| import os |
| import logging |
| from config import MODEL_NAME |
| from dotenv import load_dotenv |
| from langchain_groq import ChatGroq |
| from langchain.agents import AgentExecutor |
| from langchain.memory import ConversationBufferWindowMemory |
| from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder |
| from langchain.agents import create_tool_calling_agent |
| from langchain_core.utils.function_calling import convert_to_openai_function |
| from utils import book_slot, check_slots, reschedule_event, delete_event |
|
|
| load_dotenv() |
| logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s') |
|
|
| API_KEY = os.environ["API_KEY"] |
|
|
| def create_agent(PROMPT): |
| |
| memory = ConversationBufferWindowMemory( |
| memory_key="chat_history", |
| return_messages=True, |
| k=5 |
| ) |
| |
| |
| prompt_template = ChatPromptTemplate.from_messages([ |
| ("system", PROMPT), |
| MessagesPlaceholder(variable_name="chat_history"), |
| ("human", "{input}"), |
| MessagesPlaceholder(variable_name="agent_scratchpad"), |
| ]) |
|
|
| |
| tools = [book_slot, delete_event, check_slots, reschedule_event] |
| functions = [convert_to_openai_function(f) for f in tools] |
|
|
| |
| llm = ChatGroq( |
| model=MODEL_NAME, |
| temperature=0.7, |
| max_tokens=None, |
| timeout=60, |
| max_retries=2, |
| api_key=API_KEY |
| ).bind_functions(functions=functions) |
|
|
| |
| agent = create_tool_calling_agent(llm, tools, prompt_template) |
| |
| |
| agent_executor = AgentExecutor( |
| agent=agent, |
| tools=tools, |
| memory=memory, |
| verbose=True |
| ) |
| |
| return agent_executor |
|
|
| |
| def process_query(query: str): |
| try: |
| agent = create_agent("Your system prompt here") |
| response = agent.invoke( |
| { |
| "input": query, |
| } |
| ) |
| return response |
| except Exception as e: |
| logging.error(f"Error during query processing: {str(e)}") |
| raise |
