mirror of https://github.com/hwchase17/langchain
google-vertexai[minor]: added safety_settings property to gemini wrapper (#15344)
**Description:** Gemini model has quite annoying default safety_settings settings. In addition, current VertexAI class doesn't provide a property to override such settings. So, this PR aims to - add safety_settings property to VertexAI - fix issue with incorrect LLM output parsing when LLM responds with appropriate 'blocked' response - fix issue with incorrect parsing LLM output when Gemini API blocks prompt itself as inappropriate - add safety_settings related tests I'm not enough familiar with langchain code base and guidelines. So, any comments and/or suggestions are very welcome. **Issue:** it will likely fix #14841 --------- Co-authored-by: Erick Friis <erick@langchain.dev>pull/16211/head
Eugene Zapolsky
6 months ago
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GitHub
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from langchain_google_vertexai._enums import HarmBlockThreshold, HarmCategory
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from langchain_google_vertexai.chat_models import ChatVertexAI
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from langchain_google_vertexai.embeddings import VertexAIEmbeddings
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from langchain_google_vertexai.llms import VertexAI, VertexAIModelGarden
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__all__ = ["ChatVertexAI", "VertexAIEmbeddings", "VertexAI", "VertexAIModelGarden"]
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__all__ = [
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"ChatVertexAI",
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"VertexAIEmbeddings",
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"VertexAI",
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"VertexAIModelGarden",
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"HarmBlockThreshold",
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"HarmCategory",
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]
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from vertexai.preview.generative_models import ( # type: ignore
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HarmBlockThreshold,
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HarmCategory,
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)
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__all__ = ["HarmBlockThreshold", "HarmCategory"]
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from langchain_core.outputs import LLMResult
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from langchain_google_vertexai import HarmBlockThreshold, HarmCategory, VertexAI
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SAFETY_SETTINGS = {
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HarmCategory.HARM_CATEGORY_UNSPECIFIED: HarmBlockThreshold.BLOCK_NONE,
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HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
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HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
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HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
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HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
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}
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# below context and question are taken from one of opensource QA datasets
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BLOCKED_PROMPT = """
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You are agent designed to answer questions.
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You are given context in triple backticks.
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```
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The religion\'s failure to report abuse allegations to authorities has also been
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criticized. The Watch Tower Society\'s policy is that elders inform authorities when
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required by law to do so, but otherwise leave that action up to the victim and his
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or her family. The Australian Royal Commission into Institutional Responses to Child
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Sexual Abuse found that of 1006 alleged perpetrators of child sexual abuse
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identified by the Jehovah\'s Witnesses within their organization since 1950,
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"not one was reported by the church to secular authorities." William Bowen, a former
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Jehovah\'s Witness elder who established the Silentlambs organization to assist sex
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abuse victims within the religion, has claimed Witness leaders discourage followers
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from reporting incidents of sexual misconduct to authorities, and other critics claim
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the organization is reluctant to alert authorities in order to protect its "crime-free"
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reputation. In court cases in the United Kingdom and the United States the Watch Tower
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Society has been found to have been negligent in its failure to protect children from
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known sex offenders within the congregation and the Society has settled other child
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abuse lawsuits out of court, reportedly paying as much as $780,000 to one plaintiff
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without admitting wrongdoing.
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```
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Question: What have courts in both the UK and the US found the Watch Tower Society to
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have been for failing to protect children from sexual predators within the
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congregation ?
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Answer:
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"""
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def test_gemini_safety_settings_generate() -> None:
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llm = VertexAI(model_name="gemini-pro", safety_settings=SAFETY_SETTINGS)
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output = llm.generate(["What do you think about child abuse:"])
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assert isinstance(output, LLMResult)
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assert len(output.generations) == 1
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generation_info = output.generations[0][0].generation_info
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assert generation_info is not None
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assert len(generation_info) > 0
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assert not generation_info.get("is_blocked")
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blocked_output = llm.generate([BLOCKED_PROMPT])
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assert isinstance(blocked_output, LLMResult)
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assert len(blocked_output.generations) == 1
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assert len(blocked_output.generations[0]) == 0
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# test safety_settings passed directly to generate
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llm = VertexAI(model_name="gemini-pro")
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output = llm.generate(
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["What do you think about child abuse:"], safety_settings=SAFETY_SETTINGS
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)
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assert isinstance(output, LLMResult)
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assert len(output.generations) == 1
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generation_info = output.generations[0][0].generation_info
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assert generation_info is not None
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assert len(generation_info) > 0
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assert not generation_info.get("is_blocked")
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async def test_gemini_safety_settings_agenerate() -> None:
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llm = VertexAI(model_name="gemini-pro", safety_settings=SAFETY_SETTINGS)
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output = await llm.agenerate(["What do you think about child abuse:"])
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assert isinstance(output, LLMResult)
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assert len(output.generations) == 1
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generation_info = output.generations[0][0].generation_info
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assert generation_info is not None
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assert len(generation_info) > 0
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assert not generation_info.get("is_blocked")
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blocked_output = await llm.agenerate([BLOCKED_PROMPT])
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assert isinstance(blocked_output, LLMResult)
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assert len(blocked_output.generations) == 1
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# assert len(blocked_output.generations[0][0].generation_info) > 0
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# assert blocked_output.generations[0][0].generation_info.get("is_blocked")
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# test safety_settings passed directly to agenerate
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llm = VertexAI(model_name="gemini-pro")
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output = await llm.agenerate(
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["What do you think about child abuse:"], safety_settings=SAFETY_SETTINGS
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)
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assert isinstance(output, LLMResult)
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assert len(output.generations) == 1
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generation_info = output.generations[0][0].generation_info
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assert generation_info is not None
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assert len(generation_info) > 0
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assert not generation_info.get("is_blocked")
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