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{
"cells": [
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"from typing import Optional, Type\n",
"from langchain_core.pydantic_v1 import BaseModel, Field\n",
"from langchain_core.tools import BaseTool\n",
"\n",
"class MultiplierInput(BaseModel):\n",
" a: int = Field(description=\"first number\")\n",
" b: int = Field(description=\"second number\")\n",
"\n",
"class CustomMultiplierTool(BaseTool):\n",
" name = \"Calculator\"\n",
" description = \"useful for when you need to answer questions about math\"\n",
" args_schema: Type[BaseModel] = MultiplierInput\n",
"\n",
" def _run(\n",
" self, a: int, b: int\n",
" ) -> str:\n",
" \"\"\"Use the tool.\"\"\"\n",
" return a * b\n",
"\n",
" async def _arun(\n",
" self,\n",
" a: int,\n",
" b: int,\n",
" ) -> str:\n",
" \"\"\"Use the tool asynchronously.\"\"\"\n",
" return self._run(a,b)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"from langchain.agents import AgentExecutor, create_openai_tools_agent,Tool\n",
"from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
"from langchain_openai import ChatOpenAI\n",
"from langchain.memory import ConversationBufferMemory\n",
"from langchain.prompts import MessagesPlaceholder\n",
"from langchain.globals import set_verbose\n",
"import dotenv\n",
"\n",
"dotenv.load_dotenv()\n",
"\n",
"def create_agent(model_name):\n",
"\n",
" memory = ConversationBufferMemory(memory_key=\"chat_history\", return_messages=True)\n",
" \n",
" tools = [CustomMultiplierTool()]\n",
" \n",
" llm = ChatOpenAI(model=model_name, temperature=0)\n",
"\n",
" system_message = \"\"\"You are a general AI assistant.\n",
" You have access to several tool. Don't answer the question if you are not getting the answer from a tool.\n",
" Don't put safety and cultural warnings. Only warn about security. \n",
" \"\"\"\n",
"\n",
" prompt = ChatPromptTemplate.from_messages(\n",
" [\n",
" (\"system\", system_message),\n",
" MessagesPlaceholder(\"chat_history\", optional=True),\n",
" (\"human\", \"{input}\"),\n",
" MessagesPlaceholder(\"agent_scratchpad\"),\n",
" ]\n",
" )\n",
" agent = create_openai_tools_agent(llm, tools, prompt)\n",
" agent_exe = AgentExecutor(agent=agent, tools=tools,memory=memory)\n",
" return agent_exe\n",
"\n",
"async def run_agent(agent,user_query):\n",
" #print(agent.memory.chat_memory.messages[-2:] if len(agent.memory.chat_memory.messages) > 1 else \"\")\n",
" #set_verbose(True)\n",
" # print(agent.memory.chat_memory)\n",
" print('********************')\n",
" # print()\n",
" return await agent.ainvoke(input={\"input\":user_query},verbose=True)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"agent_exe = create_agent(\"gpt-3.5-turbo\")"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"********************\n",
"\n",
"\n",
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3m\n",
"Invoking: `Calculator` with `{'a': 2, 'b': 3}`\n",
"\n",
"\n",
"\u001b[0m\u001b[36;1m\u001b[1;3m6\u001b[0m\u001b[32;1m\u001b[1;3m2 multiplied by 3 is equal to 6.\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
"{'input': '2 multiply by 3',\n",
" 'chat_history': [HumanMessage(content='2 multiply by 3'),\n",
" AIMessage(content='2 multiplied by 3 is equal to 6.')],\n",
" 'output': '2 multiplied by 3 is equal to 6.'}"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"await run_agent(agent_exe,\"2 multiply by 3\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "stevens-chat-py311-v1",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.6"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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