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DocsGPT/application/llm/llama_cpp.py

53 lines
1.7 KiB
Python

from application.llm.base import BaseLLM
from application.core.settings import settings
class LlamaCpp(BaseLLM):
def __init__(
self,
api_key=None,
user_api_key=None,
llm_name=settings.MODEL_PATH,
*args,
**kwargs,
):
global llama
try:
from llama_cpp import Llama
except ImportError:
raise ImportError(
"Please install llama_cpp using pip install llama-cpp-python"
)
super().__init__(*args, **kwargs)
self.api_key = api_key
self.user_api_key = user_api_key
llama = Llama(model_path=llm_name, n_ctx=2048)
def _raw_gen(self, baseself, model, messages, stream=False, **kwargs):
context = messages[0]["content"]
user_question = messages[-1]["content"]
prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
result = llama(prompt, max_tokens=150, echo=False)
# import sys
# print(result['choices'][0]['text'].split('### Answer \n')[-1], file=sys.stderr)
return result["choices"][0]["text"].split("### Answer \n")[-1]
def _raw_gen_stream(self, baseself, model, messages, stream=True, **kwargs):
context = messages[0]["content"]
user_question = messages[-1]["content"]
prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
result = llama(prompt, max_tokens=150, echo=False, stream=stream)
# import sys
# print(list(result), file=sys.stderr)
for item in result:
for choice in item["choices"]:
yield choice["text"]