From fa1fcb15328a6749707ab1985cd7ec636b052802 Mon Sep 17 00:00:00 2001 From: paulpaliychuk Date: Tue, 20 Feb 2024 14:13:47 -0500 Subject: [PATCH 1/4] wip --- .../app/classification_chain.py | 128 +++++++++ examples/langchain-langserve/app/server.py | 2 + examples/langchain-langserve/poetry.lock | 268 +++++++++++++++++- examples/langchain-langserve/pyproject.toml | 1 + 4 files changed, 397 insertions(+), 2 deletions(-) create mode 100644 examples/langchain-langserve/app/classification_chain.py diff --git a/examples/langchain-langserve/app/classification_chain.py b/examples/langchain-langserve/app/classification_chain.py new file mode 100644 index 00000000..e2479945 --- /dev/null +++ b/examples/langchain-langserve/app/classification_chain.py @@ -0,0 +1,128 @@ +import os +from typing import List + +from langchain.callbacks.tracers import ConsoleCallbackHandler +from langchain.schema import format_document +from langchain_core.documents import Document +from langchain_core.output_parsers import StrOutputParser +from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder +from langchain_core.prompts.prompt import PromptTemplate +from langchain_core.pydantic_v1 import BaseModel +from langchain_core.runnables import ( + ConfigurableField, + RunnableLambda, + RunnableParallel, + RunnablePassthrough, + RunnableBranch +) +from langchain_core.runnables.history import RunnableWithMessageHistory +from langchain_core.runnables.utils import ConfigurableFieldSingleOption +from langchain_openai import ChatOpenAI + +from zep_python import ZepClient +from zep_python.langchain import ZepChatMessageHistory, ZepVectorStore + +from langchain_community.chat_models import ChatAnthropic + +ZEP_API_KEY = os.environ.get("ZEP_API_KEY") # Required for Zep Cloud +ZEP_API_URL = os.environ.get( + "ZEP_API_URL" +) # only required if you're using Zep Open Source + +if ZEP_API_KEY is None: + raise ValueError( + "ZEP_API_KEY is required for Zep Cloud. " + "Remove this check if using Zep Open Source." + ) + +zep = ZepClient( + api_key=ZEP_API_KEY, + api_url=ZEP_API_URL, # only required if you're using Zep Open Source +) + +langchain_chain = ( + PromptTemplate.from_template( + """You are an expert in langchain. \ + Always answer questions starting with "As Harrison Chase told me". \ + Respond to the following question: + + Question: {question} + Answer:""" + ) + | ChatAnthropic() +) +anthropic_chain = ( + PromptTemplate.from_template( + """You are an expert in anthropic. \ + Always answer questions starting with "As Dario Amodei told me". \ + Respond to the following question: + + Question: {question} + Answer:""" + ) + | ChatAnthropic() +) +general_chain = ( + PromptTemplate.from_template( + """Respond to the following question: + + Question: {question} + Answer:""" + ) + | ChatAnthropic() +) + +branch = RunnableBranch( + (lambda x: "anthropic" in x["topic"].lower(), anthropic_chain), + (lambda x: "langchain" in x["topic"].lower(), langchain_chain), + general_chain, +) + +topic_classifier = ( + PromptTemplate.from_template( + """Given the user question below, classify it as either being about `LangChain`, `Anthropic`, or `Other`. + + Do not respond with more than one word. + + + {question} + + + Classification:""" + ) + | ChatAnthropic() + | StrOutputParser() +) + + +# User input +class UserInput(BaseModel): + question: str + session_id: str + +def invoke_chain(user_input: UserInput): + result_chain = RunnableWithMessageHistory( + RunnablePassthrough.assign(session_id=lambda x: user_input["session_id"]) + | { + "topic": topic_classifier, + "question": lambda x: x["question"], + "topic_z": lambda x: zep.memory.class, + } | branch, + lambda session_id: ZepChatMessageHistory( + session_id=session_id, + zep_client=zep, + memory_type="perpetual", + ), + input_messages_key="question", + history_messages_key="chat_history", + ) + + return result_chain.invoke( + user_input, config={"configurable": {"session_id": user_input["session_id"]}} + ) + +chain = ( + RunnableLambda(invoke_chain) + .with_types(input_type=UserInput) + .with_config(callbacks=[ConsoleCallbackHandler()]) +) \ No newline at end of file diff --git a/examples/langchain-langserve/app/server.py b/examples/langchain-langserve/app/server.py index d597243f..b45b973f 100644 --- a/examples/langchain-langserve/app/server.py +++ b/examples/langchain-langserve/app/server.py @@ -10,6 +10,7 @@ chain as message_history_vector_store_chain, ) from rag_vector_store_chain import chain as rag_vector_store_chain +from classification_chain import chain as classification_chain app = FastAPI() @@ -24,6 +25,7 @@ async def redirect_root_to_docs(): add_routes( app, message_history_vector_store_chain, path="/message_history_vector_store" ) +add_routes(app, classification_chain, path="/classification") if __name__ == "__main__": import uvicorn diff --git a/examples/langchain-langserve/poetry.lock b/examples/langchain-langserve/poetry.lock index 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langserve = {extras = ["server"], version = ">=0.0.30"} pydantic = ">2, <3" +anthropic = "^0.16.0" [tool.poetry.group.dev.dependencies] From dfa1aecd01a4ef8d10b4ca6cbb769c7a17169047 Mon Sep 17 00:00:00 2001 From: paulpaliychuk Date: Tue, 20 Feb 2024 14:38:21 -0500 Subject: [PATCH 2/4] feat: Set up an example using zep memory classification --- .../app/classification_chain.py | 30 +++++++++++-------- 1 file changed, 17 insertions(+), 13 deletions(-) diff --git a/examples/langchain-langserve/app/classification_chain.py b/examples/langchain-langserve/app/classification_chain.py index e2479945..ac3b7d0c 100644 --- a/examples/langchain-langserve/app/classification_chain.py +++ b/examples/langchain-langserve/app/classification_chain.py @@ -1,26 +1,18 @@ import os -from typing import List from langchain.callbacks.tracers import ConsoleCallbackHandler -from langchain.schema import format_document -from langchain_core.documents import Document from langchain_core.output_parsers import StrOutputParser -from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder from langchain_core.prompts.prompt import PromptTemplate from langchain_core.pydantic_v1 import BaseModel from langchain_core.runnables import ( - ConfigurableField, RunnableLambda, - RunnableParallel, RunnablePassthrough, RunnableBranch ) from langchain_core.runnables.history import RunnableWithMessageHistory -from langchain_core.runnables.utils import ConfigurableFieldSingleOption -from langchain_openai import ChatOpenAI from zep_python import ZepClient -from zep_python.langchain import ZepChatMessageHistory, ZepVectorStore +from zep_python.langchain import ZepChatMessageHistory from langchain_community.chat_models import ChatAnthropic @@ -100,13 +92,24 @@ class UserInput(BaseModel): question: str session_id: str + +def classify_session(session_id: str): + result = zep.memory.classify_session( + session_id, + "tool", + ["langchain", "anthropic", "none"], + last_n=1, + persist=False + ) + return result.class_ + + def invoke_chain(user_input: UserInput): result_chain = RunnableWithMessageHistory( RunnablePassthrough.assign(session_id=lambda x: user_input["session_id"]) | { - "topic": topic_classifier, "question": lambda x: x["question"], - "topic_z": lambda x: zep.memory.class, + "topic": lambda x: classify_session(x["session_id"]), } | branch, lambda session_id: ZepChatMessageHistory( session_id=session_id, @@ -115,14 +118,15 @@ def invoke_chain(user_input: UserInput): ), input_messages_key="question", history_messages_key="chat_history", - ) + ) return result_chain.invoke( user_input, config={"configurable": {"session_id": user_input["session_id"]}} ) + chain = ( RunnableLambda(invoke_chain) .with_types(input_type=UserInput) .with_config(callbacks=[ConsoleCallbackHandler()]) -) \ No newline at end of file +) From 8bbc3014b0875e2b4d52f73a19a65626c7c9ec01 Mon Sep 17 00:00:00 2001 From: paulpaliychuk Date: Wed, 21 Feb 2024 14:50:10 -0500 Subject: [PATCH 3/4] feat: A more complete classification langchain example --- .../app/classification_chain.py | 5 +- .../app/real_world_classification.py | 135 ++++++ examples/langchain-langserve/app/server.py | 3 +- examples/langchain-langserve/poetry.lock | 454 +++++++++++++++++- examples/langchain-langserve/pyproject.toml | 3 + 5 files changed, 595 insertions(+), 5 deletions(-) create mode 100644 examples/langchain-langserve/app/real_world_classification.py diff --git a/examples/langchain-langserve/app/classification_chain.py b/examples/langchain-langserve/app/classification_chain.py index ac3b7d0c..90d0d5f7 100644 --- a/examples/langchain-langserve/app/classification_chain.py +++ b/examples/langchain-langserve/app/classification_chain.py @@ -96,10 +96,9 @@ class UserInput(BaseModel): def classify_session(session_id: str): result = zep.memory.classify_session( session_id, - "tool", + "intent", ["langchain", "anthropic", "none"], - last_n=1, - persist=False + persist=True ) return result.class_ diff --git a/examples/langchain-langserve/app/real_world_classification.py b/examples/langchain-langserve/app/real_world_classification.py new file mode 100644 index 00000000..ba0cbb3c --- /dev/null +++ b/examples/langchain-langserve/app/real_world_classification.py @@ -0,0 +1,135 @@ +import os +from langchain_core.output_parsers import StrOutputParser +from langchain.callbacks.tracers import ConsoleCallbackHandler +from langchain_core.prompts.prompt import PromptTemplate +from langchain_core.pydantic_v1 import BaseModel +from langchain_core.runnables import ( + RunnableLambda, + RunnablePassthrough, + RunnableBranch +) +from langchain_core.runnables.history import RunnableWithMessageHistory +from zep_python import ZepClient +from zep_python.langchain import ZepChatMessageHistory +from langchain_community.utilities import WikipediaAPIWrapper +from langchain_community.chat_models import ChatOpenAI +from langchain.agents import AgentType, initialize_agent, AgentExecutor +from langchain_community.tools.yahoo_finance_news import YahooFinanceNewsTool +from langchain_community.tools import WikipediaQueryRun +from langchain.agents import load_tools + +ZEP_API_KEY = os.environ.get("ZEP_API_KEY") # Required for Zep Cloud +ZEP_API_URL = os.environ.get( + "ZEP_API_URL" +) # only required if you're using Zep Open Source + +llm = ChatOpenAI(temperature=0.0) +yahoo_chain = initialize_agent( + [YahooFinanceNewsTool()], + llm, + agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, + verbose=True, + handle_parsing_errors=True, +) + +stack_chain = initialize_agent( + load_tools(["stackexchange"]), + llm, + agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, + verbose=True, + handle_parsing_errors=True, +) + +wiki_chain = initialize_agent( + [WikipediaQueryRun(api_wrapper=WikipediaAPIWrapper())], + llm, + agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, + verbose=True, + handle_parsing_errors=True, +) + +if ZEP_API_KEY is None: + raise ValueError( + "ZEP_API_KEY is required for Zep Cloud. " + "Remove this check if using Zep Open Source." + ) + +zep = ZepClient( + api_key=ZEP_API_KEY, + api_url=ZEP_API_URL, # only required if you're using Zep Open Source +) + +wikipedia_search_prompt = PromptTemplate.from_template( + """Please answer the question based only on the following context: +Context: {context} +Question: {question} +Answer:""" +) + + +def invoke_agent_executor(agent: AgentExecutor, x: any): + result = agent.invoke(input=x["question"]) + return result["output"] + + +general_chain = PromptTemplate.from_template( + """Please say that you cannot answer the question, be sarcastic: + +Question: {question} +Answer:""" +) + +branch = RunnableBranch( + (lambda x: "research" in x["topic"].lower(), lambda x: invoke_agent_executor(wiki_chain, x)), + (lambda x: "finance_news" in x["topic"].lower(), lambda x: invoke_agent_executor(yahoo_chain, x)), + (lambda x: "dev_question" in x["topic"].lower(), lambda x: invoke_agent_executor(stack_chain, x)), + general_chain | StrOutputParser(), +) + + +# User input +class UserInput(BaseModel): + question: str + session_id: str + + +def classify_session(session_id: str): + result = zep.memory.classify_session( + session_id, + "intent", + [ + "research", + "dev_question", + "finance_news", + "none", + ], + ) + return result.class_ + + +def invoke_chain(user_input: UserInput): + result_chain = RunnableWithMessageHistory( + RunnablePassthrough.assign(session_id=lambda x: user_input["session_id"]) + | { + "question": lambda x: x["question"], + "topic": lambda x: classify_session(x["session_id"]), + } | branch, + lambda session_id: ZepChatMessageHistory( + session_id=session_id, + zep_client=zep, + memory_type="perpetual", + ), + input_messages_key="question", + history_messages_key="chat_history", + ) + + return result_chain.invoke( + user_input, config={"configurable": {"session_id": user_input["session_id"]}} + ) + + +chain = ( + RunnableLambda(invoke_chain) + .with_types(input_type=UserInput) + .with_config(callbacks=[ConsoleCallbackHandler()]) +) diff --git a/examples/langchain-langserve/app/server.py b/examples/langchain-langserve/app/server.py index b45b973f..3475a452 100644 --- a/examples/langchain-langserve/app/server.py +++ b/examples/langchain-langserve/app/server.py @@ -11,7 +11,7 @@ ) from rag_vector_store_chain import chain as rag_vector_store_chain from classification_chain import chain as classification_chain - +from real_world_classification import chain as real_world_classification_chain app = FastAPI() @@ -26,6 +26,7 @@ async def redirect_root_to_docs(): app, message_history_vector_store_chain, path="/message_history_vector_store" ) add_routes(app, classification_chain, path="/classification") +add_routes(app, real_world_classification_chain, path="/real_world_classification") if __name__ == "__main__": import uvicorn diff --git a/examples/langchain-langserve/poetry.lock b/examples/langchain-langserve/poetry.lock index dbcec7e7..687d1425 100644 --- 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+] + +[package.dependencies] +six = ">=1.5" + +[[package]] +name = "pytz" +version = "2024.1" +description = "World timezone definitions, modern and historical" +optional = false +python-versions = "*" +files = [ + {file = "pytz-2024.1-py2.py3-none-any.whl", hash = "sha256:328171f4e3623139da4983451950b28e95ac706e13f3f2630a879749e7a8b319"}, + {file = "pytz-2024.1.tar.gz", hash = "sha256:2a29735ea9c18baf14b448846bde5a48030ed267578472d8955cd0e7443a9812"}, +] + [[package]] name = "pyyaml" version = "6.0.1" @@ -1347,6 +1697,7 @@ files = [ certifi = ">=2017.4.17" charset-normalizer = ">=2,<4" idna = ">=2.5,<4" +PySocks = {version = ">=1.5.6,<1.5.7 || >1.5.7", optional = true, markers = "extra == \"socks\""} urllib3 = ">=1.21.1,<3" [package.extras] @@ -1382,6 +1733,17 @@ files = [ {file = "shellingham-1.5.4.tar.gz", hash = "sha256:8dbca0739d487e5bd35ab3ca4b36e11c4078f3a234bfce294b0a0291363404de"}, ] +[[package]] +name = "six" +version = "1.16.0" +description = "Python 2 and 3 compatibility utilities" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*" +files = [ + {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"}, + {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"}, +] + [[package]] name = "smmap" version = "5.0.1" @@ -1404,6 +1766,17 @@ files = [ {file = "sniffio-1.3.0.tar.gz", hash = "sha256:e60305c5e5d314f5389259b7f22aaa33d8f7dee49763119234af3755c55b9101"}, ] +[[package]] +name = "soupsieve" +version = "2.5" +description = "A modern CSS selector implementation for Beautiful Soup." +optional = false +python-versions = ">=3.8" +files = [ + {file = "soupsieve-2.5-py3-none-any.whl", hash = "sha256:eaa337ff55a1579b6549dc679565eac1e3d000563bcb1c8ab0d0fefbc0c2cdc7"}, + {file = "soupsieve-2.5.tar.gz", hash = "sha256:5663d5a7b3bfaeee0bc4372e7fc48f9cff4940b3eec54a6451cc5299f1097690"}, +] + [[package]] name = "sqlalchemy" version = "2.0.25" @@ -1508,6 +1881,21 @@ fastapi = "*" starlette = "*" uvicorn = "*" +[[package]] +name = "stackapi" +version = "0.3.0" +description = "Library for interacting with the Stack Exchange API" +optional = false +python-versions = "*" +files = [ + {file = "StackAPI-0.3.0-py3-none-any.whl", hash = "sha256:217f494aae3b4f267a0e4f8565e1761c4e55ec30f0c5a50a205632a52ca28481"}, + {file = "StackAPI-0.3.0.tar.gz", hash = "sha256:4147c9587f1c719d1ff9e01a70216290766821f9f7c1401e47b60ee89c329288"}, +] + +[package.dependencies] +requests = "*" +six = "*" + [[package]] name = "starlette" version = "0.35.1" @@ -1747,6 +2135,17 @@ files = [ mypy-extensions = ">=0.3.0" typing-extensions = ">=3.7.4" +[[package]] +name = "tzdata" +version = "2024.1" +description = "Provider of IANA time zone data" +optional = false +python-versions = ">=2" +files = [ + {file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"}, + {file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"}, +] + [[package]] name = "urllib3" version = "2.2.0" @@ -1782,6 +2181,31 @@ h11 = ">=0.8" [package.extras] standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"] +[[package]] +name = "webencodings" +version = "0.5.1" +description = "Character encoding aliases for legacy web content" +optional = false +python-versions = "*" +files = [ + {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"}, + {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"}, +] + +[[package]] +name = "wikipedia" +version = "1.4.0" +description = "Wikipedia API for Python" +optional = false +python-versions = "*" +files = [ + {file = "wikipedia-1.4.0.tar.gz", hash = "sha256:db0fad1829fdd441b1852306e9856398204dc0786d2996dd2e0c8bb8e26133b2"}, +] + +[package.dependencies] +beautifulsoup4 = "*" +requests = ">=2.0.0,<3.0.0" + [[package]] name = "yarl" version = "1.9.4" @@ -1885,7 +2309,35 @@ files = [ idna = ">=2.0" multidict = ">=4.0" +[[package]] +name = "yfinance" +version = "0.2.36" +description = "Download market data from Yahoo! Finance API" +optional = false +python-versions = "*" +files = [ + {file = "yfinance-0.2.36-py2.py3-none-any.whl", hash = "sha256:700f8b8fb51d4f7ca31bcef042175be68b2f39ed680a99170163e5f54874e2a6"}, + {file = "yfinance-0.2.36.tar.gz", hash = "sha256:5367c0538cf57bb0dd393ca24866cda1ab5d4aba47e375e549760652a4a19fc2"}, +] + +[package.dependencies] +appdirs = ">=1.4.4" +beautifulsoup4 = ">=4.11.1" +frozendict = ">=2.3.4" +html5lib = ">=1.1" +lxml = ">=4.9.1" +multitasking = ">=0.0.7" +numpy = ">=1.16.5" +pandas = ">=1.3.0" +peewee = ">=3.16.2" +pytz = ">=2022.5" +requests = ">=2.31" + +[package.extras] +nospam = ["requests-cache (>=1.0)", "requests-ratelimiter (>=0.3.1)"] +repair = ["scipy (>=1.6.3)"] + [metadata] lock-version = "2.0" python-versions = "^3.11" -content-hash = "ea4cf42db9b8575574f5258d178c3e363da0e049534a09ec84d7311fca4569a2" +content-hash = "e41fda8122b79bf831b4e0c4e06928343aec7bb046882b0bae34f09c92e528e1" diff --git a/examples/langchain-langserve/pyproject.toml b/examples/langchain-langserve/pyproject.toml index a89b5a10..0f9016d9 100644 --- a/examples/langchain-langserve/pyproject.toml +++ b/examples/langchain-langserve/pyproject.toml @@ -14,6 +14,9 @@ uvicorn = "^0.23.2" langserve = {extras = ["server"], version = ">=0.0.30"} pydantic = ">2, <3" anthropic = "^0.16.0" +wikipedia = "^1.4.0" +yfinance = "^0.2.36" +stackapi = "^0.3.0" [tool.poetry.group.dev.dependencies] From a494d3d772d90d8cfebf5b9dcd3ed54797207480 Mon Sep 17 00:00:00 2001 From: paulpaliychuk Date: Wed, 21 Feb 2024 14:56:18 -0500 Subject: [PATCH 4/4] fix: Linter errors --- examples/chat_history/memory.py | 2 +- examples/chat_history/memory_async.py | 2 +- .../app/classification_chain.py | 51 ++++++++----------- .../app/real_world_classification.py | 39 ++++++++------ examples/langchain-langserve/app/server.py | 3 +- zep_python/memory/client.py | 4 +- 6 files changed, 51 insertions(+), 50 deletions(-) diff --git a/examples/chat_history/memory.py b/examples/chat_history/memory.py index e5e0a6af..12767edf 100644 --- a/examples/chat_history/memory.py +++ b/examples/chat_history/memory.py @@ -14,9 +14,9 @@ import time import uuid +from chat_history import history from dotenv import find_dotenv, load_dotenv -from chat_history import history from zep_python import ( APIError, NotFoundError, diff --git a/examples/chat_history/memory_async.py b/examples/chat_history/memory_async.py index b203981b..a91bebe4 100644 --- a/examples/chat_history/memory_async.py +++ b/examples/chat_history/memory_async.py @@ -15,9 +15,9 @@ import time import uuid +from chat_history import history from dotenv import find_dotenv, load_dotenv -from chat_history import history from zep_python import ( APIError, NotFoundError, diff --git a/examples/langchain-langserve/app/classification_chain.py b/examples/langchain-langserve/app/classification_chain.py index 90d0d5f7..ff11995d 100644 --- a/examples/langchain-langserve/app/classification_chain.py +++ b/examples/langchain-langserve/app/classification_chain.py @@ -1,21 +1,16 @@ import os from langchain.callbacks.tracers import ConsoleCallbackHandler +from langchain_community.chat_models import ChatAnthropic from langchain_core.output_parsers import StrOutputParser from langchain_core.prompts.prompt import PromptTemplate from langchain_core.pydantic_v1 import BaseModel -from langchain_core.runnables import ( - RunnableLambda, - RunnablePassthrough, - RunnableBranch -) +from langchain_core.runnables import RunnableBranch, RunnableLambda, RunnablePassthrough from langchain_core.runnables.history import RunnableWithMessageHistory from zep_python import ZepClient from zep_python.langchain import ZepChatMessageHistory -from langchain_community.chat_models import ChatAnthropic - ZEP_API_KEY = os.environ.get("ZEP_API_KEY") # Required for Zep Cloud ZEP_API_URL = os.environ.get( "ZEP_API_URL" @@ -33,35 +28,35 @@ ) langchain_chain = ( - PromptTemplate.from_template( - """You are an expert in langchain. \ + PromptTemplate.from_template( + """You are an expert in langchain. \ Always answer questions starting with "As Harrison Chase told me". \ Respond to the following question: Question: {question} Answer:""" - ) - | ChatAnthropic() + ) + | ChatAnthropic() ) anthropic_chain = ( - PromptTemplate.from_template( - """You are an expert in anthropic. \ + PromptTemplate.from_template( + """You are an expert in anthropic. \ Always answer questions starting with "As Dario Amodei told me". \ Respond to the following question: Question: {question} Answer:""" - ) - | ChatAnthropic() + ) + | ChatAnthropic() ) general_chain = ( - PromptTemplate.from_template( - """Respond to the following question: + PromptTemplate.from_template( + """Respond to the following question: Question: {question} Answer:""" - ) - | ChatAnthropic() + ) + | ChatAnthropic() ) branch = RunnableBranch( @@ -71,8 +66,8 @@ ) topic_classifier = ( - PromptTemplate.from_template( - """Given the user question below, classify it as either being about `LangChain`, `Anthropic`, or `Other`. + PromptTemplate.from_template( + """Given the user question below, classify it as either being about `LangChain`, `Anthropic`, or `Other`. Do not respond with more than one word. @@ -81,9 +76,9 @@ Classification:""" - ) - | ChatAnthropic() - | StrOutputParser() + ) + | ChatAnthropic() + | StrOutputParser() ) @@ -95,10 +90,7 @@ class UserInput(BaseModel): def classify_session(session_id: str): result = zep.memory.classify_session( - session_id, - "intent", - ["langchain", "anthropic", "none"], - persist=True + session_id, "intent", ["langchain", "anthropic", "none"], persist=True ) return result.class_ @@ -109,7 +101,8 @@ def invoke_chain(user_input: UserInput): | { "question": lambda x: x["question"], "topic": lambda x: classify_session(x["session_id"]), - } | branch, + } + | branch, lambda session_id: ZepChatMessageHistory( session_id=session_id, zep_client=zep, diff --git a/examples/langchain-langserve/app/real_world_classification.py b/examples/langchain-langserve/app/real_world_classification.py index ba0cbb3c..74e61e82 100644 --- a/examples/langchain-langserve/app/real_world_classification.py +++ b/examples/langchain-langserve/app/real_world_classification.py @@ -1,22 +1,19 @@ import os -from langchain_core.output_parsers import StrOutputParser + +from langchain.agents import AgentExecutor, AgentType, initialize_agent, load_tools from langchain.callbacks.tracers import ConsoleCallbackHandler +from langchain_community.chat_models import ChatOpenAI +from langchain_community.tools import WikipediaQueryRun +from langchain_community.tools.yahoo_finance_news import YahooFinanceNewsTool +from langchain_community.utilities import WikipediaAPIWrapper +from langchain_core.output_parsers import StrOutputParser from langchain_core.prompts.prompt import PromptTemplate from langchain_core.pydantic_v1 import BaseModel -from langchain_core.runnables import ( - RunnableLambda, - RunnablePassthrough, - RunnableBranch -) +from langchain_core.runnables import RunnableBranch, RunnableLambda, RunnablePassthrough from langchain_core.runnables.history import RunnableWithMessageHistory + from zep_python import ZepClient from zep_python.langchain import ZepChatMessageHistory -from langchain_community.utilities import WikipediaAPIWrapper -from langchain_community.chat_models import ChatOpenAI -from langchain.agents import AgentType, initialize_agent, AgentExecutor -from langchain_community.tools.yahoo_finance_news import YahooFinanceNewsTool -from langchain_community.tools import WikipediaQueryRun -from langchain.agents import load_tools ZEP_API_KEY = os.environ.get("ZEP_API_KEY") # Required for Zep Cloud ZEP_API_URL = os.environ.get( @@ -80,9 +77,18 @@ def invoke_agent_executor(agent: AgentExecutor, x: any): ) branch = RunnableBranch( - (lambda x: "research" in x["topic"].lower(), lambda x: invoke_agent_executor(wiki_chain, x)), - (lambda x: "finance_news" in x["topic"].lower(), lambda x: invoke_agent_executor(yahoo_chain, x)), - (lambda x: "dev_question" in x["topic"].lower(), lambda x: invoke_agent_executor(stack_chain, x)), + ( + lambda x: "research" in x["topic"].lower(), + lambda x: invoke_agent_executor(wiki_chain, x), + ), + ( + lambda x: "finance_news" in x["topic"].lower(), + lambda x: invoke_agent_executor(yahoo_chain, x), + ), + ( + lambda x: "dev_question" in x["topic"].lower(), + lambda x: invoke_agent_executor(stack_chain, x), + ), general_chain | StrOutputParser(), ) @@ -113,7 +119,8 @@ def invoke_chain(user_input: UserInput): | { "question": lambda x: x["question"], "topic": lambda x: classify_session(x["session_id"]), - } | branch, + } + | branch, lambda session_id: ZepChatMessageHistory( session_id=session_id, zep_client=zep, diff --git a/examples/langchain-langserve/app/server.py b/examples/langchain-langserve/app/server.py index 3475a452..ff18ce0d 100644 --- a/examples/langchain-langserve/app/server.py +++ b/examples/langchain-langserve/app/server.py @@ -2,6 +2,7 @@ load_dotenv(dotenv_path=find_dotenv()) +from classification_chain import chain as classification_chain from fastapi import FastAPI from fastapi.responses import RedirectResponse from langserve import add_routes @@ -10,8 +11,8 @@ chain as message_history_vector_store_chain, ) from rag_vector_store_chain import chain as rag_vector_store_chain -from classification_chain import chain as classification_chain from real_world_classification import chain as real_world_classification_chain + app = FastAPI() diff --git a/zep_python/memory/client.py b/zep_python/memory/client.py index a2caa61c..abce9341 100644 --- a/zep_python/memory/client.py +++ b/zep_python/memory/client.py @@ -6,6 +6,8 @@ from zep_python.exceptions import APIError, handle_response from zep_python.memory.models import ( + ClassifySessionRequest, + ClassifySessionResponse, Memory, MemorySearchPayload, MemorySearchResult, @@ -14,8 +16,6 @@ SearchScope, Session, Summary, - ClassifySessionRequest, - ClassifySessionResponse, ) from zep_python.message.models import Message from zep_python.utils import SearchType