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Piero Bosio Social Web Site Personale Logo Fediverso

Social Forum federato con il resto del mondo. Non contano le istanze, contano le persone

I am looking to host a **de-federated** mastodon instance for 300 to 500 people.

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Gli ultimi otto messaggi ricevuti dalla Federazione
  • @spacebuffer@fosstodon.org yes! It fully supports two-way federation and interacts well with Mastodon and Lemmy/Piefed/Mbin.

    There are granular visibility controls so you can have some categories federating and some not.

    There's also a feed view if you really can't give up the feed šŸ˜…

    cc @sam@break3.social

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  • @spacebuffer If you want to host an instance for a group of acquaintances and perhaps federate it with only some instances and not others, you can use Friendica.
    Friendica also allows you to create public and private groups, but most importantly, it allows users to set up different circles for posting (friends, relatives, bowling group, birdwatching group, etc.).

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  • @spacebuffer@fosstodon.org NodeBB is meant to be supported Federation, I haven't seen much from them along with the extent of there Federation for Forms based most people end up using Lemmy or Piefed, but Mbin is a good mix between the two.

    From my experience Mastodon can be pretty heavy, I've ended up moving to Sharkey for a few reasons, Lightweight-ness being one, the other benefits are stuff like the multiple names for custom emojis, S3 Support, A Private Chat system for Instance wide chatting and Custom Emoji reactions.

    Obviously I'm not sure of your use-case, especially looking to not federate the instance is a strange choice.

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  • @julian @sam

    Indeed I also felt this was a bit much but then ago mastodon's focus doesn't seem to be on being lightweight.

    NodeBB seems very interesting, probably not for this project but maybe for other things, does it support federation?

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  • @sam@break3.social @spacebuffer@fosstodon.org 8GB?! Those are insane system requirements for what is basically text and media exchange.

    An intra-org forum for 800 running NodeBB would be 2GB max, 1 CPU, and you'd really only see 100 actively using the site, if that.

    Mastodon is a beast eh.

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  • @spacebuffer 8gb and 4+ cpu + object storage/ s3

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  • @sam

    thanks for the info!
    Its for internal news at a multi-regional company.

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  • @spacebuffer@fosstodon.org You are gonna want the higher specs of 8GB min, Especially if those 300-500 people are going to be often login in.

    What's your use case of a de-federated Mastodon Instance? Would it not be better to just federate to specific instances (Not sure if you can do that on Mastodon but I know you can on Sharkey and that uses less resources)

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Post suggeriti
  • 0 Votes
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    Good day all! Upcoming episode of Fireside Fedi! The #livestream will be on: stream.firesidefedi.live Special Guest: @rileytestut@mastodon.social Building emulators and app stores for iPhone with shanegill.io So don't miss it! It will happen on 05 February 2026 at 14:00 US Eastern Time ( UTC-5 ) If by any ungodly chance you miss the show: #PeerTube ( #VOD ): tubefree/@firesidefedi #firesidefedi #fediverse #fedi #interview #freesoftware #opensource #userfreedom #freedom #resistance
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    @thenexusofprivacy Simply engage with them. Every now and then check out #introduction and give out a few welcomes. (And tell them to check out https://fedi.tips/ and ask @FediTips if they have any questions. 🤷)
  • 0 Votes
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    This tutorial will guide you through building a simple ActivityPub bot using Python. The bot will listen for mentions and, when it receives a message in a specific format, it will schedule and send a reminder back to the user after a specified delay. For example, if a user mentions the bot with a message like "@reminder@your.host.com 10m check the oven", the bot will reply 10 minutes later with a message like "šŸ”” Reminder for @user: check the oven". Prerequisites To follow this tutorial, you will need Python 3.10+ and the following libraries: apkit[server]: A powerful toolkit for building ActivityPub applications in Python. We use the server extra, which includes FastAPI-based components. uvicorn: An ASGI server to run our FastAPI application. cryptography: Used for generating and managing the cryptographic keys required for ActivityPub. uv: An optional but recommended fast package manager. You can install these dependencies using uv or pip. # Initialize a new project with uv uv init # Install dependencies uv add "apkit[server]" uvicorn cryptography Project Structure The project structure is minimal, consisting of a single Python file for our bot's logic. . ā”œā”€ā”€ main.py └── private_key.pem main.py: Contains all the code for the bot. private_key.pem: The private key for the bot's Actor. This will be generated automatically on the first run. Code Walkthrough Our application logic can be broken down into the following steps: Imports and Configuration: Set up necessary imports and basic configuration variables. Key Generation: Prepare the cryptographic keys needed for signing activities. Actor Definition: Define the bot's identity on the Fediverse. Server Initialization: Set up the apkit ActivityPub server. Data Storage: Implement a simple in-memory store for created activities. Reminder Logic: Code the core logic for parsing reminders and sending notifications. Endpoint Definitions: Create the necessary web endpoints (/actor, /inbox, etc.). Activity Handlers: Process incoming activities from other servers. Application Startup: Run the server. Let's dive into each section of the main.py file. 1. Imports and Configuration First, we import the necessary modules and define the basic configuration for our bot. # main.py import asyncio import logging import re import uuid import os from datetime import timedelta, datetime # Imports from FastAPI, cryptography, and apkit from fastapi import Request, Response from fastapi.responses import JSONResponse from cryptography.hazmat.primitives.asymmetric import rsa from cryptography.hazmat.primitives import serialization as crypto_serialization from apkit.config import AppConfig from apkit.server import ActivityPubServer from apkit.server.types import Context, ActorKey from apkit.server.responses import ActivityResponse from apkit.models import ( Actor, Application, CryptographicKey, Follow, Create, Note, Mention, Actor as APKitActor, OrderedCollection, ) from apkit.client import WebfingerResource, WebfingerResult, WebfingerLink from apkit.client.asyncio.client import ActivityPubClient # --- Logging Setup --- logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) # --- Basic Configuration --- HOST = "your.host.com" # Replace with your domain USER_ID = "reminder" # The bot's username Make sure to replace your.host.com with the actual domain where your bot will be hosted. These values determine your bot's unique identifier (e.g., @reminder@your.host.com). 2. Key Generation and Persistence ActivityPub uses HTTP Signatures to secure communication between servers. This requires each actor to have a public/private key pair. The following code generates a private key and saves it to a file if one doesn't already exist. # main.py (continued) # --- Key Persistence --- KEY_FILE = "private_key.pem" # Load the private key if it exists, otherwise generate a new one if os.path.exists(KEY_FILE): logger.info(f"Loading existing private key from {KEY_FILE}.") with open(KEY_FILE, "rb") as f: private_key = crypto_serialization.load_pem_private_key(f.read(), password=None) else: logger.info(f"No key file found. Generating new private key and saving to {KEY_FILE}.") private_key = rsa.generate_private_key(public_exponent=65537, key_size=2048) with open(KEY_FILE, "wb") as f: f.write(private_key.private_bytes( encoding=crypto_serialization.Encoding.PEM, format=crypto_serialization.PrivateFormat.PKCS8, encryption_algorithm=crypto_serialization.NoEncryption() )) # Generate the public key from the private key public_key_pem = private_key.public_key().public_bytes( encoding=crypto_serialization.Encoding.PEM, format=crypto_serialization.PublicFormat.SubjectPublicKeyInfo ).decode('utf-8') 3. Actor Definition Next, we define the bot's Actor. The Actor is the bot's identity in the ActivityPub network. We use the Application type, as this entity is automated. # main.py (continued) # --- Actor Definition --- actor = Application( id=f"https://{HOST}/actor", name="Reminder Bot", preferredUsername=USER_ID, summary="A bot that sends you reminders. Mention me like: @reminder 5m Check the oven", inbox=f"https://{HOST}/inbox", # Endpoint for receiving activities outbox=f"https://{HOST}/outbox", # Endpoint for sending activities publicKey=CryptographicKey( id=f"https://{HOST}/actor#main-key", owner=f"https://{HOST}/actor", publicKeyPem=public_key_pem ) ) 4. Server Initialization We initialize the ActivityPubServer from apkit, providing it with a function to retrieve our Actor's keys for signing outgoing activities. # main.py (continued) # --- Key Retrieval Function --- async def get_keys_for_actor(identifier: str) -> list[ActorKey]: """Returns the key for a given Actor ID.""" if identifier == actor.id: return [ActorKey(key_id=actor.publicKey.id, private_key=private_key)] return [] # --- Server Initialization --- app = ActivityPubServer(apkit_config=AppConfig( actor_keys=get_keys_for_actor # Register the key retrieval function )) 5. In-Memory Storage and Cache To serve created activities, we need to store them somewhere. For simplicity, this example uses a basic in-memory dictionary as a store and a cache. In a production application, you would replace this with a persistent database (like SQLite or PostgreSQL) and a proper cache (like Redis). # main.py (continued) # --- In-memory Store and Cache --- ACTIVITY_STORE = {} # A simple dict to store created activities CACHE = {} # A cache for recently accessed activities CACHE_TTL = timedelta(minutes=5) # Cache expiration time (5 minutes) 6. Reminder Parsing and Sending Logic This is the core logic of our bot. The parse_reminder function uses a regular expression to extract the delay and message from a mention, and send_reminder schedules the notification. # main.py (continued) # --- Reminder Parsing Logic --- def parse_reminder(text: str) -> tuple[timedelta | None, str | None, str | None]: """Parses reminder text like '5m do something'.""" # ... (implementation omitted for brevity) # --- Reminder Sending Function --- async def send_reminder(ctx: Context, delay: timedelta, message: str, target_actor: APKitActor, original_note: Note): """Waits for a specified delay and then sends a reminder.""" logger.info(f"Scheduling reminder for {target_actor.id} in {delay}: '{message}'") await asyncio.sleep(delay.total_seconds()) # Asynchronously wait logger.info(f"Sending reminder to {target_actor.id}") # Create the reminder Note reminder_note = Note(...) # Wrap it in a Create activity reminder_create = Create(...) # Store the created activities ACTIVITY_STORE[reminder_note.id] = reminder_note ACTIVITY_STORE[reminder_create.id] = reminder_create # Send the activity to the target actor's inbox keys = await get_keys_for_actor(f"https://{HOST}/actor") await ctx.send(keys, target_actor, reminder_create) logger.info(f"Reminder sent to {target_actor.id}") 7. Endpoint Definitions We define the required ActivityPub endpoints. Since apkit is built on FastAPI, we can use standard FastAPI decorators. The main endpoints are: Webfinger: Allows users on other servers to discover the bot using an address like @user@host. This is a crucial first step for federation. /actor: Serves the bot's Actor object, which contains its profile information and public key. /inbox: The endpoint where the bot receives activities from other servers. apkit handles this route automatically, directing activities to the handlers we'll define in the next step. /outbox: A collection of the activities created by the bot. but this returns placeholder collection. /notes/{note_id} and /creates/{create_id}: Endpoints to serve specific objects created by the bot, allowing other servers to fetch them by their unique ID. Here is the code for defining these endpoints: # main.py (continued) # The inbox endpoint is handled by apkit automatically. app.inbox("/inbox") @app.webfinger() async def webfinger_endpoint(request: Request, acct: WebfingerResource) -> Response: """Handles Webfinger requests to make the bot discoverable.""" if not acct.url: # Handle resource queries like acct:user@host if acct.username == USER_ID and acct.host == HOST: link = WebfingerLink(rel="self", type="application/activity+json", href=actor.id) wf_result = WebfingerResult(subject=acct, links=[link]) return JSONResponse(wf_result.to_json(), media_type="application/jrd+json") else: # Handle resource queries using a URL if acct.url == f"https://{HOST}/actor": link = WebfingerLink(rel="self", type="application/activity+json", href=actor.id) wf_result = WebfingerResult(subject=acct, links=[link]) return JSONResponse(wf_result.to_json(), media_type="application/jrd+json") return JSONResponse({"message": "Not Found"}, status_code=404) @app.get("/actor") async def get_actor_endpoint(): """Serves the bot's Actor object.""" return ActivityResponse(actor) @app.get("/outbox") async def get_outbox_endpoint(): """Serves a collection of the bot's sent activities.""" items = sorted(ACTIVITY_STORE.values(), key=lambda x: x.id, reverse=True) outbox_collection = OrderedCollection( id=actor.outbox, totalItems=len(items), orderedItems=items ) return ActivityResponse(outbox_collection) @app.get("/notes/{note_id}") async def get_note_endpoint(note_id: uuid.UUID): """Serves a specific Note object, with caching.""" note_uri = f"https://{HOST}/notes/{note_id}" # Check cache first if note_uri in CACHE and (datetime.now() - CACHE[note_uri]["timestamp"]) < CACHE_TTL: return ActivityResponse(CACHE[note_uri]["activity"]) # If not in cache, get from store if note_uri in ACTIVITY_STORE: activity = ACTIVITY_STORE[note_uri] # Add to cache before returning CACHE[note_uri] = {"activity": activity, "timestamp": datetime.now()} return ActivityResponse(activity) return Response(status_code=404) # Not Found @app.get("/creates/{create_id}") async def get_create_endpoint(create_id: uuid.UUID): """Serves a specific Create activity, with caching.""" create_uri = f"https://{HOST}/creates/{create_id}" if create_uri in CACHE and (datetime.now() - CACHE[create_uri]["timestamp"]) < CACHE_TTL: return ActivityResponse(CACHE[create_uri]["activity"]) if create_uri in ACTIVITY_STORE: activity = ACTIVITY_STORE[create_uri] CACHE[create_uri] = {"activity": activity, "timestamp": datetime.now()} return ActivityResponse(activity) return Response(status_code=404) 8. Activity Handlers We use the @app.on() decorator to define handlers for specific activity types posted to our inbox. on_follow_activity: Automatically accepts Follow requests. on_create_activity: Parses incoming Create activities (specifically for Note objects) to schedule reminders. # main.py (continued) # Handler for Follow activities @app.on(Follow) async def on_follow_activity(ctx: Context): """Automatically accepts follow requests.""" # ... (implementation omitted for brevity) # Handler for Create activities @app.on(Create) async def on_create_activity(ctx: Context): """Parses mentions to schedule reminders.""" activity = ctx.activity # Ignore if it's not a Note if not (isinstance(activity, Create) and isinstance(activity.object, Note)): return Response(status_code=202) note = activity.object # Check if the bot was mentioned is_mentioned = any( isinstance(tag, Mention) and tag.href == actor.id for tag in (note.tag or []) ) if not is_mentioned: return Response(status_code=202) # ... (Parse reminder text) delay, message, time_str = parse_reminder(command_text) # If parsing is successful, schedule the reminder as a background task if delay and message and sender_actor: asyncio.create_task(send_reminder(ctx, delay, message, sender_actor, note)) reply_content = f"<p>āœ… OK! I will remind you in {time_str}.</p>" else: # If parsing fails, send usage instructions reply_content = "<p>šŸ¤” Sorry, I didn\'t understand. Please use the format: `@reminder [time] [message]`.</p><p>Example: `@reminder 10m Check the oven`</p>" # ... (Create and send the reply Note) 9. Running the Application Finally, we run the application using uvicorn. # main.py (continued) if __name__ == "__main__": import uvicorn logger.info("Starting uvicorn server...") uvicorn.run(app, host="0.0.0.0", port=8000) How to Run the Bot Set the HOST and USER_ID variables in main.py to match your environment. Run the server from your terminal: uvicorn main:app --host 0.0.0.0 --port 8000 Your bot will be running at http://0.0.0.0:8000. Now you can mention your bot from anywhere in the Fediverse (e.g., @reminder@your.host.com) to set a reminder. Next Steps This tutorial covers the basics of creating a simple ActivityPub bot. Since it only uses in-memory storage, all reminders will be lost on server restart. Here are some potential improvements: Persistent Storage: Replace the in-memory ACTIVITY_STORE with a database like SQLite or PostgreSQL. Robust Task Queuing: Use a dedicated task queue like Celery with a Redis or RabbitMQ broker to ensure reminders are not lost if the server restarts. Advanced Commands: Add support for more complex commands, such as recurring reminders. We hope this guide serves as a good starting point for building your own ActivityPub applications! https://fedi-libs.github.io/apkit/ https://github.com/fedi-libs/apkit https://github.com/AmaseCocoa/activitypub-reminder-bot
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    @blog Thanks! Much respect for just getting this out there. Love the comments! šŸ˜‚