Query MongoDB con lenguaje natural usando LangChain y LangGraph

export OPENAI_API_KEY=<your-openai-api-key>

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import os
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from langchain_openai import ChatOpenAI
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from langgraph.prebuilt import create_react_agent
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from langchain_mongodb.agent_toolkit import (
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    MONGODB_AGENT_SYSTEM_PROMPT,
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    MongoDBDatabase,
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    MongoDBDatabaseToolkit,
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)
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MONGODB_URI = '<connection-string>'
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DB_NAME = 'sample_restaurants'
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NATURAL_LANGUAGE_QUERY = 'Find all restaurants that serve hamburgers.'
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class NaturalLanguageToMQL:
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    def __init__(self):
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        self.llm = ChatOpenAI(model="gpt-4o-mini", timeout=60)
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        self.system_message = MONGODB_AGENT_SYSTEM_PROMPT.format(top_k=5)
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        self.db_wrapper = MongoDBDatabase.from_connection_string(
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                            MONGODB_URI, 
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                            database=DB_NAME)
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        self.toolkit = MongoDBDatabaseToolkit(db=self.db_wrapper, llm=self.llm)
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        self.agent = create_react_agent(
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                        self.llm, 
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                        self.toolkit.get_tools(), 
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                        state_modifier=self.system_message)
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        self.messages = []
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    def convert_to_mql_and_execute_query(self, query):
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        # Start the agent with the agent.stream() method
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        events = self.agent.stream(
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            {"messages": [("user", query)]},
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            stream_mode="values",
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        )
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        # Add output (events) from the agent to the self.messages list
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        for event in events:
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            self.messages.extend(event["messages"])
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    def print_results(self):
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        # Print the the end-user's expected output from 
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        # the final message produced by the agent.
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        print(self.messages[-1].content)
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def main():
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    converter = NaturalLanguageToMQL()
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    converter.convert_to_mql_and_execute_query(NATURAL_LANGUAGE_QUERY)
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    converter.print_results()
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if __name__ == '__main__':
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    main()