| const CustomAgent = require('./CustomAgent'); |
| const { CustomOutputParser } = require('./outputParser'); |
| const { AgentExecutor } = require('langchain/agents'); |
| const { LLMChain } = require('langchain/chains'); |
| const { BufferMemory, ChatMessageHistory } = require('langchain/memory'); |
| const { |
| ChatPromptTemplate, |
| SystemMessagePromptTemplate, |
| HumanMessagePromptTemplate, |
| } = require('langchain/prompts'); |
|
|
| const initializeCustomAgent = async ({ |
| tools, |
| model, |
| pastMessages, |
| currentDateString, |
| ...rest |
| }) => { |
| let prompt = CustomAgent.createPrompt(tools, { currentDateString, model: model.modelName }); |
|
|
| const chatPrompt = ChatPromptTemplate.fromMessages([ |
| new SystemMessagePromptTemplate(prompt), |
| HumanMessagePromptTemplate.fromTemplate(`{chat_history} |
| Query: {input} |
| {agent_scratchpad}`), |
| ]); |
|
|
| const outputParser = new CustomOutputParser({ tools }); |
|
|
| const memory = new BufferMemory({ |
| llm: model, |
| chatHistory: new ChatMessageHistory(pastMessages), |
| |
| memoryKey: 'chat_history', |
| humanPrefix: 'User', |
| aiPrefix: 'Assistant', |
| inputKey: 'input', |
| outputKey: 'output', |
| }); |
|
|
| const llmChain = new LLMChain({ |
| prompt: chatPrompt, |
| llm: model, |
| }); |
|
|
| const agent = new CustomAgent({ |
| llmChain, |
| outputParser, |
| allowedTools: tools.map((tool) => tool.name), |
| }); |
|
|
| return AgentExecutor.fromAgentAndTools({ agent, tools, memory, ...rest }); |
| }; |
|
|
| module.exports = initializeCustomAgent; |
|
|
