dependencies for AWSBedrock are not installed."
+                'Please install with `pip install --upgrade "embedchain[aws-bedrock]"`'
+            ) from None
+
+        self.boto_client = boto3.client("bedrock-runtime", "us-west-2")
+
+        kwargs = {
+            "model_id": config.model or "amazon.titan-text-express-v1",
+            "client": self.boto_client,
+            "model_kwargs": config.model_kwargs
+            or {
+                "temperature": config.temperature,
+            },
+        }
+
+        if config.stream:
+            from langchain.callbacks.streaming_stdout import \
+                StreamingStdOutCallbackHandler
+
+            callbacks = [StreamingStdOutCallbackHandler()]
+            llm = Bedrock(**kwargs, streaming=config.stream, callbacks=callbacks)
+        else:
+            llm = Bedrock(**kwargs)
+
+        return llm(prompt)

embedchain/utils/misc.py

@@ -406,6 +406,7 @@ def validate_config(config_data):
                     "llama2",
                     "vertexai",
                     "google",
+                    "aws_bedrock",
                     "mistralai",
                 ),
                 Optional("config"): {
@@ -423,6 +424,7 @@ def validate_config(config_data):
                     Optional("query_type"): str,
                     Optional("api_key"): str,
                     Optional("endpoint"): str,
+                    Optional("model_kwargs"): dict,
                 },
             },
             Optional("vectordb"): {