repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/groq/tests/unit_tests/test_imports.py | libs/partners/groq/tests/unit_tests/test_imports.py | from langchain_groq import __all__
EXPECTED_ALL = ["ChatGroq", "__version__"]
def test_all_imports() -> None:
"""Test that all expected imports are present in `__all__`."""
assert sorted(EXPECTED_ALL) == sorted(__all__)
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/groq/tests/unit_tests/fake/callbacks.py | libs/partners/groq/tests/unit_tests/fake/callbacks.py | """A fake callback handler for testing purposes."""
from __future__ import annotations
from itertools import chain
from typing import Any
from uuid import UUID
from langchain_core.callbacks.base import AsyncCallbackHandler, BaseCallbackHandler
from langchain_core.messages import BaseMessage
from pydantic import Base... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/groq/tests/unit_tests/fake/__init__.py | libs/partners/groq/tests/unit_tests/fake/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/groq/tests/integration_tests/test_standard.py | libs/partners/groq/tests/integration_tests/test_standard.py | """Standard LangChain interface tests."""
from typing import Literal
import pytest
from langchain_core.language_models import BaseChatModel
from langchain_core.rate_limiters import InMemoryRateLimiter
from langchain_core.tools import BaseTool
from langchain_tests.integration_tests import (
ChatModelIntegrationTes... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/groq/tests/integration_tests/test_compile.py | libs/partners/groq/tests/integration_tests/test_compile.py | import pytest
@pytest.mark.compile
def test_placeholder() -> None:
"""Used for compiling integration tests without running any real tests."""
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/groq/tests/integration_tests/test_chat_models.py | libs/partners/groq/tests/integration_tests/test_chat_models.py | """Test ChatGroq chat model."""
from __future__ import annotations
import json
from typing import Any, cast
import pytest
from groq import BadRequestError
from langchain_core.messages import (
AIMessage,
AIMessageChunk,
BaseMessage,
BaseMessageChunk,
HumanMessage,
SystemMessage,
)
from langch... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/groq/tests/integration_tests/__init__.py | libs/partners/groq/tests/integration_tests/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/scripts/check_imports.py | libs/partners/ollama/scripts/check_imports.py | """load multiple Python files specified as command line arguments."""
import sys
import traceback
from importlib.machinery import SourceFileLoader
if __name__ == "__main__":
files = sys.argv[1:]
has_failure = False
for file in files:
try:
SourceFileLoader("x", file).load_module()
... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/__init__.py | libs/partners/ollama/tests/__init__.py | # Running Tests
#
# To run integration tests (`make integration_tests`), you will need the following
# models installed in your Ollama server:
#
# - `llama3.1`
# - `deepseek-r1:1.5b`
# - `gpt-oss:20b`
#
# Install these models by running:
#
# ollama pull <name-of-model>
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/unit_tests/test_auth.py | libs/partners/ollama/tests/unit_tests/test_auth.py | """Test URL authentication parsing functionality."""
import base64
from unittest.mock import MagicMock, patch
from langchain_ollama._utils import parse_url_with_auth
from langchain_ollama.chat_models import ChatOllama
from langchain_ollama.embeddings import OllamaEmbeddings
from langchain_ollama.llms import OllamaLLM... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/unit_tests/test_chat_models.py | libs/partners/ollama/tests/unit_tests/test_chat_models.py | """Unit tests for ChatOllama."""
import json
import logging
from collections.abc import Generator
from contextlib import contextmanager
from typing import Any
from unittest.mock import MagicMock, patch
import pytest
from httpx import Client, Request, Response
from langchain_core.exceptions import OutputParserExceptio... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/unit_tests/__init__.py | libs/partners/ollama/tests/unit_tests/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/unit_tests/test_llms.py | libs/partners/ollama/tests/unit_tests/test_llms.py | """Test Ollama Chat API wrapper."""
from typing import Any
from unittest.mock import patch
from langchain_ollama import OllamaLLM
MODEL_NAME = "llama3.1"
def test_initialization() -> None:
"""Test integration initialization."""
OllamaLLM(model=MODEL_NAME)
def test_model_params() -> None:
"""Test stan... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/unit_tests/test_imports.py | libs/partners/ollama/tests/unit_tests/test_imports.py | from langchain_ollama import __all__
EXPECTED_ALL = [
"OllamaLLM",
"ChatOllama",
"OllamaEmbeddings",
"__version__",
]
def test_all_imports() -> None:
assert sorted(EXPECTED_ALL) == sorted(__all__)
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/unit_tests/test_embeddings.py | libs/partners/ollama/tests/unit_tests/test_embeddings.py | """Test embedding model integration."""
from typing import Any
from unittest.mock import Mock, patch
from langchain_ollama.embeddings import OllamaEmbeddings
MODEL_NAME = "llama3.1"
def test_initialization() -> None:
"""Test embedding model initialization."""
OllamaEmbeddings(model=MODEL_NAME, keep_alive=1... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/integration_tests/test_compile.py | libs/partners/ollama/tests/integration_tests/test_compile.py | import pytest
@pytest.mark.compile
def test_placeholder() -> None:
"""Used for compiling integration tests without running any real tests."""
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/integration_tests/__init__.py | libs/partners/ollama/tests/integration_tests/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/integration_tests/test_llms.py | libs/partners/ollama/tests/integration_tests/test_llms.py | """Test OllamaLLM llm."""
import os
import pytest
from langchain_core.outputs import GenerationChunk
from langchain_core.runnables import RunnableConfig
from langchain_ollama.llms import OllamaLLM
MODEL_NAME = os.environ.get("OLLAMA_TEST_MODEL", "llama3.1")
REASONING_MODEL_NAME = os.environ.get("OLLAMA_REASONING_TE... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/integration_tests/test_embeddings.py | libs/partners/ollama/tests/integration_tests/test_embeddings.py | """Test Ollama embeddings."""
import os
from langchain_tests.integration_tests import EmbeddingsIntegrationTests
from langchain_ollama.embeddings import OllamaEmbeddings
MODEL_NAME = os.environ.get("OLLAMA_TEST_MODEL", "llama3.1")
class TestOllamaEmbeddings(EmbeddingsIntegrationTests):
@property
def embed... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models_reasoning.py | libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models_reasoning.py | """Ollama integration tests for reasoning chat models."""
import pytest
from langchain_core.messages import AIMessageChunk, BaseMessageChunk, HumanMessage
from langchain_ollama import ChatOllama
SAMPLE = "What is 3^3?"
REASONING_MODEL_NAME = "deepseek-r1:1.5b"
@pytest.mark.parametrize("model", [REASONING_MODEL_NA... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models_standard.py | libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models_standard.py | """Test chat model integration using standard integration tests."""
import pytest
from langchain_core.language_models import BaseChatModel
from langchain_tests.integration_tests import ChatModelIntegrationTests
from langchain_ollama.chat_models import ChatOllama
DEFAULT_MODEL_NAME = "llama3.1"
class TestChatOllama... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models.py | libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models.py | """Ollama specific chat model integration tests"""
from __future__ import annotations
from typing import Annotated
from unittest.mock import MagicMock, patch
import pytest
from httpx import ConnectError
from langchain_core.messages.ai import AIMessage, AIMessageChunk
from langchain_core.messages.human import HumanMe... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/tests/integration_tests/chat_models/__init__.py | libs/partners/ollama/tests/integration_tests/chat_models/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/langchain_ollama/llms.py | libs/partners/ollama/langchain_ollama/llms.py | """Ollama large language models."""
from __future__ import annotations
from collections.abc import AsyncIterator, Iterator, Mapping
from typing import Any, Literal
from langchain_core.callbacks import (
AsyncCallbackManagerForLLMRun,
CallbackManagerForLLMRun,
)
from langchain_core.language_models import Base... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/langchain_ollama/chat_models.py | libs/partners/ollama/langchain_ollama/chat_models.py | """Ollama chat models.
**Input Flow (LangChain -> Ollama)**
`_convert_messages_to_ollama_messages()`:
- Transforms LangChain messages to `ollama.Message` format
- Extracts text content, images (base64), and tool calls
`_chat_params()`:
- Combines messages with model parameters (temperature, top_p, etc.)
- Attaches... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | true |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/langchain_ollama/_compat.py | libs/partners/ollama/langchain_ollama/_compat.py | """Go from v1 content blocks to Ollama SDK format."""
from typing import Any
from langchain_core.messages import content as types
def _convert_from_v1_to_ollama(
content: list[types.ContentBlock],
model_provider: str | None, # noqa: ARG001
) -> list[dict[str, Any]]:
"""Convert v1 content blocks to Olla... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/langchain_ollama/__init__.py | libs/partners/ollama/langchain_ollama/__init__.py | """This is the langchain_ollama package.
Provides infrastructure for interacting with the [Ollama](https://ollama.com/)
service.
!!! note
**Newly added in 0.3.4:** `validate_model_on_init` param on all models.
This parameter allows you to validate the model exists in Ollama locally on
initialization. If s... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/langchain_ollama/embeddings.py | libs/partners/ollama/langchain_ollama/embeddings.py | """Ollama embeddings models."""
from __future__ import annotations
from typing import Any
from langchain_core.embeddings import Embeddings
from ollama import AsyncClient, Client
from pydantic import BaseModel, ConfigDict, PrivateAttr, model_validator
from typing_extensions import Self
from ._utils import merge_auth... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/ollama/langchain_ollama/_utils.py | libs/partners/ollama/langchain_ollama/_utils.py | """Utility function to validate Ollama models."""
from __future__ import annotations
import base64
from urllib.parse import unquote, urlparse
from httpx import ConnectError
from ollama import Client, ResponseError
def validate_model(client: Client, model_name: str) -> None:
"""Validate that a model exists in t... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/scripts/check_imports.py | libs/partners/qdrant/scripts/check_imports.py | import sys
import traceback
from importlib.machinery import SourceFileLoader
if __name__ == "__main__":
files = sys.argv[1:]
has_failure = False
for file in files:
try:
SourceFileLoader("x", file).load_module()
except Exception: # noqa: BLE001
has_failure = True
... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/__init__.py | libs/partners/qdrant/tests/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/unit_tests/test_standard.py | libs/partners/qdrant/tests/unit_tests/test_standard.py | import pytest
from langchain_core.embeddings import Embeddings
from pytest_benchmark.fixture import BenchmarkFixture # type: ignore[import-untyped]
from langchain_qdrant import QdrantVectorStore
class MockEmbeddings(Embeddings):
"""Mock embeddings for testing."""
def embed_documents(self, texts: list[str])... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/unit_tests/test_vectorstores.py | libs/partners/qdrant/tests/unit_tests/test_vectorstores.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/unit_tests/__init__.py | libs/partners/qdrant/tests/unit_tests/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/unit_tests/test_imports.py | libs/partners/qdrant/tests/unit_tests/test_imports.py | from langchain_qdrant import __all__
EXPECTED_ALL = [
"Qdrant",
"QdrantVectorStore",
"SparseEmbeddings",
"SparseVector",
"FastEmbedSparse",
"RetrievalMode",
]
def test_all_imports() -> None:
assert sorted(EXPECTED_ALL) == sorted(__all__)
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/test_embedding_interface.py | libs/partners/qdrant/tests/integration_tests/test_embedding_interface.py | from __future__ import annotations
import uuid
from collections.abc import Callable
from typing import TYPE_CHECKING
import pytest # type: ignore[import-not-found]
from langchain_qdrant import Qdrant
from tests.integration_tests.common import ConsistentFakeEmbeddings
if TYPE_CHECKING:
from langchain_core.embed... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/test_max_marginal_relevance.py | libs/partners/qdrant/tests/integration_tests/test_max_marginal_relevance.py | from __future__ import annotations
import pytest # type: ignore[import-not-found]
from langchain_core.documents import Document
from qdrant_client import models
from langchain_qdrant import Qdrant
from tests.integration_tests.common import (
ConsistentFakeEmbeddings,
assert_documents_equals,
)
@pytest.mark... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/test_from_existing_collection.py | libs/partners/qdrant/tests/integration_tests/test_from_existing_collection.py | import tempfile
import uuid
import pytest # type: ignore[import-not-found]
from langchain_qdrant import Qdrant
from tests.integration_tests.common import ConsistentFakeEmbeddings
@pytest.mark.parametrize("vector_name", ["custom-vector"])
def test_qdrant_from_existing_collection_uses_same_collection(vector_name: st... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/common.py | libs/partners/qdrant/tests/integration_tests/common.py | import requests # type: ignore[import-untyped]
from langchain_core.documents import Document
from langchain_core.embeddings import Embeddings
from langchain_qdrant import SparseEmbeddings, SparseVector
def qdrant_running_locally() -> bool:
"""Check if Qdrant is running at http://localhost:6333."""
try:
... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/test_add_texts.py | libs/partners/qdrant/tests/integration_tests/test_add_texts.py | from __future__ import annotations
import uuid
import pytest # type: ignore[import-not-found]
from langchain_core.documents import Document
from langchain_qdrant import Qdrant
from tests.integration_tests.common import (
ConsistentFakeEmbeddings,
assert_documents_equals,
)
@pytest.mark.parametrize("batch_... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/fixtures.py | libs/partners/qdrant/tests/integration_tests/fixtures.py | import logging
import os
from langchain_qdrant.qdrant import RetrievalMode
from tests.integration_tests.common import qdrant_running_locally
logger = logging.getLogger(__name__)
def qdrant_locations(use_in_memory: bool = True) -> list[str]: # noqa: FBT001, FBT002
locations = []
if use_in_memory:
l... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/conftest.py | libs/partners/qdrant/tests/integration_tests/conftest.py | import os
from qdrant_client import QdrantClient
from tests.integration_tests.fixtures import qdrant_locations
def pytest_runtest_teardown() -> None:
"""Clean up all collections after the each test."""
for location in qdrant_locations():
client = QdrantClient(location=location, api_key=os.getenv("QD... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/test_similarity_search.py | libs/partners/qdrant/tests/integration_tests/test_similarity_search.py | from __future__ import annotations
import numpy as np
import pytest # type: ignore[import-not-found]
from langchain_core.documents import Document
from qdrant_client.http import models as rest
from langchain_qdrant import Qdrant
from tests.integration_tests.common import (
ConsistentFakeEmbeddings,
assert_do... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/test_compile.py | libs/partners/qdrant/tests/integration_tests/test_compile.py | import pytest # type: ignore[import-not-found]
@pytest.mark.compile
def test_placeholder() -> None:
"""Used for compiling integration tests without running any real tests."""
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/test_from_texts.py | libs/partners/qdrant/tests/integration_tests/test_from_texts.py | from __future__ import annotations
import tempfile
import uuid
import pytest # type: ignore[import-not-found]
from langchain_core.documents import Document
from langchain_qdrant import Qdrant
from langchain_qdrant.vectorstores import QdrantException
from tests.integration_tests.common import (
ConsistentFakeEmb... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/__init__.py | libs/partners/qdrant/tests/integration_tests/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/async_api/test_max_marginal_relevance.py | libs/partners/qdrant/tests/integration_tests/async_api/test_max_marginal_relevance.py | from __future__ import annotations
import pytest # type: ignore[import-not-found]
from langchain_core.documents import Document
from langchain_qdrant import Qdrant
from tests.integration_tests.common import (
ConsistentFakeEmbeddings,
assert_documents_equals,
)
from tests.integration_tests.fixtures import (
... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/async_api/test_add_texts.py | libs/partners/qdrant/tests/integration_tests/async_api/test_add_texts.py | from __future__ import annotations
import os
import uuid
import pytest # type: ignore[import-not-found]
from langchain_qdrant import Qdrant
from tests.integration_tests.common import ConsistentFakeEmbeddings
from tests.integration_tests.fixtures import qdrant_locations
API_KEY = os.getenv("QDRANT_API_KEY")
@pyte... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/async_api/test_similarity_search.py | libs/partners/qdrant/tests/integration_tests/async_api/test_similarity_search.py | from __future__ import annotations
import numpy as np
import pytest # type: ignore[import-not-found]
from langchain_core.documents import Document
from langchain_qdrant import Qdrant
from tests.integration_tests.common import (
ConsistentFakeEmbeddings,
assert_documents_equals,
)
from tests.integration_tests... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/async_api/test_from_texts.py | libs/partners/qdrant/tests/integration_tests/async_api/test_from_texts.py | from __future__ import annotations
import os
import uuid
import pytest # type: ignore[import-not-found]
from langchain_core.documents import Document
from langchain_qdrant import Qdrant
from langchain_qdrant.vectorstores import QdrantException
from tests.integration_tests.common import (
ConsistentFakeEmbedding... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/async_api/__init__.py | libs/partners/qdrant/tests/integration_tests/async_api/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_mmr.py | libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_mmr.py | import pytest # type: ignore[import-not-found]
from langchain_core.documents import Document
from qdrant_client import models
from langchain_qdrant import QdrantVectorStore, RetrievalMode
from langchain_qdrant.qdrant import QdrantVectorStoreError
from tests.integration_tests.common import (
ConsistentFakeEmbeddin... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_add_texts.py | libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_add_texts.py | from __future__ import annotations
import uuid
import pytest
from langchain_core.documents import Document
from qdrant_client import QdrantClient, models
from langchain_qdrant import QdrantVectorStore, RetrievalMode
from tests.integration_tests.common import (
ConsistentFakeEmbeddings,
ConsistentFakeSparseEm... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_from_existing.py | libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_from_existing.py | import uuid
import pytest
from langchain_qdrant.qdrant import QdrantVectorStore, RetrievalMode
from tests.integration_tests.common import (
ConsistentFakeEmbeddings,
ConsistentFakeSparseEmbeddings,
)
from tests.integration_tests.fixtures import qdrant_locations, retrieval_modes
@pytest.mark.parametrize("loc... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_from_texts.py | libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_from_texts.py | from __future__ import annotations
import uuid
import pytest
from langchain_core.documents import Document
from qdrant_client import models
from langchain_qdrant import QdrantVectorStore, RetrievalMode
from langchain_qdrant.qdrant import QdrantVectorStoreError
from tests.integration_tests.common import (
Consist... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/__init__.py | libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_search.py | libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_search.py | import pytest
from langchain_core.documents import Document
from qdrant_client import models
from langchain_qdrant import QdrantVectorStore, RetrievalMode
from tests.integration_tests.common import (
ConsistentFakeEmbeddings,
ConsistentFakeSparseEmbeddings,
assert_documents_equals,
)
from tests.integration... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/fastembed/test_fastembed_sparse.py | libs/partners/qdrant/tests/integration_tests/fastembed/test_fastembed_sparse.py | import numpy as np
import pytest
from langchain_qdrant import FastEmbedSparse
pytest.importorskip("fastembed", reason="'fastembed' package is not installed")
@pytest.mark.parametrize(
"model_name", ["Qdrant/bm25", "Qdrant/bm42-all-minilm-l6-v2-attentions"]
)
def test_attention_embeddings(model_name: str) -> Non... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/tests/integration_tests/fastembed/__init__.py | libs/partners/qdrant/tests/integration_tests/fastembed/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/langchain_qdrant/fastembed_sparse.py | libs/partners/qdrant/langchain_qdrant/fastembed_sparse.py | from __future__ import annotations
from typing import TYPE_CHECKING, Any
from langchain_qdrant.sparse_embeddings import SparseEmbeddings, SparseVector
if TYPE_CHECKING:
from collections.abc import Sequence
class FastEmbedSparse(SparseEmbeddings):
"""An interface for sparse embedding models to use with Qdra... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/langchain_qdrant/vectorstores.py | libs/partners/qdrant/langchain_qdrant/vectorstores.py | from __future__ import annotations
import functools
import os
import uuid
import warnings
from collections.abc import Callable
from itertools import islice
from operator import itemgetter
from typing import TYPE_CHECKING, Any
import numpy as np
from langchain_core._api.deprecation import deprecated
from langchain_cor... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | true |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/langchain_qdrant/sparse_embeddings.py | libs/partners/qdrant/langchain_qdrant/sparse_embeddings.py | from abc import ABC, abstractmethod
from langchain_core.runnables.config import run_in_executor
from pydantic import BaseModel, Field
class SparseVector(BaseModel, extra="forbid"):
"""Sparse vector structure."""
indices: list[int] = Field(..., description="indices must be unique")
values: list[float] = ... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/langchain_qdrant/__init__.py | libs/partners/qdrant/langchain_qdrant/__init__.py | from langchain_qdrant.fastembed_sparse import FastEmbedSparse
from langchain_qdrant.qdrant import QdrantVectorStore, RetrievalMode
from langchain_qdrant.sparse_embeddings import SparseEmbeddings, SparseVector
from langchain_qdrant.vectorstores import Qdrant
__all__ = [
"FastEmbedSparse",
"Qdrant",
"QdrantV... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/langchain_qdrant/_utils.py | libs/partners/qdrant/langchain_qdrant/_utils.py | from typing import TypeAlias
import numpy as np
Matrix: TypeAlias = list[list[float]] | list[np.ndarray] | np.ndarray
def maximal_marginal_relevance(
query_embedding: np.ndarray,
embedding_list: list,
lambda_mult: float = 0.5,
k: int = 4,
) -> list[int]:
"""Calculate maximal marginal relevance."... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/qdrant/langchain_qdrant/qdrant.py | libs/partners/qdrant/langchain_qdrant/qdrant.py | from __future__ import annotations
import uuid
from collections.abc import Callable
from enum import Enum
from itertools import islice
from operator import itemgetter
from typing import (
TYPE_CHECKING,
Any,
)
from langchain_core.documents import Document
from langchain_core.embeddings import Embeddings
from ... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | true |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/scripts/check_imports.py | libs/partners/anthropic/scripts/check_imports.py | """Script to check for import errors in specified Python files."""
import sys
import traceback
from importlib.machinery import SourceFileLoader
if __name__ == "__main__":
files = sys.argv[1:]
has_failure = False
for file in files:
try:
SourceFileLoader("x", file).load_module()
... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/llms.py | libs/partners/anthropic/langchain_anthropic/llms.py | """Anthropic LLM wrapper. Chat models are in `chat_models.py`."""
from __future__ import annotations
import re
import warnings
from collections.abc import AsyncIterator, Callable, Iterator, Mapping
from typing import Any
import anthropic
from langchain_core.callbacks import (
AsyncCallbackManagerForLLMRun,
C... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/output_parsers.py | libs/partners/anthropic/langchain_anthropic/output_parsers.py | """Output parsers for Anthropic tool calls."""
from __future__ import annotations
from typing import Any, cast
from langchain_core.messages import AIMessage, ToolCall
from langchain_core.messages.tool import tool_call
from langchain_core.output_parsers import BaseGenerationOutputParser
from langchain_core.outputs im... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/chat_models.py | libs/partners/anthropic/langchain_anthropic/chat_models.py | """Anthropic chat models."""
from __future__ import annotations
import copy
import datetime
import json
import re
import warnings
from collections.abc import AsyncIterator, Callable, Iterator, Mapping, Sequence
from functools import cached_property
from operator import itemgetter
from typing import Any, Final, Litera... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | true |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/_compat.py | libs/partners/anthropic/langchain_anthropic/_compat.py | from __future__ import annotations
import json
from typing import Any, cast
from langchain_core.messages import content as types
def _convert_annotation_from_v1(annotation: types.Annotation) -> dict[str, Any]:
"""Convert LangChain annotation format to Anthropic's native citation format."""
if annotation["ty... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/_client_utils.py | libs/partners/anthropic/langchain_anthropic/_client_utils.py | """Helpers for creating Anthropic API clients.
This module allows for the caching of httpx clients to avoid creating new instances
for each instance of ChatAnthropic.
Logic is largely replicated from anthropic._base_client.
"""
from __future__ import annotations
import asyncio
import os
from functools import lru_ca... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/__init__.py | libs/partners/anthropic/langchain_anthropic/__init__.py | """Claude (Anthropic) partner package for LangChain."""
from langchain_anthropic.chat_models import (
ChatAnthropic,
convert_to_anthropic_tool,
)
from langchain_anthropic.llms import AnthropicLLM
__all__ = [
"AnthropicLLM",
"ChatAnthropic",
"convert_to_anthropic_tool",
]
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/experimental.py | libs/partners/anthropic/langchain_anthropic/experimental.py | """Experimental tool-calling support for Anthropic chat models."""
from __future__ import annotations
import json
from typing import (
Any,
)
SYSTEM_PROMPT_FORMAT = """In this environment you have access to a set of tools you can use to answer the user's question.
You may call them like this:
<function_calls>
<... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/middleware/anthropic_tools.py | libs/partners/anthropic/langchain_anthropic/middleware/anthropic_tools.py | """Anthropic text editor and memory tool middleware.
This module provides client-side implementations of Anthropic's text editor and
memory tools using schema-less tool definitions and tool call interception.
"""
from __future__ import annotations
import os
import shutil
from datetime import datetime, timezone
from ... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | true |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/middleware/file_search.py | libs/partners/anthropic/langchain_anthropic/middleware/file_search.py | """File search middleware for Anthropic text editor and memory tools.
This module provides Glob and Grep search tools that operate on files stored
in state or filesystem.
"""
from __future__ import annotations
import fnmatch
import re
from pathlib import Path, PurePosixPath
from typing import TYPE_CHECKING, Literal,... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/middleware/__init__.py | libs/partners/anthropic/langchain_anthropic/middleware/__init__.py | """Middleware for Anthropic models."""
from langchain_anthropic.middleware.anthropic_tools import (
FilesystemClaudeMemoryMiddleware,
FilesystemClaudeTextEditorMiddleware,
StateClaudeMemoryMiddleware,
StateClaudeTextEditorMiddleware,
)
from langchain_anthropic.middleware.bash import ClaudeBashToolMiddl... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/middleware/prompt_caching.py | libs/partners/anthropic/langchain_anthropic/middleware/prompt_caching.py | """Anthropic prompt caching middleware.
Requires:
- `langchain`: For agent middleware framework
- `langchain-anthropic`: For `ChatAnthropic` model (already a dependency)
"""
from collections.abc import Awaitable, Callable
from typing import Literal
from warnings import warn
from langchain_anthropic.chat_mode... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/middleware/bash.py | libs/partners/anthropic/langchain_anthropic/middleware/bash.py | """Anthropic-specific middleware for the Claude bash tool."""
from __future__ import annotations
from collections.abc import Awaitable, Callable
from typing import Any
from langchain.agents.middleware.shell_tool import ShellToolMiddleware
from langchain.agents.middleware.types import (
ModelRequest,
ModelRes... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/data/_profiles.py | libs/partners/anthropic/langchain_anthropic/data/_profiles.py | """Auto-generated model profiles.
DO NOT EDIT THIS FILE MANUALLY.
This file is generated by the langchain-profiles CLI tool.
It contains data derived from the models.dev project.
Source: https://github.com/sst/models.dev
License: MIT License
To update these data, refer to the instructions here:
https://docs.langch... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/langchain_anthropic/data/__init__.py | libs/partners/anthropic/langchain_anthropic/data/__init__.py | """Model profile data. All edits should be made in profile_augmentations.toml."""
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/conftest.py | libs/partners/anthropic/tests/conftest.py | from typing import Any
import pytest
from langchain_tests.conftest import CustomPersister, CustomSerializer, base_vcr_config
from vcr import VCR # type: ignore[import-untyped]
def remove_request_headers(request: Any) -> Any:
for k in request.headers:
request.headers[k] = "**REDACTED**"
return reques... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/__init__.py | libs/partners/anthropic/tests/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/test_standard.py | libs/partners/anthropic/tests/unit_tests/test_standard.py | """Standard LangChain interface tests."""
import pytest
from langchain_core.language_models import BaseChatModel
from langchain_tests.unit_tests import ChatModelUnitTests
from pytest_benchmark.fixture import BenchmarkFixture # type: ignore[import-untyped]
from langchain_anthropic import ChatAnthropic
_MODEL = "clau... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/test_chat_models.py | libs/partners/anthropic/tests/unit_tests/test_chat_models.py | """Test chat model integration."""
from __future__ import annotations
import os
from collections.abc import Callable
from typing import Any, Literal, cast
from unittest.mock import MagicMock, patch
import anthropic
import pytest
from anthropic.types import Message, TextBlock, Usage
from blockbuster import blockbuste... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | true |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/__init__.py | libs/partners/anthropic/tests/unit_tests/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/test_output_parsers.py | libs/partners/anthropic/tests/unit_tests/test_output_parsers.py | from typing import Any, Literal
from langchain_core.messages import AIMessage
from langchain_core.outputs import ChatGeneration
from pydantic import BaseModel
from langchain_anthropic.output_parsers import ToolsOutputParser
_CONTENT: list = [
{
"type": "text",
"text": "thought",
},
{"type... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/test_client_utils.py | libs/partners/anthropic/tests/unit_tests/test_client_utils.py | """Test client utility functions."""
from __future__ import annotations
from langchain_anthropic._client_utils import (
_get_default_async_httpx_client,
_get_default_httpx_client,
)
def test_sync_client_without_proxy() -> None:
"""Test sync client creation without proxy."""
client = _get_default_htt... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/test_llms.py | libs/partners/anthropic/tests/unit_tests/test_llms.py | import os
from langchain_anthropic import AnthropicLLM
os.environ["ANTHROPIC_API_KEY"] = "foo"
def test_anthropic_model_params() -> None:
# Test standard tracing params
llm = AnthropicLLM(model="foo") # type: ignore[call-arg]
ls_params = llm._get_ls_params()
assert ls_params == {
"ls_provi... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/_utils.py | libs/partners/anthropic/tests/unit_tests/_utils.py | """A fake callback handler for testing purposes."""
from __future__ import annotations
from typing import Any
from langchain_core.callbacks import BaseCallbackHandler
from pydantic import BaseModel
class BaseFakeCallbackHandler(BaseModel):
"""Base fake callback handler for testing."""
starts: int = 0
... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/test_imports.py | libs/partners/anthropic/tests/unit_tests/test_imports.py | from langchain_anthropic import __all__
EXPECTED_ALL = [
"ChatAnthropic",
"convert_to_anthropic_tool",
"AnthropicLLM",
]
def test_all_imports() -> None:
assert sorted(EXPECTED_ALL) == sorted(__all__)
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/middleware/test_anthropic_tools.py | libs/partners/anthropic/tests/unit_tests/middleware/test_anthropic_tools.py | """Unit tests for Anthropic text editor and memory tool middleware."""
from unittest.mock import MagicMock
import pytest
from langchain_core.messages import SystemMessage, ToolMessage
from langgraph.types import Command
from langchain_anthropic.middleware.anthropic_tools import (
AnthropicToolsState,
StateCl... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/middleware/test_prompt_caching.py | libs/partners/anthropic/tests/unit_tests/middleware/test_prompt_caching.py | """Tests for Anthropic prompt caching middleware."""
import warnings
from typing import Any, cast
from unittest.mock import MagicMock
import pytest
from langchain.agents.middleware.types import ModelRequest, ModelResponse
from langchain_core.callbacks import (
AsyncCallbackManagerForLLMRun,
CallbackManagerFor... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/middleware/test_file_search.py | libs/partners/anthropic/tests/unit_tests/middleware/test_file_search.py | """Unit tests for file search middleware."""
from langchain_anthropic.middleware.anthropic_tools import AnthropicToolsState
from langchain_anthropic.middleware.file_search import (
StateFileSearchMiddleware,
)
class TestSearchMiddlewareInitialization:
"""Test search middleware initialization."""
def tes... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/middleware/__init__.py | libs/partners/anthropic/tests/unit_tests/middleware/__init__.py | """Tests for Anthropic middleware."""
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/unit_tests/middleware/test_bash.py | libs/partners/anthropic/tests/unit_tests/middleware/test_bash.py | from __future__ import annotations
from unittest.mock import MagicMock
import pytest
pytest.importorskip(
"anthropic", reason="Anthropic SDK is required for Claude middleware tests"
)
from langchain_anthropic.middleware.bash import ClaudeBashToolMiddleware
def test_creates_bash_tool(monkeypatch: pytest.Monkey... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/integration_tests/test_standard.py | libs/partners/anthropic/tests/integration_tests/test_standard.py | """Standard LangChain interface tests."""
from pathlib import Path
from typing import Literal, cast
import pytest
from langchain_core.language_models import BaseChatModel
from langchain_core.messages import AIMessage, BaseMessageChunk
from langchain_tests.integration_tests import ChatModelIntegrationTests
from langc... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/integration_tests/test_compile.py | libs/partners/anthropic/tests/integration_tests/test_compile.py | import pytest
@pytest.mark.compile
def test_placeholder() -> None:
"""Used for compiling integration tests without running any real tests."""
| python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/integration_tests/test_chat_models.py | libs/partners/anthropic/tests/integration_tests/test_chat_models.py | """Test ChatAnthropic chat model."""
from __future__ import annotations
import asyncio
import json
import os
from base64 import b64encode
from typing import Literal, cast
import httpx
import pytest
import requests
from anthropic import BadRequestError
from langchain.agents import create_agent
from langchain.agents.s... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | true |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/integration_tests/__init__.py | libs/partners/anthropic/tests/integration_tests/__init__.py | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false | |
langchain-ai/langchain | https://github.com/langchain-ai/langchain/blob/e5d4acf681784d1ea356c932cf31c1c9723dbafa/libs/partners/anthropic/tests/integration_tests/test_llms.py | libs/partners/anthropic/tests/integration_tests/test_llms.py | """Test Anthropic API wrapper."""
from collections.abc import Generator
import pytest
from langchain_core.callbacks import CallbackManager
from langchain_core.outputs import LLMResult
from langchain_anthropic import AnthropicLLM
from tests.unit_tests._utils import FakeCallbackHandler
MODEL = "claude-sonnet-4-5-2025... | python | MIT | e5d4acf681784d1ea356c932cf31c1c9723dbafa | 2026-01-04T14:38:15.444279Z | false |
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