ColossalAI/applications/ColossalQA/colossalqa/local/colossalcloud_llm.py

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[Feature] Add document retrieval QA (#5020) * 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 02:33:48 +00:00
"""
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