Merge branch 'main' into litellm_ssl_caching_fix

docs/my-website/docs/providers/groq.md

@@ -48,6 +48,8 @@ We support ALL Groq models, just set `groq/` as a prefix when sending completion
 
 | Model Name               | Function Call                                                                                                                                                      |
 |--------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| llama3-8b-8192 | `completion(model="groq/llama3-8b-8192", messages)` | 
+| llama3-70b-8192 | `completion(model="groq/llama3-70b-8192", messages)` | 
 | llama2-70b-4096 | `completion(model="groq/llama2-70b-4096", messages)` | 
 | mixtral-8x7b-32768 | `completion(model="groq/mixtral-8x7b-32768", messages)` |
 | gemma-7b-it | `completion(model="groq/gemma-7b-it", messages)` |  

litellm/__init__.py

@@ -16,11 +16,24 @@ dotenv.load_dotenv()
 if set_verbose == True:
     _turn_on_debug()
 #############################################
+### Callbacks /Logging / Success / Failure Handlers ###
 input_callback: List[Union[str, Callable]] = []
 success_callback: List[Union[str, Callable]] = []
 failure_callback: List[Union[str, Callable]] = []
 service_callback: List[Union[str, Callable]] = []
 callbacks: List[Callable] = []
+_langfuse_default_tags: Optional[
+    List[
+        Literal[
+            "user_api_key_alias",
+            "user_api_key_user_id",
+            "user_api_key_user_email",
+            "user_api_key_team_alias",
+            "semantic-similarity",
+            "proxy_base_url",
+        ]
+    ]
+] = None
 _async_input_callback: List[Callable] = (
     []
 )  # internal variable - async custom callbacks are routed here.
@@ -32,6 +45,8 @@ _async_failure_callback: List[Callable] = (
 )  # internal variable - async custom callbacks are routed here.
 pre_call_rules: List[Callable] = []
 post_call_rules: List[Callable] = []
+## end of callbacks #############
+
 email: Optional[str] = (
     None  # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
 )

litellm/caching.py

@@ -1281,7 +1281,7 @@ class DualCache(BaseCache):
                         self.in_memory_cache.set_cache(key, redis_result[key], **kwargs)
 
                 for key, value in redis_result.items():
-                    result[sublist_keys.index(key)] = value
+                    result[keys.index(key)] = value
 
             print_verbose(f"async batch get cache: cache result: {result}")
             return result
@@ -1331,7 +1331,6 @@ class DualCache(BaseCache):
                     keys, **kwargs
                 )
 
-                print_verbose(f"in_memory_result: {in_memory_result}")
                 if in_memory_result is not None:
                     result = in_memory_result
             if None in result and self.redis_cache is not None and local_only == False:
@@ -1355,9 +1354,9 @@ class DualCache(BaseCache):
                                 key, redis_result[key], **kwargs
                             )
                 for key, value in redis_result.items():
-                    result[sublist_keys.index(key)] = value
+                    index = keys.index(key)
+                    result[index] = value
 
-            print_verbose(f"async batch get cache: cache result: {result}")
             return result
         except Exception as e:
             traceback.print_exc()

litellm/integrations/langfuse.py

@@ -280,13 +280,13 @@ class LangFuseLogger:
             clean_metadata = {}
             if isinstance(metadata, dict):
                 for key, value in metadata.items():
-                    # generate langfuse tags
+
-                    if key in [
+                    # generate langfuse tags - Default Tags sent to Langfuse from LiteLLM Proxy
-                        "user_api_key",
+                    if (
-                        "user_api_key_user_id",
+                        litellm._langfuse_default_tags is not None
-                        "user_api_key_team_id",
+                        and isinstance(litellm._langfuse_default_tags, list)
-                        "semantic-similarity",
+                        and key in litellm._langfuse_default_tags
-                    ]:
+                    ):
                         tags.append(f"{key}:{value}")
 
                     # clean litellm metadata before logging
@@ -300,6 +300,15 @@ class LangFuseLogger:
                     else:
                         clean_metadata[key] = value
 
+            if (
+                litellm._langfuse_default_tags is not None
+                and isinstance(litellm._langfuse_default_tags, list)
+                and "proxy_base_url" in litellm._langfuse_default_tags
+            ):
+                proxy_base_url = os.environ.get("PROXY_BASE_URL", None)
+                if proxy_base_url is not None:
+                    tags.append(f"proxy_base_url:{proxy_base_url}")
+
             api_base = litellm_params.get("api_base", None)
             if api_base:
                 clean_metadata["api_base"] = api_base

litellm/integrations/prometheus_services.py

@@ -151,7 +151,6 @@ class PrometheusServicesLogger:
         if self.mock_testing:
             self.mock_testing_success_calls += 1
 
-        print(f"LOGS SUCCESSFUL CALL TO PROMETHEUS - payload={payload}")
         if payload.service.value in self.payload_to_prometheus_map:
             prom_objects = self.payload_to_prometheus_map[payload.service.value]
             for obj in prom_objects:

litellm/llms/anthropic.py

@@ -258,8 +258,9 @@ class AnthropicChatCompletion(BaseLLM):
         self.async_handler = AsyncHTTPHandler(
             timeout=httpx.Timeout(timeout=600.0, connect=5.0)
         )
+        data["stream"] = True
         response = await self.async_handler.post(
-            api_base, headers=headers, data=json.dumps(data)
+            api_base, headers=headers, data=json.dumps(data), stream=True
         )
 
         if response.status_code != 200:

litellm/llms/custom_httpx/http_handler.py

@@ -41,13 +41,12 @@ class AsyncHTTPHandler:
         data: Optional[Union[dict, str]] = None,  # type: ignore
         params: Optional[dict] = None,
         headers: Optional[dict] = None,
+        stream: bool = False,
     ):
-        response = await self.client.post(
+        req = self.client.build_request(
-            url,
+            "POST", url, data=data, params=params, headers=headers  # type: ignore
-            data=data,  # type: ignore
-            params=params,
-            headers=headers,
         )
+        response = await self.client.send(req, stream=stream)
         return response
 
     def __del__(self) -> None:

litellm/model_prices_and_context_window_backup.json

@@ -735,6 +735,26 @@
         "mode": "chat",
         "supports_function_calling": true
     },
+    "groq/llama3-8b-8192": {
+        "max_tokens": 8192,
+        "max_input_tokens": 8192,
+        "max_output_tokens": 8192,
+        "input_cost_per_token": 0.00000010,
+        "output_cost_per_token": 0.00000010,
+        "litellm_provider": "groq",
+        "mode": "chat",
+        "supports_function_calling": true
+    },
+    "groq/llama3-70b-8192": {
+        "max_tokens": 8192,
+        "max_input_tokens": 8192,
+        "max_output_tokens": 8192,
+        "input_cost_per_token": 0.00000064,
+        "output_cost_per_token": 0.00000080,
+        "litellm_provider": "groq",
+        "mode": "chat",
+        "supports_function_calling": true
+    },
     "groq/mixtral-8x7b-32768": {
         "max_tokens": 32768,
         "max_input_tokens": 32768,

litellm/proxy/_new_secret_config.yaml

@@ -7,6 +7,14 @@ model_list:
     # api_base: http://0.0.0.0:8080
     stream_timeout: 0.001
     rpm: 10
+- model_name: fake-openai-endpoint
+  litellm_params:
+    model: openai/my-fake-model-2
+    api_key: my-fake-key
+    api_base: https://openai-function-calling-workers.tasslexyz.workers.dev/
+    # api_base: http://0.0.0.0:8080
+    stream_timeout: 0.001
+    rpm: 10
 - litellm_params:
       model: azure/chatgpt-v-2
       api_base: os.environ/AZURE_API_BASE

litellm/proxy/_types.py

@@ -792,6 +792,7 @@ class LiteLLM_VerificationTokenView(LiteLLM_VerificationToken):
     """
 
     team_spend: Optional[float] = None
+    team_alias: Optional[str] = None
     team_tpm_limit: Optional[int] = None
     team_rpm_limit: Optional[int] = None
     team_max_budget: Optional[float] = None

litellm/proxy/proxy_config.yaml

@@ -13,4 +13,8 @@ model_list:
 general_settings:
   store_model_in_db: true
   master_key: sk-1234
-  alerting: ["slack"]
+  alerting: ["slack"]
+
+litellm_settings:
+  success_callback: ["langfuse"]
+  _langfuse_default_tags: ["user_api_key_alias", "user_api_key_user_id", "user_api_key_user_email", "user_api_key_team_alias", "semantic-similarity", "proxy_base_url"]

litellm/proxy/proxy_server.py

@@ -3361,6 +3361,9 @@ async def completion(
         data["metadata"]["user_api_key_team_id"] = getattr(
             user_api_key_dict, "team_id", None
         )
+        data["metadata"]["user_api_key_team_alias"] = getattr(
+            user_api_key_dict, "team_alias", None
+        )
         _headers = dict(request.headers)
         _headers.pop(
             "authorization", None
@@ -3562,6 +3565,9 @@ async def chat_completion(
         data["metadata"]["user_api_key_team_id"] = getattr(
             user_api_key_dict, "team_id", None
         )
+        data["metadata"]["user_api_key_team_alias"] = getattr(
+            user_api_key_dict, "team_alias", None
+        )
         data["metadata"]["user_api_key_metadata"] = user_api_key_dict.metadata
         _headers = dict(request.headers)
         _headers.pop(
@@ -3793,6 +3799,9 @@ async def embeddings(
         data["metadata"]["user_api_key_team_id"] = getattr(
             user_api_key_dict, "team_id", None
         )
+        data["metadata"]["user_api_key_team_alias"] = getattr(
+            user_api_key_dict, "team_alias", None
+        )
         data["metadata"]["endpoint"] = str(request.url)
 
         ### TEAM-SPECIFIC PARAMS ###
@@ -3971,6 +3980,9 @@ async def image_generation(
         data["metadata"]["user_api_key_team_id"] = getattr(
             user_api_key_dict, "team_id", None
         )
+        data["metadata"]["user_api_key_team_alias"] = getattr(
+            user_api_key_dict, "team_alias", None
+        )
         data["metadata"]["endpoint"] = str(request.url)
 
         ### TEAM-SPECIFIC PARAMS ###
@@ -4127,6 +4139,9 @@ async def audio_transcriptions(
         data["metadata"]["user_api_key_team_id"] = getattr(
             user_api_key_dict, "team_id", None
         )
+        data["metadata"]["user_api_key_team_alias"] = getattr(
+            user_api_key_dict, "team_alias", None
+        )
         data["metadata"]["endpoint"] = str(request.url)
         data["metadata"]["file_name"] = file.filename
 
@@ -4302,6 +4317,9 @@ async def moderations(
         data["metadata"]["user_api_key_team_id"] = getattr(
             user_api_key_dict, "team_id", None
         )
+        data["metadata"]["user_api_key_team_alias"] = getattr(
+            user_api_key_dict, "team_alias", None
+        )
         data["metadata"]["endpoint"] = str(request.url)
 
         ### TEAM-SPECIFIC PARAMS ###

litellm/proxy/utils.py

@@ -1186,6 +1186,7 @@ class PrismaClient:
                     t.rpm_limit AS team_rpm_limit,
                     t.models AS team_models,
                     t.blocked AS team_blocked,
+                    t.team_alias AS team_alias,
                     m.aliases as team_model_aliases
                     FROM "LiteLLM_VerificationToken" AS v
                     LEFT JOIN "LiteLLM_TeamTable" AS t ON v.team_id = t.team_id

litellm/router_strategy/lowest_tpm_rpm_v2.py

@@ -187,6 +187,7 @@ class LowestTPMLoggingHandler_v2(CustomLogger):
                             request=httpx.Request(method="tpm_rpm_limits", url="https://github.com/BerriAI/litellm"),  # type: ignore
                         ),
                     )
+
             return deployment
         except Exception as e:
             if isinstance(e, litellm.RateLimitError):

litellm/tests/test_caching.py

@@ -33,6 +33,51 @@ def generate_random_word(length=4):
 messages = [{"role": "user", "content": "who is ishaan 5222"}]
 
 
+@pytest.mark.asyncio
+async def test_dual_cache_async_batch_get_cache():
+    """
+    Unit testing for Dual Cache async_batch_get_cache()
+    - 2 item query
+    - in_memory result has a partial hit (1/2)
+    - hit redis for the other -> expect to return None
+    - expect result = [in_memory_result, None]
+    """
+    from litellm.caching import DualCache, InMemoryCache, RedisCache
+
+    in_memory_cache = InMemoryCache()
+    redis_cache = RedisCache()  # get credentials from environment
+    dual_cache = DualCache(in_memory_cache=in_memory_cache, redis_cache=redis_cache)
+
+    in_memory_cache.set_cache(key="test_value", value="hello world")
+
+    result = await dual_cache.async_batch_get_cache(keys=["test_value", "test_value_2"])
+
+    assert result[0] == "hello world"
+    assert result[1] == None
+
+
+def test_dual_cache_batch_get_cache():
+    """
+    Unit testing for Dual Cache batch_get_cache()
+    - 2 item query
+    - in_memory result has a partial hit (1/2)
+    - hit redis for the other -> expect to return None
+    - expect result = [in_memory_result, None]
+    """
+    from litellm.caching import DualCache, InMemoryCache, RedisCache
+
+    in_memory_cache = InMemoryCache()
+    redis_cache = RedisCache()  # get credentials from environment
+    dual_cache = DualCache(in_memory_cache=in_memory_cache, redis_cache=redis_cache)
+
+    in_memory_cache.set_cache(key="test_value", value="hello world")
+
+    result = dual_cache.batch_get_cache(keys=["test_value", "test_value_2"])
+
+    assert result[0] == "hello world"
+    assert result[1] == None
+
+
 # @pytest.mark.skip(reason="")
 def test_caching_dynamic_args():  # test in memory cache
     try:

litellm/tests/test_function_calling.py

@@ -221,6 +221,9 @@ def test_parallel_function_call_stream():
 # test_parallel_function_call_stream()
 
 
+@pytest.mark.skip(
+    reason="Flaky test. Groq function calling is not reliable for ci/cd testing."
+)
 def test_groq_parallel_function_call():
     litellm.set_verbose = True
     try:

litellm/tests/test_tpm_rpm_routing_v2.py

@@ -23,6 +23,10 @@ from litellm.caching import DualCache
 
 ### UNIT TESTS FOR TPM/RPM ROUTING ###
 
+"""
+- Given 2 deployments, make sure it's shuffling deployments correctly.
+"""
+
 
 def test_tpm_rpm_updated():
     test_cache = DualCache()

model_prices_and_context_window.json

@@ -735,6 +735,26 @@
         "mode": "chat",
         "supports_function_calling": true
     },
+    "groq/llama3-8b-8192": {
+        "max_tokens": 8192,
+        "max_input_tokens": 8192,
+        "max_output_tokens": 8192,
+        "input_cost_per_token": 0.00000010,
+        "output_cost_per_token": 0.00000010,
+        "litellm_provider": "groq",
+        "mode": "chat",
+        "supports_function_calling": true
+    },
+    "groq/llama3-70b-8192": {
+        "max_tokens": 8192,
+        "max_input_tokens": 8192,
+        "max_output_tokens": 8192,
+        "input_cost_per_token": 0.00000064,
+        "output_cost_per_token": 0.00000080,
+        "litellm_provider": "groq",
+        "mode": "chat",
+        "supports_function_calling": true
+    },
     "groq/mixtral-8x7b-32768": {
         "max_tokens": 32768,
         "max_input_tokens": 32768,

proxy_server_config.yaml

@@ -55,6 +55,20 @@ model_list:
       api_base: https://openai-function-calling-workers.tasslexyz.workers.dev/
       stream_timeout: 0.001
       rpm: 1
+  - model_name: fake-openai-endpoint-3
+    litellm_params:
+      model: openai/my-fake-model
+      api_key: my-fake-key
+      api_base: https://openai-function-calling-workers.tasslexyz.workers.dev/
+      stream_timeout: 0.001
+      rpm: 10
+  - model_name: fake-openai-endpoint-3
+    litellm_params:
+      model: openai/my-fake-model-2
+      api_key: my-fake-key
+      api_base: https://openai-function-calling-workers.tasslexyz.workers.dev/
+      stream_timeout: 0.001
+      rpm: 10
   - model_name: "*"
     litellm_params:
       model: openai/*

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "litellm"
-version = "1.35.15"
+version = "1.35.16"
 description = "Library to easily interface with LLM API providers"
 authors = ["BerriAI"]
 license = "MIT"
@@ -80,7 +80,7 @@ requires = ["poetry-core", "wheel"]
 build-backend = "poetry.core.masonry.api"
 
 [tool.commitizen]
-version = "1.35.15"
+version = "1.35.16"
 version_files = [
     "pyproject.toml:^version"
 ]

tests/test_openai_endpoints.py

@@ -102,6 +102,47 @@ async def chat_completion(session, key, model="gpt-4"):
         return await response.json()
 
 
+async def chat_completion_with_headers(session, key, model="gpt-4"):
+    url = "http://0.0.0.0:4000/chat/completions"
+    headers = {
+        "Authorization": f"Bearer {key}",
+        "Content-Type": "application/json",
+    }
+    data = {
+        "model": model,
+        "messages": [
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": "Hello!"},
+        ],
+    }
+
+    async with session.post(url, headers=headers, json=data) as response:
+        status = response.status
+        response_text = await response.text()
+
+        print(response_text)
+        print()
+
+        if status != 200:
+            raise Exception(f"Request did not return a 200 status code: {status}")
+
+        response_header_check(
+            response
+        )  # calling the function to check response headers
+
+        raw_headers = response.raw_headers
+        raw_headers_json = {}
+
+        for (
+            item
+        ) in (
+            response.raw_headers
+        ):  # ((b'date', b'Fri, 19 Apr 2024 21:17:29 GMT'), (), )
+            raw_headers_json[item[0].decode("utf-8")] = item[1].decode("utf-8")
+
+        return raw_headers_json
+
+
 async def completion(session, key):
     url = "http://0.0.0.0:4000/completions"
     headers = {
@@ -222,6 +263,36 @@ async def test_chat_completion_ratelimit():
             pass
 
 
+@pytest.mark.asyncio
+async def test_chat_completion_different_deployments():
+    """
+    - call model group with 2 deployments
+    - make 5 calls
+    - expect 2 unique deployments
+    """
+    async with aiohttp.ClientSession() as session:
+        # key_gen = await generate_key(session=session)
+        key = "sk-1234"
+        results = []
+        for _ in range(5):
+            results.append(
+                await chat_completion_with_headers(
+                    session=session, key=key, model="fake-openai-endpoint-3"
+                )
+            )
+        try:
+            print(f"results: {results}")
+            init_model_id = results[0]["x-litellm-model-id"]
+            deployments_shuffled = False
+            for result in results[1:]:
+                if init_model_id != result["x-litellm-model-id"]:
+                    deployments_shuffled = True
+            if deployments_shuffled == False:
+                pytest.fail("Expected at least 1 shuffled call")
+        except Exception as e:
+            pass
+
+
 @pytest.mark.asyncio
 async def test_chat_completion_old_key():
     """

ui/litellm-dashboard/src/app/page.tsx

@@ -145,6 +145,7 @@ const CreateKeyPage = () => {
               userRole={userRole}
               token={token}
               keys={keys}
+              teams={teams}
               accessToken={accessToken}
               setKeys={setKeys}
             />

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

@@ -1,15 +1,16 @@
 import React, { useState, useEffect } from "react";
 import { Button, Modal, Form, Input, message, Select, InputNumber } from "antd";
-import { Button as Button2 } from "@tremor/react";
+import { Button as Button2, Text } from "@tremor/react";
 import { userCreateCall, modelAvailableCall } from "./networking";
 const { Option } = Select;
 
 interface CreateuserProps {
   userID: string;
   accessToken: string;
+  teams: any[] | null;
 }
 
-const Createuser: React.FC<CreateuserProps> = ({ userID, accessToken }) => {
+const Createuser: React.FC<CreateuserProps> = ({ userID, accessToken, teams }) => {
   const [form] = Form.useForm();
   const [isModalVisible, setIsModalVisible] = useState(false);
   const [apiuser, setApiuser] = useState<string | null>(null);
@@ -59,7 +60,7 @@ const Createuser: React.FC<CreateuserProps> = ({ userID, accessToken }) => {
       message.info("Making API Call");
       setIsModalVisible(true);
       console.log("formValues in create user:", formValues);
-      const response = await userCreateCall(accessToken, userID, formValues);
+      const response = await userCreateCall(accessToken, null, formValues);
       console.log("user create Response:", response);
       setApiuser(response["key"]);
       message.success("API user Created");
@@ -73,16 +74,18 @@ const Createuser: React.FC<CreateuserProps> = ({ userID, accessToken }) => {
   return (
     <div>
       <Button2 className="mx-auto" onClick={() => setIsModalVisible(true)}>
-        + Create New User
+        + Invite User
       </Button2>
       <Modal
-        title="Create User"
+        title="Invite User"
         visible={isModalVisible}
         width={800}
         footer={null}
         onOk={handleOk}
         onCancel={handleCancel}
       >
+        <Text className="mb-1">Invite a user to login to the Admin UI and create Keys</Text>
+        <Text className="mb-6"><b>Note: SSO Setup Required for this</b></Text>
         <Form
           form={form}
           onFinish={handleCreate}
@@ -90,38 +93,27 @@ const Createuser: React.FC<CreateuserProps> = ({ userID, accessToken }) => {
           wrapperCol={{ span: 16 }}
           labelAlign="left"
         >
-          <Form.Item label="User ID" name="user_id">
+          <Form.Item label="User Email" name="user_email">
-            <Input placeholder="Enter User ID" />
+            <Input placeholder="Enter User Email" />
           </Form.Item>
           <Form.Item label="Team ID" name="team_id">
-            <Input placeholder="ai_team" />
+          <Select
-          </Form.Item>
+              placeholder="Select Team ID"
-          <Form.Item label="Models" name="models">
-            <Select
-              mode="multiple"
-              placeholder="Select models"
               style={{ width: "100%" }}
             >
-              {userModels.map((model) => (
+              {teams ? (
-                <Option key={model} value={model}>
+                teams.map((team: any) => (
-                  {model}
+                  <Option key={team.team_id} value={team.team_id}>
+                    {team.team_alias}
+                  </Option>
+                ))
+              ) : (
+                <Option key="default" value={null}>
+                  Default Team
                 </Option>
-              ))}
+              )}
             </Select>
           </Form.Item>
-
-          <Form.Item label="Max Budget (USD)" name="max_budget">
-            <InputNumber step={0.01} precision={2} width={200} />
-          </Form.Item>
-          <Form.Item label="Tokens per minute Limit (TPM)" name="tpm_limit">
-            <InputNumber step={1} width={400} />
-          </Form.Item>
-          <Form.Item label="Requests per minute Limit (RPM)" name="rpm_limit">
-            <InputNumber step={1} width={400} />
-          </Form.Item>
-          <Form.Item label="Duration (eg: 30s, 30h, 30d)" name="duration">
-            <Input />
-          </Form.Item>
           <Form.Item label="Metadata" name="metadata">
             <Input.TextArea rows={4} placeholder="Enter metadata as JSON" />
           </Form.Item>
@@ -132,23 +124,19 @@ const Createuser: React.FC<CreateuserProps> = ({ userID, accessToken }) => {
       </Modal>
       {apiuser && (
         <Modal
-          title="Save Your User"
+          title="User Created Successfully"
           visible={isModalVisible}
           onOk={handleOk}
           onCancel={handleCancel}
           footer={null}
         >
           <p>
-            Please save this secret user somewhere safe and accessible. For
+            User has been created to access your proxy. Please Ask them to Log In.
-            security reasons, <b>you will not be able to view it again</b>{" "}
-            through your LiteLLM account. If you lose this secret user, you will
-            need to generate a new one.
-          </p>
-          <p>
-            {apiuser != null
-              ? `API user: ${apiuser}`
-              : "User being created, this might take 30s"}
           </p>
+          <br></br>
+
+          <p><b>Note: This Feature is only supported through SSO on the Admin UI</b></p>
+          
         </Modal>
       )}
     </div>

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

@@ -158,7 +158,7 @@ export const keyCreateCall = async (
 
 export const userCreateCall = async (
   accessToken: string,
-  userID: string,
+  userID: string | null,
   formValues: Record<string, any> // Assuming formValues is an object
 ) => {
   try {

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

@@ -36,6 +36,7 @@ interface ViewUserDashboardProps {
   keys: any[] | null;
   userRole: string | null;
   userID: string | null;
+  teams: any[] | null;
   setKeys: React.Dispatch<React.SetStateAction<Object[] | null>>;
 }
 
@@ -45,6 +46,7 @@ const ViewUserDashboard: React.FC<ViewUserDashboardProps> = ({
   keys,
   userRole,
   userID,
+  teams,
   setKeys,
 }) => {
   const [userData, setUserData] = useState<null | any[]>(null);
@@ -151,7 +153,7 @@ const ViewUserDashboard: React.FC<ViewUserDashboardProps> = ({
   return (
     <div style={{ width: "100%" }}>
       <Grid className="gap-2 p-2 h-[75vh] w-full mt-8">
-        <CreateUser userID={userID} accessToken={accessToken} />
+        <CreateUser userID={userID} accessToken={accessToken} teams={teams}/>
         <Card className="w-full mx-auto flex-auto overflow-y-auto max-h-[50vh] mb-4">
           <TabGroup>
             <TabList variant="line" defaultValue="1">