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# pip install requests
import requests
import base64
def generate_image(access_token, prompt):
url = "https://api.getimg.ai/v1/stable-diffusion/text-to-image"
headers = {"Authorization": "Bearer {}".format(access_token)}
data = {
"model": "stable-diffusion-v1-5",
"prompt": prompt,
"negative_prompt": "Disfigured, cartoon, blurry",
"width": 512,
"height": 512,
"steps": 25,
"guidance": 7.5,
"seed": 42,
"scheduler": "dpmsolver++",
"output_format": "jpeg",
}
response = requests.post(url, headers=headers, data=data)
image_string = response.content
image_bytes = base64.decodebytes(image_string)
with open("AI_Image.jpeg", "wb") as f:
f.write(image_bytes)
if __name__ == "__main__":
api_key = "YOUR_API_KEY"
prompt = "a photo of a cat dressed as a pirate"
image_bytes = generate_image(api_key, prompt)

02、人工智能校對員

需要人工智能校對器來糾正文本或文檔中的語法和拼寫錯誤，然后，使用下面的 API，它為您提供免費的 API 訪問權限，并允許您使用強大的語法檢查人工智能技術來修復您的文本。

在這里獲取您的 API

# AI Proofreading

# pip install requests

import requests

def Proofreader(text):

    api_key = "YOUR_API_KEY"

    url = 'https://api.sapling.ai/api/v1/edits'

    data = {

        'key': api_key,

        'text': text,

        'session_id': 'Test Document UUID',

        'advanced_edits': {

            'advanced_edits': True,

        },

    }

    response = requests.post(url, json=data)

    resp_json = response.json()

    edits = resp_json['edits']

    print("Corrections: ", edits)

if __name__ == '__main__':

    Proofreader("I are going to the store, She don't likes pizza")

03、人工智能文本轉語音

借助 Google Cloud 的文本轉語音 AI 技術，您可以將文本轉換為逼真的聲音。您可以靈活地選擇各種選項，例如，語言、音調、人們的聲音等等。

最重要的是，Google 提供免費的 API 供您使用。

在這里獲取您的 API

# AI Text to Speech

# pip install google-cloud-texttospeech

# pip install playsound

import io

import os

from google.cloud import texttospeech

import playsound

# Set the path to your credentials JSON file

os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "credentials.json"

def Text_to_Speech(text):

    client = texttospeech.TextToSpeechClient()

    # Set the language code and the voice name.

    language_code = "en-US"

    voice_name = "en-US-Wavenet-A"

    # Create a request to synthesize speech.

    r = texttospeech.types.SynthesizeSpeechRequest()

    r.text = text

    r.voice = texttospeech.types.VoiceSelectionParams(

        language_code=language_code, name=voice_name)

    # Set the audio encoding.

    r.audio_encoding = texttospeech.types.AudioEncoding.MP3

    # Get the response from the API.

    response = client.synthesize_speech(r)

    # Save the audio to a file.

    with io.open("audio.mp3", "wb") as f:

        f.write(response.audio_content)

    # Play the audio.

    playsound.playsound("audio.mp3", True)

if __name__ == "__main__":

    text = input("Enter the text: ")

    Text_to_Speech(text)

04、聊天機器人人工智能

如果您正在尋找類似于 chatGPT 的聊天機器人，您可以使用 OpenAI API。我在下面提供了一些代碼，演示如何使用 GPT 3.5 在 Python 中輕松創建個性化聊天機器人。

# ChatGPT AI

# pip install openai

import os

import openai

def ask(prompt):

  response = openai.ChatCompletion.create(

    model="gpt-3.5-turbo",

    messages=[

      {

        "role": "user",

        "content": prompt

      }

    ],

    temperature=1,

    max_tokens=256,

    top_p=1,

    frequency_penalty=0,

    presence_penalty=0

  )



  print("Ans: ", response)

if __name__ == "__main__":

    ask("Python or JavaScript?")

05、人工智能識別

您是否需要將掃描文檔轉換為文本或從圖像或掃描 PDF 中提取文本？您可以使用以下 OCR AI 技術從任何類型的圖像中提取文本。

下面的 API 利用了 Google Cloud Vision AI 技術，該技術擅長檢測和分析圖像中的文本。

在這里獲取您的 API

# AI OCR

# pip install google-cloud-vision

from google.cloud import vision

from google.cloud.vision import types

import os

# Set the path to your credentials JSON file

os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "credentials.json"

def OCR(img_path):

    client = vision.ImageAnnotatorClient()

    with open(img_path, 'rb') as image_file:

        content = image_file.read()

    image = types.Image(content=content)

    response = client.text_detection(image=image)

    texts = response.text_annotations

    if texts:

        return texts[0].description

    else:

        return "No text found in the image."

if __name__ == "__main__":

    image_path = "photo.jpg"

    print(OCR(image_path))