Merge branch 'master' of github.com:langchain-ai/langchain into jacob/agenttype

libs/langchain_v1/langchain/agents/factory.py

@@ -1649,6 +1649,7 @@ def create_agent(
     # https://github.com/langchain-ai/langgraph/issues/7313
     config: RunnableConfig = {"recursion_limit": 9_999}
     config["metadata"] = {"ls_integration": "langchain_create_agent"}
+    config["configurable"] = {"ls_agent_type": "root"}
     if name:
         config["metadata"]["lc_agent_name"] = name
 

libs/langchain_v1/tests/unit_tests/agents/test_injected_runtime_create_agent.py

@@ -17,9 +17,12 @@ configurations.
 from __future__ import annotations
 
 from typing import TYPE_CHECKING, Annotated, Any
+from unittest.mock import MagicMock
 
+from langchain_core.callbacks import BaseCallbackHandler
 from langchain_core.messages import HumanMessage, ToolMessage
 from langchain_core.tools import tool
+from langchain_core.tracers.langchain import LangChainTracer
 from langgraph.prebuilt import InjectedStore
 from langgraph.store.memory import InMemoryStore
 
@@ -258,6 +261,7 @@ def test_tool_runtime_config_access() -> None:
             config_data["config_keys"] = list(runtime.config.keys())
             config_data["recursion_limit"] = runtime.config.get("recursion_limit")
             config_data["metadata"] = runtime.config.get("metadata")
+            config_data["configurable"] = runtime.config.get("configurable")
         return f"Config accessed for {x}"
 
     agent = create_agent(
@@ -279,6 +283,7 @@ def test_tool_runtime_config_access() -> None:
     assert "config_keys" in config_data
     assert config_data["recursion_limit"] == 9999
     assert config_data["metadata"]["ls_integration"] == "langchain_create_agent"
+    assert config_data["configurable"]["ls_agent_type"] == "root"
 
     tool_message = result["messages"][2]
     assert isinstance(tool_message, ToolMessage)
@@ -842,3 +847,59 @@ async def test_combined_injected_state_runtime_store_async() -> None:
     # Verify store was injected and writable
     assert injected_data["store"] is not None
     assert injected_data["store_write_success"] is True
+
+
+def test_ls_agent_type_is_trace_only_metadata() -> None:
+    """Test that ls_agent_type is trace-only metadata, not streamed to callbacks."""
+    # Capture metadata from regular callback handler (simulates streamed metadata)
+    captured_callback_metadata: list[dict[str, Any]] = []
+
+    class CaptureHandler(BaseCallbackHandler):
+        def on_chain_start(
+            self,
+            serialized: dict[str, Any],
+            inputs: dict[str, Any],
+            *,
+            run_id: str,
+            parent_run_id: str | None = None,
+            tags: list[str] | None = None,
+            metadata: dict[str, Any] | None = None,
+            **kwargs: Any,
+        ) -> None:
+            captured_callback_metadata.append({"tags": tags, "metadata": metadata})
+
+    # Mock the LangSmith client to capture what gets sent to the tracer
+    mock_client = MagicMock()
+    create_run_mock = MagicMock(return_value=None)
+    mock_client.create_run = create_run_mock
+
+    tracer = LangChainTracer(client=mock_client)
+    capture = CaptureHandler()
+
+    agent = create_agent(
+        model=FakeToolCallingModel(tool_calls=[[], []]),
+        tools=[],
+        system_prompt="You are a helpful assistant.",
+    )
+
+    # Invoke with both tracer and capture handler
+    agent.invoke(
+        {"messages": [HumanMessage("hi?")]},
+        config={"callbacks": [tracer, capture]},
+    )
+
+    # Verify that ls_agent_type is NOT in the regular callback metadata
+    # (it should only go to the tracer)
+    assert len(captured_callback_metadata) > 0
+    for captured in captured_callback_metadata:
+        metadata = captured.get("metadata") or {}
+        assert metadata.get("ls_agent_type") is None, (
+            f"ls_agent_type should not be in callback metadata, but got: {metadata}"
+        )
+
+    # Verify that ls_agent_type IS in the tracer metadata (sent to LangSmith)
+    assert create_run_mock.called
+    posted_run = create_run_mock.call_args[1] if create_run_mock.call_args else None
+    if posted_run:
+        metadata = posted_run.get("extra", {}).get("metadata", {})
+        assert metadata.get("ls_agent_type") == "root"

libs/partners/huggingface/langchain_huggingface/embeddings/huggingface_endpoint.py

@@ -65,12 +65,6 @@ class HuggingFaceEndpointEmbeddings(BaseModel, Embeddings):
     @model_validator(mode="after")
     def validate_environment(self) -> Self:
         """Validate that api key and python package exists in environment."""
-        for field_name in ("model", "repo_id"):
-            value = getattr(self, field_name)
-            if value and value.startswith(("http://", "https://")):
-                msg = f"`{field_name}` must be a HuggingFace repo ID, not a URL."
-                raise ValueError(msg)
-
         huggingfacehub_api_token = self.huggingfacehub_api_token or os.getenv(
             "HF_TOKEN"
         )

libs/partners/huggingface/langchain_huggingface/llms/huggingface_endpoint.py

@@ -5,7 +5,6 @@ import logging
 import os
 from collections.abc import AsyncIterator, Iterator, Mapping
 from typing import Any
-from urllib.parse import urlparse
 
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
@@ -24,12 +23,8 @@ def _is_huggingface_hosted_url(url: str | None) -> bool:
     """True if url is HF-hosted (huggingface.co or hf.space)."""
     if not url:
         return False
-    hostname = (urlparse(url).hostname or "").lower()
-    return (
-        hostname == "huggingface.co"
-        or hostname == "hf.space"
-        or hostname.endswith((".huggingface.co", ".hf.space"))
-    )
+    url_lower = url.lower().strip()
+    return "huggingface.co" in url_lower or "hf.space" in url_lower
 
 
 VALID_TASKS = (
@@ -225,13 +220,6 @@ class HuggingFaceEndpoint(LLM):
         endpoint_url = values.get("endpoint_url")
         repo_id = values.get("repo_id")
 
-        if repo_id and repo_id.startswith(("http://", "https://")):
-            msg = (
-                "`repo_id` must be a HuggingFace repo ID, not a URL. "
-                "Use `endpoint_url` for direct endpoints."
-            )
-            raise ValueError(msg)
-
         if sum([bool(model), bool(endpoint_url), bool(repo_id)]) > 1:
             msg = (
                 "Please specify either a `model` OR an `endpoint_url` OR a `repo_id`,"

libs/partners/huggingface/pyproject.toml

@@ -20,10 +20,10 @@ classifiers = [
     "Topic :: Scientific/Engineering :: Artificial Intelligence",
 ]
 
-version = "1.2.2"
+version = "1.2.1"
 requires-python = ">=3.10.0,<4.0.0"
 dependencies = [
-    "langchain-core>=1.2.31,<2.0.0",
+    "langchain-core>=1.2.21,<2.0.0",
     "tokenizers>=0.19.1,<1.0.0",
     "huggingface-hub>=0.33.4,<2.0.0",
 ]

libs/partners/huggingface/uv.lock

@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.10.0, <4.0.0"
 resolution-markers = [
     "python_full_version >= '3.13' and platform_python_implementation == 'PyPy'",
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@@ -1049,7 +1044,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.3.0a3"
+version = "1.3.0a2"
 source = { editable = "../../core" }
 dependencies = [
     { name = "jsonpatch" },
@@ -1109,7 +1104,7 @@ typing = [
 
 [[package]]
 name = "langchain-huggingface"
-version = "1.2.2"
+version = "1.2.1"
 source = { editable = "." }
 dependencies = [
     { name = "huggingface-hub" },