Llama 3 के साथ काम करना
Imtihan Ahmed
Machine Learning Engineer





Conversation क्लास से चैट हिस्ट्री ट्रैक करेंclass Conversation:def __init__(self, llm: Llama, system_prompt='', history=[]): self.llm = llm self.system_prompt = system_promptself.history = {"role": "system", "content": self.system_prompt} + history
class Conversation: def __init__(self, llm: Llama, system_prompt='', history=[]): self.llm = llm self.system_prompt = system_prompt self.history = {"role": "system", "content": self.system_prompt} + historydef create_completion(self, user_prompt=''):self.history.append({"role": "user", "content": user_prompt}) # इनपुट जोड़ेंoutput = self.llm.create_chat_completion(messages=self.history)conversation_result = output['choices'][0]['message'] self.history.append(conversation_result) # आउटपुट जोड़ें return conversation_result['content'] # आउटपुट लौटाएँ
conversation = Conversation(llm, system_prompt="You are a virtual travel assistant helping with planning trips.")response1 = conversation.create_completion("What are some destinations in France for a short weekend break?")print(f"Response 1: {response1}")response2 = conversation.create_completion("How about Spain?")print(f"Response 2: {response2}")
print(f"Response 1: {response1}")
print(f"Response 2: {response2}")

print(f"Response 1: {response1}")
print(f"Response 2: {response2}")

Llama 3 के साथ काम करना