Feature/nvidia nim integration

contributing/samples/hello_world_nvidia/README.md

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+# Using NVIDIA Models with ADK and LiteLLM
+
+This example demonstrates how to use NVIDIA NIM (NVIDIA Inference Microservices) models with ADK through LiteLLM integration.
+
+For comprehensive information about using NVIDIA models with LiteLLM, refer to the [official LiteLLM documentation](https://github.com/BerriAI/litellm/blob/main/docs/my-website/docs/providers/nvidia_nim.md).
+
+## Setup
+
+### 1. Get an NVIDIA NIM API Key
+Use the following procedure to get an NVIDIA NIM API key.
+
+
+1. Sign up at [NVIDIA AI Foundation](https://www.nvidia.com/en-us/ai-data-science/cloud/)
+2. Navigate to API section and generate an API key
+3. Copy your API key
+
+### 2. Install LiteLLM
+
+Install LiteLLM by running the following code.
+
+
+
+```bash
+pip install litellm
+```
+
+
+## Using NVIDIA Models in ADK
+
+### Environment Variables
+
+Set the required environment variables:
+
+```bash
+export NVIDIA_NIM_API_KEY="your-nvidia-api-key"
+export NVIDIA_NIM_API_BASE="https://integrate.api.nvidia.com/v1/"  # Optional
+```
+
+### Code Examples
+
+#### Basic Agent Creation
+
+```python
+from google.adk import Agent
+from google.adk.models.lite_llm import LiteLlm
+
+# Create agent with NVIDIA NIM model
+agent = Agent(
+    model=LiteLlm(model="nvidia_nim/meta/llama3-8b-instruct"),
+    name="nvidia_agent",
+    instruction="You are a helpful assistant.",
+    description="Agent using NVIDIA model",
+)
+```
+
+#### Available Models
+
+All NVIDIA NIM models are supported. Use the `nvidia_nim/` prefix:
+
+```python
+# Examples of available models
+models = [
+    "nvidia_nim/meta/llama3-8b-instruct",
+    "nvidia_nim/meta/llama3-70b-instruct", 
+    "nvidia_nim/microsoft/phi-3-medium-4k-instruct",
+    "nvidia_nim/mistralai/mistral-7b-instruct",
+    "nvidia_nim/google/gemma-7b",
+    "nvidia_nim/nvidia/nemotron-4-340b-instruct",
+    # ... and many more
+]
+```
+
+## Integration Details
+
+ADK uses LiteLLM as a wrapper to access NVIDIA NIM models. The integration:
+
+1. **Model Format**: Uses `nvidia_nim/<organization>/<model-name>` format
+2. **Authentication**: Requires `NVIDIA_NIM_API_KEY` environment variable
+3. **Base URL**: Optional `NVIDIA_NIM_API_BASE` for custom endpoints
+4. **Compatibility**: Works with all ADK features (tools, sessions, etc.)
+5. **Supported Endpoints**: `/chat/completions`, `/completions`, `/embeddings` 

contributing/samples/hello_world_nvidia/__init__.py

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+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+from . import agent 

contributing/samples/hello_world_nvidia/agent.py

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+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import random
+
+from google.adk import Agent
+from google.adk.models.lite_llm import LiteLlm
+
+
+def roll_die(sides: int) -> int:
+  """Roll a die and return the rolled result.
+
+  Args:
+    sides: The integer number of sides the die has.
+
+  Returns:
+    An integer of the result of rolling the die.
+  """
+  return random.randint(1, sides)
+
+
+def check_prime(nums: list[int]) -> str:
+  """Check if a given list of numbers are prime.
+
+  Args:
+    nums: The list of numbers to check.
+
+  Returns:
+    A str indicating which number is prime.
+  """
+  primes = set()
+  for number in nums:
+    if number <= 1:
+      continue
+    is_prime = True
+    for i in range(2, int(number**0.5) + 1):
+      if number % i == 0:
+        is_prime = False
+        break
+    if is_prime:
+      primes.add(number)
+  return (
+      "No prime numbers found."
+      if not primes
+      else f"{', '.join(str(num) for num in primes)} are prime numbers."
+  )
+
+
+root_agent = Agent(
+    model=LiteLlm(model="nvidia_nim/meta/llama3-8b-instruct"),
+    name="hello_world_nvidia_nim_agent",
+    description=(
+        "hello world agent powered by NVIDIA NIM that can roll a dice of 8 sides and check prime"
+        " numbers."
+    ),
+    instruction="""
+      You are a helpful assistant powered by NVIDIA AI models through NVIDIA NIM.
+      You roll dice and answer questions about the outcome of the dice rolls.
+      You can roll dice of different sizes.
+      You can use multiple tools in parallel by calling functions in parallel(in one request and in one round).
+      It is ok to discuss previous dice rolls, and comment on the dice rolls.
+      When you are asked to roll a die, you must call the roll_die tool with the number of sides. Be sure to pass in an integer. Do not pass in a string.
+      You should never roll a die on your own.
+      When checking prime numbers, call the check_prime tool with a list of integers. Be sure to pass in a list of integers. You should never pass in a string.
+      You should not check prime numbers before calling the tool.
+      When you are asked to roll a die and check prime numbers, you should always make the following two function calls:
+      1. You should first call the roll_die tool to get a roll. Wait for the function response before calling the check_prime tool.
+      2. After you get the function response from roll_die tool, you should call the check_prime tool with the roll_die result.
+        2.1 If user asks you to check primes based on previous rolls, make sure you include the previous rolls in the list.
+      3. When you respond, you must include the roll_die result from step 1.
+      You should always perform the previous 3 steps when asking for a roll and checking prime numbers.
+      You should not rely on the previous history on prime results.
+    """,
+    tools=[
+        roll_die,
+        check_prime,
+    ],
+) 

contributing/samples/hello_world_nvidia/main.py

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+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import asyncio
+import os
+import time
+
+import agent
+from dotenv import load_dotenv
+from google.adk import Runner
+from google.adk.artifacts import InMemoryArtifactService
+from google.adk.cli.utils import logs
+from google.adk.sessions import InMemorySessionService
+from google.adk.sessions import Session
+from google.genai import types
+
+load_dotenv(override=True)
+logs.log_to_tmp_folder()
+
+
+async def main():
+  # Check for NVIDIA NIM API key
+  if not os.environ.get("NVIDIA_NIM_API_KEY"):
+    print(" Your NVIDIA_NIM_API_KEY is not set. Set it before you continue by running the following code:")
+    print(" export NVIDIA_NIM_API_KEY='your-nvidia-api-key'")
+    return
+
+  app_name = 'nvidia_nim_app'
+  user_id_1 = 'user1'
+  session_service = InMemorySessionService()
+  artifact_service = InMemoryArtifactService()
+  runner = Runner(
+      app_name=app_name,
+      agent=agent.root_agent,
+      artifact_service=artifact_service,
+      session_service=session_service,
+  )
+  session_11 = await session_service.create_session(
+      app_name=app_name, user_id=user_id_1
+  )
+
+  async def run_prompt(session: Session, new_message: str):
+    content = types.Content(
+        role='user', parts=[types.Part.from_text(text=new_message)]
+    )
+    print('** User says:', content.model_dump(exclude_none=True))
+    async for event in runner.run_async(
+        user_id=user_id_1,
+        session_id=session.id,
+        new_message=content,
+    ):
+      if event.content.parts and event.content.parts[0].text:
+        print(f'** {event.author}: {event.content.parts[0].text}')
+
+  start_time = time.time()
+  print('Start time:', start_time)
+  print('------------------------------------')
+  print('Testing NVIDIA NIM integration with ADK')
+  print('Model: nvidia_nim/meta/llama3-8b-instruct')
+  print('------------------------------------')
+  await run_prompt(session_11, 'Hi, introduce yourself.')
+  await run_prompt(
+      session_11,
+      'Run the following request 5 times: roll a die with 20 sides and check'
+      'if the result is prime',
+  )
+  end_time = time.time()
+  print('------------------------------------')
+  print('End time:', end_time)
+  print('Total time:', end_time - start_time)
+
+
+if __name__ == '__main__':
+  asyncio.run(main())