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from openai import OpenAI | |
class LlaMa3: | |
def __init__(self) -> None: | |
self.client = OpenAI( | |
base_url="https://integrate.api.nvidia.com/v1", | |
api_key="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" | |
) | |
self.name = "Llama3" | |
# Initial greeting and request for decision topic | |
self.initial_prompt = """ | |
Hello! I can assist you in making a decision. What decision would you like to make today? | |
Please describe the decision and provide any relevant details to help me understand. | |
""" | |
def chat(self, messages): | |
# If this is the first message, we use the initial prompt to greet and ask for the decision topic | |
if len(messages) == 0: # Initial conversation step | |
messages.append({"role": "system", "content": self.initial_prompt}) | |
# Call the API to get the model's response | |
completion = self.client.chat.completions.create( | |
model="nvidia/llama-3.1-nemotron-70b-instruct", | |
messages=messages, | |
temperature=0.5, | |
top_p=1, | |
max_tokens=1024, | |
stream=True | |
) | |
response = "" | |
for chunk in completion: | |
if chunk.choices[0].delta.content is not None: | |
response += chunk.choices[0].delta.content | |
return response | |