feat(model-profiles): support more providers (#33766)

Author: ccurme

libs/model-profiles/langchain_model_profiles/data/augmentations/providers/amazon-bedrock.toml

@@ -0,0 +1,6 @@
+[profile]
+image_url_inputs = true
+pdf_inputs = true
+pdf_tool_message = true
+image_tool_message = true
+structured_output = false

libs/model-profiles/langchain_model_profiles/data/augmentations/providers/google.toml

@@ -0,0 +1,6 @@
+[profile]
+image_url_inputs = true
+pdf_inputs = true
+image_tool_message = true
+tool_choice = true
+structured_output = true

libs/model-profiles/langchain_model_profiles/data/augmentations/providers/google_vertexai.toml

@@ -0,0 +1,6 @@
+[profile]
+image_url_inputs = true
+pdf_inputs = true
+image_tool_message = true
+tool_choice = true
+structured_output = true

libs/model-profiles/langchain_model_profiles/model_profile.py

@@ -1,5 +1,7 @@
 """Model profiles package."""
 
+import re
+
 from typing_extensions import TypedDict
 
 from langchain_model_profiles._data_loader import _DataLoader
@@ -79,27 +81,67 @@ class ModelProfile(TypedDict, total=False):
 
 _lc_type_to_provider_id = {
     "openai-chat": "openai",
+    "azure-openai-chat": "azure",
     "anthropic-chat": "anthropic",
+    "chat-google-generative-ai": "google",
+    "vertexai": "google-vertex",
+    "anthropic-chat-vertexai": "google-vertex-anthropic",
+    "amazon_bedrock_chat": "amazon-bedrock",
+    "amazon_bedrock_converse_chat": "amazon-bedrock",
+    "chat-ai21": "ai21",
+    "chat-deepseek": "deepseek",
+    "fireworks-chat": "fireworks-ai",
+    "groq-chat": "groq",
+    "huggingface-chat-wrapper": "huggingface",
+    "mistralai-chat": "mistral",
+    "chat-ollama": "ollama",
+    "perplexitychat": "perplexity",
+    "together-chat": "togetherai",
+    "upstage-chat": "upstage",
+    "xai-chat": "xai",
 }
 
 
-def get_model_profile(provider_id: str, model_id: str) -> ModelProfile | None:
+def _translate_provider_and_model_id(provider: str, model: str) -> tuple[str, str]:
+    """Translate LangChain provider and model to models.dev equivalents.
+
+    Args:
+        provider: LangChain provider ID.
+        model: LangChain model ID.
+
+    Returns:
+        A tuple containing the models.dev provider ID and model ID.
+    """
+    provider_id = _lc_type_to_provider_id.get(provider, provider)
+
+    if provider_id in ("google", "google-vertex"):
+        # convert models/gemini-2.0-flash-001 to gemini-2.0-flash
+        model_id = re.sub(r"-\d{3}$", "", model.replace("models/", ""))
+    elif provider_id == "amazon-bedrock":
+        # strip region prefixes like "us."
+        model_id = re.sub(r"^[A-Za-z]{2}\.", "", model)
+    else:
+        model_id = model
+
+    return provider_id, model_id
+
+
+def get_model_profile(provider: str, model: str) -> ModelProfile | None:
     """Get the model capabilities for a given model.
 
     Args:
-        provider_id: Identifier for provider (e.g., `'openai'`, `'anthropic'`).
-        model_id: Identifier for model (e.g., `'gpt-5'`,
+        provider: Identifier for provider (e.g., `'openai'`, `'anthropic'`).
+        model: Identifier for model (e.g., `'gpt-5'`,
             `'claude-sonnet-4-5-20250929'`).
 
     Returns:
         The model capabilities or `None` if not found in the data.
     """
-    if not provider_id or not model_id:
+    if not provider or not model:
         return None
 
-    data = _LOADER.get_profile_data(
-        _lc_type_to_provider_id.get(provider_id, provider_id), model_id
-    )
+    provider_id, model_id = _translate_provider_and_model_id(provider, model)
+    data = _LOADER.get_profile_data(provider_id, model_id)
     if not data:
         # If either (1) provider not found or (2) model not found under matched provider
         return None

libs/model-profiles/tests/unit_tests/test_chat_model.py

@@ -1,6 +1,5 @@
 """End to end test for fetching model profiles from a chat model."""
 
-import pytest
 from langchain.chat_models import init_chat_model
 
 
@@ -12,7 +11,7 @@ def test_chat_model() -> None:
     assert model.profile["structured_output"]
 
 
-def test_chat_model_no_data(monkeypatch: pytest.MonkeyPatch) -> None:
+def test_chat_model_no_data() -> None:
     """Test that chat model handles missing profile data."""
     model = init_chat_model("openai:gpt-fake", api_key="foo")
     assert model.profile == {}

libs/model-profiles/tests/unit_tests/test_model_profile.py

@@ -0,0 +1,31 @@
+"""Test provider and model ID mappings."""
+
+import pytest
+
+from langchain_model_profiles.model_profile import get_model_profile
+
+
+@pytest.mark.parametrize(
+    ("provider", "model_id"),
+    [
+        ("openai-chat", "gpt-5"),
+        ("azure-openai-chat", "gpt-5"),
+        ("anthropic-chat", "claude-sonnet-4-5"),
+        ("vertexai", "models/gemini-2.0-flash-001"),
+        ("chat-google-generative-ai", "models/gemini-2.0-flash-001"),
+        ("amazon_bedrock_chat", "anthropic.claude-sonnet-4-20250514-v1:0"),
+        ("amazon_bedrock_converse_chat", "anthropic.claude-sonnet-4-20250514-v1:0"),
+        # ("chat-ai21", "jamba-mini"),  # no data yet  # noqa: ERA001
+        ("chat-deepseek", "deepseek-reasoner"),
+        ("fireworks-chat", "accounts/fireworks/models/gpt-oss-20b"),
+        ("groq-chat", "llama-3.3-70b-versatile"),
+        ("huggingface-chat-wrapper", "Qwen/Qwen3-235B-A22B-Thinking-2507"),
+        ("mistralai-chat", "mistral-large-latest"),
+        # ("chat-ollama", "llama3.1"),  # no data yet  # noqa: ERA001
+        ("perplexitychat", "sonar"),
+        ("xai-chat", "grok-4"),
+    ],
+)
+def test_id_translation(provider: str, model_id: str) -> None:
+    """Test translation from LangChain to model / provider IDs."""
+    assert get_model_profile(provider, model_id)