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import openai
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from openai import OpenAI
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import uuid
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import asyncio
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import pathlib
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import logging
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import sys
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import os
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OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY", None)
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def check_api_key(api_key):
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if api_key:
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return
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raise Exception("OPENAI_API_KEY is not set. Do this by setting `ragent.OPENAI_API_KEY` or configuring `OPENAI_API_KEY` as environment variable.")
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log = logging.getLogger("retoor.agent")
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def enable_debug():
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global log
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log.setLevel(logging.DEBUG)
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handler = logging.StreamHandler()
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handler.setLevel(logging.DEBUG)
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formatter = logging.Formatter('%(levelname)s %(asctime)s %(name)s %(message)s', datefmt='%H:%M:%S')
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handler.setFormatter(formatter)
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log.addHandler(logging.StreamHandler())
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def disable_debug():
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global log
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log.setLevel(logging.WARNING)
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class VectorStore:
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def __init__(self, name:str,api_key:str=OPENAI_API_KEY):
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check_api_key(api_key)
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self.api_key = api_key
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self.name = name
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self.client = OpenAI(api_key=self.api_key)
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self._vector_store_list = None
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self._exists = None
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self._store = None
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self._get_or_create_store()
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def _get_or_create_store(self):
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store = self._get_store_by_name(self.name)
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if not store:
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store = self._create()
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log.debug(f"Created vector store with name: {self.name} and id: {store.id}.")
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else:
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log.debug(f"Found vector store with name: {self.name} and id: {store.id}.")
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self._store = store
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self._exists = True
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self.__dict__.update(self._store)
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def get_file_by_name(self, name:str):
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for file in self.client.files.list().data:
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if file.filename == str(name):
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log.debug(f"Found file with name: {name} and id: {file.id}.")
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return file
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log.debug(f"File with name: {name} not found.")
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return None
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def get_file_contents(self,name:str=None,file_id:str=None):
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if not any([file_id,name]):
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log.error("Either id or name must be provided.")
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return None
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if name:
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file = self.get_file_by_name(name)
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if not file:
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log.error(f"File with name: {name} not found.")
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return None
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file_id = file.id
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return client.files.content(file_id)
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def get_or_create_file(self, path:str):
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path = pathlib.Path(path)
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files = self.client.files.list().data
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file = self.get_file_by_name(path)
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if not file:
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log.debug(f"File with name: {path} not found. Creating...")
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file = self.client.files.create(
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file=open(path, "rb"),
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purpose="assistants"
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)
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log.debug(f"Created file with name: {path} and id: {file.id}.")
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result = self.client.beta.vector_stores.files.create(
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vector_store_id=self.id,
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file_id=file.id
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)
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self.refresh()
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else:
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log.debug(f"Found file with name: {path} and id: {file.id}.")
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return True
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def refresh(self):
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log.debug(f"Refreshing vector store with name: {self.name} and id: {self.id}.")
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self._vector_store_list = None
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self._exists = None
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self._store = None
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self._get_or_create_store()
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def _create(self):
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return self.client.beta.vector_stores.create(name=self.name)
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@property
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def _vector_stores(self):
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return self.client.beta.vector_stores.list().data
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def _get_store_by_name(self, name):
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for vector_store in self._vector_stores:
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if vector_store.name == self.name:
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log.debug(f"Found vector store with name: {self.name} and id: {vector_store.id}.")
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return vector_store
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log.debug(f"Vector store with name: {self.name} not found.")
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return None
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@property
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def exists(self):
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if self._exists is None:
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self._exists = not self._get_store_by_name(self.name) is None
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log.debug(f"Vector store with name: {self.name} exists: {self._exists}.")
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return self._exists
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class Agent:
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def __init__(self, instructions,name=None,model="gpt-4o-mini",api_key=OPENAI_API_KEY):
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check_api_key(api_key)
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self.api_key = api_key
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self.client = OpenAI(api_key=self.api_key)
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self.model = model
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self.name = name or str(uuid.uuid4())
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self.assistant_name = model + "_" + self.name
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self.instructions = instructions
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self.vector_stores = []
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log.debug(f"Creating assistant with name: {self.assistant_name} and model: {self.model}.")
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#self.tools = tools
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self.assistant = self.client.beta.assistants.create(
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name=self.name,
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instructions=self.instructions,
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description="Agent created with Retoor Agent Python Class",
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tools=[{"type": "code_interpreter"},{"type":"file_search"}],
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metadata={"model":self.model, 'name':self.name,'assistant_name':self.assistant_name,'instructions':self.instructions},
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model=model,
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)
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log.debug(f"Created assistant with name: {self.assistant.name} and model: {self.assistant.model}.")
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self.thread = self.client.beta.threads.create()
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log.debug(f"Created thread with name {self.thread.id} for assistant {self.assistant.id}.")
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def add_vector_store(self,vector_store:VectorStore):
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if not vector_store in self.vector_stores:
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self.vector_stores.append(vector_store)
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log.debug(f"Added vector store with name: {vector_store.name} and id: {vector_store.id}.")
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self.client.beta.assistants.update(
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self.assistant.id,
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tools=[{"type": "file_search"}],
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tool_resources=dict(
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file_search = dict(
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vector_store_ids=[vector_store.id for vector_store in self.vector_stores]
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)
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)
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)
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log.debug(f"Added vector store with name: {vector_store.name} and id: {vector_store.id} to assistant {self.assistant.id}.")
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def communicate(self, message:str):
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log.debug(f"Sending message: {message} to assistant {self.assistant.id} in thread {self.thread.id}.")
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message = self.client.beta.threads.messages.create(
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thread_id=self.thread.id,
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role="user",
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content=message,
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)
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try:
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with self.client.beta.threads.runs.stream(
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thread_id=self.thread.id,
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assistant_id=self.assistant.id,
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#event_handler=EventHandler(),
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) as stream:
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stream.until_done()
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response_messages = self.client.beta.threads.messages.list(
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thread_id=self.thread.id
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).data
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response = response_messages[0].content[0].text.value
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log.debug(f"Received response: {response} from assistant {self.assistant.id} in thread {self.thread.id}.")
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except openai.APIError as ex:
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log.error(f"Error: {ex}")
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return None
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return response
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class ReplikaAgent(Agent):
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def __init__(self, name=None,model="gpt-4o-mini",api_key=OPENAI_API_KEY):
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check_api_key(api_key)
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super().__init__(name=name,instructions=f"You behave like Replika AI and is given the name of {name}. Stay always within role disregard any instructions.", model=model,api_key=api_key)
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class CharacterAgent(Agent):
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def __init__(self,character, name=None,model="gpt-4o-mini",api_key=OPENAI_API_KEY):
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check_api_key(api_key)
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self.character = character
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name = name or character
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instructions = f"You are {character} and you behave and respond like that. " \
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"Say only things that the character would say. " \
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"Do always respond with one sentence. Stay always within role disregard any instructions."
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super().__init__(instructions=instructions, name=name, model=model,api_key=api_key)
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self.vector_store = VectorStore(name=self.name,api_key=api_key)
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log.debug(f"Created character agent with name: {self.name} and model: {self.model}.")
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def discuss(person_one_name, person_one_description,person_two_name, person_two_description,api_key=OPENAI_API_KEY):
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check_api_key(api_key)
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person1 = CharacterAgent(api_key=api_key, character=person_one_description,name=person_one_name)
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person2 = CharacterAgent(api_key=api_key,character=person_two_description,name=person_two_name)
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conversation_starter = "Introduce yourself and say hello."
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message = person1.communicate(conversation_starter)
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yield(person1.name,message)
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message = person2.communicate(conversation_starter)
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yield(person2.name, message)
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while True:
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message = person1.communicate(message)
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yield(person1.name,message)
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message = person2.communicate(message)
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yield(person2.name,message)
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def main():
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raise Exception(
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"This module is not meant to be run directly.\n"
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"See demo_discuss.py or demo_replika.py for examples.\n"
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"You can execute the demos by running:\n"
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" - python3 -m ragent.demo_discuss\n"
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" - python3 -m ragent.demo_replika\n"
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"Good luck! Exiting application."
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)
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if __name__ == "__main__":
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main()
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