fix(proxy_server.py): fix get model info when litellm_model_id is set + move model analytics to free (#7886)

* fix(proxy_server.py): fix get model info when litellm_model_id is set

Fixes https://github.com/BerriAI/litellm/issues/7873

* test(test_models.py): add test to ensure get model info on specific deployment has same value as all model info

Fixes https://github.com/BerriAI/litellm/issues/7873

* fix(usage.tsx): make model analytics free

Fixes @iqballx's feedback

* fix(fix(invoke_handler.py):-fix-bedrock-error-chunk-parsing): return correct bedrock status code and error message if chunk in stream

Improves bedrock stream error handling

* fix(proxy_server.py): fix linting errors

* test(test_auth_checks.py): remove redundant test

* fix(proxy_server.py): fix linting errors

* test: fix flaky test

* test: fix test

litellm/llms/bedrock/chat/invoke_handler.py

@@ -894,7 +894,7 @@ class BedrockLLM(BaseAWSLLM):
 
             if response.status_code != 200:
                 raise BedrockError(
-                    status_code=response.status_code, message=response.read()
+                    status_code=response.status_code, message=str(response.read())
                 )
 
             decoder = AWSEventStreamDecoder(model=model)
@@ -1247,7 +1247,23 @@ class AWSEventStreamDecoder:
         parsed_response = self.parser.parse(response_dict, get_response_stream_shape())
 
         if response_dict["status_code"] != 200:
-            raise ValueError(f"Bad response code, expected 200: {response_dict}")
+            decoded_body = response_dict["body"].decode()
+            if isinstance(decoded_body, dict):
+                error_message = decoded_body.get("message")
+            elif isinstance(decoded_body, str):
+                error_message = decoded_body
+            else:
+                error_message = ""
+            exception_status = response_dict["headers"].get(":exception-type")
+            error_message = exception_status + " " + error_message
+            raise BedrockError(
+                status_code=response_dict["status_code"],
+                message=(
+                    json.dumps(error_message)
+                    if isinstance(error_message, dict)
+                    else error_message
+                ),
+            )
         if "chunk" in parsed_response:
             chunk = parsed_response.get("chunk")
             if not chunk:

litellm/llms/huggingface/chat/handler.py

@@ -432,6 +432,7 @@ class Huggingface(BaseLLM):
         embed_url: str,
     ) -> dict:
         data: Dict = {}
+
         ## TRANSFORMATION ##
         if "sentence-transformers" in model:
             if len(input) == 0:

litellm/proxy/_new_secret_config.yaml

@@ -6,8 +6,7 @@ model_list:
       api_base: https://exampleopenaiendpoint-production.up.railway.app
   - model_name: openai-o1
     litellm_params:
-      model: openai/random_sleep
-      api_key: sk-1234
+      model: bedrock/anthropic.claude-3-sonnet-20240229-v1:0
       api_base: http://0.0.0.0:8090
       timeout: 2
       num_retries: 0

litellm/proxy/proxy_server.py

@@ -274,6 +274,7 @@ from litellm.types.llms.anthropic import (
     AnthropicResponseUsageBlock,
 )
 from litellm.types.llms.openai import HttpxBinaryResponseContent
+from litellm.types.router import DeploymentTypedDict
 from litellm.types.router import ModelInfo as RouterModelInfo
 from litellm.types.router import RouterGeneralSettings, updateDeployment
 from litellm.types.utils import CustomHuggingfaceTokenizer
@@ -6510,6 +6511,47 @@ async def model_metrics_exceptions(
     return {"data": response, "exception_types": list(exception_types)}
 
 
+def _get_proxy_model_info(model: dict) -> dict:
+    # provided model_info in config.yaml
+    model_info = model.get("model_info", {})
+
+    # read litellm model_prices_and_context_window.json to get the following:
+    # input_cost_per_token, output_cost_per_token, max_tokens
+    litellm_model_info = get_litellm_model_info(model=model)
+
+    # 2nd pass on the model, try seeing if we can find model in litellm model_cost map
+    if litellm_model_info == {}:
+        # use litellm_param model_name to get model_info
+        litellm_params = model.get("litellm_params", {})
+        litellm_model = litellm_params.get("model", None)
+        try:
+            litellm_model_info = litellm.get_model_info(model=litellm_model)
+        except Exception:
+            litellm_model_info = {}
+    # 3rd pass on the model, try seeing if we can find model but without the "/" in model cost map
+    if litellm_model_info == {}:
+        # use litellm_param model_name to get model_info
+        litellm_params = model.get("litellm_params", {})
+        litellm_model = litellm_params.get("model", None)
+        split_model = litellm_model.split("/")
+        if len(split_model) > 0:
+            litellm_model = split_model[-1]
+        try:
+            litellm_model_info = litellm.get_model_info(
+                model=litellm_model, custom_llm_provider=split_model[0]
+            )
+        except Exception:
+            litellm_model_info = {}
+    for k, v in litellm_model_info.items():
+        if k not in model_info:
+            model_info[k] = v
+    model["model_info"] = model_info
+    # don't return the llm credentials
+    model = remove_sensitive_info_from_deployment(deployment_dict=model)
+
+    return model
+
+
 @router.get(
     "/model/info",
     tags=["model management"],
@@ -6598,16 +6640,15 @@ async def model_info_v1(  # noqa: PLR0915
         deployment_info = llm_router.get_deployment(model_id=litellm_model_id)
         if deployment_info is None:
             raise HTTPException(
-                status_code=404,
+                status_code=400,
                 detail={
                     "error": f"Model id = {litellm_model_id} not found on litellm proxy"
                 },
             )
-        _deployment_info_dict = deployment_info.model_dump()
-        _deployment_info_dict = remove_sensitive_info_from_deployment(
-            deployment_dict=_deployment_info_dict
+        _deployment_info_dict = _get_proxy_model_info(
+            model=deployment_info.model_dump(exclude_none=True)
         )
-        return {"data": _deployment_info_dict}
+        return {"data": [_deployment_info_dict]}
 
     all_models: List[dict] = []
     model_access_groups: Dict[str, List[str]] = defaultdict(list)
@@ -6647,42 +6688,7 @@ async def model_info_v1(  # noqa: PLR0915
             all_models = []
 
     for model in all_models:
-        # provided model_info in config.yaml
-        model_info = model.get("model_info", {})
-
-        # read litellm model_prices_and_context_window.json to get the following:
-        # input_cost_per_token, output_cost_per_token, max_tokens
-        litellm_model_info = get_litellm_model_info(model=model)
-
-        # 2nd pass on the model, try seeing if we can find model in litellm model_cost map
-        if litellm_model_info == {}:
-            # use litellm_param model_name to get model_info
-            litellm_params = model.get("litellm_params", {})
-            litellm_model = litellm_params.get("model", None)
-            try:
-                litellm_model_info = litellm.get_model_info(model=litellm_model)
-            except Exception:
-                litellm_model_info = {}
-        # 3rd pass on the model, try seeing if we can find model but without the "/" in model cost map
-        if litellm_model_info == {}:
-            # use litellm_param model_name to get model_info
-            litellm_params = model.get("litellm_params", {})
-            litellm_model = litellm_params.get("model", None)
-            split_model = litellm_model.split("/")
-            if len(split_model) > 0:
-                litellm_model = split_model[-1]
-            try:
-                litellm_model_info = litellm.get_model_info(
-                    model=litellm_model, custom_llm_provider=split_model[0]
-                )
-            except Exception:
-                litellm_model_info = {}
-        for k, v in litellm_model_info.items():
-            if k not in model_info:
-                model_info[k] = v
-        model["model_info"] = model_info
-        # don't return the llm credentials
-        model = remove_sensitive_info_from_deployment(deployment_dict=model)
+        model = _get_proxy_model_info(model=model)
 
     verbose_proxy_logger.debug("all_models: %s", all_models)
     return {"data": all_models}

tests/llm_translation/test_bedrock_completion.py

@@ -2429,3 +2429,33 @@ async def test_bedrock_image_url_sync_client():
         except Exception as e:
             print(e)
         mock_post.assert_called_once()
+
+
+def test_bedrock_error_handling_streaming():
+    from litellm.llms.bedrock.chat.invoke_handler import (
+        AWSEventStreamDecoder,
+        BedrockError,
+    )
+    from unittest.mock import patch, Mock
+
+    event = Mock()
+    event.to_response_dict = Mock(
+        return_value={
+            "status_code": 400,
+            "headers": {
+                ":exception-type": "serviceUnavailableException",
+                ":content-type": "application/json",
+                ":message-type": "exception",
+            },
+            "body": b'{"message":"Bedrock is unable to process your request."}',
+        }
+    )
+
+    decoder = AWSEventStreamDecoder(
+        model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0"
+    )
+    with pytest.raises(Exception) as e:
+        decoder._parse_message_from_event(event)
+    assert isinstance(e.value, BedrockError)
+    assert "Bedrock is unable to process your request." in e.value.message
+    assert e.value.status_code == 400

tests/local_testing/test_embedding.py

@@ -642,19 +642,27 @@ def tgi_mock_post(*args, **kwargs):
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
 
 
-@pytest.mark.parametrize("sync_mode", [True, False])
 @pytest.mark.asyncio
-async def test_hf_embedding_sentence_sim(sync_mode):
+@patch("litellm.llms.huggingface.chat.handler.async_get_hf_task_embedding_for_model")
+@patch("litellm.llms.huggingface.chat.handler.get_hf_task_embedding_for_model")
+@pytest.mark.parametrize("sync_mode", [True, False])
+async def test_hf_embedding_sentence_sim(
+    mock_async_get_hf_task_embedding_for_model,
+    mock_get_hf_task_embedding_for_model,
+    sync_mode,
+):
     try:
         # huggingface/microsoft/codebert-base
         # huggingface/facebook/bart-large
+        mock_get_hf_task_embedding_for_model.return_value = "sentence-similarity"
+        mock_async_get_hf_task_embedding_for_model.return_value = "sentence-similarity"
         if sync_mode is True:
             client = HTTPHandler(concurrent_limit=1)
         else:
             client = AsyncHTTPHandler(concurrent_limit=1)
         with patch.object(client, "post", side_effect=tgi_mock_post) as mock_client:
             data = {
-                "model": "huggingface/TaylorAI/bge-micro-v2",
+                "model": "huggingface/sentence-transformers/TaylorAI/bge-micro-v2",
                 "input": ["good morning from litellm", "this is another item"],
                 "client": client,
             }

tests/test_models.py

@@ -88,10 +88,13 @@ async def add_models(session, model_id="123", model_name="azure-gpt-3.5"):
         return response_json
 
 
-async def get_model_info(session, key):
+async def get_model_info(session, key, litellm_model_id=None):
     """
     Make sure only models user has access to are returned
     """
+    if litellm_model_id:
+        url = f"http://0.0.0.0:4000/model/info?litellm_model_id={litellm_model_id}"
+    else:
         url = "http://0.0.0.0:4000/model/info"
     headers = {
         "Authorization": f"Bearer {key}",
@@ -148,6 +151,35 @@ async def test_get_models():
             assert m == "gpt-4"
 
 
+@pytest.mark.asyncio
+async def test_get_specific_model():
+    """
+    Return specific model info
+
+    Ensure value of model_info is same as on `/model/info` (no id set)
+    """
+    async with aiohttp.ClientSession() as session:
+        key_gen = await generate_key(session=session, models=["gpt-4"])
+        key = key_gen["key"]
+        response = await get_model_info(session=session, key=key)
+        models = [m["model_name"] for m in response["data"]]
+        model_specific_info = None
+        for idx, m in enumerate(models):
+            assert m == "gpt-4"
+            litellm_model_id = response["data"][idx]["model_info"]["id"]
+            model_specific_info = response["data"][idx]
+        assert litellm_model_id is not None
+        response = await get_model_info(
+            session=session, key=key, litellm_model_id=litellm_model_id
+        )
+        assert response["data"][0]["model_info"]["id"] == litellm_model_id
+        assert (
+            response["data"][0] == model_specific_info
+        ), "Model info is not the same. Got={}, Expected={}".format(
+            response["data"][0], model_specific_info
+        )
+
+
 async def delete_model(session, model_id="123"):
     """
     Make sure only models user has access to are returned

ui/litellm-dashboard/src/components/usage.tsx

@@ -554,9 +554,7 @@ const UsagePage: React.FC<UsagePageProps> = ({
               </Col>
               <Col numColSpan={2}>
               <Card className="mb-2">
-                <Title>✨ Spend by Provider</Title>
-                {
-                  premiumUser ? (
+                <Title>Spend by Provider</Title>
                 <>
                     <Grid numItems={2}>
                   <Col numColSpan={1}>
@@ -592,17 +590,6 @@ const UsagePage: React.FC<UsagePageProps> = ({
                   </Col>
                 </Grid>
                     </>
-                  ) : (
-                    <div>
-                    <p className="mb-2 text-gray-500 italic text-[12px]">Upgrade to use this feature</p>
-                    <Button variant="primary" className="mb-2">
-                          <a href="https://forms.gle/W3U4PZpJGFHWtHyA9" target="_blank">
-                            Get Free Trial
-                          </a>
-                        </Button>
-                    </div>
-                  )
-                }
                 
               </Card>
             </Col>
@@ -643,8 +630,6 @@ const UsagePage: React.FC<UsagePageProps> = ({
 
                 </Card>
 
-                {
-                  premiumUser ? ( 
                 <>
                     {globalActivityPerModel.map((globalActivity, index) => (
                 <Card key={index}>
@@ -678,68 +663,6 @@ const UsagePage: React.FC<UsagePageProps> = ({
                 </Card>
               ))}
                     </>             
-                  ) : 
-                  <>
-                  {globalActivityPerModel && globalActivityPerModel.length > 0 &&
-                    globalActivityPerModel.slice(0, 1).map((globalActivity, index) => (
-                      <Card key={index}>
-                        <Title>✨ Activity by Model</Title>
-                        <p className="mb-2 text-gray-500 italic text-[12px]">Upgrade to see analytics for all models</p>
-                        <Button variant="primary" className="mb-2">
-                          <a href="https://forms.gle/W3U4PZpJGFHWtHyA9" target="_blank">
-                            Get Free Trial
-                          </a>
-                        </Button>
-                        <Card>
-                        <Title>{globalActivity.model}</Title>
-                        <Grid numItems={2}>
-                          <Col>
-                            <Subtitle
-                              style={{
-                                fontSize: "15px",
-                                fontWeight: "normal",
-                                color: "#535452",
-                              }}
-                            >
-                              API Requests {valueFormatterNumbers(globalActivity.sum_api_requests)}
-                            </Subtitle>
-                            <AreaChart
-                              className="h-40"
-                              data={globalActivity.daily_data}
-                              index="date"
-                              colors={['cyan']}
-                              categories={['api_requests']}
-                              valueFormatter={valueFormatterNumbers}
-                              onValueChange={(v) => console.log(v)}
-                            />
-                          </Col>
-                          <Col>
-                            <Subtitle
-                              style={{
-                                fontSize: "15px",
-                                fontWeight: "normal",
-                                color: "#535452",
-                              }}
-                            >
-                              Tokens {valueFormatterNumbers(globalActivity.sum_total_tokens)}
-                            </Subtitle>
-                            <BarChart
-                              className="h-40"
-                              data={globalActivity.daily_data}
-                              index="date"
-                              colors={['cyan']}
-                              valueFormatter={valueFormatterNumbers}
-                              categories={['total_tokens']}
-                              onValueChange={(v) => console.log(v)}
-                            />
-                          </Col>
-                          
-                        </Grid>
-                        </Card>
-                      </Card>
-                    ))}
-                </>
-                }              
               </Grid>
             </TabPanel>
             </TabPanels>