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fix(memory): allow internal chains to use memory (#6769)
Fixed #6768. This is a workaround only. I think a better longer-term solution is for chains to declare how many input variables they *actually* need (as opposed to ones that are in the prompt, where some may be satisfied by the memory). Then, a wrapping chain can check the input match against the actual input variables. @hwchase17
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@ -62,6 +62,9 @@ class SequentialChain(Chain):
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for chain in chains:
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missing_vars = set(chain.input_keys).difference(known_variables)
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if chain.memory:
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missing_vars = missing_vars.difference(chain.memory.memory_variables)
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if missing_vars:
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raise ValueError(
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f"Missing required input keys: {missing_vars}, "
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@ -6,6 +6,7 @@ import pytest
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from langchain.callbacks.manager import CallbackManagerForChainRun
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from langchain.chains.base import Chain
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from langchain.chains.sequential import SequentialChain, SimpleSequentialChain
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from langchain.memory import ConversationBufferMemory
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from langchain.memory.simple import SimpleMemory
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@ -81,6 +82,21 @@ def test_sequential_usage_memory() -> None:
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)
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def test_sequential_internal_chain_use_memory() -> None:
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"""Test sequential usage with memory for one of the internal chains."""
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memory = ConversationBufferMemory(memory_key="bla")
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memory.save_context({"input": "yo"}, {"output": "ya"})
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chain_1 = FakeChain(
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input_variables=["foo", "bla"], output_variables=["bar"], memory=memory
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)
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chain_2 = FakeChain(input_variables=["bar"], output_variables=["baz"])
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chain = SequentialChain(chains=[chain_1, chain_2], input_variables=["foo"])
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output = chain({"foo": "123"})
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print("HEYYY OUTPUT", output)
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expected_output = {"foo": "123", "baz": "123 Human: yo\nAI: yafoofoo"}
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assert output == expected_output
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def test_sequential_usage_multiple_outputs() -> None:
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"""Test sequential usage on multiple output chains."""
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chain_1 = FakeChain(input_variables=["foo"], output_variables=["bar", "test"])
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