diff --git a/litellm/__init__.py b/litellm/__init__.py
index e42bfbf031..017bd46acb 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -570,6 +570,7 @@ from .utils import (
     _calculate_retry_after,
     _should_retry,
     get_secret,
+    get_mapped_model_params,
 )
 from .llms.huggingface_restapi import HuggingfaceConfig
 from .llms.anthropic import AnthropicConfig
@@ -592,6 +593,7 @@ from .llms.bedrock import (
     AmazonTitanConfig,
     AmazonAI21Config,
     AmazonAnthropicConfig,
+    AmazonAnthropicClaude3Config,
     AmazonCohereConfig,
     AmazonLlamaConfig,
     AmazonStabilityConfig,
diff --git a/litellm/llms/bedrock.py b/litellm/llms/bedrock.py
index 1a25e167a9..79ba04f42e 100644
--- a/litellm/llms/bedrock.py
+++ b/litellm/llms/bedrock.py
@@ -1,11 +1,17 @@
 import json, copy, types
 import os
 from enum import Enum
-import time
+import time, uuid
 from typing import Callable, Optional, Any, Union, List
 import litellm
 from litellm.utils import ModelResponse, get_secret, Usage, ImageResponse
-from .prompt_templates.factory import prompt_factory, custom_prompt
+from .prompt_templates.factory import (
+    prompt_factory,
+    custom_prompt,
+    construct_tool_use_system_prompt,
+    extract_between_tags,
+    parse_xml_params,
+)
 import httpx
 
 
@@ -70,6 +76,59 @@ class AmazonTitanConfig:
         }
 
 
+class AmazonAnthropicClaude3Config:
+    """
+    Reference: https://us-west-2.console.aws.amazon.com/bedrock/home?region=us-west-2#/providers?model=claude
+
+    Supported Params for the Amazon / Anthropic Claude 3 models:
+
+    - `max_tokens` (integer) max tokens,
+    - `anthropic_version` (string) version of anthropic for bedrock - e.g. "bedrock-2023-05-31"
+    """
+
+    max_tokens: Optional[int] = litellm.max_tokens
+    anthropic_version: Optional[str] = "bedrock-2023-05-31"
+
+    def __init__(
+        self,
+        max_tokens: Optional[int] = None,
+        anthropic_version: Optional[str] = None,
+    ) -> None:
+        locals_ = locals()
+        for key, value in locals_.items():
+            if key != "self" and value is not None:
+                setattr(self.__class__, key, value)
+
+    @classmethod
+    def get_config(cls):
+        return {
+            k: v
+            for k, v in cls.__dict__.items()
+            if not k.startswith("__")
+            and not isinstance(
+                v,
+                (
+                    types.FunctionType,
+                    types.BuiltinFunctionType,
+                    classmethod,
+                    staticmethod,
+                ),
+            )
+            and v is not None
+        }
+
+    def get_supported_openai_params(self):
+        return ["max_tokens", "tools", "tool_choice", "stream"]
+
+    def map_openai_params(self, non_default_params: dict, optional_params: dict):
+        for param, value in non_default_params.items():
+            if param == "max_tokens":
+                optional_params["max_tokens"] = value
+            if param == "tools":
+                optional_params["tools"] = value
+        return optional_params
+
+
 class AmazonAnthropicConfig:
     """
     Reference: https://us-west-2.console.aws.amazon.com/bedrock/home?region=us-west-2#/providers?model=claude
@@ -123,6 +182,25 @@ class AmazonAnthropicConfig:
             and v is not None
         }
 
+    def get_supported_openai_params(
+        self,
+    ):
+        return ["max_tokens", "temperature", "stop", "top_p", "stream"]
+
+    def map_openai_params(self, non_default_params: dict, optional_params: dict):
+        for param, value in non_default_params.items():
+            if param == "max_tokens":
+                optional_params["max_tokens_to_sample"] = value
+            if param == "temperature":
+                optional_params["temperature"] = value
+            if param == "top_p":
+                optional_params["top_p"] = value
+            if param == "stop":
+                optional_params["stop_sequences"] = value
+            if param == "stream" and value == True:
+                optional_params["stream"] = value
+        return optional_params
+
 
 class AmazonCohereConfig:
     """
@@ -330,7 +408,8 @@ class AmazonMistralConfig:
             )
             and v is not None
         }
-                
+
+
 class AmazonStabilityConfig:
     """
     Reference: https://us-west-2.console.aws.amazon.com/bedrock/home?region=us-west-2#/providers?model=stability.stable-diffusion-xl-v0
@@ -542,7 +621,9 @@ def convert_messages_to_prompt(model, messages, provider, custom_prompt_dict):
                 model=model, messages=messages, custom_llm_provider="bedrock"
             )
     elif provider == "mistral":
-        prompt = prompt_factory(model=model, messages=messages, custom_llm_provider="bedrock")
+        prompt = prompt_factory(
+            model=model, messages=messages, custom_llm_provider="bedrock"
+        )
     else:
         prompt = ""
         for message in messages:
@@ -619,14 +700,47 @@ def completion(
         inference_params = copy.deepcopy(optional_params)
         stream = inference_params.pop("stream", False)
         if provider == "anthropic":
-            ## LOAD CONFIG
-            config = litellm.AmazonAnthropicConfig.get_config()
-            for k, v in config.items():
-                if (
-                    k not in inference_params
-                ):  # completion(top_k=3) > anthropic_config(top_k=3) <- allows for dynamic variables to be passed in
-                    inference_params[k] = v
-            data = json.dumps({"prompt": prompt, **inference_params})
+            if model.startswith("anthropic.claude-3"):
+                # Separate system prompt from rest of message
+                system_prompt_idx: Optional[int] = None
+                for idx, message in enumerate(messages):
+                    if message["role"] == "system":
+                        inference_params["system"] = message["content"]
+                        system_prompt_idx = idx
+                        break
+                if system_prompt_idx is not None:
+                    messages.pop(system_prompt_idx)
+                # Format rest of message according to anthropic guidelines
+                messages = prompt_factory(
+                    model=model, messages=messages, custom_llm_provider="anthropic"
+                )
+                ## LOAD CONFIG
+                config = litellm.AmazonAnthropicClaude3Config.get_config()
+                for k, v in config.items():
+                    if (
+                        k not in inference_params
+                    ):  # completion(top_k=3) > anthropic_config(top_k=3) <- allows for dynamic variables to be passed in
+                        inference_params[k] = v
+                ## Handle Tool Calling
+                if "tools" in inference_params:
+                    tool_calling_system_prompt = construct_tool_use_system_prompt(
+                        tools=inference_params["tools"]
+                    )
+                    inference_params["system"] = (
+                        inference_params.get("system", "\n")
+                        + tool_calling_system_prompt
+                    )  # add the anthropic tool calling prompt to the system prompt
+                    inference_params.pop("tools")
+                data = json.dumps({"messages": messages, **inference_params})
+            else:
+                ## LOAD CONFIG
+                config = litellm.AmazonAnthropicConfig.get_config()
+                for k, v in config.items():
+                    if (
+                        k not in inference_params
+                    ):  # completion(top_k=3) > anthropic_config(top_k=3) <- allows for dynamic variables to be passed in
+                        inference_params[k] = v
+                data = json.dumps({"prompt": prompt, **inference_params})
         elif provider == "ai21":
             ## LOAD CONFIG
             config = litellm.AmazonAI21Config.get_config()
@@ -646,9 +760,9 @@ def completion(
                 ):  # completion(top_k=3) > anthropic_config(top_k=3) <- allows for dynamic variables to be passed in
                     inference_params[k] = v
             if optional_params.get("stream", False) == True:
-                inference_params[
-                    "stream"
-                ] = True  # cohere requires stream = True in inference params
+                inference_params["stream"] = (
+                    True  # cohere requires stream = True in inference params
+                )
             data = json.dumps({"prompt": prompt, **inference_params})
         elif provider == "meta":
             ## LOAD CONFIG
@@ -674,7 +788,7 @@ def completion(
                     "textGenerationConfig": inference_params,
                 }
             )
-        elif provider == "mistral":  
+        elif provider == "mistral":
             ## LOAD CONFIG
             config = litellm.AmazonMistralConfig.get_config()
             for k, v in config.items():
@@ -783,8 +897,42 @@ def completion(
         if provider == "ai21":
             outputText = response_body.get("completions")[0].get("data").get("text")
         elif provider == "anthropic":
-            outputText = response_body["completion"]
-            model_response["finish_reason"] = response_body["stop_reason"]
+            if model.startswith("anthropic.claude-3"):
+                outputText = response_body.get("content")[0].get("text", None)
+                if "<invoke>" in outputText:  # OUTPUT PARSE FUNCTION CALL
+                    function_name = extract_between_tags("tool_name", outputText)[0]
+                    function_arguments_str = extract_between_tags("invoke", outputText)[
+                        0
+                    ].strip()
+                    function_arguments_str = (
+                        f"<invoke>{function_arguments_str}</invoke>"
+                    )
+                    function_arguments = parse_xml_params(function_arguments_str)
+                    _message = litellm.Message(
+                        tool_calls=[
+                            {
+                                "id": f"call_{uuid.uuid4()}",
+                                "type": "function",
+                                "function": {
+                                    "name": function_name,
+                                    "arguments": json.dumps(function_arguments),
+                                },
+                            }
+                        ],
+                        content=None,
+                    )
+                    model_response.choices[0].message = _message  # type: ignore
+                model_response["finish_reason"] = response_body["stop_reason"]
+                _usage = litellm.Usage(
+                    prompt_tokens=response_body["usage"]["input_tokens"],
+                    completion_tokens=response_body["usage"]["output_tokens"],
+                    total_tokens=response_body["usage"]["input_tokens"]
+                    + response_body["usage"]["output_tokens"],
+                )
+                model_response.usage = _usage
+            else:
+                outputText = response_body["completion"]
+                model_response["finish_reason"] = response_body["stop_reason"]
         elif provider == "cohere":
             outputText = response_body["generations"][0]["text"]
         elif provider == "meta":
@@ -803,8 +951,19 @@ def completion(
             )
         else:
             try:
-                if len(outputText) > 0:
+                if (
+                    len(outputText) > 0
+                    and hasattr(model_response.choices[0], "message")
+                    and getattr(model_response.choices[0].message, "tool_calls", None)
+                    is None
+                ):
                     model_response["choices"][0]["message"]["content"] = outputText
+                elif (
+                    hasattr(model_response.choices[0], "message")
+                    and getattr(model_response.choices[0].message, "tool_calls", None)
+                    is not None
+                ):
+                    pass
                 else:
                     raise Exception()
             except:
@@ -814,26 +973,28 @@ def completion(
                 )
 
         ## CALCULATING USAGE - baseten charges on time, not tokens - have some mapping of cost here.
-        prompt_tokens = response_metadata.get(
-            "x-amzn-bedrock-input-token-count", len(encoding.encode(prompt))
-        )
-        completion_tokens = response_metadata.get(
-            "x-amzn-bedrock-output-token-count",
-            len(
-                encoding.encode(
-                    model_response["choices"][0]["message"].get("content", "")
-                )
-            ),
-        )
+        if getattr(model_response.usage, "total_tokens", None) is None:
+            prompt_tokens = response_metadata.get(
+                "x-amzn-bedrock-input-token-count", len(encoding.encode(prompt))
+            )
+            completion_tokens = response_metadata.get(
+                "x-amzn-bedrock-output-token-count",
+                len(
+                    encoding.encode(
+                        model_response["choices"][0]["message"].get("content", "")
+                    )
+                ),
+            )
+            usage = Usage(
+                prompt_tokens=prompt_tokens,
+                completion_tokens=completion_tokens,
+                total_tokens=prompt_tokens + completion_tokens,
+            )
+            model_response.usage = usage
 
         model_response["created"] = int(time.time())
         model_response["model"] = model
-        usage = Usage(
-            prompt_tokens=prompt_tokens,
-            completion_tokens=completion_tokens,
-            total_tokens=prompt_tokens + completion_tokens,
-        )
-        model_response.usage = usage
+
         model_response._hidden_params["region_name"] = client.meta.region_name
         print_verbose(f"model_response._hidden_params: {model_response._hidden_params}")
         return model_response
@@ -1118,4 +1279,4 @@ def image_generation(
         image_dict = {"url": artifact["base64"]}
 
     model_response.data = image_dict
-    return model_response
\ No newline at end of file
+    return model_response
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 23afaf04d6..111b9f8c3c 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -1266,6 +1266,15 @@
         "litellm_provider": "bedrock",
         "mode": "completion"
     },
+    "anthropic.claude-3-sonnet-20240229-v1:0": {
+        "max_tokens": 200000, 
+        "max_input_tokens": 200000,
+        "max_output_tokens": 4096,
+        "input_cost_per_token": 0.000003,
+        "output_cost_per_token": 0.000015,
+        "litellm_provider": "bedrock",
+        "mode": "chat"
+    },
     "anthropic.claude-v1": {
         "max_tokens": 100000, 
         "max_output_tokens": 8191,
diff --git a/litellm/proxy/proxy_cli.py b/litellm/proxy/proxy_cli.py
index f6034cba3a..f7eba02ecb 100644
--- a/litellm/proxy/proxy_cli.py
+++ b/litellm/proxy/proxy_cli.py
@@ -19,6 +19,8 @@ telemetry = None
 
 
 def append_query_params(url, params):
+    print(f"url: {url}")
+    print(f"params: {params}")
     parsed_url = urlparse.urlparse(url)
     parsed_query = urlparse.parse_qs(parsed_url.query)
     parsed_query.update(params)
diff --git a/litellm/tests/log.txt b/litellm/tests/log.txt
new file mode 100644
index 0000000000..7b53823b0f
--- /dev/null
+++ b/litellm/tests/log.txt
@@ -0,0 +1,118 @@
+============================= test session starts ==============================
+platform darwin -- Python 3.11.6, pytest-7.3.1, pluggy-1.3.0
+rootdir: /Users/krrishdholakia/Documents/litellm/litellm/tests
+plugins: timeout-2.2.0, asyncio-0.23.2, anyio-3.7.1, xdist-3.3.1
+asyncio: mode=Mode.STRICT
+collected 1 item
+
+test_custom_callback_input.py .                                          [100%]
+
+=============================== warnings summary ===============================
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
+  /opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271: PydanticDeprecatedSince20: Support for class-based `config` is deprecated, use ConfigDict instead. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
+    warnings.warn(DEPRECATION_MESSAGE, DeprecationWarning)
+
+../proxy/_types.py:99
+  /Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:99: PydanticDeprecatedSince20: `pydantic.config.Extra` is deprecated, use literal values instead (e.g. `extra='allow'`). Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
+    extra = Extra.allow  # Allow extra fields
+
+../proxy/_types.py:102
+  /Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:102: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
+    @root_validator(pre=True)
+
+../proxy/_types.py:131
+  /Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:131: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
+    @root_validator(pre=True)
+
+../proxy/_types.py:177
+  /Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:177: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
+    @root_validator(pre=True)
+
+../proxy/_types.py:232
+  /Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:232: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
+    @root_validator(pre=True)
+
+../proxy/_types.py:244
+  /Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:244: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
+    @root_validator(pre=True)
+
+../proxy/_types.py:279
+  /Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:279: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
+    @root_validator(pre=True)
+
+../proxy/_types.py:305
+  /Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:305: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
+    @root_validator(pre=True)
+
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_fields.py:149
+  /opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_fields.py:149: UserWarning: Field "model_max_budget" has conflict with protected namespace "model_".
+  
+  You may be able to resolve this warning by setting `model_config['protected_namespaces'] = ()`.
+    warnings.warn(
+
+../proxy/_types.py:553
+  /Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:553: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
+    @root_validator(pre=True)
+
+../proxy/_types.py:574
+  /Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:574: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
+    @root_validator(pre=True)
+
+../utils.py:36
+  /Users/krrishdholakia/Documents/litellm/litellm/utils.py:36: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html
+    import pkg_resources
+
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: 10 warnings
+  /opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google')`.
+  Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
+    declare_namespace(pkg)
+
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
+  /opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google.cloud')`.
+  Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
+    declare_namespace(pkg)
+
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2350
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2350
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2350
+  /opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2350: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google')`.
+  Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
+    declare_namespace(parent)
+
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
+  /opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google.logging')`.
+  Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
+    declare_namespace(pkg)
+
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
+  /opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google.iam')`.
+  Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
+    declare_namespace(pkg)
+
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
+  /opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('mpl_toolkits')`.
+  Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
+    declare_namespace(pkg)
+
+../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
+  /opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('sphinxcontrib')`.
+  Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
+    declare_namespace(pkg)
+
+../llms/prompt_templates/factory.py:6
+  /Users/krrishdholakia/Documents/litellm/litellm/llms/prompt_templates/factory.py:6: DeprecationWarning: 'imghdr' is deprecated and slated for removal in Python 3.13
+    import imghdr, base64
+
+-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
+======================= 1 passed, 43 warnings in 13.05s ========================
diff --git a/litellm/tests/test_amazing_s3_logs.py b/litellm/tests/test_amazing_s3_logs.py
index 74d6eb5b94..0ccc0bc15c 100644
--- a/litellm/tests/test_amazing_s3_logs.py
+++ b/litellm/tests/test_amazing_s3_logs.py
@@ -1,4 +1,4 @@
-## @pytest.mark.skip(reason="AWS Suspended Account")
+# # @pytest.mark.skip(reason="AWS Suspended Account")
 # import sys
 # import os
 # import io, asyncio
diff --git a/litellm/tests/test_bedrock_completion.py b/litellm/tests/test_bedrock_completion.py
index 3e3d8b6bbc..8284b05158 100644
--- a/litellm/tests/test_bedrock_completion.py
+++ b/litellm/tests/test_bedrock_completion.py
@@ -1,293 +1,401 @@
 # @pytest.mark.skip(reason="AWS Suspended Account")
-# import sys, os
-# import traceback
-# from dotenv import load_dotenv
-#
-# load_dotenv()
-# import os, io
-#
-# sys.path.insert(
-#     0, os.path.abspath("../..")
-# )  # Adds the parent directory to the system path
-# import pytest
-# import litellm
-# from litellm import embedding, completion, completion_cost, Timeout, ModelResponse
-# from litellm import RateLimitError
-#
-# # litellm.num_retries = 3
-# litellm.cache = None
-# litellm.success_callback = []
-# user_message = "Write a short poem about the sky"
-# messages = [{"content": user_message, "role": "user"}]
-#
-#
-# @pytest.fixture(autouse=True)
-# def reset_callbacks():
-#     print("\npytest fixture - resetting callbacks")
-#     litellm.success_callback = []
-#     litellm._async_success_callback = []
-#     litellm.failure_callback = []
-#     litellm.callbacks = []
+import sys, os
+import traceback
+from dotenv import load_dotenv
+
+load_dotenv()
+import os, io
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+import pytest
+import litellm
+from litellm import embedding, completion, completion_cost, Timeout, ModelResponse
+from litellm import RateLimitError
+
+# litellm.num_retries = 3
+litellm.cache = None
+litellm.success_callback = []
+user_message = "Write a short poem about the sky"
+messages = [{"content": user_message, "role": "user"}]
 
 
-# def test_completion_bedrock_claude_completion_auth():
-#     print("calling bedrock claude completion params auth")
-#     import os
-
-#     aws_access_key_id = os.environ["AWS_ACCESS_KEY_ID"]
-#     aws_secret_access_key = os.environ["AWS_SECRET_ACCESS_KEY"]
-#     aws_region_name = os.environ["AWS_REGION_NAME"]
-
-#     os.environ.pop("AWS_ACCESS_KEY_ID", None)
-#     os.environ.pop("AWS_SECRET_ACCESS_KEY", None)
-#     os.environ.pop("AWS_REGION_NAME", None)
-
-#     try:
-#         response = completion(
-#             model="bedrock/anthropic.claude-instant-v1",
-#             messages=messages,
-#             max_tokens=10,
-#             temperature=0.1,
-#             aws_access_key_id=aws_access_key_id,
-#             aws_secret_access_key=aws_secret_access_key,
-#             aws_region_name=aws_region_name,
-#         )
-#         # Add any assertions here to check the response
-#         print(response)
-
-#         os.environ["AWS_ACCESS_KEY_ID"] = aws_access_key_id
-#         os.environ["AWS_SECRET_ACCESS_KEY"] = aws_secret_access_key
-#         os.environ["AWS_REGION_NAME"] = aws_region_name
-#     except RateLimitError:
-#         pass
-#     except Exception as e:
-#         pytest.fail(f"Error occurred: {e}")
+@pytest.fixture(autouse=True)
+def reset_callbacks():
+    print("\npytest fixture - resetting callbacks")
+    litellm.success_callback = []
+    litellm._async_success_callback = []
+    litellm.failure_callback = []
+    litellm.callbacks = []
 
 
-# # test_completion_bedrock_claude_completion_auth()
+def test_completion_bedrock_claude_completion_auth():
+    print("calling bedrock claude completion params auth")
+    import os
+
+    aws_access_key_id = os.environ["AWS_ACCESS_KEY_ID"]
+    aws_secret_access_key = os.environ["AWS_SECRET_ACCESS_KEY"]
+    aws_region_name = os.environ["AWS_REGION_NAME"]
+
+    os.environ.pop("AWS_ACCESS_KEY_ID", None)
+    os.environ.pop("AWS_SECRET_ACCESS_KEY", None)
+    os.environ.pop("AWS_REGION_NAME", None)
+
+    try:
+        response = completion(
+            model="bedrock/anthropic.claude-instant-v1",
+            messages=messages,
+            max_tokens=10,
+            temperature=0.1,
+            aws_access_key_id=aws_access_key_id,
+            aws_secret_access_key=aws_secret_access_key,
+            aws_region_name=aws_region_name,
+        )
+        # Add any assertions here to check the response
+        print(response)
+
+        os.environ["AWS_ACCESS_KEY_ID"] = aws_access_key_id
+        os.environ["AWS_SECRET_ACCESS_KEY"] = aws_secret_access_key
+        os.environ["AWS_REGION_NAME"] = aws_region_name
+    except RateLimitError:
+        pass
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
 
 
-# def test_completion_bedrock_claude_2_1_completion_auth():
-#     print("calling bedrock claude 2.1 completion params auth")
-#     import os
-
-#     aws_access_key_id = os.environ["AWS_ACCESS_KEY_ID"]
-#     aws_secret_access_key = os.environ["AWS_SECRET_ACCESS_KEY"]
-#     aws_region_name = os.environ["AWS_REGION_NAME"]
-
-#     os.environ.pop("AWS_ACCESS_KEY_ID", None)
-#     os.environ.pop("AWS_SECRET_ACCESS_KEY", None)
-#     os.environ.pop("AWS_REGION_NAME", None)
-#     try:
-#         response = completion(
-#             model="bedrock/anthropic.claude-v2:1",
-#             messages=messages,
-#             max_tokens=10,
-#             temperature=0.1,
-#             aws_access_key_id=aws_access_key_id,
-#             aws_secret_access_key=aws_secret_access_key,
-#             aws_region_name=aws_region_name,
-#         )
-#         # Add any assertions here to check the response
-#         print(response)
-
-#         os.environ["AWS_ACCESS_KEY_ID"] = aws_access_key_id
-#         os.environ["AWS_SECRET_ACCESS_KEY"] = aws_secret_access_key
-#         os.environ["AWS_REGION_NAME"] = aws_region_name
-#     except RateLimitError:
-#         pass
-#     except Exception as e:
-#         pytest.fail(f"Error occurred: {e}")
+# test_completion_bedrock_claude_completion_auth()
 
 
-# # test_completion_bedrock_claude_2_1_completion_auth()
+def test_completion_bedrock_claude_2_1_completion_auth():
+    print("calling bedrock claude 2.1 completion params auth")
+    import os
+
+    aws_access_key_id = os.environ["AWS_ACCESS_KEY_ID"]
+    aws_secret_access_key = os.environ["AWS_SECRET_ACCESS_KEY"]
+    aws_region_name = os.environ["AWS_REGION_NAME"]
+
+    os.environ.pop("AWS_ACCESS_KEY_ID", None)
+    os.environ.pop("AWS_SECRET_ACCESS_KEY", None)
+    os.environ.pop("AWS_REGION_NAME", None)
+    try:
+        response = completion(
+            model="bedrock/anthropic.claude-v2:1",
+            messages=messages,
+            max_tokens=10,
+            temperature=0.1,
+            aws_access_key_id=aws_access_key_id,
+            aws_secret_access_key=aws_secret_access_key,
+            aws_region_name=aws_region_name,
+        )
+        # Add any assertions here to check the response
+        print(response)
+
+        os.environ["AWS_ACCESS_KEY_ID"] = aws_access_key_id
+        os.environ["AWS_SECRET_ACCESS_KEY"] = aws_secret_access_key
+        os.environ["AWS_REGION_NAME"] = aws_region_name
+    except RateLimitError:
+        pass
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
 
 
-# def test_completion_bedrock_claude_external_client_auth():
-#     print("\ncalling bedrock claude external client auth")
-#     import os
-
-#     aws_access_key_id = os.environ["AWS_ACCESS_KEY_ID"]
-#     aws_secret_access_key = os.environ["AWS_SECRET_ACCESS_KEY"]
-#     aws_region_name = os.environ["AWS_REGION_NAME"]
-
-#     os.environ.pop("AWS_ACCESS_KEY_ID", None)
-#     os.environ.pop("AWS_SECRET_ACCESS_KEY", None)
-#     os.environ.pop("AWS_REGION_NAME", None)
-
-#     try:
-#         import boto3
-
-#         litellm.set_verbose = True
-
-#         bedrock = boto3.client(
-#             service_name="bedrock-runtime",
-#             region_name=aws_region_name,
-#             aws_access_key_id=aws_access_key_id,
-#             aws_secret_access_key=aws_secret_access_key,
-#             endpoint_url=f"https://bedrock-runtime.{aws_region_name}.amazonaws.com",
-#         )
-
-#         response = completion(
-#             model="bedrock/anthropic.claude-instant-v1",
-#             messages=messages,
-#             max_tokens=10,
-#             temperature=0.1,
-#             aws_bedrock_client=bedrock,
-#         )
-#         # Add any assertions here to check the response
-#         print(response)
-
-#         os.environ["AWS_ACCESS_KEY_ID"] = aws_access_key_id
-#         os.environ["AWS_SECRET_ACCESS_KEY"] = aws_secret_access_key
-#         os.environ["AWS_REGION_NAME"] = aws_region_name
-#     except RateLimitError:
-#         pass
-#     except Exception as e:
-#         pytest.fail(f"Error occurred: {e}")
+# test_completion_bedrock_claude_2_1_completion_auth()
 
 
-# # test_completion_bedrock_claude_external_client_auth()
+def test_completion_bedrock_claude_external_client_auth():
+    print("\ncalling bedrock claude external client auth")
+    import os
+
+    aws_access_key_id = os.environ["AWS_ACCESS_KEY_ID"]
+    aws_secret_access_key = os.environ["AWS_SECRET_ACCESS_KEY"]
+    aws_region_name = os.environ["AWS_REGION_NAME"]
+
+    os.environ.pop("AWS_ACCESS_KEY_ID", None)
+    os.environ.pop("AWS_SECRET_ACCESS_KEY", None)
+    os.environ.pop("AWS_REGION_NAME", None)
+
+    try:
+        import boto3
+
+        litellm.set_verbose = True
+
+        bedrock = boto3.client(
+            service_name="bedrock-runtime",
+            region_name=aws_region_name,
+            aws_access_key_id=aws_access_key_id,
+            aws_secret_access_key=aws_secret_access_key,
+            endpoint_url=f"https://bedrock-runtime.{aws_region_name}.amazonaws.com",
+        )
+
+        response = completion(
+            model="bedrock/anthropic.claude-instant-v1",
+            messages=messages,
+            max_tokens=10,
+            temperature=0.1,
+            aws_bedrock_client=bedrock,
+        )
+        # Add any assertions here to check the response
+        print(response)
+
+        os.environ["AWS_ACCESS_KEY_ID"] = aws_access_key_id
+        os.environ["AWS_SECRET_ACCESS_KEY"] = aws_secret_access_key
+        os.environ["AWS_REGION_NAME"] = aws_region_name
+    except RateLimitError:
+        pass
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
 
 
-# @pytest.mark.skip(reason="Expired token, need to renew")
-# def test_completion_bedrock_claude_sts_client_auth():
-#     print("\ncalling bedrock claude external client auth")
-#     import os
-
-#     aws_access_key_id = os.environ["AWS_TEMP_ACCESS_KEY_ID"]
-#     aws_secret_access_key = os.environ["AWS_TEMP_SECRET_ACCESS_KEY"]
-#     aws_region_name = os.environ["AWS_REGION_NAME"]
-#     aws_role_name = os.environ["AWS_TEMP_ROLE_NAME"]
-
-#     try:
-#         import boto3
-
-#         litellm.set_verbose = True
-
-#         response = completion(
-#             model="bedrock/anthropic.claude-instant-v1",
-#             messages=messages,
-#             max_tokens=10,
-#             temperature=0.1,
-#             aws_region_name=aws_region_name,
-#             aws_access_key_id=aws_access_key_id,
-#             aws_secret_access_key=aws_secret_access_key,
-#             aws_role_name=aws_role_name,
-#             aws_session_name="my-test-session",
-#         )
-
-#         response = embedding(
-#             model="cohere.embed-multilingual-v3",
-#             input=["hello world"],
-#             aws_region_name="us-east-1",
-#             aws_access_key_id=aws_access_key_id,
-#             aws_secret_access_key=aws_secret_access_key,
-#             aws_role_name=aws_role_name,
-#             aws_session_name="my-test-session",
-#         )
-
-#         response = completion(
-#             model="gpt-3.5-turbo",
-#             messages=messages,
-#             aws_region_name="us-east-1",
-#             aws_access_key_id=aws_access_key_id,
-#             aws_secret_access_key=aws_secret_access_key,
-#             aws_role_name=aws_role_name,
-#             aws_session_name="my-test-session",
-#         )
-#         # Add any assertions here to check the response
-#         print(response)
-#     except RateLimitError:
-#         pass
-#     except Exception as e:
-#         pytest.fail(f"Error occurred: {e}")
+# test_completion_bedrock_claude_external_client_auth()
 
 
-# # test_completion_bedrock_claude_sts_client_auth()
+@pytest.mark.skip(reason="Expired token, need to renew")
+def test_completion_bedrock_claude_sts_client_auth():
+    print("\ncalling bedrock claude external client auth")
+    import os
+
+    aws_access_key_id = os.environ["AWS_TEMP_ACCESS_KEY_ID"]
+    aws_secret_access_key = os.environ["AWS_TEMP_SECRET_ACCESS_KEY"]
+    aws_region_name = os.environ["AWS_REGION_NAME"]
+    aws_role_name = os.environ["AWS_TEMP_ROLE_NAME"]
+
+    try:
+        import boto3
+
+        litellm.set_verbose = True
+
+        response = completion(
+            model="bedrock/anthropic.claude-instant-v1",
+            messages=messages,
+            max_tokens=10,
+            temperature=0.1,
+            aws_region_name=aws_region_name,
+            aws_access_key_id=aws_access_key_id,
+            aws_secret_access_key=aws_secret_access_key,
+            aws_role_name=aws_role_name,
+            aws_session_name="my-test-session",
+        )
+
+        response = embedding(
+            model="cohere.embed-multilingual-v3",
+            input=["hello world"],
+            aws_region_name="us-east-1",
+            aws_access_key_id=aws_access_key_id,
+            aws_secret_access_key=aws_secret_access_key,
+            aws_role_name=aws_role_name,
+            aws_session_name="my-test-session",
+        )
+
+        response = completion(
+            model="gpt-3.5-turbo",
+            messages=messages,
+            aws_region_name="us-east-1",
+            aws_access_key_id=aws_access_key_id,
+            aws_secret_access_key=aws_secret_access_key,
+            aws_role_name=aws_role_name,
+            aws_session_name="my-test-session",
+        )
+        # Add any assertions here to check the response
+        print(response)
+    except RateLimitError:
+        pass
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
 
 
-# def test_provisioned_throughput():
-#     try:
-#         litellm.set_verbose = True
-#         import botocore, json, io
-#         import botocore.session
-#         from botocore.stub import Stubber
-
-#         bedrock_client = botocore.session.get_session().create_client(
-#             "bedrock-runtime", region_name="us-east-1"
-#         )
-
-#         expected_params = {
-#             "accept": "application/json",
-#             "body": '{"prompt": "\\n\\nHuman: Hello, how are you?\\n\\nAssistant: ", '
-#             '"max_tokens_to_sample": 256}',
-#             "contentType": "application/json",
-#             "modelId": "provisioned-model-arn",
-#         }
-#         response_from_bedrock = {
-#             "body": io.StringIO(
-#                 json.dumps(
-#                     {
-#                         "completion": " Here is a short poem about the sky:",
-#                         "stop_reason": "max_tokens",
-#                         "stop": None,
-#                     }
-#                 )
-#             ),
-#             "contentType": "contentType",
-#             "ResponseMetadata": {"HTTPStatusCode": 200},
-#         }
-
-#         with Stubber(bedrock_client) as stubber:
-#             stubber.add_response(
-#                 "invoke_model",
-#                 service_response=response_from_bedrock,
-#                 expected_params=expected_params,
-#             )
-#             response = litellm.completion(
-#                 model="bedrock/anthropic.claude-instant-v1",
-#                 model_id="provisioned-model-arn",
-#                 messages=[{"content": "Hello, how are you?", "role": "user"}],
-#                 aws_bedrock_client=bedrock_client,
-#             )
-#             print("response stubbed", response)
-#     except Exception as e:
-#         pytest.fail(f"Error occurred: {e}")
+# test_completion_bedrock_claude_sts_client_auth()
 
 
-# # test_provisioned_throughput()
+def test_bedrock_claude_3():
+    try:
+        litellm.set_verbose = True
+        response: ModelResponse = completion(
+            model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0",
+            messages=messages,
+            max_tokens=10,
+        )
+        # Add any assertions here to check the response
+        assert len(response.choices) > 0
+        assert len(response.choices[0].message.content) > 0
+    except RateLimitError:
+        pass
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
 
 
-# def test_completion_bedrock_mistral_completion_auth():
-#     print("calling bedrock mistral completion params auth")
-#     import os
-#
-#     # aws_access_key_id = os.environ["AWS_ACCESS_KEY_ID"]
-#     # aws_secret_access_key = os.environ["AWS_SECRET_ACCESS_KEY"]
-#     # aws_region_name = os.environ["AWS_REGION_NAME"]
-#
-#     # os.environ.pop("AWS_ACCESS_KEY_ID", None)
-#     # os.environ.pop("AWS_SECRET_ACCESS_KEY", None)
-#     # os.environ.pop("AWS_REGION_NAME", None)
-#     try:
-#         response:ModelResponse = completion(
-#             model="bedrock/mistral.mistral-7b-instruct-v0:2",
-#             messages=messages,
-#             max_tokens=10,
-#             temperature=0.1,
-#         )
-#         # Add any assertions here to check the response
-#         assert len(response.choices) > 0
-#         assert len(response.choices[0].message.content) > 0
-#
-#         # os.environ["AWS_ACCESS_KEY_ID"] = aws_access_key_id
-#         # os.environ["AWS_SECRET_ACCESS_KEY"] = aws_secret_access_key
-#         # os.environ["AWS_REGION_NAME"] = aws_region_name
-#     except RateLimitError:
-#         pass
-#     except Exception as e:
-#         pytest.fail(f"Error occurred: {e}")
-#
-#
-# test_completion_bedrock_mistral_completion_auth()
\ No newline at end of file
+def test_bedrock_claude_3_tool_calling():
+    try:
+        litellm.set_verbose = True
+        tools = [
+            {
+                "type": "function",
+                "function": {
+                    "name": "get_current_weather",
+                    "description": "Get the current weather in a given location",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "location": {
+                                "type": "string",
+                                "description": "The city and state, e.g. San Francisco, CA",
+                            },
+                            "unit": {
+                                "type": "string",
+                                "enum": ["celsius", "fahrenheit"],
+                            },
+                        },
+                        "required": ["location"],
+                    },
+                },
+            }
+        ]
+        messages = [
+            {"role": "user", "content": "What's the weather like in Boston today?"}
+        ]
+        response: ModelResponse = completion(
+            model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0",
+            messages=messages,
+            tools=tools,
+            tool_choice="auto",
+        )
+        print(f"response: {response}")
+        # Add any assertions here to check the response
+        assert isinstance(response.choices[0].message.tool_calls[0].function.name, str)
+        assert isinstance(
+            response.choices[0].message.tool_calls[0].function.arguments, str
+        )
+    except RateLimitError:
+        pass
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+
+
+def encode_image(image_path):
+    import base64
+
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode("utf-8")
+
+
+@pytest.mark.skip(
+    reason="we already test claude-3, this is just another way to pass images"
+)
+def test_completion_claude_3_base64():
+    try:
+        litellm.set_verbose = True
+        litellm.num_retries = 3
+        image_path = "../proxy/cached_logo.jpg"
+        # Getting the base64 string
+        base64_image = encode_image(image_path)
+        resp = litellm.completion(
+            model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0",
+            messages=[
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": "Whats in this image?"},
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": "data:image/jpeg;base64," + base64_image
+                            },
+                        },
+                    ],
+                }
+            ],
+        )
+
+        prompt_tokens = resp.usage.prompt_tokens
+        raise Exception("it worked!")
+    except Exception as e:
+        if "500 Internal error encountered.'" in str(e):
+            pass
+        else:
+            pytest.fail(f"An exception occurred - {str(e)}")
+
+
+def test_provisioned_throughput():
+    try:
+        litellm.set_verbose = True
+        import botocore, json, io
+        import botocore.session
+        from botocore.stub import Stubber
+
+        bedrock_client = botocore.session.get_session().create_client(
+            "bedrock-runtime", region_name="us-east-1"
+        )
+
+        expected_params = {
+            "accept": "application/json",
+            "body": '{"prompt": "\\n\\nHuman: Hello, how are you?\\n\\nAssistant: ", '
+            '"max_tokens_to_sample": 256}',
+            "contentType": "application/json",
+            "modelId": "provisioned-model-arn",
+        }
+        response_from_bedrock = {
+            "body": io.StringIO(
+                json.dumps(
+                    {
+                        "completion": " Here is a short poem about the sky:",
+                        "stop_reason": "max_tokens",
+                        "stop": None,
+                    }
+                )
+            ),
+            "contentType": "contentType",
+            "ResponseMetadata": {"HTTPStatusCode": 200},
+        }
+
+        with Stubber(bedrock_client) as stubber:
+            stubber.add_response(
+                "invoke_model",
+                service_response=response_from_bedrock,
+                expected_params=expected_params,
+            )
+            response = litellm.completion(
+                model="bedrock/anthropic.claude-instant-v1",
+                model_id="provisioned-model-arn",
+                messages=[{"content": "Hello, how are you?", "role": "user"}],
+                aws_bedrock_client=bedrock_client,
+            )
+            print("response stubbed", response)
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+
+
+# test_provisioned_throughput()
+
+
+def test_completion_bedrock_mistral_completion_auth():
+    print("calling bedrock mistral completion params auth")
+    import os
+
+    # aws_access_key_id = os.environ["AWS_ACCESS_KEY_ID"]
+    # aws_secret_access_key = os.environ["AWS_SECRET_ACCESS_KEY"]
+    # aws_region_name = os.environ["AWS_REGION_NAME"]
+
+    # os.environ.pop("AWS_ACCESS_KEY_ID", None)
+    # os.environ.pop("AWS_SECRET_ACCESS_KEY", None)
+    # os.environ.pop("AWS_REGION_NAME", None)
+    try:
+        response: ModelResponse = completion(
+            model="bedrock/mistral.mistral-7b-instruct-v0:2",
+            messages=messages,
+            max_tokens=10,
+            temperature=0.1,
+        )
+        # Add any assertions here to check the response
+        assert len(response.choices) > 0
+        assert len(response.choices[0].message.content) > 0
+
+        # os.environ["AWS_ACCESS_KEY_ID"] = aws_access_key_id
+        # os.environ["AWS_SECRET_ACCESS_KEY"] = aws_secret_access_key
+        # os.environ["AWS_REGION_NAME"] = aws_region_name
+    except RateLimitError:
+        pass
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+
+
+# test_completion_bedrock_mistral_completion_auth()
diff --git a/litellm/tests/test_caching.py b/litellm/tests/test_caching.py
index 3a7f969e5c..f649bff027 100644
--- a/litellm/tests/test_caching.py
+++ b/litellm/tests/test_caching.py
@@ -546,7 +546,6 @@ def test_redis_cache_acompletion_stream():
 # test_redis_cache_acompletion_stream()
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_redis_cache_acompletion_stream_bedrock():
     import asyncio
 
diff --git a/litellm/tests/test_completion.py b/litellm/tests/test_completion.py
index 22d8b2f6a1..57b0e436f0 100644
--- a/litellm/tests/test_completion.py
+++ b/litellm/tests/test_completion.py
@@ -1646,7 +1646,6 @@ def test_completion_chat_sagemaker_mistral():
 # test_completion_chat_sagemaker_mistral()
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_completion_bedrock_titan_null_response():
     try:
         response = completion(
@@ -1672,7 +1671,6 @@ def test_completion_bedrock_titan_null_response():
         pytest.fail(f"An error occurred - {str(e)}")
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_completion_bedrock_titan():
     try:
         response = completion(
@@ -1694,7 +1692,6 @@ def test_completion_bedrock_titan():
 # test_completion_bedrock_titan()
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_completion_bedrock_claude():
     print("calling claude")
     try:
@@ -1716,7 +1713,6 @@ def test_completion_bedrock_claude():
 # test_completion_bedrock_claude()
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_completion_bedrock_cohere():
     print("calling bedrock cohere")
     litellm.set_verbose = True
diff --git a/litellm/tests/test_completion_cost.py b/litellm/tests/test_completion_cost.py
index 034048c633..947da71669 100644
--- a/litellm/tests/test_completion_cost.py
+++ b/litellm/tests/test_completion_cost.py
@@ -171,7 +171,6 @@ def test_cost_openai_image_gen():
     assert cost == 0.019922944
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_cost_bedrock_pricing():
     """
     - get pricing specific to region for a model
diff --git a/litellm/tests/test_configs/test_config_no_auth.yaml b/litellm/tests/test_configs/test_config_no_auth.yaml
index 9cc32bb0bf..1c5ddf2266 100644
--- a/litellm/tests/test_configs/test_config_no_auth.yaml
+++ b/litellm/tests/test_configs/test_config_no_auth.yaml
@@ -115,4 +115,13 @@ model_list:
   model_info:
     description: this is a test openai model
     id: 34cb2419-7c63-44ae-a189-53f1d1ce5953
-  model_name: test_openai_models
\ No newline at end of file
+  model_name: test_openai_models
+- litellm_params:
+    model: amazon.titan-embed-text-v1
+  model_name: amazon-embeddings
+- litellm_params:
+    model: gpt-3.5-turbo
+  model_info:
+    description: this is a test openai model
+    id: 753dca9a-898d-4ff7-9961-5acf7cdf38cf
+  model_name: test_openai_models
diff --git a/litellm/tests/test_custom_callback_input.py b/litellm/tests/test_custom_callback_input.py
index 683173b21e..9249333197 100644
--- a/litellm/tests/test_custom_callback_input.py
+++ b/litellm/tests/test_custom_callback_input.py
@@ -478,7 +478,6 @@ async def test_async_chat_azure_stream():
 
 
 ## Test Bedrock + sync
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_chat_bedrock_stream():
     try:
         customHandler = CompletionCustomHandler()
@@ -519,7 +518,6 @@ def test_chat_bedrock_stream():
 
 
 ## Test Bedrock + Async
-@pytest.mark.skip(reason="AWS Suspended Account")
 @pytest.mark.asyncio
 async def test_async_chat_bedrock_stream():
     try:
@@ -796,7 +794,6 @@ async def test_async_embedding_azure():
 
 
 ## Test Bedrock + Async
-@pytest.mark.skip(reason="AWS Suspended Account")
 @pytest.mark.asyncio
 async def test_async_embedding_bedrock():
     try:
diff --git a/litellm/tests/test_embedding.py b/litellm/tests/test_embedding.py
index 2c9de496c4..a2f71eb982 100644
--- a/litellm/tests/test_embedding.py
+++ b/litellm/tests/test_embedding.py
@@ -256,7 +256,6 @@ async def test_vertexai_aembedding():
         pytest.fail(f"Error occurred: {e}")
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_bedrock_embedding_titan():
     try:
         # this tests if we support str input for bedrock embedding
@@ -302,7 +301,6 @@ def test_bedrock_embedding_titan():
 # test_bedrock_embedding_titan()
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_bedrock_embedding_cohere():
     try:
         litellm.set_verbose = False
diff --git a/litellm/tests/test_image_generation.py b/litellm/tests/test_image_generation.py
index 0672319a21..59ccaacd8d 100644
--- a/litellm/tests/test_image_generation.py
+++ b/litellm/tests/test_image_generation.py
@@ -121,7 +121,6 @@ async def test_async_image_generation_azure():
             pytest.fail(f"An exception occurred - {str(e)}")
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_image_generation_bedrock():
     try:
         litellm.set_verbose = True
@@ -142,7 +141,6 @@ def test_image_generation_bedrock():
             pytest.fail(f"An exception occurred - {str(e)}")
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 @pytest.mark.asyncio
 async def test_aimage_generation_bedrock_with_optional_params():
     try:
diff --git a/litellm/tests/test_provider_specific_config.py b/litellm/tests/test_provider_specific_config.py
index dcb4dcb4c7..08a84b5604 100644
--- a/litellm/tests/test_provider_specific_config.py
+++ b/litellm/tests/test_provider_specific_config.py
@@ -515,7 +515,6 @@ def sagemaker_test_completion():
 #  Bedrock
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def bedrock_test_completion():
     litellm.AmazonCohereConfig(max_tokens=10)
     # litellm.set_verbose=True
diff --git a/litellm/tests/test_proxy_server.py b/litellm/tests/test_proxy_server.py
index 3db4a980a9..d5e8f09c68 100644
--- a/litellm/tests/test_proxy_server.py
+++ b/litellm/tests/test_proxy_server.py
@@ -125,7 +125,6 @@ def test_embedding(client_no_auth):
         pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}")
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_bedrock_embedding(client_no_auth):
     global headers
     from litellm.proxy.proxy_server import user_custom_auth
diff --git a/litellm/tests/test_router.py b/litellm/tests/test_router.py
index 7c182ee686..dc2076aa36 100644
--- a/litellm/tests/test_router.py
+++ b/litellm/tests/test_router.py
@@ -575,7 +575,6 @@ def test_azure_embedding_on_router():
 # test_azure_embedding_on_router()
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_bedrock_on_router():
     litellm.set_verbose = True
     print("\n Testing bedrock on router\n")
diff --git a/litellm/tests/test_router_timeout.py b/litellm/tests/test_router_timeout.py
index 3816c649e9..dff30113be 100644
--- a/litellm/tests/test_router_timeout.py
+++ b/litellm/tests/test_router_timeout.py
@@ -87,7 +87,6 @@ def test_router_timeouts():
         print("********** TOKENS USED SO FAR = ", total_tokens_used)
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 @pytest.mark.asyncio
 async def test_router_timeouts_bedrock():
     import openai
diff --git a/litellm/tests/test_streaming.py b/litellm/tests/test_streaming.py
index 5767a944b2..c513447b02 100644
--- a/litellm/tests/test_streaming.py
+++ b/litellm/tests/test_streaming.py
@@ -727,6 +727,7 @@ def test_completion_claude_stream_bad_key():
 #         pytest.fail(f"Error occurred: {e}")
 
 
+@pytest.mark.skip(reason="Replicate changed exceptions")
 def test_completion_replicate_stream_bad_key():
     try:
         api_key = "bad-key"
@@ -764,7 +765,6 @@ def test_completion_replicate_stream_bad_key():
 # test_completion_replicate_stream_bad_key()
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_completion_bedrock_claude_stream():
     try:
         litellm.set_verbose = False
@@ -811,7 +811,6 @@ def test_completion_bedrock_claude_stream():
 # test_completion_bedrock_claude_stream()
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
 def test_completion_bedrock_ai21_stream():
     try:
         litellm.set_verbose = False
@@ -1060,6 +1059,7 @@ def ai21_completion_call_bad_key():
 # ai21_completion_call_bad_key()
 
 
+@pytest.mark.skip(reason="flaky test")
 @pytest.mark.asyncio
 async def test_hf_completion_tgi_stream():
     try:
diff --git a/litellm/utils.py b/litellm/utils.py
index 0b601521f9..d4d85cad1b 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -245,10 +245,12 @@ class Message(OpenAIObject):
         self.role = role
         if function_call is not None:
             self.function_call = FunctionCall(**function_call)
+
         if tool_calls is not None:
             self.tool_calls = []
             for tool_call in tool_calls:
                 self.tool_calls.append(ChatCompletionMessageToolCall(**tool_call))
+
         if logprobs is not None:
             self._logprobs = logprobs
 
@@ -4111,6 +4113,7 @@ def get_optional_params(
             and custom_llm_provider != "together_ai"
             and custom_llm_provider != "mistral"
             and custom_llm_provider != "anthropic"
+            and custom_llm_provider != "bedrock"
         ):
             if custom_llm_provider == "ollama" or custom_llm_provider == "ollama_chat":
                 # ollama actually supports json output
@@ -4518,20 +4521,24 @@ def get_optional_params(
             if stream:
                 optional_params["stream"] = stream
         elif "anthropic" in model:
-            supported_params = ["max_tokens", "temperature", "stop", "top_p", "stream"]
+            supported_params = get_mapped_model_params(
+                model=model, custom_llm_provider=custom_llm_provider
+            )
             _check_valid_arg(supported_params=supported_params)
             # anthropic params on bedrock
             # \"max_tokens_to_sample\":300,\"temperature\":0.5,\"top_p\":1,\"stop_sequences\":[\"\\\\n\\\\nHuman:\"]}"
-            if max_tokens is not None:
-                optional_params["max_tokens_to_sample"] = max_tokens
-            if temperature is not None:
-                optional_params["temperature"] = temperature
-            if top_p is not None:
-                optional_params["top_p"] = top_p
-            if stop is not None:
-                optional_params["stop_sequences"] = stop
-            if stream:
-                optional_params["stream"] = stream
+            if model.startswith("anthropic.claude-3"):
+                optional_params = (
+                    litellm.AmazonAnthropicClaude3Config().map_openai_params(
+                        non_default_params=non_default_params,
+                        optional_params=optional_params,
+                    )
+                )
+            else:
+                optional_params = litellm.AmazonAnthropicConfig().map_openai_params(
+                    non_default_params=non_default_params,
+                    optional_params=optional_params,
+                )
         elif "amazon" in model:  # amazon titan llms
             supported_params = ["max_tokens", "temperature", "stop", "top_p", "stream"]
             _check_valid_arg(supported_params=supported_params)
@@ -4996,6 +5003,17 @@ def get_optional_params(
     return optional_params
 
 
+def get_mapped_model_params(model: str, custom_llm_provider: str):
+    """
+    Returns the supported openai params for a given model + provider
+    """
+    if custom_llm_provider == "bedrock":
+        if model.startswith("anthropic.claude-3"):
+            return litellm.AmazonAnthropicClaude3Config().get_supported_openai_params()
+        else:
+            return litellm.AmazonAnthropicConfig().get_supported_openai_params()
+
+
 def get_llm_provider(
     model: str,
     custom_llm_provider: Optional[str] = None,
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 23afaf04d6..111b9f8c3c 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -1266,6 +1266,15 @@
         "litellm_provider": "bedrock",
         "mode": "completion"
     },
+    "anthropic.claude-3-sonnet-20240229-v1:0": {
+        "max_tokens": 200000, 
+        "max_input_tokens": 200000,
+        "max_output_tokens": 4096,
+        "input_cost_per_token": 0.000003,
+        "output_cost_per_token": 0.000015,
+        "litellm_provider": "bedrock",
+        "mode": "chat"
+    },
     "anthropic.claude-v1": {
         "max_tokens": 100000, 
         "max_output_tokens": 8191,