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[PYTHON/LANGCHAIN] MultiQueryRetriever 클래스 : invoke 메소드 사용하기 2

■ MultiQueryRetriever 클래스의 invoke 메소드를 사용하는 방법을 보여준다. 2 ※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다. ▶ main.py


from dotenv import load_dotenv
from typing import List

from langchain_community.document_loaders import WebBaseLoader
from langchain_text_splitters             import RecursiveCharacterTextSplitter
from langchain_openai                     import OpenAIEmbeddings
from langchain_chroma                     import Chroma
from langchain_core.prompts               import PromptTemplate
from langchain_openai                     import ChatOpenAI
from langchain_core.output_parsers        import BaseOutputParser
from langchain.retrievers.multi_query     import MultiQueryRetriever

load_dotenv()

webBaseLoader = WebBaseLoader("https://lilianweng.github.io/posts/2023-06-23-agent/")

documentList = webBaseLoader.load()

recursiveCharacterTextSplitter = RecursiveCharacterTextSplitter(chunk_size = 500, chunk_overlap = 0)

splitdocumentList = recursiveCharacterTextSplitter.split_documents(documentList)

openAIEmbeddings = OpenAIEmbeddings()

chroma = Chroma.from_documents(documents = splitdocumentList, embedding = openAIEmbeddings)

promptTemplate = PromptTemplate(
    input_variables = ["question"],
    template        = """You are an AI language model assistant.
Your task is to generate five different versions of the given user question to retrieve relevant documents from a vector database.
By generating multiple perspectives on the user question, your goal is to help the user overcome some of the limitations of the distance-based similarity search.
Provide these alternative questions separated by newlines.
Original question : {question}"""
)

chatOpenAI = ChatOpenAI(temperature = 0)

class LineListOutputParser(BaseOutputParser[List[str]]):
    """Output parser for a list of lines."""

    def parse(self, text : str) -> List[str]:
        lineList = text.strip().split("\n")
        return list(filter(None, lineList))

lineListOutputParser = LineListOutputParser()

runnableSequence = promptTemplate | chatOpenAI | lineListOutputParser

rultiQueryRetriever = MultiQueryRetriever(retriever = chroma.as_retriever(), llm_chain = runnableSequence, parser_key = "lines")

responseDocumentList = rultiQueryRetriever.invoke("What does the course say about regression?")

print(len(responseDocumentList))

from dotenv import load_dotenv

from typing import List

from langchain_community.document_loaders import WebBaseLoader

from langchain_text_splitters import RecursiveCharacterTextSplitter

from langchain_openai import OpenAIEmbeddings

from langchain_chroma import Chroma

from langchain_core.prompts import PromptTemplate

from langchain_openai import ChatOpenAI

from langchain_core.output_parsers import BaseOutputParser

from langchain.retrievers.multi_query import MultiQueryRetriever

load_dotenv()

webBaseLoader = WebBaseLoader("https://lilianweng.github.io/posts/2023-06-23-agent/")

documentList = webBaseLoader.load()

recursiveCharacterTextSplitter = RecursiveCharacterTextSplitter(chunk_size = 500, chunk_overlap = 0)

splitdocumentList = recursiveCharacterTextSplitter.split_documents(documentList)

openAIEmbeddings = OpenAIEmbeddings()

chroma = Chroma.from_documents(documents = splitdocumentList, embedding = openAIEmbeddings)

promptTemplate = PromptTemplate(

input_variables = ["question"],

template = """You are an AI language model assistant.

Your task is to generate five different versions of the given user question to retrieve relevant documents from a vector database.

By generating multiple perspectives on the user question, your goal is to help the user overcome some of the limitations of the distance-based similarity search.

Provide these alternative questions separated by newlines.

Original question : {question}"""

)

chatOpenAI = ChatOpenAI(temperature = 0)

class LineListOutputParser(BaseOutputParser[List[str]]):

"""Output parser for a list of lines."""

def parse(self, text : str) -> List[str]:

lineList = text.strip().split("\n")

return list(filter(None, lineList))

lineListOutputParser = LineListOutputParser()

runnableSequence = promptTemplate | chatOpenAI | lineListOutputParser

rultiQueryRetriever = MultiQueryRetriever(retriever = chroma.as_retriever(), llm_chain = runnableSequence, parser_key = "lines")

responseDocumentList = rultiQueryRetriever.invoke("What does the course say about regression?")

print(len(responseDocumentList))

▶ requirements.txt

[PYTHON/LANGCHAIN] MultiQueryRetriever 클래스 : invoke 메소드 사용하기 1

■ MultiQueryRetriever 클래스의 invoke 메소드를 사용하는 방법을 보여준다. ※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다. ▶ main.py


import logging

from dotenv import load_dotenv

from langchain_community.document_loaders import WebBaseLoader
from langchain_text_splitters             import RecursiveCharacterTextSplitter
from langchain_openai                     import OpenAIEmbeddings
from langchain_chroma                     import Chroma
from langchain_openai                     import ChatOpenAI
from langchain.retrievers.multi_query     import MultiQueryRetriever

logging.basicConfig()

logger = logging.getLogger("langchain.retrievers.multi_query")

logger.setLevel(logging.INFO)

load_dotenv()

webBaseLoader = WebBaseLoader("https://lilianweng.github.io/posts/2023-06-23-agent/")

documentList = webBaseLoader.load()

recursiveCharacterTextSplitter = RecursiveCharacterTextSplitter(chunk_size = 500, chunk_overlap = 0)

splitDocumentList = recursiveCharacterTextSplitter.split_documents(documentList)

openAIEmbeddings = OpenAIEmbeddings()

chroma = Chroma.from_documents(documents = splitDocumentList, embedding = openAIEmbeddings)

vectorStoreRetriever = chroma.as_retriever()

chatOpenAI = ChatOpenAI(temperature = 0)

multiQueryRetriever = MultiQueryRetriever.from_llm(retriever = vectorStoreRetriever, llm = chatOpenAI)

question = "What are the approaches to Task Decomposition?"

responseDocumentList = multiQueryRetriever.invoke(question)

print(len(responseDocumentList))

print(responseDocumentList[0].page_content)

"""
5
Task decomposition can be done (1) by LLM with simple prompting like "Steps for XYZ.\n1.", "What are the subgoals for achieving XYZ?", (2) by using task-specific instructions; e.g. "Write a story outline." for writing a novel, or (3) with human inputs.
"""

import logging

from dotenv import load_dotenv

from langchain_community.document_loaders import WebBaseLoader

from langchain_text_splitters import RecursiveCharacterTextSplitter

from langchain_openai import OpenAIEmbeddings

from langchain_chroma import Chroma

from langchain_openai import ChatOpenAI

from langchain.retrievers.multi_query import MultiQueryRetriever

logging.basicConfig()

logger = logging.getLogger("langchain.retrievers.multi_query")

logger.setLevel(logging.INFO)

load_dotenv()

webBaseLoader = WebBaseLoader("https://lilianweng.github.io/posts/2023-06-23-agent/")

documentList = webBaseLoader.load()

recursiveCharacterTextSplitter = RecursiveCharacterTextSplitter(chunk_size = 500, chunk_overlap = 0)

splitDocumentList = recursiveCharacterTextSplitter.split_documents(documentList)

openAIEmbeddings = OpenAIEmbeddings()

chroma = Chroma.from_documents(documents = splitDocumentList, embedding = openAIEmbeddings)

vectorStoreRetriever = chroma.as_retriever()

chatOpenAI = ChatOpenAI(temperature = 0)

multiQueryRetriever = MultiQueryRetriever.from_llm(retriever = vectorStoreRetriever, llm = chatOpenAI)

question = "What are the approaches to Task Decomposition?"

responseDocumentList = multiQueryRetriever.invoke(question)

print(len(responseDocumentList))

print(responseDocumentList[0].page_content)

"""

Task decomposition can be done (1) by LLM with simple prompting like "Steps for XYZ.\n1.", "What are the subgoals for achieving XYZ?", (2) by using task-specific instructions; e.g. "Write a story outline." for writing a novel, or (3) with human inputs.

"""

▶ requirements.txt


aiohappyeyeballs==2.3.5
aiohttp==3.10.3
aiosignal==1.3.1
annotated-types==0.7.0
anyio==4.4.0
asgiref==3.8.1
async-timeout==4.0.3
attrs==24.2.0
backoff==2.2.1
bcrypt==4.2.0
beautifulsoup4==4.12.3
bs4==0.0.2
build==1.2.1
cachetools==5.4.0
certifi==2024.7.4
charset-normalizer==3.3.2
chroma-hnswlib==0.7.6
chromadb==0.5.5
click==8.1.7
coloredlogs==15.0.1
dataclasses-json==0.6.7
Deprecated==1.2.14
distro==1.9.0
exceptiongroup==1.2.2
fastapi==0.112.0
filelock==3.15.4
flatbuffers==24.3.25
frozenlist==1.4.1
fsspec==2024.6.1
google-auth==2.33.0
googleapis-common-protos==1.63.2
greenlet==3.0.3
grpcio==1.65.4
h11==0.14.0
httpcore==1.0.5
httptools==0.6.1
httpx==0.27.0
huggingface-hub==0.24.5
humanfriendly==10.0
idna==3.7
importlib_metadata==8.0.0
importlib_resources==6.4.0
jiter==0.5.0
jsonpatch==1.33
jsonpointer==3.0.0
kubernetes==30.1.0
langchain==0.2.12
langchain-chroma==0.1.2
langchain-community==0.2.11
langchain-core==0.2.29
langchain-openai==0.1.21
langchain-text-splitters==0.2.2
langsmith==0.1.98
markdown-it-py==3.0.0
marshmallow==3.21.3
mdurl==0.1.2
mmh3==4.1.0
monotonic==1.6
mpmath==1.3.0
multidict==6.0.5
mypy-extensions==1.0.0
numpy==1.26.4
oauthlib==3.2.2
onnxruntime==1.18.1
openai==1.40.3
opentelemetry-api==1.26.0
opentelemetry-exporter-otlp-proto-common==1.26.0
opentelemetry-exporter-otlp-proto-grpc==1.26.0
opentelemetry-instrumentation==0.47b0
opentelemetry-instrumentation-asgi==0.47b0
opentelemetry-instrumentation-fastapi==0.47b0
opentelemetry-proto==1.26.0
opentelemetry-sdk==1.26.0
opentelemetry-semantic-conventions==0.47b0
opentelemetry-util-http==0.47b0
orjson==3.10.7
overrides==7.7.0
packaging==24.1
posthog==3.5.0
protobuf==4.25.4
pyasn1==0.6.0
pyasn1_modules==0.4.0
pydantic==2.8.2
pydantic_core==2.20.1
Pygments==2.18.0
PyPika==0.48.9
pyproject_hooks==1.1.0
python-dateutil==2.9.0.post0
python-dotenv==1.0.1
PyYAML==6.0.2
regex==2024.7.24
requests==2.32.3
requests-oauthlib==2.0.0
rich==13.7.1
rsa==4.9
shellingham==1.5.4
six==1.16.0
sniffio==1.3.1
soupsieve==2.5
SQLAlchemy==2.0.32
starlette==0.37.2
sympy==1.13.1
tenacity==8.5.0
tiktoken==0.7.0
tokenizers==0.20.0
tomli==2.0.1
tqdm==4.66.5
typer==0.12.3
typing-inspect==0.9.0
typing_extensions==4.12.2
urllib3==2.2.2
uvicorn==0.30.5
uvloop==0.19.0
watchfiles==0.23.0
websocket-client==1.8.0
websockets==12.0
wrapt==1.16.0
yarl==1.9.4
zipp==3.19.2

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aiohappyeyeballs==2.3.5

aiohttp==3.10.3

aiosignal==1.3.1

annotated-types==0.7.0

anyio==4.4.0

asgiref==3.8.1

async-timeout==4.0.3

attrs==24.2.0

backoff==2.2.1

bcrypt==4.2.0

beautifulsoup4==4.12.3

bs4==0.0.2

build==1.2.1

cachetools==5.4.0

certifi==2024.7.4

charset-normalizer==3.3.2

chroma-hnswlib==0.7.6

chromadb==0.5.5

click==8.1.7

coloredlogs==15.0.1

dataclasses-json==0.6.7

Deprecated==1.2.14

distro==1.9.0

exceptiongroup==1.2.2

fastapi==0.112.0

filelock==3.15.4

flatbuffers==24.3.25

frozenlist==1.4.1

fsspec==2024.6.1

google-auth==2.33.0

googleapis-common-protos==1.63.2

greenlet==3.0.3

grpcio==1.65.4

h11==0.14.0

httpcore==1.0.5

httptools==0.6.1

httpx==0.27.0

huggingface-hub==0.24.5

humanfriendly==10.0

idna==3.7

importlib_metadata==8.0.0

importlib_resources==6.4.0

jiter==0.5.0

jsonpatch==1.33

jsonpointer==3.0.0

kubernetes==30.1.0

langchain==0.2.12

langchain-chroma==0.1.2

langchain-community==0.2.11

langchain-core==0.2.29

langchain-openai==0.1.21

langchain-text-splitters==0.2.2

langsmith==0.1.98

markdown-it-py==3.0.0

marshmallow==3.21.3

mdurl==0.1.2

mmh3==4.1.0

monotonic==1.6

mpmath==1.3.0

multidict==6.0.5

mypy-extensions==1.0.0

numpy==1.26.4

oauthlib==3.2.2

onnxruntime==1.18.1

openai==1.40.3

opentelemetry-api==1.26.0

opentelemetry-exporter-otlp-proto-common==1.26.0

opentelemetry-exporter-otlp-proto-grpc==1.26.0

opentelemetry-instrumentation==0.47b0

opentelemetry-instrumentation-asgi==0.47b0

opentelemetry-instrumentation-fastapi==0.47b0

opentelemetry-proto==1.26.0

opentelemetry-sdk==1.26.0

opentelemetry-semantic-conventions==0.47b0

opentelemetry-util-http==0.47b0

orjson==3.10.7

overrides==7.7.0

packaging==24.1

posthog==3.5.0

protobuf==4.25.4

pyasn1==0.6.0

pyasn1_modules==0.4.0

pydantic==2.8.2

pydantic_core==2.20.1

Pygments==2.18.0

PyPika==0.48.9

pyproject_hooks==1.1.0

python-dateutil==2.9.0.post0

python-dotenv==1.0.1

PyYAML==6.0.2

regex==2024.7.24

requests==2.32.3

requests-oauthlib==2.0.0

rich==13.7.1

rsa==4.9

shellingham==1.5.4

six==1.16.0

sniffio==1.3.1

soupsieve==2.5

SQLAlchemy==2.0.32

starlette==0.37.2

sympy==1.13.1

tenacity==8.5.0

tiktoken==0.7.0

tokenizers==0.20.0

tomli==2.0.1

tqdm==4.66.5

typer==0.12.3

typing-inspect==0.9.0

typing_extensions==4.12.2

urllib3==2.2.2

uvicorn==0.30.5

uvloop==0.19.0

watchfiles==0.23.0

websocket-client==1.8.0

websockets==12.0

wrapt==1.16.0

yarl==1.9.4

zipp==3.19.2

[PYTHON/LANGCHAIN] MultiQueryRetriever 클래스 : 생성자에서 retriever/llm_chain/parser_key 인자를 사용해 MultiQueryRetriever 객체 만들기

■ MultiQueryRetriever 클래스의 생성자에서 retriever/llm_chain/parser_key 인자를 사용해 MultiQueryRetriever 객체를 만드는 방법을 보여준다. ※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다. ▶ 예제

[PYTHON/LANGCHAIN] from_llm 함수 : retriever/llm 인자를 사용해 multiQueryRetriever 객체 만들기

■ from_llm 함수의 retriever/llm 인자를 사용해 multiQueryRetriever 객체를 만드는 방법을 보여준다. ※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다. ▶ 예제 코드

[PYTHON/LANGCHAIN] from_documents 함수 : documents/embedding 인자를 사용해 메모리 내 벡터 저장소를 위한 Chroma 객체 만들기

■ from_documents 함수의 documents/embedding 인자를 사용해 메모리 내 벡터 저장소를 위한 Chroma 객체를 만드는 방법을 보여준다. ※ OPENAI_API_KEY 환경 변수 값은 .env

[PYTHON/LANGCHAIN] WebBaseLoader 클래스 : 생성자에서 web_paths/bs_kwargs 인자를 사용해 웹 문서 로더 만들기

■ WebBaseLoader 클래스의 생성자에서 web_paths/bs_kwargs 인자를 사용해 웹 문서 로더를 만드는 방법을 보여준다. ▶ main.py


import bs4

from langchain_community.document_loaders import WebBaseLoader

webBaseLoader = WebBaseLoader(
    web_paths = ("https://lilianweng.github.io/posts/2023-06-23-agent/",),
    bs_kwargs = dict(parse_only = bs4.SoupStrainer(class_ = ("post-content", "post-title", "post-header")))
)

import bs4

from langchain_community.document_loaders import WebBaseLoader

webBaseLoader = WebBaseLoader(

web_paths = ("https://lilianweng.github.io/posts/2023-06-23-agent/",),

bs_kwargs = dict(parse_only = bs4.SoupStrainer(class_ = ("post-content", "post-title", "post-header")))

)

[PYTHON/LANGCHAIN] WebBaseLoader 클래스 : load 메소드를 사용해 웹 문서 로드하기

■ WebBaseLoader 클래스의 load 메소드를 사용해 웹 문서를 로드하는 방법을 보여준다. ▶ 예제 코드 (PY)


from langchain_community.document_loaders import WebBaseLoader

webBaseLoader = WebBaseLoader("https://lilianweng.github.io/posts/2023-06-23-agent/")

documentList = webBaseLoader.load()

from langchain_community.document_loaders import WebBaseLoader

webBaseLoader = WebBaseLoader("https://lilianweng.github.io/posts/2023-06-23-agent/")

documentList = webBaseLoader.load()

[PYTHON/LANGCHAIN] WebBaseLoader 클래스 : 웹 문서 로더 만들기

■ WebBaseLoader 클래스를 사용해 웹 문서 로더를 만드는 방법을 보여준다. ▶ 예제 코드 (PY)


from langchain_community.document_loaders import WebBaseLoader

webBaseLoader = WebBaseLoader("https://lilianweng.github.io/posts/2023-06-23-agent/")

from langchain_community.document_loaders import WebBaseLoader

webBaseLoader = WebBaseLoader("https://lilianweng.github.io/posts/2023-06-23-agent/")

[C#/WINUI3/.NET8] Launcher 클래스 : LaunchUriAsync 정적 메소드를 사용해 웹 브라우저 실행하기

■ Launcher 클래스의 LaunchUriAsync 정적 메소드를 사용해 웹 브라우저를 실행하는 방법을 보여준다. ▶ 예제 코드 (C#)


using System;
using Windows.System;

#region 웹 브라우저 실행하기 (비동기) - ExecuteWebBrowserAsync(url)

/// <summary>
/// 웹 브라우저 실행하기 (비동기)
/// </summary>
/// <param name="url">URL</param>
public async void ExecuteWebBrowserAsync(string url)
{
    Uri uri = new Uri(url);

    await Launcher.LaunchUriAsync(uri);
}

#endregion

using System;

using Windows.System;

#region 웹 브라우저 실행하기 (비동기) - ExecuteWebBrowserAsync(url)

/// <summary>

/// 웹 브라우저 실행하기 (비동기)

/// </summary>

/// <param name="url">URL</param>

public async void ExecuteWebBrowserAsync(string url)

{

Uri uri = new Uri(url);

await Launcher.LaunchUriAsync(uri);

}

#endregion

[PYTHON/LANGCHAIN] WebBaseLoader 클래스 : load 메소드를 사용해 웹 문서 로드하기

■ WebBaseLoader 클래스의 load 메소드를 사용해 웹 문서를 로드하는 방법을 보여준다. ▶ main.py


import bs4

from langchain_community.document_loaders import WebBaseLoader

webBaseLoader = WebBaseLoader(
    web_paths = ("https://lilianweng.github.io/posts/2023-06-23-agent/",),
    bs_kwargs = dict(parse_only = bs4.SoupStrainer(class_ = ("post-content", "post-title", "post-header")))
)

documentList = webBaseLoader.load()

import bs4

from langchain_community.document_loaders import WebBaseLoader

webBaseLoader = WebBaseLoader(

web_paths = ("https://lilianweng.github.io/posts/2023-06-23-agent/",),

bs_kwargs = dict(parse_only = bs4.SoupStrainer(class_ = ("post-content", "post-title", "post-header")))

)

documentList = webBaseLoader.load()

▶ requirements.txt


aiohttp==3.9.5
aiosignal==1.3.1
annotated-types==0.7.0
async-timeout==4.0.3
attrs==23.2.0
beautifulsoup4==4.12.3
bs4==0.0.2
certifi==2024.6.2
charset-normalizer==3.3.2
dataclasses-json==0.6.7
frozenlist==1.4.1
greenlet==3.0.3
idna==3.7
jsonpatch==1.33
jsonpointer==3.0.0
langchain==0.2.3
langchain-community==0.2.4
langchain-core==0.2.5
langchain-text-splitters==0.2.1
langsmith==0.1.76
marshmallow==3.21.3
multidict==6.0.5
mypy-extensions==1.0.0
numpy==1.26.4
orjson==3.10.4
packaging==23.2
pydantic==2.7.3
pydantic_core==2.18.4
PyYAML==6.0.1
requests==2.32.3
soupsieve==2.5
SQLAlchemy==2.0.30
tenacity==8.3.0
typing-inspect==0.9.0
typing_extensions==4.12.2
urllib3==2.2.1
yarl==1.9.4

aiohttp==3.9.5

aiosignal==1.3.1

annotated-types==0.7.0

async-timeout==4.0.3

attrs==23.2.0

beautifulsoup4==4.12.3

bs4==0.0.2

certifi==2024.6.2

charset-normalizer==3.3.2

dataclasses-json==0.6.7

frozenlist==1.4.1

greenlet==3.0.3

idna==3.7

jsonpatch==1.33

jsonpointer==3.0.0

langchain==0.2.3

langchain-community==0.2.4

langchain-core==0.2.5

langchain-text-splitters==0.2.1

langsmith==0.1.76

marshmallow==3.21.3

multidict==6.0.5

mypy-extensions==1.0.0

numpy==1.26.4

orjson==3.10.4

packaging==23.2

pydantic==2.7.3

pydantic_core==2.18.4

PyYAML==6.0.1

requests==2.32.3

soupsieve==2.5

SQLAlchemy==2.0.30

tenacity==8.3.0

typing-inspect==0.9.0

typing_extensions==4.12.2

urllib3==2.2.1

yarl==1.9.4

※ pip install bs4 langchain_community

[RUST/TIDE] tide 크레이트를 사용해 값 입력 웹 서버 만들기

■ tide 크레이트를 사용해 값을 입력받는 웹 서버를 만드는 방법을 보여준다. ▶ Cargo.toml


[package]
name = "test_server"
version = "0.1.0"
edition = "2021"

[dependencies]
tide = "0.16"
async-std = {version = "1.8.0", features = ["attributes"]}
serde = {version = "1.0", features = ["derive"]}

[package]

name = "test_server"

version = "0.1.0"

edition = "2021"

[dependencies]

tide = "0.16"

async-std = {version = "1.8.0", features = ["attributes"]}

serde = {version = "1.0", features = ["derive"]}

▶ src/main.rs


use tide::prelude::*;

const SERVER_ADDRESS : &str = "127.0.0.1:8888";

#[derive(Deserialize, Serialize)]
struct UserInformation
{
    name : String
}

#[async_std::main]
async fn main() -> tide::Result<()>
{
    println!("http://{}/", SERVER_ADDRESS);

    let mut server : tide::Server<()> = tide::new();

    server.at("/")
        .get
        (
            |_| async
            {
                Ok
                (
                    tide::Response::builder(200)
                    .content_type(tide::http::mime::HTML)
                    .body
                    (
r#"<html>
<body>
<form action='hello'>
name : <input name='name' value='홍길동'>
<input type='submit' value='전송'>
</form>
</body>
</html>"#
                    )
                    .build()
                )
            }
        );

    server.at("/hello")
        .get
        (
            |request : tide::Request<()>| async move
            {
                let user_information : UserInformation = request.query()?;

                return Ok
                (
                    tide::Response::builder(200)
                        .content_type(tide::http::mime::HTML)
                        .body(format!("<h1>안녕하세요, {}님</h1>", user_information.name))
                        .build()
                );
            }
        );

    server.listen(SERVER_ADDRESS).await?;

    return Ok(());
}

use tide::prelude::*;

const SERVER_ADDRESS : &str = "127.0.0.1:8888";

#[derive(Deserialize, Serialize)]

struct UserInformation

{

name : String

}

#[async_std::main]

async fn main() -> tide::Result<()>

{

println!("http://{}/", SERVER_ADDRESS);

let mut server : tide::Server<()> = tide::new();

server.at("/")

.get

(

|_| async

{

(

tide::Response::builder(200)

.content_type(tide::http::mime::HTML)

.body

(

r#"<html>

<body>

name : <input name='name' value='홍길동'>

</form>

</body>

</html>"#

)

.build()

)

}

);

server.at("/hello")

.get

(

|request : tide::Request<()>| async move

{

let user_information : UserInformation = request.query()?;

return Ok

(

tide::Response::builder(200)

.content_type(tide::http::mime::HTML)

.body(format!("<h1>안녕하세요, {}님</h1>", user_information.name))

.build()

);

}

);

server.listen(SERVER_ADDRESS).await?;

return Ok(());

}

test_server.zip

[RUST/TIDE] tide 크레이트를 사용해 단순 웹 서버 만들기

■ tide 크레이트를 사용해 단순 웹 서버를 만드는 방법을 보여준다. ▶ Cargo.toml


[package]
name = "test_server"
version = "0.1.0"
edition = "2021"

[dependencies]
tide = "0.16"
async-std = {version = "1.8.0", features = ["attributes"]}

[package]

name = "test_server"

version = "0.1.0"

edition = "2021"

[dependencies]

tide = "0.16"

async-std = {version = "1.8.0", features = ["attributes"]}

▶ src/main.rs


const SERVER_ADDRESS : &str = "127.0.0.1:8888";

#[async_std::main]
async fn main() -> tide::Result<()>
{
    println!("http://{}/", SERVER_ADDRESS);

    let mut server : tide::Server<()> = tide::new();

    server.at("/").get
    (
        |_| async
        {
            return Ok("Hello, World!");
        }
    );

    server.listen(SERVER_ADDRESS).await?;

    return Ok(());
}

const SERVER_ADDRESS : &str = "127.0.0.1:8888";

#[async_std::main]

async fn main() -> tide::Result<()>

{

println!("http://{}/", SERVER_ADDRESS);

let mut server : tide::Server<()> = tide::new();

server.at("/").get

(

|_| async

{

return Ok("Hello, World!");

}

);

server.listen(SERVER_ADDRESS).await?;

return Ok(());

}

test_server.zip

[RUST/COMMON] 크레이트 설치 : tide

■ tide 크레이트를 설치하는 방법을 보여준다. ▶ Cargo.toml


...

[dependencies]
tide = "0.16"

...

[dependencies]

tide = "0.16"

[RUST/ACTIX-WEB] Actix Web 프레임워크를 사용해 BMI 판정 웹 서버 만들기

■ Actix Web 프레임워크를 사용해 BMI 판정 웹 서버를 만드는 방법을 보여준다. ▶ Cargo.toml


[package]
name = "test_server"
version = "0.1.0"
edition = "2021"

[dependencies]
actix-web = "3"
serde = "1.0"

[package]

name = "test_server"

version = "0.1.0"

edition = "2021"

[dependencies]

actix-web = "3"

serde = "1.0"

▶ src/main.rs


use std::io;

use actix_web::web;
use serde;

const SERVER_ADDRESS : &str = "127.0.0.1:8888";

#[actix_web::main]
async fn main() -> io::Result<()>
{
    println!("[서버] http://{}/", SERVER_ADDRESS);

    actix_web::HttpServer::new
    (
        ||
        {
            actix_web::App::new()
                .service(index)
                .service(calculate)
        }
    )
    .bind(SERVER_ADDRESS)?
    .run()
    .await
}

#[actix_web::get("/")]
async fn index(_ : actix_web::HttpRequest) -> Result<actix_web::HttpResponse, actix_web::Error>
{
    return Ok
    (
        actix_web::HttpResponse::Ok()
            .content_type("text/html; charset=utf-8")
            .body
            (
r#"
<html>
<body>
<h1>BMI 계산 및 비만도 판정</h1>
<form action='calculate'>
<div>키 : <div><label><input name='height' value='160'></label></div></div>
<div>몸무게 : <div><label><input name='weight' value='70'></label></div></div>
<div><label><input type='submit' value='확인'></label></div>
</form>
</body>
</html>
"#
            )
    );
}

#[derive(serde::Deserialize, Debug)]
pub struct BMI
{
    height : f64,
    weight : f64,
}

#[actix_web::get("/calculate")]
async fn calculate(bmi : web::Query<BMI>) -> Result<actix_web::HttpResponse, actix_web::Error>
{
    println!("{:?}", bmi);

    let temporary_height : f64 = bmi.height / 100.0;
    let bmi              : f64 = bmi.weight / (temporary_height * temporary_height);
    let bmi_percentage   : f64 = (bmi / 22.0) * 100.0;

    return Ok(actix_web::HttpResponse::Ok()
        .content_type("text/html; charset=utf-8")
        .body(format!("<h3>BMI = {:.1}, 비만율 = {:.0}%</h3>", bmi, bmi_percentage)));
}

use std::io;

use actix_web::web;

use serde;

const SERVER_ADDRESS : &str = "127.0.0.1:8888";

#[actix_web::main]

async fn main() -> io::Result<()>

{

println!("[서버] http://{}/", SERVER_ADDRESS);

actix_web::HttpServer::new

(

{

actix_web::App::new()

.service(index)

.service(calculate)

}

)

.bind(SERVER_ADDRESS)?

.run()

.await

}

#[actix_web::get("/")]

async fn index(_ : actix_web::HttpRequest) -> Result<actix_web::HttpResponse, actix_web::Error>

{

return Ok

(

actix_web::HttpResponse::Ok()

.content_type("text/html; charset=utf-8")

.body

(

r#"

<html>

<body>

</form>

</body>

</html>

)

);

}

#[derive(serde::Deserialize, Debug)]

pub struct BMI

{

height : f64,

weight : f64,

}

#[actix_web::get("/calculate")]

async fn calculate(bmi : web::Query<BMI>) -> Result<actix_web::HttpResponse, actix_web::Error>

{

println!("{:?}", bmi);

let temporary_height : f64 = bmi.height / 100.0;

let bmi : f64 = bmi.weight / (temporary_height * temporary_height);

let bmi_percentage : f64 = (bmi / 22.0) * 100.0;

return Ok(actix_web::HttpResponse::Ok()

.content_type("text/html; charset=utf-8")

.body(format!("<h3>BMI = {:.1}, 비만율 = {:.0}%</h3>", bmi, bmi_percentage)));

}

test_server.zip

[RUST/ACTIX-WEB] Actix Web 프레임워크를 사용해 단순 웹 서버 만들기

■ Actix Web 프레임워크를 사용해 단순 웹 서버를 만드는 방법을 보여준다. ▶ Cargo.toml


[package]
name = "test_server"
version = "0.1.0"
edition = "2021"

[dependencies]
actix-web = "3"

[package]

name = "test_server"

version = "0.1.0"

edition = "2021"

[dependencies]

actix-web = "3"

▶ src/main.rs


use actix_web;

const SERVER_ADDRESS : &str = "127.0.0.1:8888";

#[actix_web::main]
async fn main() -> Result<(), actix_web::Error>
{
    println!("[서버] http://{}/", SERVER_ADDRESS);

    actix_web::HttpServer::new
    (
        ||
        {
            actix_web::App::new().route("/", actix_web::web::get().to(index))
        }
    )
    .bind(SERVER_ADDRESS)?
    .run()
    .await?;

    return Ok(());
}

async fn index(request : actix_web::HttpRequest) -> Result<actix_web::HttpResponse, actix_web::Error>
{
    println!("요청 : {:?}", request);

    let result : &str = "안녕하세요.";

    Ok(actix_web::HttpResponse::Ok().body(result))
}

use actix_web;

const SERVER_ADDRESS : &str = "127.0.0.1:8888";

#[actix_web::main]

async fn main() -> Result<(), actix_web::Error>

{

println!("[서버] http://{}/", SERVER_ADDRESS);

actix_web::HttpServer::new

(

{

actix_web::App::new().route("/", actix_web::web::get().to(index))

}

)

.bind(SERVER_ADDRESS)?

.run()

.await?;

return Ok(());

}

async fn index(request : actix_web::HttpRequest) -> Result<actix_web::HttpResponse, actix_web::Error>

{

println!("요청 : {:?}", request);

let result : &str = "안녕하세요.";

Ok(actix_web::HttpResponse::Ok().body(result))

}

test_server.zip

[RUST/COMMON] 크레이트 설치 : actix-web

■ actix-web 크레이트를 설치하는 방법을 보여준다. ▶ Cargo.toml


...

[dependencies]
actix-web = "3"

...

[dependencies]

actix-web = "3"

[WEB] 애드센스 광고 안나오는 경우 처리하기

■ 애드센스 광고 안나오는 경우 처리하는 방법을 보여준다. 1. 웹 브라우저를 실행한다. 2. 해당 티스토리 관리자 페이지로 이동한다. 3. 관리자 페이지 좌측

[C#/UWP] Launcher 클래스 : LaunchUriAsync 정적 메소드를 사용해 웹 브라우저 실행하기

■ Launcher 클래스의 LaunchUriAsync 정적 메소드를 사용해 웹 브라우저를 실행하는 방법을 보여준다. ▶ 예제 코드 (C#)


using System;
using Windows.System;

#region 웹 브라우저 실행하기 (비동기) - ExecuteWebBrowserAsync(url)

/// <summary>
/// 웹 브라우저 실행하기 (비동기)
/// </summary>
/// <param name="url">URL</param>
public async void ExecuteWebBrowserAsync(string url)
{
    Uri uri = new Uri(url);

    await Launcher.LaunchUriAsync(uri);
}

#endregion

using System;

using Windows.System;

#region 웹 브라우저 실행하기 (비동기) - ExecuteWebBrowserAsync(url)

/// <summary>

/// 웹 브라우저 실행하기 (비동기)

/// </summary>

/// <param name="url">URL</param>

public async void ExecuteWebBrowserAsync(string url)

{

Uri uri = new Uri(url);

await Launcher.LaunchUriAsync(uri);

}

#endregion

[C#/COMMON/OUTLOOK] MAPIFolder 인터페이스 : WebViewURL/WebViewOn 속성을 사용해 아웃룩 폴더에 웹 페이지 연결하기

■ MAPIFolder 인터페이스의 WebViewURL/WebViewOn 속성을 사용해 아웃룩 폴더에 웹 페이지를 연결하는 방법을 보여준다. ▶ CustomAddIn.cs


using Microsoft.Office.Interop.Outlook;
using System;
using System.Windows.Forms;

namespace TestProject
{
    /// <summary>
    /// 커스텀 애드인
    /// </summary>
    public partial class CustomAddIn
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Method
        ////////////////////////////////////////////////////////////////////////////////////////// Private
        //////////////////////////////////////////////////////////////////////////////// Event

        #region 커스텀 애드인 시작시 처리하기 - CustomAddIn_Startup(sender, e)

        /// <summary>
        /// 커스텀 애드인 시작시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void CustomAddIn_Startup(object sender, EventArgs e)
        {
            CreateHTMLFolder();
        }

        #endregion
        #region 커스텀 애드인 셧다운시 처리하기 - CustomAddIn_Shutdown(sender, e)

        /// <summary>
        /// 커스텀 애드인 셧다운시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void CustomAddIn_Shutdown(object sender, EventArgs e)
        {
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////// Function

        #region VSTO에서 생성한 코드

        /// <summary>
        /// 디자이너 지원에 필요한 메서드입니다.
        /// 이 메서드의 내용을 코드 편집기로 수정하지 마세요.
        /// </summary>
        private void InternalStartup()
        {
            this.Startup  += new System.EventHandler(CustomAddIn_Startup );
            this.Shutdown += new System.EventHandler(CustomAddIn_Shutdown);
        }

        #endregion

        #region HTML 폴더 생성하기 - CreateHTMLFolder()

        /// <summary>
        /// HTML 폴더 생성하기
        /// </summary>
        private void CreateHTMLFolder()
        {
            MAPIFolder inboxFolder = Application.ActiveExplorer().Session.GetDefaultFolder(OlDefaultFolders.olFolderInbox);

            Folders folders = inboxFolder.Folders;

            MAPIFolder htmlViewFolder = null;

            foreach(MAPIFolder folder in folders)
            {
                if(folder.Name == "HTMLView")
                {
                    htmlViewFolder = inboxFolder.Folders["HTMLView"];

                    break;
                }
            }

            if(htmlViewFolder != null)
            {
                htmlViewFolder = (MAPIFolder)inboxFolder.Folders.Add("HTMLView", OlDefaultFolders.olFolderInbox);

                htmlViewFolder.WebViewURL = "http://www.microsoft.com";
                htmlViewFolder.WebViewOn  = true;
            }

            Application.ActiveExplorer().SelectFolder(htmlViewFolder);

            Application.ActiveExplorer().CurrentFolder.Display();
        }

        #endregion
    }
}

using Microsoft.Office.Interop.Outlook;

using System;

using System.Windows.Forms;

namespace TestProject

{

/// <summary>

/// 커스텀 애드인

/// </summary>

public partial class CustomAddIn

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Method

////////////////////////////////////////////////////////////////////////////////////////// Private

//////////////////////////////////////////////////////////////////////////////// Event

#region 커스텀 애드인 시작시 처리하기 - CustomAddIn_Startup(sender, e)

/// <summary>

/// 커스텀 애드인 시작시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void CustomAddIn_Startup(object sender, EventArgs e)

{

CreateHTMLFolder();

}

#endregion

#region 커스텀 애드인 셧다운시 처리하기 - CustomAddIn_Shutdown(sender, e)

/// <summary>

/// 커스텀 애드인 셧다운시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void CustomAddIn_Shutdown(object sender, EventArgs e)

{

}

#endregion

//////////////////////////////////////////////////////////////////////////////// Function

#region VSTO에서 생성한 코드

/// <summary>

/// 디자이너 지원에 필요한 메서드입니다.

/// 이 메서드의 내용을 코드 편집기로 수정하지 마세요.

/// </summary>

private void InternalStartup()

{

this.Startup += new System.EventHandler(CustomAddIn_Startup );

this.Shutdown += new System.EventHandler(CustomAddIn_Shutdown);

}

#endregion

#region HTML 폴더 생성하기 - CreateHTMLFolder()

/// <summary>

/// HTML 폴더 생성하기

/// </summary>

private void CreateHTMLFolder()

{

MAPIFolder inboxFolder = Application.ActiveExplorer().Session.GetDefaultFolder(OlDefaultFolders.olFolderInbox);

Folders folders = inboxFolder.Folders;

MAPIFolder htmlViewFolder = null;

foreach(MAPIFolder folder in folders)

{

if(folder.Name == "HTMLView")

{

htmlViewFolder = inboxFolder.Folders["HTMLView"];

break;

}

if(htmlViewFolder != null)

{

htmlViewFolder = (MAPIFolder)inboxFolder.Folders.Add("HTMLView", OlDefaultFolders.olFolderInbox);

htmlViewFolder.WebViewURL = "http://www.microsoft.com";

htmlViewFolder.WebViewOn = true;

}

Application.ActiveExplorer().SelectFolder(htmlViewFolder);

Application.ActiveExplorer().CurrentFolder.Display();

}

#endregion

}

※ Outlook 2019에서 실행은 되나 정확히

[WEB] 티스토리 사이트맵 주소 만들기

■ 티스토리 사이트맵 주소를 만드는 방법을 보여준다. 1. 크롬 브라우저를 실행한다. 2. 크롬 브라우저에서 티스토리 블로그 주소를 입력한다. 3. [관리자] 버튼을 클릭하고

[WEB] 티스토리 사이트맵 파일 구하기

■ 티스토리 사이트맵 파일을 구하는 방법을 보여준다. 1. Internet Explorer를 실행한다. 2. 아래 주소를 입력한다. ▶ 주소


https://icodebroker.tistory.com/sitemap.xml

https://icodebroker.tistory.com/sitemap.xml

※ icodebroker.tistory.com : 각자

[WEB] 티스토리 OPEN API 액세스 토큰 구하기

■ 티스토리에서 OPEN API 액세스 토큰을 구하는 방법을 보여준다. 1. 웹 브라우저를 실행하고 아래 주소를 입력한다. ▶ URL


https://www.tistory.com/guide/api/manage/register

https://www.tistory.com/guide/api/manage/register

2. [앱 등록]

[WEB] .config 파일 다운로드 설정하기

■ .config 파일의 다운로드를 설정하는 방법을 보여준다. 1. [명령 프롬프트]를 관리자 권한으로 실행한다. 2. 아래 명령을 실행한다. ▶ 실행 명령


c:\windows\system32\inetsrv\appcmd.exe set config -section:system.webServer/security/requestFiltering /-fileExtensions.[fileExtension='.config']

또는

c:\Windows\system32\inetsrv\appcmd.exe set config "MySite/MyApp/MyFolder" -section:system.webServer/security/requestFiltering /-fileExtensions.[fileExtension='.config']

c:\windows\system32\inetsrv\appcmd.exe set config -section:system.webServer/security/requestFiltering /-fileExtensions.[fileExtension='.config']

또는

c:\Windows\system32\inetsrv\appcmd.exe set config "MySite/MyApp/MyFolder" -section:system.webServer/security/requestFiltering /-fileExtensions.[fileExtension='.config']