Samantha/add conversation chain (#166)

Add MemoryChain and ConversationChain as chains that take a docstore in
addition to the prompt, and use the docstore to stuff context into the
prompt. This can be used to have an ongoing conversation with a chatbot.

Probably needs a bit of refactoring for code quality

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>

tests/unit_tests/chains/test_conversation.py

@@ -0,0 +1,68 @@
+"""Test conversation chain and memory."""
+import pytest
+
+from langchain.chains.base import Memory
+from langchain.chains.conversation.base import ConversationChain
+from langchain.chains.conversation.memory import (
+    ConversationBufferMemory,
+    ConversationSummaryMemory,
+)
+from langchain.prompts.prompt import PromptTemplate
+from tests.unit_tests.llms.fake_llm import FakeLLM
+
+
+def test_conversation_chain_works() -> None:
+    """Test that conversation chain works in basic setting."""
+    llm = FakeLLM()
+    prompt = PromptTemplate(input_variables=["foo", "bar"], template="{foo} {bar}")
+    memory = ConversationBufferMemory(dynamic_key="foo")
+    chain = ConversationChain(llm=llm, prompt=prompt, memory=memory, input_key="bar")
+    chain.run("foo")
+
+
+def test_conversation_chain_errors_bad_prompt() -> None:
+    """Test that conversation chain works in basic setting."""
+    llm = FakeLLM()
+    prompt = PromptTemplate(input_variables=[], template="nothing here")
+    with pytest.raises(ValueError):
+        ConversationChain(llm=llm, prompt=prompt)
+
+
+def test_conversation_chain_errors_bad_variable() -> None:
+    """Test that conversation chain works in basic setting."""
+    llm = FakeLLM()
+    prompt = PromptTemplate(input_variables=["foo"], template="{foo}")
+    memory = ConversationBufferMemory(dynamic_key="foo")
+    with pytest.raises(ValueError):
+        ConversationChain(llm=llm, prompt=prompt, memory=memory, input_key="foo")
+
+
+@pytest.mark.parametrize(
+    "memory",
+    [
+        ConversationBufferMemory(dynamic_key="baz"),
+        ConversationSummaryMemory(llm=FakeLLM(), dynamic_key="baz"),
+    ],
+)
+def test_conversation_memory(memory: Memory) -> None:
+    """Test basic conversation memory functionality."""
+    # This is a good input because the input is not the same as baz.
+    good_inputs = {"foo": "bar", "baz": "foo"}
+    # This is a good output because these is one variable.
+    good_outputs = {"bar": "foo"}
+    memory._save_context(good_inputs, good_outputs)
+    # This is a bad input because there are two variables that aren't the same as baz.
+    bad_inputs = {"foo": "bar", "foo1": "bar"}
+    with pytest.raises(ValueError):
+        memory._save_context(bad_inputs, good_outputs)
+    # This is a bad input because the only variable is the same as baz.
+    bad_inputs = {"baz": "bar"}
+    with pytest.raises(ValueError):
+        memory._save_context(bad_inputs, good_outputs)
+    # This is a bad output because it is empty.
+    with pytest.raises(ValueError):
+        memory._save_context(good_inputs, {})
+    # This is a bad output because there are two keys.
+    bad_outputs = {"foo": "bar", "foo1": "bar"}
+    with pytest.raises(ValueError):
+        memory._save_context(good_inputs, bad_outputs)