ColossalAI/applications/ColossalQA/colossalqa/local/pangu_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 Pangu
Usage:
# URL: “盘古大模型套件管理”->点击“服务管理”->“模型列表”->点击想要使用的模型的“复制路径”
# USERNAME: 华为云控制台:“我的凭证”->“API凭证”下的“IAM用户名”也就是你登录IAM账户的名字
# PASSWORD: IAM用户的密码
# DOMAIN_NAME: 华为云控制台:“我的凭证”->“API凭证”下的“用户名”也就是公司管理IAM账户的总账户名
os.environ["URL"] = ""
os.environ["URLNAME"] = ""
os.environ["PASSWORD"] = ""
os.environ["DOMAIN_NAME"] = ""
pg = Pangu(id=1)
pg.set_auth_config()
res = pg('你是谁') # 您好,我是华为盘古大模型。我能够通过和您对话互动为您提供帮助。请问您有什么想问我的吗?
"""
import http.client
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 Pangu(LLM):
"""
A custom LLM class that integrates pangu models
"""
n: int
gen_config: dict = None
auth_config: dict = None
def __init__(self, gen_config=None, **kwargs):
super(Pangu, self).__init__(**kwargs)
if gen_config is None:
self.gen_config = {"user": "User", "max_tokens": 50, "temperature": 0.95, "n": 1}
else:
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 "pangu"
def _call(self, prompt: str, stop: Optional[List[str]] = None, **kwargs) -> 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 in self.gen_config:
self.gen_config[key] = value
response = self.text_completion(prompt, self.gen_config, self.auth_config)
text = response["choices"][0]["text"]
if stop is not None:
for stopping_words in stop:
if stopping_words in text:
text = text.split(stopping_words)[0]
return text
def set_auth_config(self, **kwargs):
url = get_from_dict_or_env(kwargs, "url", "URL")
username = get_from_dict_or_env(kwargs, "username", "USERNAME")
password = get_from_dict_or_env(kwargs, "password", "PASSWORD")
domain_name = get_from_dict_or_env(kwargs, "domain_name", "DOMAIN_NAME")
region = url.split(".")[1]
auth_config = {}
auth_config["endpoint"] = url[url.find("https://") + 8 : url.find(".com") + 4]
auth_config["resource_path"] = url[url.find(".com") + 4 :]
auth_config["auth_token"] = self.get_latest_auth_token(region, username, password, domain_name)
self.auth_config = auth_config
def get_latest_auth_token(self, region, username, password, domain_name):
url = f"https://iam.{region}.myhuaweicloud.com/v3/auth/tokens"
payload = json.dumps(
{
"auth": {
"identity": {
"methods": ["password"],
"password": {"user": {"name": username, "password": password, "domain": {"name": domain_name}}},
},
"scope": {"project": {"name": region}},
}
}
)
headers = {"Content-Type": "application/json"}
response = requests.request("POST", url, headers=headers, data=payload)
return response.headers["X-Subject-Token"]
def text_completion(self, text, gen_config, auth_config):
conn = http.client.HTTPSConnection(auth_config["endpoint"])
payload = json.dumps(
{
"prompt": text,
"user": gen_config["user"],
"max_tokens": gen_config["max_tokens"],
"temperature": gen_config["temperature"],
"n": gen_config["n"],
}
)
headers = {
"X-Auth-Token": auth_config["auth_token"],
"Content-Type": "application/json",
}
conn.request("POST", auth_config["resource_path"], payload, headers)
res = conn.getresponse()
data = res.read()
data = json.loads(data.decode("utf-8"))
return data
def chat_model(self, messages, gen_config, auth_config):
conn = http.client.HTTPSConnection(auth_config["endpoint"])
payload = json.dumps(
{
"messages": messages,
"user": gen_config["user"],
"max_tokens": gen_config["max_tokens"],
"temperature": gen_config["temperature"],
"n": gen_config["n"],
}
)
headers = {
"X-Auth-Token": auth_config["auth_token"],
"Content-Type": "application/json",
}
conn.request("POST", auth_config["resource_path"], payload, headers)
res = conn.getresponse()
data = res.read()
data = json.loads(data.decode("utf-8"))
return data