44 lines
1.5 KiB
Python
44 lines
1.5 KiB
Python
import os
|
|
from typing import Optional
|
|
|
|
from langchain.schema import HumanMessage, SystemMessage
|
|
from langchain_community.chat_models import JinaChat
|
|
|
|
from embedchain.config import BaseLlmConfig
|
|
from embedchain.helpers.json_serializable import register_deserializable
|
|
from embedchain.llm.base import BaseLlm
|
|
|
|
|
|
@register_deserializable
|
|
class JinaLlm(BaseLlm):
|
|
def __init__(self, config: Optional[BaseLlmConfig] = None):
|
|
if "JINACHAT_API_KEY" not in os.environ:
|
|
raise ValueError("Please set the JINACHAT_API_KEY environment variable.")
|
|
super().__init__(config=config)
|
|
|
|
def get_llm_model_answer(self, prompt):
|
|
response = JinaLlm._get_answer(prompt, self.config)
|
|
return response
|
|
|
|
@staticmethod
|
|
def _get_answer(prompt: str, config: BaseLlmConfig) -> str:
|
|
messages = []
|
|
if config.system_prompt:
|
|
messages.append(SystemMessage(content=config.system_prompt))
|
|
messages.append(HumanMessage(content=prompt))
|
|
kwargs = {
|
|
"temperature": config.temperature,
|
|
"max_tokens": config.max_tokens,
|
|
"model_kwargs": {},
|
|
}
|
|
if config.top_p:
|
|
kwargs["model_kwargs"]["top_p"] = config.top_p
|
|
if config.stream:
|
|
from langchain.callbacks.streaming_stdout import \
|
|
StreamingStdOutCallbackHandler
|
|
|
|
chat = JinaChat(**kwargs, streaming=config.stream, callbacks=[StreamingStdOutCallbackHandler()])
|
|
else:
|
|
chat = JinaChat(**kwargs)
|
|
return chat(messages).content
|