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b2a11ce686
### Prem SDK integration in LangChain This PR adds the integration with [PremAI's](https://www.premai.io/) prem-sdk with langchain. User can now access to deployed models (llms/embeddings) and use it with langchain's ecosystem. This PR adds the following: ### This PR adds the following: - [x] Add chat support - [X] Adding embedding support - [X] writing integration tests - [X] writing tests for chat - [X] writing tests for embedding - [X] writing unit tests - [X] writing tests for chat - [X] writing tests for embedding - [X] Adding documentation - [X] writing documentation for chat - [X] writing documentation for embedding - [X] run `make test` - [X] run `make lint`, `make lint_diff` - [X] Final checks (spell check, lint, format and overall testing) --------- Co-authored-by: Anindyadeep Sannigrahi <anindyadeepsannigrahi@Anindyadeeps-MacBook-Pro.local> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
71 lines
2.3 KiB
Python
71 lines
2.3 KiB
Python
"""Test ChatPremAI from PremAI API wrapper.
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Note: This test must be run with the PREMAI_API_KEY environment variable set to a valid
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API key and a valid project_id.
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For this we need to have a project setup in PremAI's platform: https://app.premai.io
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"""
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import pytest
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from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage
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from langchain_core.outputs import ChatGeneration, LLMResult
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from langchain_community.chat_models import ChatPremAI
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@pytest.fixture
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def chat() -> ChatPremAI:
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return ChatPremAI(project_id=8)
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def test_chat_premai() -> None:
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"""Test ChatPremAI wrapper."""
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chat = ChatPremAI(project_id=8)
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message = HumanMessage(content="Hello")
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response = chat([message])
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assert isinstance(response, BaseMessage)
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assert isinstance(response.content, str)
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def test_chat_prem_system_message() -> None:
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"""Test ChatPremAI wrapper for system message"""
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chat = ChatPremAI(project_id=8)
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system_message = SystemMessage(content="You are to chat with the user.")
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human_message = HumanMessage(content="Hello")
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response = chat([system_message, human_message])
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assert isinstance(response, BaseMessage)
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assert isinstance(response.content, str)
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def test_chat_prem_model() -> None:
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"""Test ChatPremAI wrapper handles model_name."""
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chat = ChatPremAI(model="foo", project_id=8)
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assert chat.model == "foo"
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def test_chat_prem_generate() -> None:
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"""Test ChatPremAI wrapper with generate."""
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chat = ChatPremAI(project_id=8)
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message = HumanMessage(content="Hello")
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response = chat.generate([[message], [message]])
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assert isinstance(response, LLMResult)
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assert len(response.generations) == 2
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for generations in response.generations:
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for generation in generations:
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assert isinstance(generation, ChatGeneration)
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assert isinstance(generation.text, str)
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assert generation.text == generation.message.content
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async def test_prem_invoke(chat: ChatPremAI) -> None:
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"""Tests chat completion with invoke"""
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result = chat.invoke("How is the weather in New York today?")
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assert isinstance(result.content, str)
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def test_prem_streaming() -> None:
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"""Test streaming tokens from Prem."""
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chat = ChatPremAI(project_id=8, streaming=True)
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for token in chat.stream("I'm Pickle Rick"):
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assert isinstance(token.content, str)
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