Merge pull request #4788 from BerriAI/litellm_ai21_jamba

feat(bedrock_httpx.py): add ai21 jamba instruct as bedrock model

litellm/llms/anthropic.py

@@ -895,7 +895,7 @@ class AnthropicChatCompletion(BaseLLM):
             ):  # if function call - fake the streaming (need complete blocks for output parsing in openai format)
                 print_verbose("makes anthropic streaming POST request")
                 data["stream"] = stream
-                response = requests.post(
+                response = client.post(
                     api_base,
                     headers=headers,
                     data=json.dumps(data),

litellm/llms/bedrock_httpx.py

@@ -75,6 +75,7 @@ BEDROCK_CONVERSE_MODELS = [
     "anthropic.claude-v2:1",
     "anthropic.claude-v1",
     "anthropic.claude-instant-v1",
+    "ai21.jamba-instruct-v1:0",
 ]
 
 
@@ -195,13 +196,39 @@ async def make_call(
         if client is None:
             client = _get_async_httpx_client()  # Create a new client if none provided
 
-        response = await client.post(api_base, headers=headers, data=data, stream=True)
+        response = await client.post(
+            api_base,
+            headers=headers,
+            data=data,
+            stream=True if "ai21" not in api_base else False,
+        )
 
         if response.status_code != 200:
             raise BedrockError(status_code=response.status_code, message=response.text)
 
+        if "ai21" in api_base:
+            aws_bedrock_process_response = BedrockConverseLLM()
+            model_response: (
+                ModelResponse
+            ) = aws_bedrock_process_response.process_response(
+                model=model,
+                response=response,
+                model_response=litellm.ModelResponse(),
+                stream=True,
+                logging_obj=logging_obj,
+                optional_params={},
+                api_key="",
+                data=data,
+                messages=messages,
+                print_verbose=litellm.print_verbose,
+                encoding=litellm.encoding,
+            )  # type: ignore
+            completion_stream: Any = MockResponseIterator(model_response=model_response)
+        else:
             decoder = AWSEventStreamDecoder(model=model)
-        completion_stream = decoder.aiter_bytes(response.aiter_bytes(chunk_size=1024))
+            completion_stream = decoder.aiter_bytes(
+                response.aiter_bytes(chunk_size=1024)
+            )
 
         # LOGGING
         logging_obj.post_call(
@@ -233,11 +260,33 @@ def make_sync_call(
     if client is None:
         client = _get_httpx_client()  # Create a new client if none provided
 
-    response = client.post(api_base, headers=headers, data=data, stream=True)
+    response = client.post(
+        api_base,
+        headers=headers,
+        data=data,
+        stream=True if "ai21" not in api_base else False,
+    )
 
     if response.status_code != 200:
         raise BedrockError(status_code=response.status_code, message=response.read())
 
+    if "ai21" in api_base:
+        aws_bedrock_process_response = BedrockConverseLLM()
+        model_response: ModelResponse = aws_bedrock_process_response.process_response(
+            model=model,
+            response=response,
+            model_response=litellm.ModelResponse(),
+            stream=True,
+            logging_obj=logging_obj,
+            optional_params={},
+            api_key="",
+            data=data,
+            messages=messages,
+            print_verbose=litellm.print_verbose,
+            encoding=litellm.encoding,
+        )  # type: ignore
+        completion_stream: Any = MockResponseIterator(model_response=model_response)
+    else:
         decoder = AWSEventStreamDecoder(model=model)
         completion_stream = decoder.iter_bytes(response.iter_bytes(chunk_size=1024))
 
@@ -1348,7 +1397,7 @@ class BedrockConverseLLM(BaseLLM):
         response: Union[requests.Response, httpx.Response],
         model_response: ModelResponse,
         stream: bool,
-        logging_obj: Logging,
+        logging_obj: Optional[Logging],
         optional_params: dict,
         api_key: str,
         data: Union[dict, str],
@@ -1358,6 +1407,7 @@ class BedrockConverseLLM(BaseLLM):
     ) -> Union[ModelResponse, CustomStreamWrapper]:
 
         ## LOGGING
+        if logging_obj is not None:
             logging_obj.post_call(
                 input=messages,
                 api_key=api_key,
@@ -1900,7 +1950,7 @@ class BedrockConverseLLM(BaseLLM):
         if acompletion:
             if isinstance(client, HTTPHandler):
                 client = None
-            if stream is True and provider != "ai21":
+            if stream is True:
                 return self.async_streaming(
                     model=model,
                     messages=messages,
@@ -1937,7 +1987,7 @@ class BedrockConverseLLM(BaseLLM):
                 client=client,
             )  # type: ignore
 
-        if (stream is not None and stream is True) and provider != "ai21":
+        if stream is not None and stream is True:
 
             streaming_response = CustomStreamWrapper(
                 completion_stream=None,
@@ -1981,7 +2031,7 @@ class BedrockConverseLLM(BaseLLM):
             model=model,
             response=response,
             model_response=model_response,
-            stream=stream,
+            stream=stream if isinstance(stream, bool) else False,
             logging_obj=logging_obj,
             optional_params=optional_params,
             api_key="",
@@ -2168,3 +2218,49 @@ class AWSEventStreamDecoder:
                 return None
 
             return chunk.decode()  # type: ignore[no-any-return]
+
+
+class MockResponseIterator:  # for returning ai21 streaming responses
+    def __init__(self, model_response):
+        self.model_response = model_response
+        self.is_done = False
+
+    # Sync iterator
+    def __iter__(self):
+        return self
+
+    def _chunk_parser(self, chunk_data: ModelResponse) -> GenericStreamingChunk:
+
+        try:
+            chunk_usage: litellm.Usage = getattr(chunk_data, "usage")
+            processed_chunk = GenericStreamingChunk(
+                text=chunk_data.choices[0].message.content or "",  # type: ignore
+                tool_use=None,
+                is_finished=True,
+                finish_reason=chunk_data.choices[0].finish_reason,  # type: ignore
+                usage=ConverseTokenUsageBlock(
+                    inputTokens=chunk_usage.prompt_tokens,
+                    outputTokens=chunk_usage.completion_tokens,
+                    totalTokens=chunk_usage.total_tokens,
+                ),
+                index=0,
+            )
+            return processed_chunk
+        except Exception:
+            raise ValueError(f"Failed to decode chunk: {chunk_data}")
+
+    def __next__(self):
+        if self.is_done:
+            raise StopIteration
+        self.is_done = True
+        return self._chunk_parser(self.model_response)
+
+    # Async iterator
+    def __aiter__(self):
+        return self
+
+    async def __anext__(self):
+        if self.is_done:
+            raise StopAsyncIteration
+        self.is_done = True
+        return self._chunk_parser(self.model_response)

litellm/model_prices_and_context_window_backup.json

@@ -2803,6 +2803,16 @@
         "litellm_provider": "bedrock",
         "mode": "chat"
     },
+    "ai21.jamba-instruct-v1:0": {
+        "max_tokens": 4096,
+        "max_input_tokens": 70000,
+        "max_output_tokens": 4096,
+        "input_cost_per_token": 0.0000005,
+        "output_cost_per_token": 0.0000007,
+        "litellm_provider": "bedrock",
+        "mode": "chat",
+        "supports_system_messages": true
+    },
     "amazon.titan-text-lite-v1": {
         "max_tokens": 4000, 
         "max_input_tokens": 42000,

litellm/proxy/_new_secret_config.yaml

@@ -1,5 +1,13 @@
 model_list:
   - model_name: bad-azure-model
     litellm_params:
-      model: gpt-4
+      model: azure/chatgpt-v-2
-      request_timeout: 1
+      azure_ad_token: ""
+      api_base: os.environ/AZURE_API_BASE
+
+  - model_name: good-openai-model
+    litellm_params:
+      model: gpt-3.5-turbo
+
+litellm_settings:
+  fallbacks: [{"bad-azure-model": ["good-openai-model"]}]

litellm/proxy/proxy_config.yaml

@@ -4,5 +4,7 @@ model_list:
       model: fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct
       api_key: "os.environ/FIREWORKS_AI_API_KEY"
 
+router_settings:
+  enable_tag_filtering: True # 👈 Key Change
 general_settings: 
   master_key: sk-1234

litellm/tests/test_streaming.py

@@ -1312,22 +1312,22 @@ async def test_completion_replicate_llama3_streaming(sync_mode):
 #         pytest.fail(f"Error occurred: {e}")
 
 
-@pytest.mark.parametrize("sync_mode", [True])  # False
+@pytest.mark.parametrize("sync_mode", [True, False])  #
 @pytest.mark.parametrize(
-    "model",
+    "model, region",
     [
-        "bedrock/cohere.command-r-plus-v1:0",
+        ["bedrock/ai21.jamba-instruct-v1:0", "us-east-1"],
-        "anthropic.claude-3-sonnet-20240229-v1:0",
+        ["bedrock/cohere.command-r-plus-v1:0", None],
-        "anthropic.claude-instant-v1",
+        ["anthropic.claude-3-sonnet-20240229-v1:0", None],
-        "bedrock/ai21.j2-mid",
+        ["anthropic.claude-instant-v1", None],
-        "mistral.mistral-7b-instruct-v0:2",
+        ["mistral.mistral-7b-instruct-v0:2", None],
-        "bedrock/amazon.titan-tg1-large",
+        ["bedrock/amazon.titan-tg1-large", None],
-        "meta.llama3-8b-instruct-v1:0",
+        ["meta.llama3-8b-instruct-v1:0", None],
-        "cohere.command-text-v14",
+        ["cohere.command-text-v14", None],
     ],
 )
 @pytest.mark.asyncio
-async def test_bedrock_httpx_streaming(sync_mode, model):
+async def test_bedrock_httpx_streaming(sync_mode, model, region):
     try:
         litellm.set_verbose = True
         if sync_mode:
@@ -1337,6 +1337,7 @@ async def test_bedrock_httpx_streaming(sync_mode, model):
                 messages=messages,
                 max_tokens=10,  # type: ignore
                 stream=True,
+                aws_region_name=region,
             )
             complete_response = ""
             # Add any assertions here to check the response
@@ -1358,6 +1359,7 @@ async def test_bedrock_httpx_streaming(sync_mode, model):
                 messages=messages,
                 max_tokens=100,  # type: ignore
                 stream=True,
+                aws_region_name=region,
             )
             complete_response = ""
             # Add any assertions here to check the response

model_prices_and_context_window.json

@@ -2803,6 +2803,16 @@
         "litellm_provider": "bedrock",
         "mode": "chat"
     },
+    "ai21.jamba-instruct-v1:0": {
+        "max_tokens": 4096,
+        "max_input_tokens": 70000,
+        "max_output_tokens": 4096,
+        "input_cost_per_token": 0.0000005,
+        "output_cost_per_token": 0.0000007,
+        "litellm_provider": "bedrock",
+        "mode": "chat",
+        "supports_system_messages": true
+    },
     "amazon.titan-text-lite-v1": {
         "max_tokens": 4000, 
         "max_input_tokens": 42000,