mirror of
https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +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
78 lines
3.3 KiB
Python
78 lines
3.3 KiB
Python
from langchain_core.output_parsers import StrOutputParser
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from langchain_core.prompts import PromptTemplate
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from langchain_core.runnables import RunnableParallel
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import langchain_community.utilities.opaqueprompts as op
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from langchain_community.llms import OpenAI
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from langchain_community.llms.opaqueprompts import OpaquePrompts
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prompt_template = """
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As an AI assistant, you will answer questions according to given context.
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Sensitive personal information in the question is masked for privacy.
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For instance, if the original text says "Giana is good," it will be changed
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to "PERSON_998 is good."
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Here's how to handle these changes:
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* Consider these masked phrases just as placeholders, but still refer to
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them in a relevant way when answering.
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* It's possible that different masked terms might mean the same thing.
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Stick with the given term and don't modify it.
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* All masked terms follow the "TYPE_ID" pattern.
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* Please don't invent new masked terms. For instance, if you see "PERSON_998,"
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don't come up with "PERSON_997" or "PERSON_999" unless they're already in the question.
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Conversation History: ```{history}```
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Context : ```During our recent meeting on February 23, 2023, at 10:30 AM,
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John Doe provided me with his personal details. His email is johndoe@example.com
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and his contact number is 650-456-7890. He lives in New York City, USA, and
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belongs to the American nationality with Christian beliefs and a leaning towards
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the Democratic party. He mentioned that he recently made a transaction using his
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credit card 4111 1111 1111 1111 and transferred bitcoins to the wallet address
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1A1zP1eP5QGefi2DMPTfTL5SLmv7DivfNa. While discussing his European travels, he
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noted down his IBAN as GB29 NWBK 6016 1331 9268 19. Additionally, he provided
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his website as https://johndoeportfolio.com. John also discussed
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some of his US-specific details. He said his bank account number is
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1234567890123456 and his drivers license is Y12345678. His ITIN is 987-65-4321,
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and he recently renewed his passport,
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the number for which is 123456789. He emphasized not to share his SSN, which is
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669-45-6789. Furthermore, he mentioned that he accesses his work files remotely
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through the IP 192.168.1.1 and has a medical license number MED-123456. ```
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Question: ```{question}```
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"""
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def test_opaqueprompts() -> None:
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chain = PromptTemplate.from_template(prompt_template) | OpaquePrompts(llm=OpenAI())
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output = chain.invoke(
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{
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"question": "Write a text message to remind John to do password reset \
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for his website through his email to stay secure."
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}
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)
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assert isinstance(output, str)
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def test_opaqueprompts_functions() -> None:
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prompt = (PromptTemplate.from_template(prompt_template),)
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llm = OpenAI()
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pg_chain = (
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op.sanitize
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| RunnableParallel(
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secure_context=lambda x: x["secure_context"], # type: ignore
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response=(lambda x: x["sanitized_input"]) # type: ignore
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| prompt
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| llm
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| StrOutputParser(),
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)
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| (lambda x: op.desanitize(x["response"], x["secure_context"]))
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)
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pg_chain.invoke(
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{
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"question": "Write a text message to remind John to do password reset\
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for his website through his email to stay secure.",
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"history": "",
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}
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)
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