Templates (#12294)

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>

templates/openai-functions-agent/LICENSE

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+MIT License
+
+Copyright (c) 2023 LangChain, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

templates/openai-functions-agent/README.md

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+# OpenAI Functions Agent
+
+This template creates an agent that uses OpenAI function calling to communicate its decisions of what actions to take.
+This example creates an agent that can optionally look up things on the internet using Tavily's search engine.
+
+##  LLM
+
+This template will use `OpenAI` by default. 
+
+Be sure that `OPENAI_API_KEY` is set in your environment.
+
+##  Tools
+
+This template will use `Tavily` by default. 
+
+Be sure that `TAVILY_API_KEY` is set in your environment.

templates/openai-functions-agent/main.py

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+from openai_functions_agent.agent import agent_executor
+
+if __name__ == "__main__":
+    question = "who won the womens world cup in 2023?"
+    print(agent_executor.invoke({"input": question, "chat_history": []}))

templates/openai-functions-agent/openai_functions_agent/__init__.py

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+from openai_functions_agent.agent import agent_executor
+
+__all__ = ["agent_executor"]

templates/openai-functions-agent/openai_functions_agent/agent.py

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+from typing import List, Tuple
+from langchain.schema.messages import HumanMessage, AIMessage
+from langchain.chat_models import ChatOpenAI
+from langchain.agents import AgentExecutor
+from langchain.utilities.tavily_search import TavilySearchAPIWrapper
+from langchain.tools.tavily_search import TavilySearchResults
+from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain.tools.render import format_tool_to_openai_function
+from langchain.agents.format_scratchpad import format_to_openai_functions
+from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser
+from langchain.pydantic_v1 import BaseModel
+
+
+# Fake Tool
+search = TavilySearchAPIWrapper()
+tavily_tool = TavilySearchResults(api_wrapper=search)
+
+tools = [tavily_tool]
+
+llm = ChatOpenAI(temperature=0)
+prompt = ChatPromptTemplate.from_messages([
+    ("system", "You are very powerful assistant, but bad at calculating lengths of words."),
+    MessagesPlaceholder(variable_name="chat_history"),
+    ("user", "{input}"),
+    MessagesPlaceholder(variable_name="agent_scratchpad"),
+])
+
+llm_with_tools = llm.bind(
+    functions=[format_tool_to_openai_function(t) for t in tools]
+)
+
+def _format_chat_history(chat_history: List[Tuple[str, str]]):
+    buffer = []
+    for human, ai in chat_history:
+        buffer.append(HumanMessage(content=human))
+        buffer.append(AIMessage(content=ai))
+    return buffer
+
+
+agent = {
+    "input": lambda x: x["input"],
+    "chat_history": lambda x: _format_chat_history(x['chat_history']),
+    "agent_scratchpad": lambda x: format_to_openai_functions(x['intermediate_steps']),
+} | prompt | llm_with_tools | OpenAIFunctionsAgentOutputParser()
+
+class AgentInput(BaseModel):
+    input: str
+    chat_history: List[Tuple[str, str]]
+
+agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True).with_types(
+    input_type=AgentInput
+)
+
+agent_executor = agent_executor | (lambda x: x["output"])

templates/openai-functions-agent/pyproject.toml

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+[tool.poetry]
+name = "openai-functions-agent"
+version = "0.1.0"
+description = ""
+authors = ["Lance Martin <lance@langchain.dev>"]
+readme = "README.md"
+
+[tool.poetry.dependencies]
+python = ">=3.8.1,<4.0"
+langchain = ">=0.0.322"
+openai = ">=0.5.0"
+tavily-python = "^0.1.9"
+
+[tool.langserve]
+export_module = "openai_functions_agent"
+export_attr = "agent_executor"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"