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refactor: streamline OpenAI_Chat initialization and deprecate old parameters #734

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refactor: streamline OpenAI_Chat initialization and deprecate old parameters #734

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44 changes: 16 additions & 28 deletions src/vanna/openai/openai_chat.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,37 +9,28 @@ class OpenAI_Chat(VannaBase):
def __init__(self, client=None, config=None):
VannaBase.__init__(self, config=config)

# default parameters - can be overrided using config
self.temperature = 0.7
# Ensure config is a dictionary
config = config or {}

if "temperature" in config:
self.temperature = config["temperature"]
# Default parameters - can be overridden using config
self.temperature = config.get("temperature", 0.7)

if "api_type" in config:
raise Exception(
"Passing api_type is now deprecated. Please pass an OpenAI client instead."
)

if "api_base" in config:
raise Exception(
"Passing api_base is now deprecated. Please pass an OpenAI client instead."
)

if "api_version" in config:
raise Exception(
"Passing api_version is now deprecated. Please pass an OpenAI client instead."
)
# Raise exceptions for deprecated parameters
for deprecated_param in ["api_type", "api_base", "api_version"]:
if deprecated_param in config:
raise Exception(
f"Passing {deprecated_param} is now deprecated. Please pass an OpenAI client instead."
)

if client is not None:
self.client = client
return

if config is None and client is None:
self.client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
return

if "api_key" in config:
self.client = OpenAI(api_key=config["api_key"])
# Initialize the OpenAI client with optional overrides from config
self.client = OpenAI(
api_key=config.get("api_key"),
base_url=config.get("base_url")
)

def system_message(self, message: str) -> any:
return {"role": "system", "content": message}
Expand Down Expand Up @@ -106,10 +97,7 @@ def submit_prompt(self, prompt, **kwargs) -> str:
temperature=self.temperature,
)
else:
if num_tokens > 3500:
model = "gpt-3.5-turbo-16k"
else:
model = "gpt-3.5-turbo"
model = "gpt-4o-mini"

print(f"Using model {model} for {num_tokens} tokens (approx)")
response = self.client.chat.completions.create(
Expand Down