mirror of
https://github.com/arc53/DocsGPT
synced 2024-11-02 03:40:17 +00:00
40 lines
1.4 KiB
Python
40 lines
1.4 KiB
Python
from application.llm.base import BaseLLM
|
|
from application.core.settings import settings
|
|
|
|
class LlamaCpp(BaseLLM):
|
|
|
|
def __init__(self, api_key, llm_name=settings.MODEL_PATH, **kwargs):
|
|
global llama
|
|
try:
|
|
from llama_cpp import Llama
|
|
except ImportError:
|
|
raise ImportError("Please install llama_cpp using pip install llama-cpp-python")
|
|
|
|
llama = Llama(model_path=llm_name, n_ctx=2048)
|
|
|
|
def gen(self, model, engine, 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 gen_stream(self, model, engine, 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']
|