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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>
This commit is contained in:
YeAnbang
GitHub
150
applications/ColossalQA/colossalqa/local/pangu_llm.py
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150
applications/ColossalQA/colossalqa/local/pangu_llm.py
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"""
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LLM wrapper for Pangu
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Usage:
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# 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”
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# 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
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# PASSWORD: IAM用户的密码
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# 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
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os.environ["URL"] = ""
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os.environ["URLNAME"] = ""
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os.environ["PASSWORD"] = ""
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os.environ["DOMAIN_NAME"] = ""
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pg = Pangu(id=1)
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pg.set_auth_config()
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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?
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"""
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import http.client
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import json
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from typing import Any, List, Mapping, Optional
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import requests
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from langchain.llms.base import LLM
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from langchain.utils import get_from_dict_or_env
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class Pangu(LLM):
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"""
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A custom LLM class that integrates pangu models
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"""
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n: int
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gen_config: dict = None
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auth_config: dict = None
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def __init__(self, gen_config=None, **kwargs):
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super(Pangu, self).__init__(**kwargs)
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if gen_config is None:
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self.gen_config = {"user": "User", "max_tokens": 50, "temperature": 0.95, "n": 1}
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else:
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self.gen_config = gen_config
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@property
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def _identifying_params(self) -> Mapping[str, Any]:
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"""Get the identifying parameters."""
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return {"n": self.n}
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@property
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def _llm_type(self) -> str:
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return "pangu"
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def _call(self, prompt: str, stop: Optional[List[str]] = None, **kwargs) -> str:
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"""
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Args:
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prompt: The prompt to pass into the model.
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stop: A list of strings to stop generation when encountered
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Returns:
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The string generated by the model
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"""
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# Update the generation arguments
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for key, value in kwargs.items():
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if key in self.gen_config:
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self.gen_config[key] = value
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response = self.text_completion(prompt, self.gen_config, self.auth_config)
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text = response["choices"][0]["text"]
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if stop is not None:
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for stopping_words in stop:
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if stopping_words in text:
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text = text.split(stopping_words)[0]
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return text
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def set_auth_config(self, **kwargs):
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url = get_from_dict_or_env(kwargs, "url", "URL")
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username = get_from_dict_or_env(kwargs, "username", "USERNAME")
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password = get_from_dict_or_env(kwargs, "password", "PASSWORD")
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domain_name = get_from_dict_or_env(kwargs, "domain_name", "DOMAIN_NAME")
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region = url.split(".")[1]
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auth_config = {}
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auth_config["endpoint"] = url[url.find("https://") + 8 : url.find(".com") + 4]
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auth_config["resource_path"] = url[url.find(".com") + 4 :]
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auth_config["auth_token"] = self.get_latest_auth_token(region, username, password, domain_name)
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self.auth_config = auth_config
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def get_latest_auth_token(self, region, username, password, domain_name):
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url = f"https://iam.{region}.myhuaweicloud.com/v3/auth/tokens"
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payload = json.dumps(
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{
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"auth": {
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"identity": {
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"methods": ["password"],
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"password": {"user": {"name": username, "password": password, "domain": {"name": domain_name}}},
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},
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"scope": {"project": {"name": region}},
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}
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}
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)
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headers = {"Content-Type": "application/json"}
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response = requests.request("POST", url, headers=headers, data=payload)
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return response.headers["X-Subject-Token"]
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def text_completion(self, text, gen_config, auth_config):
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conn = http.client.HTTPSConnection(auth_config["endpoint"])
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payload = json.dumps(
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{
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"prompt": text,
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"user": gen_config["user"],
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"max_tokens": gen_config["max_tokens"],
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"temperature": gen_config["temperature"],
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"n": gen_config["n"],
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}
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)
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headers = {
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"X-Auth-Token": auth_config["auth_token"],
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"Content-Type": "application/json",
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}
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conn.request("POST", auth_config["resource_path"], payload, headers)
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res = conn.getresponse()
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data = res.read()
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data = json.loads(data.decode("utf-8"))
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return data
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def chat_model(self, messages, gen_config, auth_config):
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conn = http.client.HTTPSConnection(auth_config["endpoint"])
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payload = json.dumps(
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{
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"messages": messages,
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"user": gen_config["user"],
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"max_tokens": gen_config["max_tokens"],
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"temperature": gen_config["temperature"],
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"n": gen_config["n"],
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}
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)
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headers = {
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"X-Auth-Token": auth_config["auth_token"],
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"Content-Type": "application/json",
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}
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conn.request("POST", auth_config["resource_path"], payload, headers)
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res = conn.getresponse()
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data = res.read()
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data = json.loads(data.decode("utf-8"))
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return data
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