A Python toolkit for advanced data processing and API interactions
Project description
descartcan
LLM
Step1
llm_config.yaml
openai:
keys:
- name: "openai_key1"
api_key: "XXX"
models:
gpt4: "gpt-4-0125-preview"
gpt40: "gpt-4o"
bedrock:
keys:
- name: "bedrock"
api_key: "XXX"
api_secret: "XXXXX"
models:
haiku35: "us.anthropic.claude-3-5-haiku-20241022-v1:0"
Step2
load models
from descartcan.llm.factory import LLModelFactory
model_factory = LLModelFactory.from_config(config="llm_config.yaml")
model = model_factory.get_model("openai.gpt4")
# 单轮对话
response = await model.chat(
question="Show Python",
system="你是一个编程专家"
)
print(f"回复: {response.content}")
print(f"Token统计: 提示词{response.prompt_tokens}, 生成{response.completion_tokens}, 总计{response.total_tokens}")
# 多轮对话
history = [
{"role": "user", "content": "Python和Java的区别是什么?"},
{"role": "assistant", "content": "Python和Java有以下主要区别:..."}
]
response = await model.chat(
question="哪个更适合初学者?",
system="你是一个编程专家",
history=history
)
print(f"多轮对话回复: {response.content}")
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