mirror of
https://github.com/hwchase17/langchain
synced 2024-11-20 03:25:56 +00:00
ed58eeb9c5
Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
83 lines
2.7 KiB
Python
83 lines
2.7 KiB
Python
"""Test MosaicML API wrapper."""
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import re
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import pytest
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from langchain_community.llms.mosaicml import PROMPT_FOR_GENERATION_FORMAT, MosaicML
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def test_mosaicml_llm_call() -> None:
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"""Test valid call to MosaicML."""
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llm = MosaicML(model_kwargs={})
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output = llm("Say foo:")
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assert isinstance(output, str)
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def test_mosaicml_endpoint_change() -> None:
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"""Test valid call to MosaicML."""
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new_url = "https://models.hosted-on.mosaicml.hosting/mpt-30b-instruct/v1/predict"
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llm = MosaicML(endpoint_url=new_url)
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assert llm.endpoint_url == new_url
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output = llm("Say foo:")
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assert isinstance(output, str)
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def test_mosaicml_extra_kwargs() -> None:
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llm = MosaicML(model_kwargs={"max_new_tokens": 1})
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assert llm.model_kwargs == {"max_new_tokens": 1}
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output = llm("Say foo:")
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assert isinstance(output, str)
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# should only generate one new token (which might be a new line or whitespace token)
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assert len(output.split()) <= 1
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def test_instruct_prompt() -> None:
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"""Test instruct prompt."""
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llm = MosaicML(inject_instruction_format=True, model_kwargs={"max_new_tokens": 10})
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instruction = "Repeat the word foo"
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prompt = llm._transform_prompt(instruction)
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expected_prompt = PROMPT_FOR_GENERATION_FORMAT.format(instruction=instruction)
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assert prompt == expected_prompt
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output = llm(prompt)
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assert isinstance(output, str)
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def test_retry_logic() -> None:
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"""Tests that two queries (which would usually exceed the rate limit) works"""
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llm = MosaicML(inject_instruction_format=True, model_kwargs={"max_new_tokens": 10})
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instruction = "Repeat the word foo"
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prompt = llm._transform_prompt(instruction)
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expected_prompt = PROMPT_FOR_GENERATION_FORMAT.format(instruction=instruction)
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assert prompt == expected_prompt
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output = llm(prompt)
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assert isinstance(output, str)
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output = llm(prompt)
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assert isinstance(output, str)
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def test_short_retry_does_not_loop() -> None:
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"""Tests that two queries with a short retry sleep does not infinite loop"""
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llm = MosaicML(
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inject_instruction_format=True,
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model_kwargs={"do_sample": False},
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retry_sleep=0.1,
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)
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instruction = "Repeat the word foo"
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prompt = llm._transform_prompt(instruction)
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expected_prompt = PROMPT_FOR_GENERATION_FORMAT.format(instruction=instruction)
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assert prompt == expected_prompt
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with pytest.raises(
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ValueError,
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match=re.escape(
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"Error raised by inference API: rate limit exceeded.\nResponse: You have "
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"reached maximum request limit.\n"
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),
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):
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for _ in range(10):
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output = llm(prompt)
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assert isinstance(output, str)
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