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FROM python:3.10-slim
WORKDIR /app
COPY bin/requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY bin/ollamarama.py .
CMD ["python", "ollamarama.py"]

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FROM ollama/ollama
COPY start.sh /start.sh
RUN chmod +x /start.sh
# Standardbefehl zum Starten des Servers
ENTRYPOINT ["/start.sh"]

116
README.md
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# ollamarama-matrix-chatbot
# ollamarama-matrix
Ollamarama is an AI chatbot for the [Matrix](https://matrix.org/) chat protocol using Ollama. It can roleplay as almost anything you can think of. You can set any default personality you would like. It can be changed at any time, and each user has their own separate chat history with their chosen personality setting. Users can interact with each others chat histories for collaboration if they would like, but otherwise, conversations are separated, per channel, per user.
### Zuerst das Wichtigste:
This is based on my earlier project, [infinigpt-matrix](https://github.com/h1ddenpr0cess20/infinigpt-matrix), which uses OpenAI and costs money to use. (Now updated with OpenAI/Ollama model switching)
Dies ist ein Fork von [Dustin Whyte](https://github.com/h1ddenpr0cess20/ollamarama-matrix), welchen ich anschließend in Docker inpelementiert habe.
Ollamarama ist ein KI-Chatbot für das [Matrix](https://matrix.org/) Chatprotokoll mit Ollama. Er kann fast alles spielen, was Du dir vorstellen kannst. Du kannst jede Standardpersönlichkeit einstellen, die du möchtest. Sie kann jederzeit geändert werden, und jeder Benutzer hat seinen eigenen Chatverlauf mit der von ihm gewählten Persönlichkeitseinstellung. Die Benutzer können mit den Chatverläufen der anderen interagieren, um zusammenzuarbeiten, wenn sie das möchten, aber ansonsten sind die Unterhaltungen getrennt, pro Kanal und pro Benutzer.
Dieser Chatbot kommt zusammen mit dem Ollama Docker, zu finden [hier](https://hub.docker.com/r/ollama/ollama).
IRC version available at [ollamarama-irc](https://github.com/h1ddenpr0cess20/ollamarama-irc)
Terminal-based version at [ollamarama](https://github.com/h1ddenpr0cess20/ollamarama)
## Setup
Installiere dir zuerst Docker. Dies kannst du mit [diesem Script](https://github.com/h1ddenpr0cess20/ollamarama-matrix) machen.
Install and familiarize yourself with [Ollama](https://ollama.ai/), make sure you can run local LLMs, etc.
Anschließend clonst du mein Projekt:
```bash
git clone https://git.techniverse.net/scriptos/ollamarama-matrix
You can install and update it with this command:
```
Anschließend ins Verzeichnis wechseln und die Konfigurationsdatei für den Matrix-Chatbot konfigurieren:
```bash
cd ollamarama-matrix && nano data/chatbot/config.json)
```
In der `config.json` werden die Zugangsdaten für den Chatbot gepflegt. Dieser muss im Vorfeld auf dem Matrix Server erstellt werden. Dies kann [hier](https://app.element.io/) gemacht werden.
Weiterhin können in dieser Konfigurationsdatei weitere Modelle gepflegt werden, welche vom Chatbot anschließend verwendet werden könnten.
In der Datei `start.sh` können weitere Modelle gepflegt werden, welche dann nach dem Starten vom Ollama Docker Container runtergeladen werden.
Weitere Modelle können [hier](https://ollama.ai/library) geladen werden.
Wenn die Konfiguration gemacht ist, kann der Docker mit
```bash
docker-compose up --build
```
gestartet werden.
Dies ist ideal um gleich auch die Logs zu sehen.
Nun tritt der Bot automatisch den konfigurierten Channels bei und sollte dir im Idealfall direkt zu Verfügung stehen.
Den Docker startest du richtig mit
```bash
docker-compose -d
```
Die erste Nachricht versendest du mit `.ai message`
Ein Beispiel:
```bash
.ai Hallo, wie geht es dir?
curl https://ollama.ai/install.sh | sh
```
# Verwendung
Once it's all set up, you'll need to [download the models](https://ollama.ai/library) you want to use. You can play with the available ones and see what works best for you. Add those to the config.json file. If you want to use the ones I've included, just run ollama pull _modelname_ for each.
**.ai _nachricht_** oder **botname: _nachricht_**
Grundlegende Verwendung.
You'll also need to install matrix-nio
```
pip3 install matrix-nio
```
**.x _benutzer_ _nachricht_**
Set up a [Matrix account](https://app.element.io/) for your bot. You'll need the server, username and password.
Erlaubt es dir, auf die Chat-Historie eines anderen Benutzers zuzugreifen.
Add those to the config.json file.
_benutzer_ ist der Anzeigename des Benutzers, dessen Historie du verwenden möchtest.
```
python3 ollamarama.py
```
**.persona _persönlichkeit_**
## Use
Ändert die Persönlichkeit. Es kann eine Figur, ein Persönlichkeitstyp, ein Objekt, eine Idee, was auch immer sein. Nutze deine Fantasie.
**.custom _eingabeaufforderung_**
**.ai _message_** or **botname: _message_**
Erlaubt die Verwendung einer benutzerdefinierten Systemaufforderung anstelle der Rollenspielaufforderung.
 Basic usage.
**.x _user_ _message_**
 This allows you to talk to another user's chat history.
 _user_ is the display name of the user whose history you want to use
**.persona _personality_**
 Changes the personality. It can be a character, personality type, object, idea, whatever. Use your imagination.
**.custom _prompt_**
 Allows use of a custom system prompt instead of the roleplaying prompt
**.reset**
Verlauf löschen und auf voreingestellte Persönlichkeit zurücksetzen.
 Clear history and reset to preset personality
**.stock**
Verlauf löschen und ohne Systemaufforderung verwenden.
 Clear history and use without a system prompt
**Nur für Admins**
**.model _modell_**
**Admin only commands**
Lasse den Modellnamen weg, um das aktuelle Modell und verfügbare Modelle anzuzeigen.
Gib den Modellnamen ein, um das Modell zu wechseln.
**.model _model_**
 Omit model name to show current model and available models
 Include model name to change model
**.clear**
Setzt den Bot für alle zurück.
 Reset bot for everyone

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matrix-nio
requests
markdown

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},
"ollama":
{
"api_base": "http://ollama:11434",
"api_base": "http://localhost:11434",
"options":
{
"temperature": 0.8,

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services:
ollama:
image: ollama/ollama
build:
context: .
dockerfile: Dockerfile.ollama
hostname: ollama
container_name: ollama
networks:
dockernet:
ipv4_address: 172.16.0.51
ports:
- "11434:11434"
volumes:
- ./data/ollama/history:/root/.ollama
restart: unless-stopped
matrix-chatbot:
image: matrix-chatbot:latest
build:
context: .
dockerfile: Dockerfile.chatbot
container_name: matrix-chatbot
hostname: matrix-chatbot
networks:
dockernet:
ipv4_address: 172.16.0.50
depends_on:
- ollama
volumes:
- ./data/chatbot/config.json:/app/config.json:ro
restart: unless-stopped
networks:
dockernet:
external: true

33
help.txt Normal file
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**.ai _message_** or **botname: _message_**
 Basic usage.
**.x _user_ _message_**
 This allows you to talk to another user's chat history.
 _user_ is the display name of the user whose history you want to use
**.persona _personality_**
 Changes the personality. It can be a character, personality type, object, idea, whatever. Use your imagination.
**.custom _prompt_**
 Allows use of a custom system prompt instead of the roleplaying prompt
**.reset**
 Clear history and reset to preset personality
**.stock**
 Clear history and use without a system prompt
**Available at** https://github.com/h1ddenpr0cess20/ollamarama-matrix
~~~
**Admin only commands**
**.model _model_**
 Omit model name to show current model and available models
 Include model name to change model
**.clear**
 Reset bot for everyone

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"""
# Beschreibung: ollamarama-matrix: An AI chatbot for the Matrix chat protocol with infinite personalities.
# Autor: Dustin Whyte (https://github.com/h1ddenpr0cess20/ollamarama-matrix)
# Erstellt am: December 2023
# Modifiziert von: Patrick Asmus
# Web: https://www.techniverse.net
# Git-Reposit.: https://git.techniverse.net/scriptos/ollamarama-matrix.git
# Version: 2.0
# Datum: 27.11.2024
# Modifikation: Logging eingebaut
#####################################################
ollamarama-matrix: An AI chatbot for the Matrix chat protocol with infinite personalities.
Author: Dustin Whyte
Date: December 2023
"""
from nio import AsyncClient, MatrixRoom, RoomMessageText
@ -18,35 +12,30 @@ import asyncio
import requests
import markdown
class ollamarama:
def __init__(self):
# Load config file
#load config file
self.config_file = "config.json"
with open(self.config_file, "r") as f:
config = json.load(f)
f.close()
self.server, self.username, self.password, self.channels, self.admins = config["matrix"].values()
self.client = AsyncClient(self.server, self.username)
# Time program started and joined channels
# time program started and joined channels
self.join_time = datetime.datetime.now()
# Store chat history
# store chat history
self.messages = {}
# API URL
self.api_url = config["ollama"]["api_base"] + "/api/chat"
print(f"API URL: {self.api_url}")
# Model configuration
self.models = config["ollama"]["models"]
self.default_model = self.models[config["ollama"]["default_model"]]
self.model = self.default_model
print(f"Default model: {self.model}")
# Options
self.temperature, self.top_p, self.repeat_penalty = config["ollama"]["options"].values()
self.defaults = {
"temperature": self.temperature,
@ -58,14 +47,15 @@ class ollamarama:
self.personality = self.default_personality
self.prompt = config["ollama"]["prompt"]
# get the display name for a user
async def display_name(self, user):
try:
name = await self.client.get_displayname(user)
return name.displayname
except Exception as e:
print(f"Error fetching display name: {e}")
return user
# simplifies sending messages to the channel
async def send_message(self, channel, message):
await self.client.room_send(
room_id=channel,
@ -74,26 +64,27 @@ class ollamarama:
"msgtype": "m.text",
"body": message,
"format": "org.matrix.custom.html",
"formatted_body": markdown.markdown(message, extensions=["fenced_code", "nl2br"]),
},
"formatted_body": markdown.markdown(message, extensions=['fenced_code', 'nl2br'])},
)
# add messages to the history dictionary
async def add_history(self, role, channel, sender, message):
if channel not in self.messages:
self.messages[channel] = {}
if sender not in self.messages[channel]:
self.messages[channel][sender] = [
{"role": "system", "content": self.prompt[0] + self.personality + self.prompt[1]}
]
]
self.messages[channel][sender].append({"role": role, "content": message})
# Trim history
#trim history
if len(self.messages[channel][sender]) > 24:
if self.messages[channel][sender][0]["role"] == "system":
del self.messages[channel][sender][1:3]
else:
del self.messages[channel][sender][0:2]
#generate Ollama model response
async def respond(self, channel, sender, message, sender2=None):
try:
data = {
@ -103,56 +94,54 @@ class ollamarama:
"options": {
"top_p": self.top_p,
"temperature": self.temperature,
"repeat_penalty": self.repeat_penalty,
},
}
# Log the data being sent
print(f"Sending data to API: {json.dumps(data, indent=2)}")
response = requests.post(self.api_url, json=data, timeout=300)
"repeat_penalty": self.repeat_penalty
}
}
response = requests.post(self.api_url, json=data, timeout=300) #may need to increase for larger models, only tested on small models
response.raise_for_status()
data = response.json()
# Log the API response
print(f"API response: {json.dumps(data, indent=2)}")
except Exception as e:
error_message = f"Error communicating with Ollama API: {e}"
await self.send_message(channel, error_message)
print(error_message)
await self.send_message(channel, "Something went wrong")
print(e)
else:
response_text = data["message"]["content"]
await self.add_history("assistant", channel, sender, response_text)
display_name = await self.display_name(sender2 if sender2 else sender)
# .x function was used
if sender2:
display_name = await self.display_name(sender2)
# .ai was used
else:
display_name = await self.display_name(sender)
response_text = f"**{display_name}**:\n{response_text.strip()}"
try:
await self.send_message(channel, response_text)
except Exception as e:
print(f"Error sending message: {e}")
print(e)
#set personality or custom system prompt
async def set_prompt(self, channel, sender, persona=None, custom=None, respond=True):
#clear existing history
try:
self.messages[channel][sender].clear()
except KeyError:
except:
pass
if persona:
if persona != None and persona != "":
# combine personality with prompt parts
prompt = self.prompt[0] + persona + self.prompt[1]
elif custom:
if custom != None and custom != "":
prompt = custom
await self.add_history("system", channel, sender, prompt)
if respond:
await self.add_history("user", channel, sender, "introduce yourself")
await self.respond(channel, sender, self.messages[channel][sender])
async def ai(self, channel, message, sender, x=False):
try:
if x and len(message) > 2:
if x and message[2]:
name = message[1]
message = message[2:]
if channel in self.messages:
@ -161,58 +150,126 @@ class ollamarama:
username = await self.display_name(user)
if name == username:
name_id = user
except Exception as e:
print(f"Error in .x command: {e}")
except:
name_id = name
await self.add_history("user", channel, name_id, " ".join(message))
await self.add_history("user", channel, name_id, ' '.join(message))
await self.respond(channel, name_id, self.messages[channel][name_id], sender)
else:
await self.add_history("user", channel, sender, " ".join(message[1:]))
await self.add_history("user", channel, sender, ' '.join(message[1:]))
await self.respond(channel, sender, self.messages[channel][sender])
except Exception as e:
print(f"Error in .ai command: {e}")
except:
pass
async def reset(self, channel, sender, sender_display, stock=False):
if channel in self.messages:
try:
self.messages[channel][sender].clear()
except:
self.messages[channel] = {}
self.messages[channel][sender] = []
if not stock:
await self.send_message(channel, f"{self.bot_id} reset to default for {sender_display}")
await self.set_prompt(channel, sender, persona=self.personality, respond=False)
else:
await self.send_message(channel, f"Stock settings applied for {sender_display}")
async def help_menu(self, channel, sender_display):
with open("help.txt", "r") as f:
help_menu, help_admin = f.read().split("~~~")
f.close()
await self.send_message(channel, help_menu)
if sender_display in self.admins:
await self.send_message(channel, help_admin)
async def change_model(self, channel, model=False):
with open(self.config_file, "r") as f:
config = json.load(f)
f.close()
self.models = config["ollama"]["models"]
if model:
try:
if model in self.models:
self.model = self.models[model]
elif model == 'reset':
self.model = self.default_model
await self.send_message(channel, f"Model set to **{self.model}**")
except:
pass
else:
current_model = f"**Current model**: {self.model}\n**Available models**: {', '.join(sorted(list(self.models)))}"
await self.send_message(channel, current_model)
async def clear(self, channel):
self.messages.clear()
self.model = self.default_model
self.personality = self.default_personality
self.temperature, self.top_p, self.repeat_penalty = self.defaults.values()
await self.send_message(channel, "Bot has been reset for everyone")
async def handle_message(self, message, sender, sender_display, channel):
user_commands = {
".ai": lambda: self.ai(channel, message, sender),
".reset": lambda: self.set_prompt(channel, sender, persona=self.personality, respond=False),
f"{self.bot_id}:": lambda: self.ai(channel, message, sender),
".x": lambda: self.ai(channel, message, sender, x=True),
".persona": lambda: self.set_prompt(channel, sender, persona=' '.join(message[1:])),
".custom": lambda: self.set_prompt(channel, sender, custom=' '.join(message[1:])),
".reset": lambda: self.reset(channel, sender, sender_display),
".stock": lambda: self.reset(channel, sender, sender_display, stock=True),
".help": lambda: self.help_menu(channel, sender_display),
}
admin_commands = {
".model": lambda: self.change_model(channel, model=message[1] if len(message) > 1 else False),
".clear": lambda: self.clear(channel),
}
#may add back temperature controls later, per user, for now you can just change that in config on the fly
command = message[0]
if command in user_commands:
action = user_commands[command]
await action()
if sender_display in self.admins and command in admin_commands:
action = admin_commands[command]
await action()
async def message_callback(self, room: MatrixRoom, event: RoomMessageText):
if isinstance(event, RoomMessageText):
message_time = datetime.datetime.fromtimestamp(event.server_timestamp / 1000)
message = event.body.split(" ")
message_time = event.server_timestamp / 1000
message_time = datetime.datetime.fromtimestamp(message_time)
message = event.body
message = message.split(" ")
sender = event.sender
sender_display = await self.display_name(sender)
channel = room.room_id
#check if the message was sent after joining and not by the bot
if message_time > self.join_time and sender != self.username:
try:
await self.handle_message(message, sender, sender_display, channel)
except Exception as e:
print(f"Error handling message: {e}")
except:
pass
async def main(self):
# Login, print "Logged in as @alice:example.org device id: RANDOMDID"
print(await self.client.login(self.password))
# get account display name
self.bot_id = await self.display_name(self.username)
# join channels
for channel in self.channels:
try:
await self.client.join(channel)
print(f"{self.bot_id} joined {channel}")
except Exception as e:
print(f"Couldn't join {channel}: {e}")
except:
print(f"Couldn't join {channel}")
# start listening for messages
self.client.add_event_callback(self.message_callback, RoomMessageText)
await self.client.sync_forever(timeout=30000, full_state=True)
await self.client.sync_forever(timeout=30000, full_state=True)
if __name__ == "__main__":
ollamarama = ollamarama()
asyncio.run(ollamarama.main())
asyncio.get_event_loop().run_until_complete(ollamarama.main())

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#!/bin/bash
set -x
# Server starten
ollama serve&
# Modelle installieren
ollama pull llama3.1:8b-instruct-q5_K_M
ollama pull llama3.2
wait