Merge pull request #1618 from BerriAI/litellm_sagemaker_cost_tracking_fixes

fix(utils.py): fix sagemaker cost tracking for streaming

.circleci/config.yml

@@ -147,6 +147,9 @@ jobs:
               -e AZURE_API_KEY=$AZURE_API_KEY \
               -e AZURE_FRANCE_API_KEY=$AZURE_FRANCE_API_KEY \
               -e AZURE_EUROPE_API_KEY=$AZURE_EUROPE_API_KEY \
+              -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
+              -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
+              -e AWS_REGION_NAME=$AWS_REGION_NAME \
               --name my-app \
               -v $(pwd)/proxy_server_config.yaml:/app/config.yaml \
               my-app:latest \

litellm/llms/sagemaker.py

@@ -34,22 +34,35 @@ class TokenIterator:
         self.byte_iterator = iter(stream)
         self.buffer = io.BytesIO()
         self.read_pos = 0
+        self.end_of_data = False
 
     def __iter__(self):
         return self
 
     def __next__(self):
-        while True:
-            self.buffer.seek(self.read_pos)
-            line = self.buffer.readline()
-            if line and line[-1] == ord("\n"):
-                self.read_pos += len(line) + 1
-                full_line = line[:-1].decode("utf-8")
-                line_data = json.loads(full_line.lstrip("data:").rstrip("/n"))
-                return line_data["token"]["text"]
-            chunk = next(self.byte_iterator)
-            self.buffer.seek(0, io.SEEK_END)
-            self.buffer.write(chunk["PayloadPart"]["Bytes"])
+        try:
+            while True:
+                self.buffer.seek(self.read_pos)
+                line = self.buffer.readline()
+                if line and line[-1] == ord("\n"):
+                    response_obj = {"text": "", "is_finished": False}
+                    self.read_pos += len(line) + 1
+                    full_line = line[:-1].decode("utf-8")
+                    line_data = json.loads(full_line.lstrip("data:").rstrip("/n"))
+                    if line_data.get("generated_text", None) is not None:
+                        self.end_of_data = True
+                        response_obj["is_finished"] = True
+                    response_obj["text"] = line_data["token"]["text"]
+                    return response_obj
+                chunk = next(self.byte_iterator)
+                self.buffer.seek(0, io.SEEK_END)
+                self.buffer.write(chunk["PayloadPart"]["Bytes"])
+        except StopIteration as e:
+            if self.end_of_data == True:
+                raise e  # Re-raise StopIteration
+            else:
+                self.end_of_data = True
+                return "data: [DONE]"
 
 
 class SagemakerConfig:

litellm/main.py

@@ -15,7 +15,7 @@ import dotenv, traceback, random, asyncio, time, contextvars
 from copy import deepcopy
 import httpx
 import litellm
-
+from ._logging import verbose_logger
 from litellm import (  # type: ignore
     client,
     exception_type,
@@ -274,14 +274,10 @@ async def acompletion(
         else:
             # Call the synchronous function using run_in_executor
             response = await loop.run_in_executor(None, func_with_context)  # type: ignore
-        # if kwargs.get("stream", False):  # return an async generator
-        #     return _async_streaming(
-        #         response=response,
-        #         model=model,
-        #         custom_llm_provider=custom_llm_provider,
-        #         args=args,
-        #     )
-        # else:
+        if isinstance(response, CustomStreamWrapper):
+            response.set_logging_event_loop(
+                loop=loop
+            )  # sets the logging event loop if the user does sync streaming (e.g. on proxy for sagemaker calls)
         return response
     except Exception as e:
         custom_llm_provider = custom_llm_provider or "openai"
@@ -1520,11 +1516,6 @@ def completion(
             if (
                 "stream" in optional_params and optional_params["stream"] == True
             ):  ## [BETA]
-                # sagemaker does not support streaming as of now so we're faking streaming:
-                # https://discuss.huggingface.co/t/streaming-output-text-when-deploying-on-sagemaker/39611
-                # "SageMaker is currently not supporting streaming responses."
-
-                # fake streaming for sagemaker
                 print_verbose(f"ENTERS SAGEMAKER CUSTOMSTREAMWRAPPER")
                 from .llms.sagemaker import TokenIterator
 
@@ -1535,6 +1526,12 @@ def completion(
                     custom_llm_provider="sagemaker",
                     logging_obj=logging,
                 )
+                ## LOGGING
+                logging.post_call(
+                    input=messages,
+                    api_key=None,
+                    original_response=response,
+                )
                 return response
 
             ## RESPONSE OBJECT
@@ -3348,6 +3345,16 @@ def stream_chunk_builder(
     chunks: list, messages: Optional[list] = None, start_time=None, end_time=None
 ):
     model_response = litellm.ModelResponse()
+    ### SORT CHUNKS BASED ON CREATED ORDER ##
+    print_verbose("Goes into checking if chunk has hiddden created at param")
+    if chunks[0]._hidden_params.get("created_at", None):
+        print_verbose("Chunks have a created at hidden param")
+        # Sort chunks based on created_at in ascending order
+        chunks = sorted(
+            chunks, key=lambda x: x._hidden_params.get("created_at", float("inf"))
+        )
+        print_verbose("Chunks sorted")
+
     # set hidden params from chunk to model_response
     if model_response is not None and hasattr(model_response, "_hidden_params"):
         model_response._hidden_params = chunks[0].get("_hidden_params", {})

litellm/proxy/proxy_server.py

@@ -718,6 +718,9 @@ async def update_database(
                     existing_spend_obj = await custom_db_client.get_data(
                         key=id, table_name="user"
                     )
+                verbose_proxy_logger.debug(
+                    f"Updating existing_spend_obj: {existing_spend_obj}"
+                )
                 if existing_spend_obj is None:
                     existing_spend = 0
                     existing_spend_obj = LiteLLM_UserTable(

litellm/proxy/utils.py

@@ -467,7 +467,9 @@ class PrismaClient:
                     hashed_token = token
                     if token.startswith("sk-"):
                         hashed_token = self.hash_token(token=token)
-                print_verbose("PrismaClient: find_unique")
+                    verbose_proxy_logger.debug(
+                        f"PrismaClient: find_unique for token: {hashed_token}"
+                    )
                 if query_type == "find_unique":
                     response = await self.db.litellm_verificationtoken.find_unique(
                         where={"token": hashed_token}
@@ -774,7 +776,6 @@ class PrismaClient:
                 Batch write update queries
                 """
                 batcher = self.db.batch_()
-                verbose_proxy_logger.debug(f"data list for user table: {data_list}")
                 for idx, user in enumerate(data_list):
                     try:
                         data_json = self.jsonify_object(data=user.model_dump())

litellm/tests/test_custom_callback_input.py

@@ -556,6 +556,47 @@ async def test_async_chat_bedrock_stream():
 
 # asyncio.run(test_async_chat_bedrock_stream())
 
+
+## Test Sagemaker + Async
+@pytest.mark.asyncio
+async def test_async_chat_sagemaker_stream():
+    try:
+        customHandler = CompletionCustomHandler()
+        litellm.callbacks = [customHandler]
+        response = await litellm.acompletion(
+            model="sagemaker/berri-benchmarking-Llama-2-70b-chat-hf-4",
+            messages=[{"role": "user", "content": "Hi 👋 - i'm async sagemaker"}],
+        )
+        # test streaming
+        response = await litellm.acompletion(
+            model="sagemaker/berri-benchmarking-Llama-2-70b-chat-hf-4",
+            messages=[{"role": "user", "content": "Hi 👋 - i'm async sagemaker"}],
+            stream=True,
+        )
+        print(f"response: {response}")
+        async for chunk in response:
+            print(f"chunk: {chunk}")
+            continue
+        ## test failure callback
+        try:
+            response = await litellm.acompletion(
+                model="sagemaker/berri-benchmarking-Llama-2-70b-chat-hf-4",
+                messages=[{"role": "user", "content": "Hi 👋 - i'm async sagemaker"}],
+                aws_region_name="my-bad-key",
+                stream=True,
+            )
+            async for chunk in response:
+                continue
+        except:
+            pass
+        time.sleep(1)
+        print(f"customHandler.errors: {customHandler.errors}")
+        assert len(customHandler.errors) == 0
+        litellm.callbacks = []
+    except Exception as e:
+        pytest.fail(f"An exception occurred: {str(e)}")
+
+
 # Text Completion
 
 

litellm/tests/test_custom_logger.py

@@ -206,12 +206,12 @@ def test_azure_completion_stream():
         # checks if the model response available in the async + stream callbacks is equal to the received response
         customHandler2 = MyCustomHandler()
         litellm.callbacks = [customHandler2]
-        litellm.set_verbose = False
+        litellm.set_verbose = True
         messages = [
             {"role": "system", "content": "You are a helpful assistant."},
             {
                 "role": "user",
-                "content": "write 1 sentence about litellm being amazing",
+                "content": f"write 1 sentence about litellm being amazing {time.time()}",
             },
         ]
         complete_streaming_response = ""

litellm/tests/test_streaming.py

@@ -847,9 +847,13 @@ def test_sagemaker_weird_response():
             logging_obj=logging_obj,
         )
         complete_response = ""
-        for chunk in response:
-            print(chunk)
-            complete_response += chunk["choices"][0]["delta"]["content"]
+        for idx, chunk in enumerate(response):
+            # print
+            chunk, finished = streaming_format_tests(idx, chunk)
+            has_finish_reason = finished
+            complete_response += chunk
+            if finished:
+                break
         assert len(complete_response) > 0
     except Exception as e:
         pytest.fail(f"An exception occurred - {str(e)}")
@@ -872,41 +876,53 @@ async def test_sagemaker_streaming_async():
         )
 
         # Add any assertions here to check the response
+        print(response)
         complete_response = ""
+        has_finish_reason = False
+        # Add any assertions here to check the response
+        idx = 0
         async for chunk in response:
-            complete_response += chunk.choices[0].delta.content or ""
-        print(f"complete_response: {complete_response}")
-        assert len(complete_response) > 0
+            # print
+            chunk, finished = streaming_format_tests(idx, chunk)
+            has_finish_reason = finished
+            complete_response += chunk
+            if finished:
+                break
+            idx += 1
+        if has_finish_reason is False:
+            raise Exception("finish reason not set for last chunk")
+        if complete_response.strip() == "":
+            raise Exception("Empty response received")
+        print(f"completion_response: {complete_response}")
     except Exception as e:
         pytest.fail(f"An exception occurred - {str(e)}")
 
 
-# def test_completion_sagemaker_stream():
-#     try:
-#         response = completion(
-#             model="sagemaker/jumpstart-dft-meta-textgeneration-llama-2-7b",
-#             messages=messages,
-#             temperature=0.2,
-#             max_tokens=80,
-#             stream=True,
-#         )
-#         complete_response = ""
-#         has_finish_reason = False
-#         # Add any assertions here to check the response
-#         for idx, chunk in enumerate(response):
-#             chunk, finished = streaming_format_tests(idx, chunk)
-#             has_finish_reason = finished
-#             if finished:
-#                 break
-#             complete_response += chunk
-#         if has_finish_reason is False:
-#             raise Exception("finish reason not set for last chunk")
-#         if complete_response.strip() == "":
-#             raise Exception("Empty response received")
-#     except InvalidRequestError as e:
-#         pass
-#     except Exception as e:
-#         pytest.fail(f"Error occurred: {e}")
+def test_completion_sagemaker_stream():
+    try:
+        response = completion(
+            model="sagemaker/berri-benchmarking-Llama-2-70b-chat-hf-4",
+            messages=messages,
+            temperature=0.2,
+            max_tokens=80,
+            stream=True,
+        )
+        complete_response = ""
+        has_finish_reason = False
+        # Add any assertions here to check the response
+        for idx, chunk in enumerate(response):
+            chunk, finished = streaming_format_tests(idx, chunk)
+            has_finish_reason = finished
+            if finished:
+                break
+            complete_response += chunk
+        if has_finish_reason is False:
+            raise Exception("finish reason not set for last chunk")
+        if complete_response.strip() == "":
+            raise Exception("Empty response received")
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+
 
 # test_completion_sagemaker_stream()
 

litellm/utils.py

@@ -1418,7 +1418,9 @@ class Logging:
         """
         Implementing async callbacks, to handle asyncio event loop issues when custom integrations need to use async functions.
         """
-        print_verbose(f"Async success callbacks: {litellm._async_success_callback}")
+        verbose_logger.debug(
+            f"Async success callbacks: {litellm._async_success_callback}"
+        )
         start_time, end_time, result = self._success_handler_helper_fn(
             start_time=start_time, end_time=end_time, result=result, cache_hit=cache_hit
         )
@@ -1427,7 +1429,7 @@ class Logging:
         if self.stream:
             if result.choices[0].finish_reason is not None:  # if it's the last chunk
                 self.streaming_chunks.append(result)
-                # print_verbose(f"final set of received chunks: {self.streaming_chunks}")
+                # verbose_logger.debug(f"final set of received chunks: {self.streaming_chunks}")
                 try:
                     complete_streaming_response = litellm.stream_chunk_builder(
                         self.streaming_chunks,
@@ -1436,14 +1438,16 @@ class Logging:
                         end_time=end_time,
                     )
                 except Exception as e:
-                    print_verbose(
+                    verbose_logger.debug(
                         f"Error occurred building stream chunk: {traceback.format_exc()}"
                     )
                     complete_streaming_response = None
             else:
                 self.streaming_chunks.append(result)
         if complete_streaming_response is not None:
-            print_verbose("Async success callbacks: Got a complete streaming response")
+            verbose_logger.debug(
+                "Async success callbacks: Got a complete streaming response"
+            )
             self.model_call_details[
                 "complete_streaming_response"
             ] = complete_streaming_response
@@ -7152,6 +7156,7 @@ class CustomStreamWrapper:
             "model_id": (_model_info.get("id", None))
         }  # returned as x-litellm-model-id response header in proxy
         self.response_id = None
+        self.logging_loop = None
 
     def __iter__(self):
         return self
@@ -7722,6 +7727,27 @@ class CustomStreamWrapper:
             }
         return ""
 
+    def handle_sagemaker_stream(self, chunk):
+        if "data: [DONE]" in chunk:
+            text = ""
+            is_finished = True
+            finish_reason = "stop"
+            return {
+                "text": text,
+                "is_finished": is_finished,
+                "finish_reason": finish_reason,
+            }
+        elif isinstance(chunk, dict):
+            if chunk["is_finished"] == True:
+                finish_reason = "stop"
+            else:
+                finish_reason = ""
+            return {
+                "text": chunk["text"],
+                "is_finished": chunk["is_finished"],
+                "finish_reason": finish_reason,
+            }
+
     def chunk_creator(self, chunk):
         model_response = ModelResponse(stream=True, model=self.model)
         if self.response_id is not None:
@@ -7729,6 +7755,7 @@ class CustomStreamWrapper:
         else:
             self.response_id = model_response.id
         model_response._hidden_params["custom_llm_provider"] = self.custom_llm_provider
+        model_response._hidden_params["created_at"] = time.time()
         model_response.choices = [StreamingChoices()]
         model_response.choices[0].finish_reason = None
         response_obj = {}
@@ -7847,8 +7874,14 @@ class CustomStreamWrapper:
                     ]
                     self.sent_last_chunk = True
             elif self.custom_llm_provider == "sagemaker":
-                print_verbose(f"ENTERS SAGEMAKER STREAMING for chunk {chunk}")
-                completion_obj["content"] = chunk
+                verbose_logger.debug(f"ENTERS SAGEMAKER STREAMING for chunk {chunk}")
+                response_obj = self.handle_sagemaker_stream(chunk)
+                completion_obj["content"] = response_obj["text"]
+                if response_obj["is_finished"]:
+                    model_response.choices[0].finish_reason = response_obj[
+                        "finish_reason"
+                    ]
+                    self.sent_last_chunk = True
             elif self.custom_llm_provider == "petals":
                 if len(self.completion_stream) == 0:
                     if self.sent_last_chunk:
@@ -8024,6 +8057,27 @@ class CustomStreamWrapper:
                 original_exception=e,
             )
 
+    def set_logging_event_loop(self, loop):
+        self.logging_loop = loop
+
+    async def your_async_function(self):
+        # Your asynchronous code here
+        return "Your asynchronous code is running"
+
+    def run_success_logging_in_thread(self, processed_chunk):
+        # Create an event loop for the new thread
+        ## ASYNC LOGGING
+        if self.logging_loop is not None:
+            future = asyncio.run_coroutine_threadsafe(
+                self.logging_obj.async_success_handler(processed_chunk),
+                loop=self.logging_loop,
+            )
+            result = future.result()
+        else:
+            asyncio.run(self.logging_obj.async_success_handler(processed_chunk))
+        ## SYNC LOGGING
+        self.logging_obj.success_handler(processed_chunk)
+
     ## needs to handle the empty string case (even starting chunk can be an empty string)
     def __next__(self):
         try:
@@ -8042,8 +8096,9 @@ class CustomStreamWrapper:
                         continue
                     ## LOGGING
                     threading.Thread(
-                        target=self.logging_obj.success_handler, args=(response,)
+                        target=self.run_success_logging_in_thread, args=(response,)
                     ).start()  # log response
+
                     # RETURN RESULT
                     return response
         except StopIteration:
@@ -8099,13 +8154,34 @@ class CustomStreamWrapper:
                 raise StopAsyncIteration
             else:  # temporary patch for non-aiohttp async calls
                 # example - boto3 bedrock llms
-                processed_chunk = next(self)
-                asyncio.create_task(
-                    self.logging_obj.async_success_handler(
-                        processed_chunk,
-                    )
-                )
-                return processed_chunk
+                while True:
+                    if isinstance(self.completion_stream, str) or isinstance(
+                        self.completion_stream, bytes
+                    ):
+                        chunk = self.completion_stream
+                    else:
+                        chunk = next(self.completion_stream)
+                    if chunk is not None and chunk != b"":
+                        print_verbose(f"PROCESSED CHUNK PRE CHUNK CREATOR: {chunk}")
+                        processed_chunk = self.chunk_creator(chunk=chunk)
+                        print_verbose(
+                            f"PROCESSED CHUNK POST CHUNK CREATOR: {processed_chunk}"
+                        )
+                        if processed_chunk is None:
+                            continue
+                        ## LOGGING
+                        threading.Thread(
+                            target=self.logging_obj.success_handler,
+                            args=(processed_chunk,),
+                        ).start()  # log processed_chunk
+                        asyncio.create_task(
+                            self.logging_obj.async_success_handler(
+                                processed_chunk,
+                            )
+                        )
+
+                        # RETURN RESULT
+                        return processed_chunk
         except StopAsyncIteration:
             raise
         except StopIteration:

proxy_server_config.yaml

@@ -11,6 +11,10 @@ model_list:
       api_base: https://openai-gpt-4-test-v-1.openai.azure.com/
       api_version: "2023-05-15"
       api_key: os.environ/AZURE_API_KEY # The `os.environ/` prefix tells litellm to read this from the env. See https://docs.litellm.ai/docs/simple_proxy#load-api-keys-from-vault
+  - model_name: sagemaker-completion-model
+    litellm_params:
+      model: sagemaker/berri-benchmarking-Llama-2-70b-chat-hf-4
+      input_cost_per_second: 0.000420  
   - model_name: gpt-4
     litellm_params:
       model: azure/gpt-turbo

tests/test_keys.py

@@ -13,17 +13,21 @@ sys.path.insert(
 import litellm
 
 
-async def generate_key(session, i, budget=None, budget_duration=None):
+async def generate_key(
+    session, i, budget=None, budget_duration=None, models=["azure-models", "gpt-4"]
+):
     url = "http://0.0.0.0:4000/key/generate"
     headers = {"Authorization": "Bearer sk-1234", "Content-Type": "application/json"}
     data = {
-        "models": ["azure-models", "gpt-4"],
+        "models": models,
         "aliases": {"mistral-7b": "gpt-3.5-turbo"},
         "duration": None,
         "max_budget": budget,
         "budget_duration": budget_duration,
     }
 
+    print(f"data: {data}")
+
     async with session.post(url, headers=headers, json=data) as response:
         status = response.status
         response_text = await response.text()
@@ -293,7 +297,7 @@ async def test_key_info_spend_values():
         rounded_response_cost = round(response_cost, 8)
         rounded_key_info_spend = round(key_info["info"]["spend"], 8)
         assert rounded_response_cost == rounded_key_info_spend
-        ## streaming
+        ## streaming - azure
         key_gen = await generate_key(session=session, i=0)
         new_key = key_gen["key"]
         prompt_tokens, completion_tokens = await chat_completion_streaming(
@@ -318,6 +322,41 @@ async def test_key_info_spend_values():
         assert rounded_response_cost == rounded_key_info_spend
 
 
+@pytest.mark.asyncio
+async def test_key_info_spend_values_sagemaker():
+    """
+    Tests the sync streaming loop to ensure spend is correctly calculated.
+    - create key
+    - make completion call
+    - assert cost is expected value
+    """
+    async with aiohttp.ClientSession() as session:
+        ## streaming - sagemaker
+        key_gen = await generate_key(session=session, i=0, models=[])
+        new_key = key_gen["key"]
+        prompt_tokens, completion_tokens = await chat_completion_streaming(
+            session=session, key=new_key, model="sagemaker-completion-model"
+        )
+        # print(f"prompt_tokens: {prompt_tokens}, completion_tokens: {completion_tokens}")
+        # prompt_cost, completion_cost = litellm.cost_per_token(
+        #     model="azure/gpt-35-turbo",
+        #     prompt_tokens=prompt_tokens,
+        #     completion_tokens=completion_tokens,
+        # )
+        # response_cost = prompt_cost + completion_cost
+        await asyncio.sleep(5)  # allow db log to be updated
+        key_info = await get_key_info(
+            session=session, get_key=new_key, call_key=new_key
+        )
+        # print(
+        #     f"response_cost: {response_cost}; key_info spend: {key_info['info']['spend']}"
+        # )
+        # rounded_response_cost = round(response_cost, 8)
+        rounded_key_info_spend = round(key_info["info"]["spend"], 8)
+        assert rounded_key_info_spend > 0
+        # assert rounded_response_cost == rounded_key_info_spend
+
+
 @pytest.mark.asyncio
 async def test_key_with_budgets():
     """
@@ -337,7 +376,7 @@ async def test_key_with_budgets():
         print(f"hashed_token: {hashed_token}")
         key_info = await get_key_info(session=session, get_key=key, call_key=key)
         reset_at_init_value = key_info["info"]["budget_reset_at"]
-        await asyncio.sleep(15)
+        await asyncio.sleep(30)
         key_info = await get_key_info(session=session, get_key=key, call_key=key)
         reset_at_new_value = key_info["info"]["budget_reset_at"]
         assert reset_at_init_value != reset_at_new_value