feat(models): Enable multi-provider support for Claude and LiteLLM

Merges: https://github.com/google/adk-python/pull/2810

Co-authored-by: Xuan Yang <xygoogle@google.com>
PiperOrigin-RevId: 836706608

src/google/adk/models/__init__.py

@@ -33,3 +33,23 @@ __all__ = [
 LLMRegistry.register(Gemini)
 LLMRegistry.register(Gemma)
 LLMRegistry.register(ApigeeLlm)
+
+# Optionally register Claude if anthropic package is installed
+try:
+  from .anthropic_llm import Claude
+
+  LLMRegistry.register(Claude)
+  __all__.append('Claude')
+except Exception:
+  # Claude support requires: pip install google-adk[extensions]
+  pass
+
+# Optionally register LiteLlm if litellm package is installed
+try:
+  from .lite_llm import LiteLlm
+
+  LLMRegistry.register(LiteLlm)
+  __all__.append('LiteLlm')
+except Exception:
+  # LiteLLM support requires: pip install google-adk[extensions]
+  pass

src/google/adk/models/lite_llm.py

@@ -1388,11 +1388,19 @@ class LiteLlm(BaseLlm):
   def supported_models(cls) -> list[str]:
     """Provides the list of supported models.
 
-    LiteLlm supports all models supported by litellm. We do not keep track of
-    these models here. So we return an empty list.
+    This registers common provider prefixes. LiteLlm can handle many more,
+    but these patterns activate the integration for the most common use cases.
+    See https://docs.litellm.ai/docs/providers for a full list.
 
     Returns:
       A list of supported models.
     """
 
-    return []
+    return [
+        # For OpenAI models (e.g., "openai/gpt-4o")
+        r"openai/.*",
+        # For Groq models via Groq API (e.g., "groq/llama3-70b-8192")
+        r"groq/.*",
+        # For Anthropic models (e.g., "anthropic/claude-3-opus-20240229")
+        r"anthropic/.*",
+    ]

src/google/adk/models/registry.py

@@ -99,4 +99,26 @@ class LLMRegistry:
       if re.compile(regex).fullmatch(model):
         return llm_class
 
-    raise ValueError(f'Model {model} not found.')
+    # Provide helpful error messages for known patterns
+    error_msg = f'Model {model} not found.'
+
+    # Check if it matches known patterns that require optional dependencies
+    if re.match(r'^claude-', model):
+      error_msg += (
+          '\n\nClaude models require the anthropic package.'
+          '\nInstall it with: pip install google-adk[extensions]'
+          '\nOr: pip install anthropic>=0.43.0'
+      )
+    elif '/' in model:
+      # Any model with provider/model format likely needs LiteLLM
+      error_msg += (
+          '\n\nProvider-style models (e.g., "provider/model-name") require'
+          ' the litellm package.'
+          '\nInstall it with: pip install google-adk[extensions]'
+          '\nOr: pip install litellm>=1.75.5'
+          '\n\nSupported providers include: openai, groq, anthropic, and 100+'
+          ' others.'
+          '\nSee https://docs.litellm.ai/docs/providers for a full list.'
+      )
+
+    raise ValueError(error_msg)

tests/unittests/agents/test_llm_agent_fields.py

@@ -22,6 +22,9 @@ from google.adk.agents.callback_context import CallbackContext
 from google.adk.agents.invocation_context import InvocationContext
 from google.adk.agents.llm_agent import LlmAgent
 from google.adk.agents.readonly_context import ReadonlyContext
+from google.adk.models.anthropic_llm import Claude
+from google.adk.models.google_llm import Gemini
+from google.adk.models.lite_llm import LiteLlm
 from google.adk.models.llm_request import LlmRequest
 from google.adk.models.registry import LLMRegistry
 from google.adk.sessions.in_memory_session_service import InMemorySessionService
@@ -411,3 +414,47 @@ class TestCanonicalTools:
     assert len(tools) == 1
     assert tools[0].name == 'vertex_ai_search'
     assert tools[0].__class__.__name__ == 'VertexAiSearchTool'
+
+
+# Tests for multi-provider model support via string model names
+@pytest.mark.parametrize(
+    'model_name',
+    [
+        'gemini-1.5-flash',
+        'gemini-2.0-flash-exp',
+    ],
+)
+def test_agent_with_gemini_string_model(model_name):
+  """Test that Agent accepts Gemini model strings and resolves to Gemini."""
+  agent = LlmAgent(name='test_agent', model=model_name)
+  assert isinstance(agent.canonical_model, Gemini)
+  assert agent.canonical_model.model == model_name
+
+
+@pytest.mark.parametrize(
+    'model_name',
+    [
+        'claude-3-5-sonnet-v2@20241022',
+        'claude-sonnet-4@20250514',
+    ],
+)
+def test_agent_with_claude_string_model(model_name):
+  """Test that Agent accepts Claude model strings and resolves to Claude."""
+  agent = LlmAgent(name='test_agent', model=model_name)
+  assert isinstance(agent.canonical_model, Claude)
+  assert agent.canonical_model.model == model_name
+
+
+@pytest.mark.parametrize(
+    'model_name',
+    [
+        'openai/gpt-4o',
+        'groq/llama3-70b-8192',
+        'anthropic/claude-3-opus-20240229',
+    ],
+)
+def test_agent_with_litellm_string_model(model_name):
+  """Test that Agent accepts LiteLLM provider strings."""
+  agent = LlmAgent(name='test_agent', model=model_name)
+  assert isinstance(agent.canonical_model, LiteLlm)
+  assert agent.canonical_model.model == model_name

tests/unittests/models/test_models.py

@@ -15,7 +15,7 @@
 from google.adk import models
 from google.adk.models.anthropic_llm import Claude
 from google.adk.models.google_llm import Gemini
-from google.adk.models.registry import LLMRegistry
+from google.adk.models.lite_llm import LiteLlm
 import pytest
 
 
@@ -34,6 +34,7 @@ import pytest
     ],
 )
 def test_match_gemini_family(model_name):
+  """Test that Gemini models are resolved correctly."""
   assert models.LLMRegistry.resolve(model_name) is Gemini
 
 
@@ -51,12 +52,63 @@ def test_match_gemini_family(model_name):
     ],
 )
 def test_match_claude_family(model_name):
-  LLMRegistry.register(Claude)
-
+  """Test that Claude models are resolved correctly."""
   assert models.LLMRegistry.resolve(model_name) is Claude
 
 
+@pytest.mark.parametrize(
+    'model_name',
+    [
+        'openai/gpt-4o',
+        'openai/gpt-4o-mini',
+        'groq/llama3-70b-8192',
+        'groq/mixtral-8x7b-32768',
+        'anthropic/claude-3-opus-20240229',
+        'anthropic/claude-3-5-sonnet-20241022',
+    ],
+)
+def test_match_litellm_family(model_name):
+  """Test that LiteLLM models are resolved correctly."""
+  assert models.LLMRegistry.resolve(model_name) is LiteLlm
+
+
 def test_non_exist_model():
   with pytest.raises(ValueError) as e_info:
     models.LLMRegistry.resolve('non-exist-model')
   assert 'Model non-exist-model not found.' in str(e_info.value)
+
+
+def test_helpful_error_for_claude_without_extensions():
+  """Test that missing Claude models show helpful install instructions.
+
+  Note: This test may pass even when anthropic IS installed, because it
+  only checks the error message format when a model is not found.
+  """
+  # Use a non-existent Claude model variant to trigger error
+  with pytest.raises(ValueError) as e_info:
+    models.LLMRegistry.resolve('claude-nonexistent-model-xyz')
+
+  error_msg = str(e_info.value)
+  # The error should mention anthropic package and installation instructions
+  # These checks work whether or not anthropic is actually installed
+  assert 'Model claude-nonexistent-model-xyz not found' in error_msg
+  assert 'anthropic package' in error_msg
+  assert 'pip install' in error_msg
+
+
+def test_helpful_error_for_litellm_without_extensions():
+  """Test that missing LiteLLM models show helpful install instructions.
+
+  Note: This test may pass even when litellm IS installed, because it
+  only checks the error message format when a model is not found.
+  """
+  # Use a non-existent provider to trigger error
+  with pytest.raises(ValueError) as e_info:
+    models.LLMRegistry.resolve('unknown-provider/gpt-4o')
+
+  error_msg = str(e_info.value)
+  # The error should mention litellm package for provider-style models
+  assert 'Model unknown-provider/gpt-4o not found' in error_msg
+  assert 'litellm package' in error_msg
+  assert 'pip install' in error_msg
+  assert 'Provider-style models' in error_msg