diff options
Diffstat (limited to 'main.py')
| -rw-r--r-- | main.py | 114 |
1 files changed, 73 insertions, 41 deletions
@@ -75,16 +75,17 @@ telephony_server = TelephonyServer( inbound_call_configs=[ TwilioInboundCallConfig( url="/inbound_call", - # agent_config=ChatGPTAgentConfig( - # initial_message=BaseMessage(text="What up."), - # prompt_preamble="Act as a customer talking to 'Cosmos', a pizza establisment ordering a large pepperoni pizza for pickup. If asked for a name, your name is 'Hunter McRobie', and your credit card number is 4743 2401 5792 0539 CVV: 123 and expiratoin is 10/25. If asked for numbers, say them one by one",#"Have a polite conversation about life while talking like a pirate.", - # generate_responses=True, - # model_name="gpt-3.5-turbo" - # ), - agent_config=SpellerAgentConfig(generate_responses=False, initial_message=BaseMessage(text="What up.")), + agent_config=ChatGPTAgentConfig( + initial_message=BaseMessage(text="Ahoy Matey! Pizza Ahoy here! How may I help you."), + prompt_preamble="You are receiving calls on behald of 'Pizza Ahoy!', a pizza establisment taking orders only for pickup. YOu will be provided the transcript from a speech to text model, say what you would say in that siutation. Talk like a pirate. Apologise to customer if they ask for delivery.", + generate_responses=True, + model_name="gpt-3.5-turbo" + ), + # agent_config=SpellerAgentConfig(generate_responses=False, initial_message=BaseMessage(text="What up.")), twilio_config=TwilioConfig( account_sid=os.environ["TWILIO_ACCOUNT_SID"], auth_token=os.environ["TWILIO_AUTH_TOKEN"], + record=True ), synthesizer_config=ElevenLabsSynthesizerConfig.from_telephone_output_device( api_key=os.getenv("ELEVENLABS_API_KEY"), @@ -96,45 +97,76 @@ telephony_server = TelephonyServer( logger=logger, ) -async def send_message(message: str) -> AsyncIterable[str]: - callback = AsyncIteratorCallbackHandler() - model = ChatOpenAI( - streaming=True, - verbose=True, - callbacks=[callback], - ) - - async def wrap_done(fn: Awaitable, event: asyncio.Event): - """Wrap an awaitable with a event to signal when it's done or an exception is raised.""" - try: - await fn - except Exception as e: - # TODO: handle exception - print(f"Caught exception: {e}") - finally: - # Signal the aiter to stop. - event.set() - - # Begin a task that runs in the background. - task = asyncio.create_task(wrap_done( - model.agenerate(messages=[[HumanMessage(content=message)]]), - callback.done), - ) +import os +import sys +import typing +from dotenv import load_dotenv - async for token in callback.aiter(): - # Use server-sent-events to stream the response - yield f"data: {token}\n\n" +from tools.contacts import get_all_contacts +from tools.vocode import call_phone_number +from tools.summarize import summarize +from tools.get_user_inputs import get_desired_inputs +from tools.email_tool import email_tasks +from langchain.memory import ConversationBufferMemory +from langchain.agents import load_tools - await task +from stdout_filterer import RedactPhoneNumbers +load_dotenv() -class StreamRequest(BaseModel): - """Request body for streaming.""" - message: str +from langchain.chat_models import ChatOpenAI +# from langchain.chat_models import BedrockChat +from langchain.agents import initialize_agent +from langchain.agents import AgentType + +from langchain.tools import WikipediaQueryRun + +memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True) +tools=load_tools(["human", "wikipedia"]) + [get_all_contacts, call_phone_number, email_tasks, summarize] + +tools_desc = "" +for tool in tools: + tools_desc += tool.name + " : " + tool.description + "\n" + +def rephrase_prompt(objective: str) -> str: + # llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo") # type: ignore + # pred = llm.predict(f"Based on these tools {tools_desc} with the {objective} should be done in the following manner (outputting a single sentence), allowing for failure: ") + # print(pred) + # return pred + return f"{objective}" + +with open("info.txt") as f: + my_info = f.read() + memory.chat_memory.add_user_message("User information to us " + my_info + " end of user information.") + + +class QueryItem(BaseModel): + query: str + +@app.post("/senpai") +def exec_and_return(item: QueryItem): + query = item.query + verbose_value = False + print(query) + OBJECTIVE = ( + query + or "Find a random person in my contacts and tell them a joke" + ) + llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo") # type: ignore + #llm = BedrockChat(model_id="anthropic.claude-instant-v1", model_kwargs={"temperature":0}) # type: ignore + #memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True) + # Logging of LLMChains + verbose = True + agent = initialize_agent( + tools=tools, + llm=llm, + agent=AgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION, + verbose=verbose_value, + memory=memory, + ) + out = agent.run(OBJECTIVE) -@app.post("/stream") -def stream(body: StreamRequest): - return StreamingResponse(send_message(body.message), media_type="text/event-stream") + return out app.include_router(telephony_server.get_router())
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