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mirror of https://github.com/hpcaitech/ColossalAI.git synced 2025-05-05 23:18:22 +00:00
ColossalAI/applications/ColossalQA/colossalqa/local/colossalcloud_llm.py
YeAnbang e53e729d8e
[Feature] Add document retrieval QA ()
* add langchain

* add langchain

* Add files via upload

* add langchain

* fix style

* fix style: remove extra space

* add pytest; modified retriever

* add pytest; modified retriever

* add tests to build_on_pr.yml

* fix build_on_pr.yml

* fix build on pr; fix environ vars

* seperate unit tests for colossalqa from build from pr

* fix container setting; fix environ vars

* commented dev code

* add incremental update

* remove stale code

* fix style

* change to sha3 224

* fix retriever; fix style; add unit test for document loader

* fix ci workflow config

* fix ci workflow config

* add set cuda visible device script in ci

* fix doc string

* fix style; update readme; refactored

* add force log info

* change build on pr, ignore colossalqa

* fix docstring, captitalize all initial letters

* fix indexing; fix text-splitter

* remove debug code, update reference

* reset previous commit

* update LICENSE update README add key-value mode, fix bugs

* add files back

* revert force push

* remove junk file

* add test files

* fix retriever bug, add intent classification

* change conversation chain design

* rewrite prompt and conversation chain

* add ui v1

* ui v1

* fix atavar

* add header

* Refactor the RAG Code and support Pangu

* Refactor the ColossalQA chain to Object-Oriented Programming and the UI demo.

* resolved conversation. tested scripts under examples. web demo still buggy

* fix ci tests

* Some modifications to add ChatGPT api

* modify llm.py and remove unnecessary files

* Delete applications/ColossalQA/examples/ui/test_frontend_input.json

* Remove OpenAI api key

* add colossalqa

* move files

* move files

* move files

* move files

* fix style

* Add Readme and fix some bugs.

* Add something to readme and modify some code

* modify a directory name for clarity

* remove redundant directory

* Correct a type in  llm.py

* fix AI prefix

* fix test_memory.py

* fix conversation

* fix some erros and typos

* Fix a missing import in RAG_ChatBot.py

* add colossalcloud LLM wrapper, correct issues in code review

---------

Co-authored-by: YeAnbang <anbangy2@outlook.com>
Co-authored-by: Orion-Zheng <zheng_zian@u.nus.edu>
Co-authored-by: Zian(Andy) Zheng <62330719+Orion-Zheng@users.noreply.github.com>
Co-authored-by: Orion-Zheng <zhengzian@u.nus.edu>
2023-11-23 10:33:48 +08:00

126 lines
4.1 KiB
Python

"""
LLM wrapper for LLMs running on ColossalCloud Platform
Usage:
os.environ['URL'] = ""
os.environ['HOST'] = ""
gen_config = {
'max_new_tokens': 100,
# 'top_k': 2,
'top_p': 0.9,
'temperature': 0.5,
'repetition_penalty': 2,
}
llm = ColossalCloudLLM(n=1)
llm.set_auth_config()
resp = llm(prompt='What do you call a three-ton kangaroo?', **gen_config)
print(resp) # super-heavyweight awesome-natured yawning Australian creature!
"""
import json
from typing import Any, List, Mapping, Optional
import requests
from langchain.llms.base import LLM
from langchain.utils import get_from_dict_or_env
class ColossalCloudLLM(LLM):
"""
A custom LLM class that integrates LLMs running on the ColossalCloud Platform
"""
n: int
gen_config: dict = None
auth_config: dict = None
valid_gen_para: list = ['max_new_tokens', 'top_k',
'top_p', 'temperature', 'repetition_penalty']
def __init__(self, gen_config=None, **kwargs):
"""
Args:
gen_config: config for generation,
max_new_tokens: 50 by default
top_k: (1, vocab_size)
top_p: (0, 1) if not None
temperature: (0, inf) if not None
repetition_penalty: (1, inf) if not None
"""
super(ColossalCloudLLM, self).__init__(**kwargs)
if gen_config is None:
self.gen_config = {"max_new_tokens": 50}
else:
assert "max_new_tokens" in gen_config, "max_new_tokens is a compulsory key in the gen config"
self.gen_config = gen_config
@property
def _identifying_params(self) -> Mapping[str, Any]:
"""Get the identifying parameters."""
return {"n": self.n}
@property
def _llm_type(self) -> str:
return 'ColossalCloudLLM'
def set_auth_config(self, **kwargs):
url = get_from_dict_or_env(kwargs, "url", "URL")
host = get_from_dict_or_env(kwargs, "host", "HOST")
auth_config = {}
auth_config['endpoint'] = url
auth_config['Host'] = host
self.auth_config = auth_config
def _call(self, prompt: str, stop=None, **kwargs: Any) -> str:
"""
Args:
prompt: The prompt to pass into the model.
stop: A list of strings to stop generation when encountered
Returns:
The string generated by the model
"""
# Update the generation arguments
for key, value in kwargs.items():
if key not in self.valid_gen_para:
raise KeyError(f"Invalid generation parameter: '{key}'. Valid keys are: {', '.join(self.valid_gen_para)}")
if key in self.gen_config:
self.gen_config[key] = value
resp_text = self.text_completion(prompt, self.gen_config, self.auth_config)
# TODO: This may cause excessive tokens count
if stop is not None:
for stopping_words in stop:
if stopping_words in resp_text:
resp_text = resp_text.split(stopping_words)[0]
return resp_text
def text_completion(self, prompt, gen_config, auth_config):
# Complusory Parameters
endpoint = auth_config.pop('endpoint')
max_new_tokens = gen_config.pop('max_new_tokens')
# Optional Parameters
optional_params = ['top_k', 'top_p', 'temperature', 'repetition_penalty'] # Self.optional
gen_config = {key: gen_config[key] for key in optional_params if key in gen_config}
# Define the data payload
data = {
"max_new_tokens": max_new_tokens,
"history": [
{"instruction": prompt, "response": ""}
],
**gen_config
}
headers = {
"Content-Type": "application/json",
**auth_config # 'Host',
}
# Make the POST request
response = requests.post(endpoint, headers=headers, data=json.dumps(data))
response.raise_for_status() # raise error if return code is not 200(success)
# Check the response
return response.text