Webpage Singer 🎶

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1# Feel free to add your Python dependencies below. For formatting guidelines, see:
2# https://pip.pypa.io/en/latest/reference/requirements-file-format/
3
4apify < 3.0
5openai == 1.63.*
6requests

# First, specify the base Docker image.
# You can see the Docker images from Apify at https://hub.docker.com/r/apify/.
# You can also use any other image from Docker Hub.
FROM apify/actor-python:3.13

# Second, copy just requirements.txt into the Actor image,
# since it should be the only file that affects the dependency install in the next step,
# in order to speed up the build
COPY requirements.txt ./

# Install the packages specified in requirements.txt,
# Print the installed Python version, pip version
# and all installed packages with their versions for debugging
RUN echo "Python version:" \
 && python --version \
 && echo "Pip version:" \
 && pip --version \
 && echo "Installing dependencies:" \
 && pip install -r requirements.txt \
 && echo "All installed Python packages:" \
 && pip freeze

# Next, copy the remaining files and directories with the source code.
# Since we do this after installing the dependencies, quick build will be really fast
# for most source file changes.
COPY . ./

# Use compileall to ensure the runnability of the Actor Python code.
RUN python3 -m compileall -q .

# Specify how to launch the source code of your Actor.
# By default, the "python3 -m src" command is run
CMD ["python3", "-m", "src"]

{
	"actorSpecification": 1,
	"name": "webpage-singer",
	"title": "Webpage Singer",
	"description": "Ever wondered what a website would sound like as a song? This Actor takes any webpage, turns its content into lyrics, and transforms it into a track in your favorite genre. Just drop in a URL, pick a style, and let the AI do the rest.",
	"version": "0.0",
	"buildTag": "latest",
	"meta": {
		"templateId": "python-start"
	},
	"input": "./input_schema.json",
	"dockerfile": "./Dockerfile",
	"storages": {
        "dataset": "./dataset_schema.json"
    }
}

{
  "actorSpecification": 1,
  "views": {
    "overview": {
      "title": "Overview",
      "transformation": {
        "fields": [
          "variant", "download url", "play url", "lyrics"
        ]
      },
      "display": {
        "component": "table",
        "properties": {
          "variant": {
            "label": "variant",
            "format": "text"
          },
          "play url": {
            "label": "play url",
            "format": "link"
          },
          "download url": {
            "label": "download url",
            "format": "link"
          },
          "lyrics": {
            "label": "lyrics",
            "format": "text"
          }
        }
      }
    }
  }
}

{
    "title": "Scrape data from a web page",
    "type": "object",
    "schemaVersion": 1,
    "properties": {
        "url": {
            "title": "Page URL",
            "type": "string",
            "description": "Just enter the URL of a web page and it will be used to generate lyrics for the song.",
            "editor": "textfield",
            "prefill": "https://apify.com/about"
        },
        "topmediai_api_key": {
            "title": "API key for TopMediai",
            "type": "string",
            "isSecret": true,
            "description": "If you provide your own TopMediai API key, you will be charged less.",
            "editor": "textfield"
        },
        "song_genre": {
            "title": "Song genre",
            "type": "string",
            "description": "Song genre used to generate the song. If you don't provide a genre, the AI will suggest one based on the page content.",
            "editor": "textfield",
            "prefill": "Hip Hop"
        }

    },
    "required": ["url"]
}

1

1import asyncio
2
3from .main import main
4
5# Execute the Actor entry point.
6asyncio.run(main())

1from apify import Actor
2
3
4async def fetch_content(url):
5    run = await Actor.call(
6        actor_id="apify/website-content-crawler",
7        run_input={
8            "startUrls": [{"url": url}],
9            "maxCrawlPages": 1,
10            "crawlerType": "playwright:adaptive",
11            "proxyConfiguration": {
12                "useApifyProxy": True,
13            },
14        },
15        memory_mbytes=4096,  # Reduce memory so that it can run on free accounts.
16    )
17
18    if run is None or run.status != "SUCCEEDED":
19        raise RuntimeError("Website Content Crawler failed to scrape the page")
20
21    page = await Actor.apify_client.dataset(run.default_dataset_id).list_items(limit=1)
22
23    if not page.items:
24        raise ValueError("No content scraped")
25
26    return page.items[0].get("markdown")

1from src.open_ai import get_open_api_client, OPENAI_MODEL
2
3SYSTEM_PROMPT = """
4You are a helpful, analytical assistant that can summarize text. You try to be non-biased and sticking to facts.
5"""
6
7USER_PROMPT = """
8Summarize the following text into a song-like structure.
9
10 - It should consist of max 4 verses, each around 30 words, all of the roughly same length.
11 - Don't rhyme it, unless the text is in English.
12 - The text remains understandable, clear and factual.
13 - Don't change the meaning, the story should stay as is.
14 - Stick to the original order of information.
15 - Stick to the original language.
16 - Don't print headlines like "Verse 1".
17 - Spell out numbers, as in never produce numerical symbols. Instead of 35, write thirty-five.
18"""
19
20
21async def generate_lyrics(content):
22    chat_completion = await get_open_api_client().chat.completions.create(
23        messages=[
24            {"role": "system", "content": SYSTEM_PROMPT},
25            {"role": "user", "content": f"{USER_PROMPT}\n\n```{content}```"},
26        ],
27        model=OPENAI_MODEL,
28    )
29
30    return chat_completion.choices[0].message.content

1import os
2
3from apify import Actor
4
5from src.fetch_content import fetch_content
6from src.music_generation import get_song, generate_songs
7from src.lyrics_generation import generate_lyrics
8from src.open_ai import truncate_to_max_content_length
9from src.suggest_music_genre import suggest_music_genre
10
11
12async def main() -> None:
13    async with Actor:
14        actor_input = await Actor.get_input()
15        kvs = await Actor.open_key_value_store()
16        dataset = await Actor.open_dataset()  # Alternative visualisation
17
18        url = actor_input.get("url")
19        if not url:
20            raise ValueError('Missing "url" attribute in input!')
21
22        # Fetch page content.
23        try:
24            await Actor.set_status_message("Fetching page content")
25            Actor.log.info("Fetching page content", extra={"url": url})
26            page_content = truncate_to_max_content_length(await fetch_content(url))
27        except Exception as e:
28            await Actor.fail(
29                exception=e, status_message="Fetching page content failed."
30            )
31
32        # Generate song lyrics + determine genre.
33        try:
34            await Actor.set_status_message("Generating lyrics using AI")
35            Actor.log.info(
36                "Generating lyrics using AI", extra={"page_content": page_content}
37            )
38            lyrics = await generate_lyrics(page_content)
39            song_genre = actor_input.get("song_genre") or await suggest_music_genre(
40                page_content
41            )
42            await kvs.set_value(
43                key="lyrics.txt", value=lyrics, content_type="text/plain"
44            )
45        except Exception as e:
46            await Actor.fail(
47                exception=e, status_message="Generating lyrics using AI failed."
48            )
49
50        # Generate song.
51        try:
52            await Actor.set_status_message(
53                "Generating the song (this might take a few minutes)"
54            )
55            Actor.log.info(
56                "Generating the song", extra={"lyrics": lyrics, "genre": song_genre}
57            )
58            topmediai_api_key = actor_input.get("topmediai_api_key") or os.environ.get(
59                "TOPMEDIAI_API_KEY"
60            )
61
62            song_links = generate_songs(
63                lyrics=lyrics,
64                api_key=topmediai_api_key,
65                genre=song_genre,
66                logger=Actor.log,
67            )
68            for variant, song_link in enumerate(song_links, start=1):
69                await kvs.set_value(
70                    key=f"song_variant_{variant}",
71                    value=get_song(song_link),
72                    content_type="audio/mpeg",
73                )
74                await dataset.push_data(
75                    {
76                        "variant": variant,
77                        "download url": song_link,
78                        "play url": await kvs.get_public_url(f"song_variant_{variant}"),
79                        "lyrics": lyrics,
80                    }
81                )
82        except Exception as e:
83            await Actor.fail(
84                exception=e, status_message="Generating song using TopMediaAI failed."
85            )
86
87        # Charge user based on the resources used
88        if actor_input.get("topmediai_api_key"):
89            await Actor.charge(event_name="song_with_user_api_key", count=1)
90        else:
91            await Actor.charge(event_name="song_with_actor_api_key", count=1)

1from logging import getLogger
2
3import requests
4import json
5
6
7def generate_songs(
8    lyrics: str, api_key: str, genre: str = "Hip Hop", logger=getLogger(__name__)
9) -> [str]:
10    """Generate song and return generated song link."""
11    api_url = "https://api.topmediai.com/v1/music"
12
13    payload = {"is_auto": 0, "prompt": genre, "lyrics": lyrics}
14    headers = {"x-api-key": api_key, "Content-Type": "application/json"}
15
16    response = requests.request("POST", api_url, json=payload, headers=headers)
17    if response.status_code != 200:
18        raise RuntimeError(response.text)
19
20    response_text = json.loads(response.text)
21
22    if response_text.get("status", None) != 200:
23        raise RuntimeError(
24            f"TopMediai song generation temporarily out of order. Please try again later."
25            f" Details in response: {response.text}"
26        )
27
28    songs = [song["audio_file"] for song in response_text.get("data", [])]
29
30    if not songs:
31        raise RuntimeError(
32            "TopMediai song generation temporarily out of order. Please try again later."
33        )
34
35    return songs
36
37
38def get_song(link: str) -> bytes:
39    """Get song from link."""
40    return requests.request("GET", link).content

1import os
2
3from apify import Actor
4from openai import AsyncOpenAI
5
6OPENAI_MODEL = "gpt-4o"
7
8# Max content length as supported by OpenAI API and the gpt-4o model
9OPENAI_MAX_CONTENT_LENGTH_TOKENS = 128000
10
11
12def get_open_api_client():
13    return AsyncOpenAI(
14        api_key=os.environ.get("OPENAI_API_KEY"),
15    )
16
17
18def truncate_to_max_content_length(content):
19    # Simple heuristic: 1 word = 4 tokens. This is a pessimistic conversion, which should be safe for most languages.
20    truncated_content = " ".join(
21        content.split()[: OPENAI_MAX_CONTENT_LENGTH_TOKENS // 4]
22    )
23
24    if len(truncated_content) < len(content):
25        Actor.log.warning(
26            "Fetched page was too long for OpenAI API and was truncated",
27            extra={
28                "original_length": len(content),
29                "truncated_length": len(truncated_content),
30            },
31        )
32
33    return truncated_content

1from src.open_ai import get_open_api_client
2
3from src.open_ai import truncate_to_max_content_length, OPENAI_MODEL
4
5SYSTEM_PROMPT = """
6You are a helpful, sensitive and empathetic assistant that understands nuances and emotions in text.
7"""
8
9USER_PROMPT = """
10The following text will be turned into a song. Please suggest a music genre that fits the text.
11
12Take into account the mood, tone, severity, topic etc.
13
14Return just the genre and nothing else.
15
16Sample outputs: "indie britpop", "experimental rock", "opera".
17"""
18
19
20async def suggest_music_genre(content):
21    chat_completion = await get_open_api_client().chat.completions.create(
22        messages=[
23            {"role": "system", "content": SYSTEM_PROMPT},
24            {"role": "user", "content": f"{USER_PROMPT}\n\n```{content}```"},
25        ],
26        model=OPENAI_MODEL,
27    )
28
29    return chat_completion.choices[0].message.content