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"jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"] [metadata] lock-version = "2.0" python-versions = ">=3.10,<4.0" -content-hash = "53516562055d56da19caa612888302112845b0d2c2c272a7220d2a43b5d7968d" +content-hash = "1c9222993daf4821949c02fdabb08d550ea8a4e9c1e9ee9f68a297641033458c" diff --git a/pyproject.toml b/pyproject.toml index a0ad087..9042f6a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -9,18 +9,22 @@ packages = [{include = "streamlit_agent"}] [tool.poetry.dependencies] python = ">=3.10,<4.0" -langchain = {version = ">=0.0.252"} -openai = "^0.27.8" +langchain = {version = ">=0.1.0"} +openai = ">=1.6.1" duckduckgo-search = "^3.8.3" pypdf = "^3.12.2" sentence-transformers = "^2.2.2" torch = ">=2.0.0, !=2.0.1" tabulate = "^0.9.0" streamlit-feedback = "^0.0.9" -langchain-experimental = "^0.0.10" +langchain-experimental = "^0.0.49" streamlit = ">=1.26" docarray = "^0.38.0" hnswlib = "^0.7.0" +langchain-community = "^0.0.12" +langchain-openai = "^0.0.2.post1" +numexpr = "^2.8.8" +langchainhub = "^0.1.14" [tool.poetry.group.dev.dependencies] black = "^23.3.0" diff --git a/streamlit_agent/basic_memory.py b/streamlit_agent/basic_memory.py index 9e1a766..2de2246 100644 --- a/streamlit_agent/basic_memory.py +++ b/streamlit_agent/basic_memory.py @@ -1,8 +1,8 @@ from langchain.chains import LLMChain -from langchain.llms import OpenAI from langchain.memory import ConversationBufferMemory -from langchain.memory.chat_message_histories import StreamlitChatMessageHistory from langchain.prompts import PromptTemplate +from langchain_community.chat_message_histories import StreamlitChatMessageHistory +from langchain_openai import OpenAI import streamlit as st st.set_page_config(page_title="StreamlitChatMessageHistory", page_icon="📖") @@ -49,8 +49,8 @@ for msg in msgs.messages: if prompt := st.chat_input(): st.chat_message("human").write(prompt) # Note: new messages are saved to history automatically by Langchain during run - response = llm_chain.run(prompt) - st.chat_message("ai").write(response) + response = llm_chain.invoke(prompt) + st.chat_message("ai").write(response["text"]) # Draw the messages at the end, so newly generated ones show up immediately with view_messages: diff --git a/streamlit_agent/basic_streaming.py b/streamlit_agent/basic_streaming.py index d90e856..ec70ae2 100644 --- a/streamlit_agent/basic_streaming.py +++ b/streamlit_agent/basic_streaming.py @@ -1,6 +1,6 @@ from langchain.callbacks.base import BaseCallbackHandler -from langchain.chat_models import ChatOpenAI from langchain.schema import ChatMessage +from langchain_openai import ChatOpenAI import streamlit as st @@ -34,5 +34,5 @@ if prompt := st.chat_input(): with st.chat_message("assistant"): stream_handler = StreamHandler(st.empty()) llm = ChatOpenAI(openai_api_key=openai_api_key, streaming=True, callbacks=[stream_handler]) - response = llm(st.session_state.messages) + response = llm.invoke(st.session_state.messages) st.session_state.messages.append(ChatMessage(role="assistant", content=response.content)) diff --git a/streamlit_agent/callbacks/capturing_callback_handler.py b/streamlit_agent/callbacks/capturing_callback_handler.py index 110f437..de640ac 100644 --- a/streamlit_agent/callbacks/capturing_callback_handler.py +++ b/streamlit_agent/callbacks/capturing_callback_handler.py @@ -92,7 +92,7 @@ def playback_callbacks( # Return the agent's result for record in records: if record["callback_type"] == CallbackType.ON_AGENT_FINISH: - return record["args"][0][0]["output"] + return record["args"][0].return_values return "[Missing Agent Result]" @@ -107,16 +107,12 @@ class CapturingCallbackHandler(BaseCallbackHandler): with open(path, "wb") as file: pickle.dump(self._records, file) - def _append_record( - self, type: str, args: tuple[Any, ...], kwargs: dict[str, Any] - ) -> None: + def _append_record(self, type: str, args: tuple[Any, ...], kwargs: dict[str, Any]) -> None: time_now = time.time() time_delta = time_now - self._last_time if self._last_time is not None else 0 self._last_time = time_now self._records.append( - CallbackRecord( - callback_type=type, args=args, kwargs=kwargs, time_delta=time_delta - ) + CallbackRecord(callback_type=type, args=args, kwargs=kwargs, time_delta=time_delta) ) def on_llm_start(self, *args: Any, **kwargs: Any) -> None: diff --git a/streamlit_agent/chat_pandas_df.py b/streamlit_agent/chat_pandas_df.py index 73c2eb8..f64b242 100644 --- a/streamlit_agent/chat_pandas_df.py +++ b/streamlit_agent/chat_pandas_df.py @@ -1,5 +1,5 @@ from langchain.agents import AgentType -from langchain.agents import create_pandas_dataframe_agent +from langchain_experimental.agents import create_pandas_dataframe_agent from langchain.callbacks import StreamlitCallbackHandler from langchain.chat_models import ChatOpenAI import streamlit as st diff --git a/streamlit_agent/mrkl_demo.py b/streamlit_agent/mrkl_demo.py index 095ecc3..3aa93e9 100644 --- a/streamlit_agent/mrkl_demo.py +++ b/streamlit_agent/mrkl_demo.py @@ -2,14 +2,14 @@ from pathlib import Path import streamlit as st -from langchain import SQLDatabase -from langchain.agents import AgentType -from langchain.agents import initialize_agent, Tool -from langchain.callbacks import StreamlitCallbackHandler +from langchain import hub +from langchain.agents import AgentExecutor, Tool, create_react_agent from langchain.chains import LLMMathChain -from langchain.llms import OpenAI -from langchain.utilities import DuckDuckGoSearchAPIWrapper +from langchain_community.callbacks import StreamlitCallbackHandler +from langchain_community.utilities import DuckDuckGoSearchAPIWrapper, SQLDatabase +from langchain_core.runnables import RunnableConfig from langchain_experimental.sql import SQLDatabaseChain +from langchain_openai import OpenAI from streamlit_agent.callbacks.capturing_callback_handler import playback_callbacks from streamlit_agent.clear_results import with_clear_container @@ -18,7 +18,7 @@ DB_PATH = (Path(__file__).parent / "Chinook.db").absolute() SAVED_SESSIONS = { "Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?": "leo.pickle", - "What is the full name of the artist who recently released an album called " + "What is the full name of the female artist who recently released an album called " "'The Storm Before the Calm' and are they in the FooBar database? If so, what albums of theirs " "are in the FooBar database?": "alanis.pickle", } @@ -66,7 +66,8 @@ tools = [ ] # Initialize agent -mrkl = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True) +react_agent = create_react_agent(llm, tools, hub.pull("hwchase17/react")) +mrkl = AgentExecutor(agent=react_agent, tools=tools) with st.form(key="form"): if not enable_custom: @@ -87,6 +88,8 @@ if with_clear_container(submit_clicked): answer_container = output_container.chat_message("assistant", avatar="🦜") st_callback = StreamlitCallbackHandler(answer_container) + cfg = RunnableConfig() + cfg["callbacks"] = [st_callback] # If we've saved this question, play it back instead of actually running LangChain # (so that we don't exhaust our API calls unnecessarily) @@ -96,6 +99,6 @@ if with_clear_container(submit_clicked): print(f"Playing saved session: {session_path}") answer = playback_callbacks([st_callback], str(session_path), max_pause_time=2) else: - answer = mrkl.run(user_input, callbacks=[st_callback]) + answer = mrkl.invoke({"input": user_input}, cfg) - answer_container.write(answer) + answer_container.write(answer["output"]) diff --git a/streamlit_agent/runs/alanis.pickle b/streamlit_agent/runs/alanis.pickle index d35fe86..5449007 100644 Binary files a/streamlit_agent/runs/alanis.pickle and b/streamlit_agent/runs/alanis.pickle differ diff --git a/streamlit_agent/runs/leo.pickle b/streamlit_agent/runs/leo.pickle index 41d32e9..b54b8a5 100644 Binary files a/streamlit_agent/runs/leo.pickle and b/streamlit_agent/runs/leo.pickle differ diff --git a/streamlit_agent/search_and_chat.py b/streamlit_agent/search_and_chat.py index 0220b7f..2602663 100644 --- a/streamlit_agent/search_and_chat.py +++ b/streamlit_agent/search_and_chat.py @@ -1,9 +1,11 @@ from langchain.agents import ConversationalChatAgent, AgentExecutor -from langchain.callbacks import StreamlitCallbackHandler -from langchain.chat_models import ChatOpenAI from langchain.memory import ConversationBufferMemory -from langchain.memory.chat_message_histories import StreamlitChatMessageHistory -from langchain.tools import DuckDuckGoSearchRun +from langchain_community.callbacks import StreamlitCallbackHandler +from langchain_community.chat_message_histories import StreamlitChatMessageHistory +from langchain_community.tools import DuckDuckGoSearchRun +from langchain_core.runnables import RunnableConfig +from langchain_openai import ChatOpenAI + import streamlit as st st.set_page_config(page_title="LangChain: Chat with search", page_icon="🦜") @@ -51,6 +53,8 @@ if prompt := st.chat_input(placeholder="Who won the Women's U.S. Open in 2018?") ) with st.chat_message("assistant"): st_cb = StreamlitCallbackHandler(st.container(), expand_new_thoughts=False) - response = executor(prompt, callbacks=[st_cb]) + cfg = RunnableConfig() + cfg["callbacks"] = [st_cb] + response = executor.invoke(prompt, cfg) st.write(response["output"]) st.session_state.steps[str(len(msgs.messages) - 1)] = response["intermediate_steps"] diff --git a/streamlit_agent/simple_feedback.py b/streamlit_agent/simple_feedback.py index 3c303c9..718f374 100644 --- a/streamlit_agent/simple_feedback.py +++ b/streamlit_agent/simple_feedback.py @@ -1,11 +1,14 @@ -from langchain.llms import OpenAI -from langchain.callbacks import LangChainTracer from langchain.chains import ConversationChain from langchain.memory import ConversationBufferMemory -from langchain.memory.chat_message_histories import StreamlitChatMessageHistory +from langchain_community.chat_message_histories import StreamlitChatMessageHistory +from langchain_core.runnables import RunnableConfig +from langchain_core.tracers import LangChainTracer +from langchain_core.tracers.run_collector import RunCollectorCallbackHandler +from langchain_openai import OpenAI from langsmith import Client import streamlit as st from streamlit_feedback import streamlit_feedback +import time st.set_page_config(page_title="LangChain: Simple feedback", page_icon="🦜") st.title("🦜 LangChain: Simple feedback") @@ -25,6 +28,9 @@ if not langchain_api_key or not openai_api_key: langchain_endpoint = "https://api.smith.langchain.com" client = Client(api_url=langchain_endpoint, api_key=langchain_api_key) ls_tracer = LangChainTracer(project_name=project, client=client) +run_collector = RunCollectorCallbackHandler() +cfg = RunnableConfig() +cfg["callbacks"] = [ls_tracer, run_collector] msgs = StreamlitChatMessageHistory() memory = ConversationBufferMemory(chat_memory=msgs) @@ -43,13 +49,14 @@ for msg in msgs.messages: if input := st.chat_input(placeholder="Tell me a joke about a shark?"): st.chat_message("user").write(input) with st.chat_message("assistant"): - response = llm_chain(input, callbacks=[ls_tracer], include_run_info=True) + response = llm_chain.invoke(input, cfg) st.write(response["response"]) - st.session_state.last_run = response["__run"].run_id + st.session_state.last_run = run_collector.traced_runs[0].id @st.cache_data(ttl="2h", show_spinner=False) def get_run_url(run_id): + time.sleep(1) return client.read_run(run_id).url