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Running
on
Zero
Running
on
Zero
File size: 1,890 Bytes
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from .Model import Model
import tiktoken
from transformers import AutoTokenizer
import time
import anthropic
class Claude(Model):
def __init__(self, config):
super().__init__(config)
api_keys = config["api_key_info"]["api_keys"]
api_pos = int(config["api_key_info"]["api_key_use"])
assert (0 <= api_pos < len(api_keys)), "Please enter a valid API key to use"
self.max_output_tokens = int(config["params"]["max_output_tokens"])
self.client = anthropic.Anthropic(
# defaults to os.environ.get("ANTHROPIC_API_KEY")
api_key=api_keys[api_pos],
)
self.llama_tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct")
self.encoding = tiktoken.encoding_for_model("gpt-3.5-turbo")
self.seed = 10
def query(self, msg, max_tokens=128000):
super().query(max_tokens)
while True:
try:
message = self.client.messages.create(
model=self.name,
temperature=self.temperature,
max_tokens=self.max_output_tokens,
messages=[
{"role": "user", "content": msg}
]
)
print(message.content)
time.sleep(1)
break
except Exception as e:
print(e)
time.sleep(10)
return message.content[0].text
def get_prompt_length(self,msg):
encoding = tiktoken.encoding_for_model("gpt-3.5-turbo")
num_tokens = len(encoding.encode(msg))
return num_tokens
def cut_context(self,msg,max_length):
tokens = self.encoding.encode(msg)
truncated_tokens = tokens[:max_length]
truncated_text = self.encoding.decode(truncated_tokens)
return truncated_text
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