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import anthropic
import openai
class ClaudeCompletion:
def __init__(
self,
prompt,
model="claude-v1.3",
max_tokens_to_sample=256,
stop_sequences=[anthropic.HUMAN_PROMPT],
stream=False,
temperature=1.0,
top_k=-1,
top_p=-1
):
self.model = model
self.prompt = prompt
self.max_tokens_to_sample = max_tokens_to_sample
self.stop_sequences = stop_sequences
self.stream = stream
self.temperature = temperature
self.top_k = top_k
self.top_p = top_p
def execute(self, claudeClient):
response = claudeClient.completion(
prompt = f"{anthropic.HUMAN_PROMPT} {self.prompt} {anthropic.AI_PROMPT}",
model = self.model,
max_tokens_to_sample = self.max_tokens_to_sample,
stop_sequences = self.stop_sequences,
steam = self.stream,
temperature = self.temperature,
top_k = self.top_k,
top_p = self.top_p,
)
return response["completion"].strip()
def chatComplete(self, claudeClient, chatHistory):
for i in range(len(chatHistory)-1):
self.prompt = self.prompt + f"{anthropic.HUMAN_PROMPT} {chatHistory[i][0]} {anthropic.AI_PROMPT}"
self.prompt = self.prompt + f"{anthropic.AI_PROMPT} {chatHistory[i][1]}"
self.prompt = self.prompt + f"{anthropic.HUMAN_PROMPT} {chatHistory[-1][0]} {anthropic.AI_PROMPT}"
# print("------------anthropic------------")
# print(self.prompt)
response = claudeClient.completion(
prompt = self.prompt,
model = self.model,
max_tokens_to_sample = self.max_tokens_to_sample,
stop_sequences = self.stop_sequences,
steam = self.stream,
temperature = self.temperature,
top_k = self.top_k,
top_p = self.top_p,
)
return response["completion"].strip()
class GPTCompletion:
def __init__(
self,
system="You are a helpful AI assistant",
model="gpt-3.5-turbo",
temperature=1.0,
top_p=1.0,
n=1,
stream=False,
stop=None,
max_tokens=256,
presence_penalty=0.0,
frequency_penalty=0.0,
logit_bias={}
):
self.system = system
self.model = model
self.messages = [{"role": "system", "content": f"{self.system}"}]
self.temperature = temperature
self.top_p = top_p
self.n = n
self.stream = stream
self.stop = stop
self.max_tokens = max_tokens
self.presence_penalty = presence_penalty
self.frequency_penalty = frequency_penalty
self.logit_bias = logit_bias
def chatComplete(self, chatHistory, firstMessage=""):
self.messages.append({"role": "user", "content": f"{firstMessage}"})
for i in range(len(chatHistory)):
self.messages.append({"role": "assistant", "content": f"{chatHistory[i][0]}"})
self.messages.append({"role": "user", "content": f"{chatHistory[i][1]}"})
response = openai.ChatCompletion.create(
model=self.model,
messages=self.messages,
temperature=self.temperature,
top_p=self.top_p,
n=self.n,
stream=self.stream,
stop=self.stop,
max_tokens=self.max_tokens,
presence_penalty=self.presence_penalty,
frequency_penalty=self.frequency_penalty,
logit_bias=self.logit_bias
)
return response["choices"][0].message["content"].strip()
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