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https://github.com/hwchase17/langchain.git
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Merge branch 'master' into fix/rag-tutorial-part-1
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commit
ebb1024966
@ -36,6 +36,8 @@ class FakeMessagesListChatModel(BaseChatModel):
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run_manager: Optional[CallbackManagerForLLMRun] = None,
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run_manager: Optional[CallbackManagerForLLMRun] = None,
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**kwargs: Any,
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**kwargs: Any,
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) -> ChatResult:
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) -> ChatResult:
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if self.sleep is not None:
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time.sleep(self.sleep)
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response = self.responses[self.i]
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response = self.responses[self.i]
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if self.i < len(self.responses) - 1:
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if self.i < len(self.responses) - 1:
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self.i += 1
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self.i += 1
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@ -150,6 +150,11 @@ def parse_tag(template: str, l_del: str, r_del: str) -> tuple[tuple[str, str], s
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msg = f"unclosed tag at line {_CURRENT_LINE}"
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msg = f"unclosed tag at line {_CURRENT_LINE}"
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raise ChevronError(msg) from e
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raise ChevronError(msg) from e
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# Check for empty tags
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if not tag.strip():
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msg = f"empty tag at line {_CURRENT_LINE}"
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raise ChevronError(msg)
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# Find the type meaning of the first character
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# Find the type meaning of the first character
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tag_type = tag_types.get(tag[0], "variable")
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tag_type = tag_types.get(tag[0], "variable")
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@ -1,5 +1,6 @@
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"""Tests for verifying that testing utility code works as expected."""
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"""Tests for verifying that testing utility code works as expected."""
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import time
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from itertools import cycle
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from itertools import cycle
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from typing import Any, Optional, Union
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from typing import Any, Optional, Union
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from uuid import UUID
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from uuid import UUID
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@ -9,10 +10,11 @@ from typing_extensions import override
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from langchain_core.callbacks.base import AsyncCallbackHandler
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from langchain_core.callbacks.base import AsyncCallbackHandler
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from langchain_core.language_models import (
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from langchain_core.language_models import (
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FakeListChatModel,
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FakeListChatModel,
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FakeMessagesListChatModel,
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GenericFakeChatModel,
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GenericFakeChatModel,
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ParrotFakeChatModel,
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ParrotFakeChatModel,
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)
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)
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from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage
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from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage, HumanMessage
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from langchain_core.outputs import ChatGenerationChunk, GenerationChunk
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from langchain_core.outputs import ChatGenerationChunk, GenerationChunk
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from tests.unit_tests.stubs import (
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from tests.unit_tests.stubs import (
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_any_id_ai_message,
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_any_id_ai_message,
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@ -230,3 +232,18 @@ def test_fake_list_chat_model_batch() -> None:
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fake = FakeListChatModel(responses=["a", "b", "c"])
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fake = FakeListChatModel(responses=["a", "b", "c"])
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resp = fake.batch(["1", "2", "3"])
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resp = fake.batch(["1", "2", "3"])
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assert resp == expected
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assert resp == expected
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def test_fake_messages_list_chat_model_sleep_delay() -> None:
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sleep_time = 0.1
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model = FakeMessagesListChatModel(
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responses=[AIMessage(content="A"), AIMessage(content="B")],
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sleep=sleep_time,
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)
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messages = [HumanMessage(content="C")]
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start = time.time()
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model.invoke(messages)
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elapsed = time.time() - start
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assert elapsed >= sleep_time
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@ -2,6 +2,7 @@ from functools import partial
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from inspect import isclass
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from inspect import isclass
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from typing import Any, Union, cast
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from typing import Any, Union, cast
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import pytest
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from pydantic import BaseModel
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from pydantic import BaseModel
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from langchain_core.language_models import FakeListChatModel
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from langchain_core.language_models import FakeListChatModel
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@ -10,6 +11,7 @@ from langchain_core.load.load import loads
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from langchain_core.messages import HumanMessage
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from langchain_core.messages import HumanMessage
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from langchain_core.prompts.structured import StructuredPrompt
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from langchain_core.prompts.structured import StructuredPrompt
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from langchain_core.runnables.base import Runnable, RunnableLambda
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from langchain_core.runnables.base import Runnable, RunnableLambda
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from langchain_core.utils.mustache import ChevronError
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from langchain_core.utils.pydantic import is_basemodel_subclass
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from langchain_core.utils.pydantic import is_basemodel_subclass
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@ -128,3 +130,8 @@ def test_structured_prompt_template_format() -> None:
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assert prompt.invoke({"person": {"name": "foo"}}).to_messages() == [
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assert prompt.invoke({"person": {"name": "foo"}}).to_messages() == [
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HumanMessage("hi foo")
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HumanMessage("hi foo")
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]
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]
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def test_structured_prompt_template_empty_vars() -> None:
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with pytest.raises(ChevronError, match="empty tag"):
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StructuredPrompt([("human", "hi {{}}")], schema={}, template_format="mustache")
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