diff --git a/litellm/__init__.py b/litellm/__init__.py
index fe0cbe49e..8b8a50e46 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -179,6 +179,11 @@ aleph_alpha_models = [
 
 baseten_models = ["qvv0xeq", "q841o8w", "31dxrj3"]  # FALCON 7B  # WizardLM  # Mosaic ML
 
+bedrock_models = [
+    "amazon.titan-tg1-large",
+    "ai21.j2-grande-instruct"
+]
+
 model_list = (
     open_ai_chat_completion_models
     + open_ai_text_completion_models
@@ -212,6 +217,7 @@ provider_list = [
     "bedrock",
     "vllm",
     "nlp_cloud",
+    "bedrock",
     "custom", # custom apis
 ]
 
@@ -226,6 +232,7 @@ models_by_provider = {
     "openrouter": openrouter_models,
     "vertex_ai": vertex_chat_models + vertex_text_models,
     "ai21": ai21_models,
+    "bedrock": bedrock_models,
 }
 
 ####### EMBEDDING MODELS ###################
diff --git a/litellm/llms/bedrock.py b/litellm/llms/bedrock.py
index 0310dd325..bc5d0e721 100644
--- a/litellm/llms/bedrock.py
+++ b/litellm/llms/bedrock.py
@@ -15,6 +15,32 @@ class BedrockError(Exception):
             self.message
         )  # Call the base class constructor with the parameters it needs
 
+def init_bedrock_client(boto3, region_name):
+    import subprocess
+    try:
+        client = boto3.client(
+            service_name="bedrock",
+            region_name=region_name,
+            endpoint_url=f'https://bedrock.{region_name}.amazonaws.com'
+        )
+    except:
+        try:
+            command1 = "python3 -m pip install https://github.com/BerriAI/litellm/raw/main/cookbook/bedrock_resources/boto3-1.28.21-py3-none-any.whl"
+            subprocess.run(command1, shell=True, check=True)
+            # Command 2: Install boto3 from URL
+            command2 = "python3 -m pip install https://github.com/BerriAI/litellm/raw/main/cookbook/bedrock_resources/botocore-1.31.21-py3-none-any.whl"
+            subprocess.run(command2, shell=True, check=True)
+
+            import boto3
+            client = boto3.client(
+                service_name="bedrock",
+                region_name=region_name,
+                endpoint_url=f'https://bedrock.{region_name}.amazonaws.com'
+            )
+        except Exception as e:
+            raise e
+    return client
+
 """
 BEDROCK AUTH Keys/Vars
 os.environ['AWS_ACCESS_KEY_ID'] = ""
@@ -36,17 +62,17 @@ def completion(
 ):
     import sys
     if 'boto3' not in sys.modules:
-        import boto3
+        try:
+            import boto3
+        except:
+            raise Exception("Please Install boto3 to use bedrock with LiteLLM, run 'pip install boto3'")
 
     region_name = (
         get_secret("AWS_REGION_NAME") or
         "us-west-2" # default to us-west-2
     )
 
-    client = boto3.client(
-        service_name="bedrock",
-        region_name=region_name
-    )
+    client = init_bedrock_client(boto3, region_name)
 
     model = model
     prompt = ""
diff --git a/litellm/main.py b/litellm/main.py
index 26d54cf67..8e1913a2c 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -748,6 +748,29 @@ def completion(
                 )
                 return response
 
+            ## RESPONSE OBJECT
+            response = model_response
+        elif custom_llm_provider == "bedrock":
+            # boto3 reads keys from .env
+            model_response = bedrock.completion(
+                model=model,
+                messages=messages,
+                model_response=model_response,
+                print_verbose=print_verbose,
+                optional_params=optional_params,
+                litellm_params=litellm_params,
+                logger_fn=logger_fn,
+                encoding=encoding,
+                logging_obj=logging
+            )
+
+            if "stream" in optional_params and optional_params["stream"] == True: ## [BETA]
+                # don't try to access stream object,
+                response = CustomStreamWrapper(
+                    iter(model_response), model, custom_llm_provider="bedrock", logging_obj=logging
+                )
+                return response
+
             ## RESPONSE OBJECT
             response = model_response
         elif custom_llm_provider == "vllm":