fix openai env vars

examples/streaming_conversation.py

@@ -46,17 +46,17 @@ async def main():
 
     conversation = StreamingConversation(
         output_device=speaker_output,
-        transcriber=DeepgramTranscriberConfig.from_input_device(
+        transcriber_config=DeepgramTranscriberConfig.from_input_device(
             microphone_input, endpointing_config=PunctuationEndpointingConfig()
         ),
-        agent=ChatGPTAgentConfig(
+        agent_config=ChatGPTAgentConfig(
             initial_message=BaseMessage(text="What up"),
             prompt_preamble="""You are a helpful gen Z AI assistant. You use slang like um, but, and like a LOT. All of your responses are 10 words or less. Be super chill, use slang like
 hella, down,     fire, totally, but like, slay, vibing, queen, go off, bet, sus, simp, cap, big yikes, main character, dank""",
             generate_responses=True,
             cut_off_response=CutOffResponse(),
         ),
-        synthesizer=AzureSynthesizerConfig.from_output_device(speaker_output),
+        synthesizer_config=AzureSynthesizerConfig.from_output_device(speaker_output),
         logger=logger,
     )
     await conversation.start()

vocode/streaming/agent/bot_sentiment_analyser.py

@@ -3,6 +3,8 @@ from langchain.llms import OpenAI
 from langchain.prompts import PromptTemplate
 from pydantic import BaseModel
 
+from vocode import getenv
+
 TEMPLATE = """
 Read the following conversation classify the final emotion of the Bot as one of [{emotions}].
 Output the degree of emotion as a value between 0 and 1 in the format EMOTION,DEGREE: ex. {example_emotion},0.5
@@ -22,7 +24,7 @@ class BotSentimentAnalyser:
     def __init__(self, emotions: list[str], model_name: str = "text-davinci-003"):
         self.model_name = model_name
         self.llm = OpenAI(
-            model_name=self.model_name,
+            model_name=self.model_name, openai_api_key=getenv("OPENAI_API_KEY")
         )
         assert len(emotions) > 0
         self.emotions = [e.lower() for e in emotions]

vocode/streaming/agent/chat_gpt_agent.py

@@ -57,6 +57,7 @@ class ChatGPTAgent(BaseAgent):
             model_name=self.agent_config.model_name,
             temperature=self.agent_config.temperature,
             max_tokens=self.agent_config.max_tokens,
+            openai_api_key=openai.api_key,
         )
         self.conversation = ConversationChain(
             memory=self.memory, prompt=self.prompt, llm=self.llm

vocode/streaming/agent/llm_agent.py

@@ -5,6 +5,7 @@ from langchain import OpenAI
 from langchain.llms import OpenAIChat
 from typing import Generator
 import logging
+from vocode import getenv
 
 from vocode.streaming.agent.base_agent import BaseAgent
 from vocode.streaming.agent.utils import stream_llm_response
@@ -43,6 +44,7 @@ class LLMAgent(BaseAgent):
             model_name=self.agent_config.model_name,
             temperature=self.agent_config.temperature,
             max_tokens=self.agent_config.max_tokens,
+            openai_api_key=getenv("OPENAI_API_KEY"),
         )
         self.stop_tokens = [f"{recipient}:"]
         self.first_response = (