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8 Commits

Author SHA1 Message Date
veguAI
611f77a730 Prep 0.16.0 (#40)
* remove dbg message

* more work to make clients and agents modular
allow conversation and narrator to attempt to auto break AI repetition

* application settings refactor
setup third party api keys through application settings

* runpod docs

* fix wording

* docs

* improvements to auto-break-repetition functionality

* more auto-break-repetition improvements

* some cleanup to narrate on dialogue chance calculations

* changing api keys via ux should now reflect to ux instantly.

* memory agent / chromadb agent - wrap blocking functions calls in asyncio

* clean up narrate progression prompt and function

* turn off dedupe debug message for now

* encourage the AI to break repetition as well

* indicate if the current model is missing a LLM prompt template
add prompt template to client modal
fix a bunch of bad vue code

* only show llm prompt when editing client

* OpenHermes-2.5-neural-chat
RpBird-Yi-34B

* fix bug with auto rep break when no repetition was found

* allow giving extra instructions to narrator agent

* emit agents as needed, not constantly

* fix a bunch of vue alerts

* fix request-client-status event

* remove undefined reference

* log client / status emit

* worldstate component track scene time

* Tess
Noromaid

* fix narrate-character prompt context length overflow issues

* disable worldstate refresh button while waiting for response

* history timestamp moved to tooltip off of history button

* fixes #39: using openai embeddings for chromadb tends to error

* adjust conversation again default instructions

* poetry lock

* remove debug message

* chromadb - agent status error if openai embeddings are selected in api key isn't set

* prep 0.16.0
2023-12-08 22:57:44 +02:00
veguAI
0738899ac9 Prep 0.15.0 (#38)
* send one request for assign all clients

* tweak narrate-after-dialogue prompt

* elevenlabs default to turbo model and make model id configurable

* improve add client dialogue to be more robust

* prompt for default character creation on character card loads

* rename to model as to not conflict with pydantic

* narrate after dialogue strip dialogue generation unless enabled via new option

* starling and capybara-tess

* narrate dialogue context increased

* relabel tts agent to Voice, show agent label in status bar

* dont expect LLM to handle * and " - most of them are not stable / consistent enough with it

* starling template updated

* if allow dialogue in narration is disabled just assume the entire string is a narration

* reorganization the narrate after dialogue template

* fix more issues with time passage calculations

* move punkt download to agent init and silence

* improved RAG during conversation if AI selected is enabled in conversation agent

* prompt tweaks

* deepseek, chromomaid-storytelling

* relock

* narrate-after-dialogue prompt tweaks

* runpod status queries every 15 secs instead of 60

* default player character prompting when loading character card from talemate storage

* better chunking during split tts generation

* tweak narrate progress prompt

* improvements to ensure_dialogue_format and tests

* to pytest

* prep 0.15.0

* update packages

* dialogue cleanup fixes

* fix openai default model name
fix not being able to edit client due to name check

* free form analyst was using wrong system prompt causing gpt-4 to actually generate json responses
2023-12-02 00:40:14 +02:00
veguAI
76b7b5c0e0 templating overview (#37)
readme updates

readme updates
2023-11-26 16:35:09 +02:00
veguAI
cae5e8d217 Update README.md
Update textgenwebui setup picture to be in line with current api url requirements
2023-11-26 16:32:50 +02:00
veguAI
97bfd3a672 Add files via upload 2023-11-26 16:31:49 +02:00
veguAI
8fb1341b93 Update README.md
fix references to old repo
2023-11-26 16:25:46 +02:00
fiwo
cba4412f3d Update README.md 2023-11-25 01:49:44 +02:00
fiwo
2ad87f6e8a Prep 0.14.1 (#35)
* tts dont try to play sound if agent not ready

* tts: flag agent as uninitlized if no voice is selected
tts: fix some config issues with voice selection

* 0.14.1
2023-11-25 00:13:33 +02:00
58 changed files with 2326 additions and 896 deletions

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@@ -2,14 +2,17 @@
Allows you to play roleplay scenarios with large language models. Allows you to play roleplay scenarios with large language models.
It does not run any large language models itself but relies on existing APIs. Currently supports **text-generation-webui** and **openai**.
This means you need to either have an openai api key or know how to setup [oobabooga/text-generation-webui](https://github.com/oobabooga/text-generation-webui) (locally or remotely via gpu renting. `--extension openai` flag needs to be set) |![Screenshot 1](docs/img/Screenshot_9.png)|![Screenshot 2](docs/img/Screenshot_2.png)|
|------------------------------------------|------------------------------------------|
As of version 0.13.0 the legacy text-generator-webui API `--extension api` is no longer supported, please use their new `--extension openai` api implementation instead. > :warning: **It does not run any large language models itself but relies on existing APIs. Currently supports OpenAI, text-generation-webui and LMStudio.**
![Screenshot 1](docs/img/Screenshot_9.png) This means you need to either have:
![Screenshot 2](docs/img/Screenshot_2.png) - an [OpenAI](https://platform.openai.com/overview) api key
- OR setup local (or remote via runpod) LLM inference via one of these options:
- [oobabooga/text-generation-webui](https://github.com/oobabooga/text-generation-webui)
- [LMStudio](https://lmstudio.ai/)
## Current features ## Current features
@@ -22,7 +25,8 @@ As of version 0.13.0 the legacy text-generator-webui API `--extension api` is no
- editor: improves AI responses (very hit and miss at the moment) - editor: improves AI responses (very hit and miss at the moment)
- world state: generates world snapshot and handles passage of time (objects and characters) - world state: generates world snapshot and handles passage of time (objects and characters)
- creator: character / scenario creator - creator: character / scenario creator
- multi-client (agents can be connected to separate APIs) - tts: text to speech via elevenlabs, coqui studio, coqui local
- multi-client support (agents can be connected to separate APIs)
- long term memory - long term memory
- chromadb integration - chromadb integration
- passage of time - passage of time
@@ -40,7 +44,7 @@ Kinda making it up as i go along, but i want to lean more into gameplay through
In no particular order: In no particular order:
- TTS support
- Extension support - Extension support
- modular agents and clients - modular agents and clients
- Improved world state - Improved world state
@@ -60,13 +64,13 @@ In no particular order:
## Installation ## Installation
Post [here](https://github.com/final-wombat/talemate/issues/17) if you run into problems during installation. Post [here](https://github.com/vegu-ai/talemate/issues/17) if you run into problems during installation.
### Windows ### Windows
1. Download and install Python 3.10 or higher from the [official Python website](https://www.python.org/downloads/windows/). 1. Download and install Python 3.10 or higher from the [official Python website](https://www.python.org/downloads/windows/).
1. Download and install Node.js from the [official Node.js website](https://nodejs.org/en/download/). This will also install npm. 1. Download and install Node.js from the [official Node.js website](https://nodejs.org/en/download/). This will also install npm.
1. Download the Talemate project to your local machine. Download from [the Releases page](https://github.com/final-wombat/talemate/releases). 1. Download the Talemate project to your local machine. Download from [the Releases page](https://github.com/vegu-ai/talemate/releases).
1. Unpack the download and run `install.bat` by double clicking it. This will set up the project on your local machine. 1. Unpack the download and run `install.bat` by double clicking it. This will set up the project on your local machine.
1. Once the installation is complete, you can start the backend and frontend servers by running `start.bat`. 1. Once the installation is complete, you can start the backend and frontend servers by running `start.bat`.
1. Navigate your browser to http://localhost:8080 1. Navigate your browser to http://localhost:8080
@@ -75,7 +79,7 @@ Post [here](https://github.com/final-wombat/talemate/issues/17) if you run into
`python 3.10` or higher is required. `python 3.10` or higher is required.
1. `git clone git@github.com:final-wombat/talemate` 1. `git clone git@github.com:vegu-ai/talemate`
1. `cd talemate` 1. `cd talemate`
1. `source install.sh` 1. `source install.sh`
1. Start the backend: `python src/talemate/server/run.py runserver --host 0.0.0.0 --port 5050`. 1. Start the backend: `python src/talemate/server/run.py runserver --host 0.0.0.0 --port 5050`.
@@ -118,15 +122,15 @@ https://www.reddit.com/r/LocalLLaMA/comments/17fhp9k/huge_llm_comparisontest_39_
On the right hand side click the "Add Client" button. If there is no button, you may need to toggle the client options by clicking this button: On the right hand side click the "Add Client" button. If there is no button, you may need to toggle the client options by clicking this button:
As of version 0.13.0 the legacy text-generator-webui API `--extension api` is no longer supported, please use their new `--extension openai` api implementation instead.
![Client options](docs/img/client-options-toggle.png) ![Client options](docs/img/client-options-toggle.png)
### Text-generation-webui ### Text-generation-webui
> :warning: As of version 0.13.0 the legacy text-generator-webui API `--extension api` is no longer supported, please use their new `--extension openai` api implementation instead.
In the modal if you're planning to connect to text-generation-webui, you can likely leave everything as is and just click Save. In the modal if you're planning to connect to text-generation-webui, you can likely leave everything as is and just click Save.
![Add client modal](docs/img/add-client-modal.png) ![Add client modal](docs/img/client-setup-0.13.png)
### OpenAI ### OpenAI
@@ -164,8 +168,8 @@ Make sure you save the scene after the character is loaded as it can then be loa
Please read the documents in the `docs` folder for more advanced configuration and usage. Please read the documents in the `docs` folder for more advanced configuration and usage.
- Creative mode (docs WIP) - [Prompt template overrides](docs/templates.md)
- Prompt template overrides
- [Text-to-Speech (TTS)](docs/tts.md) - [Text-to-Speech (TTS)](docs/tts.md)
- [ChromaDB (long term memory)](docs/chromadb.md) - [ChromaDB (long term memory)](docs/chromadb.md)
- Runpod Integration - [Runpod Integration](docs/runpod.md)
- Creative mode

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@@ -7,12 +7,7 @@ creator:
- a thrilling action story aimed at an adult audience. - a thrilling action story aimed at an adult audience.
- a mysterious adventure aimed at an adult audience. - a mysterious adventure aimed at an adult audience.
- an epic sci-fi adventure aimed at an adult audience. - an epic sci-fi adventure aimed at an adult audience.
game: game: {}
default_player_character:
color: '#6495ed'
description: a young man with a penchant for adventure.
gender: male
name: Elmer
## Long-term memory ## Long-term memory

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@@ -0,0 +1,52 @@
## RunPod integration
RunPod allows you to quickly set up and run text-generation-webui instances on powerful GPUs, remotely. If you want to run the significantly larger models (like 70B parameters) with reasonable speeds, this is probably the best way to do it.
### Create / grab your RunPod API key and add it to the talemate config
You can manage your RunPod api keys at [https://www.runpod.io/console/user/settings](https://www.runpod.io/console/user/settings)
Add the key to your Talemate config file (config.yaml):
```yaml
runpod:
api_key: <your api key>
```
Then restart Talemate.
### Create a RunPod instance
#### Community Cloud
The community cloud pods are cheaper and there are generally more GPUs available. They do however not support persistent storage and you will have to download your model and data every time you deploy a pod.
#### Secure Cloud
The secure cloud pods are more expensive and there are generally fewer GPUs available, but they do support persistent storage.
Peristent volumes are super convenient, but optional for our purposes and are **not** free and you will have to pay for the storage you use.
### Deploy pod
For us it does not matter which cloud you choose. The only thing that matters is that it deploys a text-generation-webui instance, and you ensure that by choosing the right template.
Pick the GPU you want to use, for 70B models you want at least 48GB of VRAM and click `Deploy`, then select a template and deploy.
When choosing the template for your pod, choose the `RunPod TheBloke LLMs` template. This template is pre-configured with all the dependencies needed to run text-generation-webui. There are other text-generation-webui templates, but they are usually out of date and this one i found to be consistently good.
> :warning: The name of your pod is important and ensures that Talemate will be able to find it. Talemate will only be able to find pods that have the word `thebloke llms` or `textgen` in their name. (case insensitive)
Once your pod is deployed and has finished setup and is running, the client will automatically appear in the Talemate client list, making it available for you to use like you would use a locally hosted text-generation-webui instance.
![RunPod client](img/runpod-docs-1.png)
### Connecting to the text-generation-webui UI
To manage your text-generation-webui instance, click the `Connect` button in your RunPod pod dashboard at [https://www.runpod.io/console/pods](https://www.runpod.io/console/pods) and in the popup click on `Connect to HTTP Service [Port 7860]` to open the text-generation-webui UI. Then just download and load your model as you normally would.
## :warning: Always check your pod status on the RunPod dashboard
Talemate is not a suitable or reliable way for you to determine whether your pod is currently running or not. **Always** check the runpod dashboard to see if your pod is running or not.
While your pod us running it will be eating up your credits, so make sure to stop it when you're not using it.

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@@ -0,0 +1,82 @@
# Template Overrides in Talemate
## Introduction to Templates
In Talemate, templates are used to generate dynamic content for various agents involved in roleplaying scenarios. These templates leverage the Jinja2 templating engine, allowing for the inclusion of variables, conditional logic, and custom functions to create rich and interactive narratives.
## Template Structure
A typical template in Talemate consists of several sections, each enclosed within special section tags (`<|SECTION:NAME|>` and `<|CLOSE_SECTION|>`). These sections can include character details, dialogue examples, scenario overviews, tasks, and additional context. Templates utilize loops and blocks to iterate over data and render content conditionally based on the task requirements.
## Overriding Templates
Users can customize the behavior of Talemate by overriding the default templates. To override a template, create a new template file with the same name in the `./templates/prompts/{agent}/` directory. When a custom template is present, Jinja2 will prioritize it over the default template located in the `./src/talemate/prompts/templates/{agent}/` directory.
## Creator Agent Templates
The creator agent templates allow for the creation of new characters within the character creator. Following the naming convention `character-attributes-*.jinja2`, `character-details-*.jinja2`, and `character-example-dialogue-*.jinja2`, users can add new templates that will be available for selection in the character creator.
### Requirements for Creator Templates
- All three types (`attributes`, `details`, `example-dialogue`) need to be available for a choice to be valid in the character creator.
- Users can check the human templates for an understanding of how to structure these templates.
### Example Templates
- [Character Attributes Human Template](src/talemate/prompts/templates/creator/character-attributes-human.jinja2)
- [Character Details Human Template](src/talemate/prompts/templates/creator/character-details-human.jinja2)
- [Character Example Dialogue Human Template](src/talemate/prompts/templates/creator/character-example-dialogue-human.jinja2)
These example templates can serve as a guide for users to create their own custom templates for the character creator.
### Extending Existing Templates
Jinja2's template inheritance feature allows users to extend existing templates and add extra information. By using the `{% extends "template-name.jinja2" %}` tag, a new template can inherit everything from an existing template and then add or override specific blocks of content.
#### Example
To add a description of a character's hairstyle to the human character details template, you could create a new template like this:
```jinja2
{% extends "character-details-human.jinja2" %}
{% block questions %}
{% if character_details.q("what does "+character.name+"'s hair look like?") -%}
Briefly describe {{ character.name }}'s hair-style using a narrative writing style that reminds of mid 90s point and click adventure games. (2 - 3 sentences).
{% endif %}
{% endblock %}
```
This example shows how to extend the `character-details-human.jinja2` template and add a block for questions about the character's hair. The `{% block questions %}` tag is used to define a section where additional questions can be inserted or existing ones can be overridden.
## Advanced Template Topics
### Jinja2 Functions in Talemate
Talemate exposes several functions to the Jinja2 template environment, providing utilities for data manipulation, querying, and controlling content flow. Here's a list of available functions:
1. `set_prepared_response(response, prepend)`: Sets the prepared response with an optional prepend string. This function allows the template to specify the beginning of the LLM response when processing the rendered template. For example, `set_prepared_response("Certainly!")` will ensure that the LLM's response starts with "Certainly!".
2. `set_prepared_response_random(responses, prefix)`: Chooses a random response from a list and sets it as the prepared response with an optional prefix.
3. `set_eval_response(empty)`: Prepares the response for evaluation, optionally initializing a counter for an empty string.
4. `set_json_response(initial_object, instruction, cutoff)`: Prepares for a JSON response with an initial object and optional instruction and cutoff.
5. `set_question_eval(question, trigger, counter, weight)`: Sets up a question for evaluation with a trigger, counter, and weight.
6. `disable_dedupe()`: Disables deduplication of the response text.
7. `random(min, max)`: Generates a random integer between the specified minimum and maximum.
8. `query_scene(query, at_the_end, as_narrative)`: Queries the scene with a question and returns the formatted response.
9. `query_text(query, text, as_question_answer)`: Queries a text with a question and returns the formatted response.
10. `query_memory(query, as_question_answer, **kwargs)`: Queries the memory with a question and returns the formatted response.
11. `instruct_text(instruction, text)`: Instructs the text with a command and returns the result.
12. `retrieve_memories(lines, goal)`: Retrieves memories based on the provided lines and an optional goal.
13. `uuidgen()`: Generates a UUID string.
14. `to_int(x)`: Converts the given value to an integer.
15. `config`: Accesses the configuration settings.
16. `len(x)`: Returns the length of the given object.
17. `count_tokens(x)`: Counts the number of tokens in the given text.
18. `print(x)`: Prints the given object (mainly for debugging purposes).
These functions enhance the capabilities of templates, allowing for dynamic and interactive content generation.
### Error Handling
Errors encountered during template rendering are logged and propagated to the user interface. This ensures that users are informed of any issues that may arise, allowing them to troubleshoot and resolve problems effectively.
By following these guidelines, users can create custom templates that tailor the Talemate experience to their specific storytelling needs.# Template Overrides in Talemate

1171
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@@ -4,7 +4,7 @@ build-backend = "poetry.masonry.api"
[tool.poetry] [tool.poetry]
name = "talemate" name = "talemate"
version = "0.14.0" version = "0.16.0"
description = "AI-backed roleplay and narrative tools" description = "AI-backed roleplay and narrative tools"
authors = ["FinalWombat"] authors = ["FinalWombat"]
license = "GNU Affero General Public License v3.0" license = "GNU Affero General Public License v3.0"
@@ -32,7 +32,7 @@ beautifulsoup4 = "^4.12.2"
python-dotenv = "^1.0.0" python-dotenv = "^1.0.0"
websockets = "^11.0.3" websockets = "^11.0.3"
structlog = "^23.1.0" structlog = "^23.1.0"
runpod = "==1.2.0" runpod = "^1.2.0"
nest_asyncio = "^1.5.7" nest_asyncio = "^1.5.7"
isodate = ">=0.6.1" isodate = ">=0.6.1"
thefuzz = ">=0.20.0" thefuzz = ">=0.20.0"

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@@ -2,4 +2,4 @@ from .agents import Agent
from .client import TextGeneratorWebuiClient from .client import TextGeneratorWebuiClient
from .tale_mate import * from .tale_mate import *
VERSION = "0.14.0" VERSION = "0.16.0"

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@@ -1,6 +1,5 @@
from .base import Agent from .base import Agent
from .creator import CreatorAgent from .creator import CreatorAgent
from .context import ContextAgent
from .conversation import ConversationAgent from .conversation import ConversationAgent
from .director import DirectorAgent from .director import DirectorAgent
from .memory import ChromaDBMemoryAgent, MemoryAgent from .memory import ChromaDBMemoryAgent, MemoryAgent

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@@ -9,6 +9,7 @@ from blinker import signal
import talemate.instance as instance import talemate.instance as instance
import talemate.util as util import talemate.util as util
from talemate.agents.context import ActiveAgent
from talemate.emit import emit from talemate.emit import emit
from talemate.events import GameLoopStartEvent from talemate.events import GameLoopStartEvent
import talemate.emit.async_signals import talemate.emit.async_signals
@@ -23,21 +24,12 @@ __all__ = [
log = structlog.get_logger("talemate.agents.base") log = structlog.get_logger("talemate.agents.base")
class CallableConfigValue:
def __init__(self, fn):
self.fn = fn
def __str__(self):
return "CallableConfigValue"
def __repr__(self):
return "CallableConfigValue"
class AgentActionConfig(pydantic.BaseModel): class AgentActionConfig(pydantic.BaseModel):
type: str type: str
label: str label: str
description: str = "" description: str = ""
value: Union[int, float, str, bool, None] value: Union[int, float, str, bool, None] = None
default_value: Union[int, float, str, bool] = None default_value: Union[int, float, str, bool] = None
max: Union[int, float, None] = None max: Union[int, float, None] = None
min: Union[int, float, None] = None min: Union[int, float, None] = None
@@ -65,11 +57,12 @@ def set_processing(fn):
""" """
async def wrapper(self, *args, **kwargs): async def wrapper(self, *args, **kwargs):
try: with ActiveAgent(self, fn):
await self.emit_status(processing=True) try:
return await fn(self, *args, **kwargs) await self.emit_status(processing=True)
finally: return await fn(self, *args, **kwargs)
await self.emit_status(processing=False) finally:
await self.emit_status(processing=False)
wrapper.__name__ = fn.__name__ wrapper.__name__ = fn.__name__
@@ -85,6 +78,7 @@ class Agent(ABC):
verbose_name = None verbose_name = None
set_processing = set_processing set_processing = set_processing
requires_llm_client = True requires_llm_client = True
auto_break_repetition = False
@property @property
def agent_details(self): def agent_details(self):
@@ -291,6 +285,22 @@ class Agent(ABC):
current_memory_context.append(memory) current_memory_context.append(memory)
return current_memory_context return current_memory_context
# LLM client related methods. These are called during or after the client
# sends the prompt to the API.
def inject_prompt_paramters(self, prompt_param:dict, kind:str, agent_function_name:str):
"""
Injects prompt parameters before the client sends off the prompt
Override as needed.
"""
pass
def allow_repetition_break(self, kind:str, agent_function_name:str, auto:bool=False):
"""
Returns True if repetition breaking is allowed, False otherwise.
"""
return False
@dataclasses.dataclass @dataclasses.dataclass
class AgentEmission: class AgentEmission:

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@@ -1,54 +1,33 @@
from .base import Agent
from .registry import register
from typing import Callable, TYPE_CHECKING
import contextvars
import pydantic
@register __all__ = [
class ContextAgent(Agent): "active_agent",
""" ]
Agent that helps retrieve context for the continuation
of dialogue.
"""
agent_type = "context" active_agent = contextvars.ContextVar("active_agent", default=None)
def __init__(self, client, **kwargs): class ActiveAgentContext(pydantic.BaseModel):
self.client = client agent: object
fn: Callable
class Config:
arbitrary_types_allowed=True
@property
def action(self):
return self.fn.__name__
def determine_questions(self, scene_text): class ActiveAgent:
prompt = [
"You are tasked to continue the following dialogue in a roleplaying session, but before you can do so you can ask three questions for extra context." def __init__(self, agent, fn):
"", self.agent = ActiveAgentContext(agent=agent, fn=fn)
"What are the questions you would ask?",
"", def __enter__(self):
"Known context and dialogue:" "", self.token = active_agent.set(self.agent)
scene_text,
"", def __exit__(self, *args, **kwargs):
"Questions:", active_agent.reset(self.token)
"", return False
]
prompt = "\n".join(prompt)
questions = self.client.send_prompt(prompt, kind="question")
questions = self.clean_result(questions)
return questions.split("\n")
def get_answer(self, question, context):
prompt = [
"Read the context and answer the question:",
"",
"Context:",
"",
context,
"",
f"Question: {question}",
"Answer:",
]
prompt = "\n".join(prompt)
answer = self.client.send_prompt(prompt, kind="answer")
answer = self.clean_result(answer)
return answer

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@@ -85,20 +85,25 @@ class ConversationAgent(Agent):
"instructions": AgentActionConfig( "instructions": AgentActionConfig(
type="text", type="text",
label="Instructions", label="Instructions",
value="1-3 sentences.", value="Write 1-3 sentences. Never wax poetic.",
description="Extra instructions to give the AI for dialog generatrion.", description="Extra instructions to give the AI for dialog generatrion.",
), ),
"jiggle": AgentActionConfig( "jiggle": AgentActionConfig(
type="number", type="number",
label="Jiggle", label="Jiggle (Increased Randomness)",
description="If > 0.0 will cause certain generation parameters to have a slight random offset applied to them. The bigger the number, the higher the potential offset.", description="If > 0.0 will cause certain generation parameters to have a slight random offset applied to them. The bigger the number, the higher the potential offset.",
value=0.0, value=0.0,
min=0.0, min=0.0,
max=1.0, max=1.0,
step=0.1, step=0.1,
), )
} }
), ),
"auto_break_repetition": AgentAction(
enabled = True,
label = "Auto Break Repetition",
description = "Will attempt to automatically break AI repetition.",
),
"natural_flow": AgentAction( "natural_flow": AgentAction(
enabled = True, enabled = True,
label = "Natural Flow", label = "Natural Flow",
@@ -131,7 +136,7 @@ class ConversationAgent(Agent):
config = { config = {
"ai_selected": AgentActionConfig( "ai_selected": AgentActionConfig(
type="bool", type="bool",
label="AI Selected", label="AI memory retrieval",
description="If enabled, the AI will select the long term memory to use. (will increase how long it takes to generate a response)", description="If enabled, the AI will select the long term memory to use. (will increase how long it takes to generate a response)",
value=False, value=False,
), ),
@@ -534,3 +539,11 @@ class ConversationAgent(Agent):
actor.scene.push_history(messages) actor.scene.push_history(messages)
return messages return messages
def allow_repetition_break(self, kind: str, agent_function_name: str, auto: bool = False):
if auto and not self.actions["auto_break_repetition"].enabled:
return False
return agent_function_name == "converse"

View File

@@ -156,6 +156,12 @@ class EditorAgent(Agent):
message = content.split(character_prefix)[1] message = content.split(character_prefix)[1]
content = f"{character_prefix}*{message.strip('*')}*" content = f"{character_prefix}*{message.strip('*')}*"
return content return content
elif '"' in content:
# if both are present we strip the * and add them back later
# through ensure_dialog_format - right now most LLMs aren't
# smart enough to do quotes and italics at the same time consistently
# especially throughout long conversations
content = content.replace('*', '')
content = util.clean_dialogue(content, main_name=character.name) content = util.clean_dialogue(content, main_name=character.name)
content = util.strip_partial_sentences(content) content = util.strip_partial_sentences(content)

View File

@@ -6,10 +6,14 @@ from typing import TYPE_CHECKING, Callable, List, Optional, Union
from chromadb.config import Settings from chromadb.config import Settings
import talemate.events as events import talemate.events as events
import talemate.util as util import talemate.util as util
from talemate.emit import emit
from talemate.emit.signals import handlers
from talemate.context import scene_is_loading from talemate.context import scene_is_loading
from talemate.config import load_config from talemate.config import load_config
from talemate.agents.base import set_processing
import structlog import structlog
import shutil import shutil
import functools
try: try:
import chromadb import chromadb
@@ -57,6 +61,15 @@ class MemoryAgent(Agent):
self.scene = scene self.scene = scene
self.memory_tracker = {} self.memory_tracker = {}
self.config = load_config() self.config = load_config()
handlers["config_saved"].connect(self.on_config_saved)
def on_config_saved(self, event):
openai_key = self.openai_api_key
self.config = load_config()
if openai_key != self.openai_api_key:
loop = asyncio.get_running_loop()
loop.run_until_complete(self.emit_status())
async def set_db(self): async def set_db(self):
raise NotImplementedError() raise NotImplementedError()
@@ -67,33 +80,43 @@ class MemoryAgent(Agent):
async def count(self): async def count(self):
raise NotImplementedError() raise NotImplementedError()
@set_processing
async def add(self, text, character=None, uid=None, ts:str=None, **kwargs): async def add(self, text, character=None, uid=None, ts:str=None, **kwargs):
if not text: if not text:
return return
if self.readonly: if self.readonly:
log.debug("memory agent", status="readonly") log.debug("memory agent", status="readonly")
return return
await self._add(text, character=character, uid=uid, ts=ts, **kwargs)
loop = asyncio.get_running_loop()
await loop.run_in_executor(None, functools.partial(self._add, text, character, uid=uid, ts=ts, **kwargs))
async def _add(self, text, character=None, ts:str=None, **kwargs): def _add(self, text, character=None, ts:str=None, **kwargs):
raise NotImplementedError() raise NotImplementedError()
@set_processing
async def add_many(self, objects: list[dict]): async def add_many(self, objects: list[dict]):
if self.readonly: if self.readonly:
log.debug("memory agent", status="readonly") log.debug("memory agent", status="readonly")
return return
await self._add_many(objects)
loop = asyncio.get_running_loop()
await loop.run_in_executor(None, self._add_many, objects)
async def _add_many(self, objects: list[dict]): def _add_many(self, objects: list[dict]):
""" """
Add multiple objects to the memory Add multiple objects to the memory
""" """
raise NotImplementedError() raise NotImplementedError()
@set_processing
async def get(self, text, character=None, **query): async def get(self, text, character=None, **query):
return await self._get(str(text), character, **query) loop = asyncio.get_running_loop()
return await loop.run_in_executor(None, functools.partial(self._get, text, character, **query))
async def _get(self, text, character=None, **query): def _get(self, text, character=None, **query):
raise NotImplementedError() raise NotImplementedError()
def get_document(self, id): def get_document(self, id):
@@ -140,6 +163,10 @@ class MemoryAgent(Agent):
""" """
memory_context = [] memory_context = []
if not query:
return memory_context
for memory in await self.get(query): for memory in await self.get(query):
if memory in memory_context: if memory in memory_context:
continue continue
@@ -179,6 +206,10 @@ class MemoryAgent(Agent):
memory_context = [] memory_context = []
for query in queries: for query in queries:
if not query:
continue
i = 0 i = 0
for memory in await self.get(formatter(query), limit=iterate, **where): for memory in await self.get(formatter(query), limit=iterate, **where):
if memory in memory_context: if memory in memory_context:
@@ -210,6 +241,10 @@ class ChromaDBMemoryAgent(MemoryAgent):
@property @property
def ready(self): def ready(self):
if self.embeddings == "openai" and not self.openai_api_key:
return False
if getattr(self, "db_client", None): if getattr(self, "db_client", None):
return True return True
return False return False
@@ -218,10 +253,18 @@ class ChromaDBMemoryAgent(MemoryAgent):
def status(self): def status(self):
if self.ready: if self.ready:
return "active" if not getattr(self, "processing", False) else "busy" return "active" if not getattr(self, "processing", False) else "busy"
if self.embeddings == "openai" and not self.openai_api_key:
return "error"
return "waiting" return "waiting"
@property @property
def agent_details(self): def agent_details(self):
if self.embeddings == "openai" and not self.openai_api_key:
return "No OpenAI API key set"
return f"ChromaDB: {self.embeddings}" return f"ChromaDB: {self.embeddings}"
@property @property
@@ -266,6 +309,10 @@ class ChromaDBMemoryAgent(MemoryAgent):
def db_name(self): def db_name(self):
return getattr(self, "collection_name", "<unnamed>") return getattr(self, "collection_name", "<unnamed>")
@property
def openai_api_key(self):
return self.config.get("openai",{}).get("api_key")
def make_collection_name(self, scene): def make_collection_name(self, scene):
if self.USE_OPENAI: if self.USE_OPENAI:
@@ -286,17 +333,19 @@ class ChromaDBMemoryAgent(MemoryAgent):
await asyncio.sleep(0) await asyncio.sleep(0)
return self.db.count() return self.db.count()
@set_processing
async def set_db(self): async def set_db(self):
await self.emit_status(processing=True) loop = asyncio.get_running_loop()
await loop.run_in_executor(None, self._set_db)
def _set_db(self):
if not getattr(self, "db_client", None): if not getattr(self, "db_client", None):
log.info("chromadb agent", status="setting up db client to persistent db") log.info("chromadb agent", status="setting up db client to persistent db")
self.db_client = chromadb.PersistentClient( self.db_client = chromadb.PersistentClient(
settings=Settings(anonymized_telemetry=False) settings=Settings(anonymized_telemetry=False)
) )
openai_key = self.config.get("openai").get("api_key") or os.environ.get("OPENAI_API_KEY") openai_key = self.openai_api_key
self.collection_name = collection_name = self.make_collection_name(self.scene) self.collection_name = collection_name = self.make_collection_name(self.scene)
@@ -341,8 +390,6 @@ class ChromaDBMemoryAgent(MemoryAgent):
self.db = self.db_client.get_or_create_collection(collection_name) self.db = self.db_client.get_or_create_collection(collection_name)
self.scene._memory_never_persisted = self.db.count() == 0 self.scene._memory_never_persisted = self.db.count() == 0
await self.emit_status(processing=False)
log.info("chromadb agent", status="db ready") log.info("chromadb agent", status="db ready")
def clear_db(self): def clear_db(self):
@@ -383,12 +430,10 @@ class ChromaDBMemoryAgent(MemoryAgent):
self.db = None self.db = None
async def _add(self, text, character=None, uid=None, ts:str=None, **kwargs): def _add(self, text, character=None, uid=None, ts:str=None, **kwargs):
metadatas = [] metadatas = []
ids = [] ids = []
await self.emit_status(processing=True)
if character: if character:
meta = {"character": character.name, "source": "talemate"} meta = {"character": character.name, "source": "talemate"}
if ts: if ts:
@@ -413,17 +458,13 @@ class ChromaDBMemoryAgent(MemoryAgent):
#log.debug("chromadb agent add", text=text, meta=meta, id=id) #log.debug("chromadb agent add", text=text, meta=meta, id=id)
self.db.upsert(documents=[text], metadatas=metadatas, ids=ids) self.db.upsert(documents=[text], metadatas=metadatas, ids=ids)
await self.emit_status(processing=False)
async def _add_many(self, objects: list[dict]): def _add_many(self, objects: list[dict]):
documents = [] documents = []
metadatas = [] metadatas = []
ids = [] ids = []
await self.emit_status(processing=True)
for obj in objects: for obj in objects:
documents.append(obj["text"]) documents.append(obj["text"])
meta = obj.get("meta", {}) meta = obj.get("meta", {})
@@ -436,11 +477,7 @@ class ChromaDBMemoryAgent(MemoryAgent):
ids.append(uid) ids.append(uid)
self.db.upsert(documents=documents, metadatas=metadatas, ids=ids) self.db.upsert(documents=documents, metadatas=metadatas, ids=ids)
await self.emit_status(processing=False) def _get(self, text, character=None, limit:int=15, **kwargs):
async def _get(self, text, character=None, limit:int=15, **kwargs):
await self.emit_status(processing=True)
where = {} where = {}
where.setdefault("$and", []) where.setdefault("$and", [])
@@ -480,7 +517,7 @@ class ChromaDBMemoryAgent(MemoryAgent):
if distance < 1: if distance < 1:
try: try:
log.debug("chromadb agent get", ts=ts, scene_ts=self.scene.ts) #log.debug("chromadb agent get", ts=ts, scene_ts=self.scene.ts)
date_prefix = util.iso8601_diff_to_human(ts, self.scene.ts) date_prefix = util.iso8601_diff_to_human(ts, self.scene.ts)
except Exception as e: except Exception as e:
log.error("chromadb agent", error="failed to get date prefix", details=e, ts=ts, scene_ts=self.scene.ts) log.error("chromadb agent", error="failed to get date prefix", details=e, ts=ts, scene_ts=self.scene.ts)
@@ -497,6 +534,4 @@ class ChromaDBMemoryAgent(MemoryAgent):
if len(results) > limit: if len(results) > limit:
break break
await self.emit_status(processing=False)
return results return results

View File

@@ -68,6 +68,24 @@ class NarratorAgent(Agent):
# agent actions # agent actions
self.actions = { self.actions = {
"generation_override": AgentAction(
enabled = True,
label = "Generation Override",
description = "Override generation parameters",
config = {
"instructions": AgentActionConfig(
type="text",
label="Instructions",
value="Never wax poetic.",
description="Extra instructions to give to the AI for narrative generation.",
),
}
),
"auto_break_repetition": AgentAction(
enabled = True,
label = "Auto Break Repetition",
description = "Will attempt to automatically break AI repetition.",
),
"narrate_time_passage": AgentAction(enabled=True, label="Narrate Time Passage", description="Whenever you indicate passage of time, narrate right after"), "narrate_time_passage": AgentAction(enabled=True, label="Narrate Time Passage", description="Whenever you indicate passage of time, narrate right after"),
"narrate_dialogue": AgentAction( "narrate_dialogue": AgentAction(
enabled=True, enabled=True,
@@ -92,10 +110,22 @@ class NarratorAgent(Agent):
max=1.0, max=1.0,
step=0.1, step=0.1,
), ),
"generate_dialogue": AgentActionConfig(
type="bool",
label="Allow Dialogue in Narration",
description="Allow the narrator to generate dialogue in narration",
value=False,
),
} }
), ),
} }
@property
def extra_instructions(self):
if self.actions["generation_override"].enabled:
return self.actions["generation_override"].config["instructions"].value
return ""
def clean_result(self, result): def clean_result(self, result):
""" """
@@ -153,16 +183,22 @@ class NarratorAgent(Agent):
if not self.actions["narrate_dialogue"].enabled: if not self.actions["narrate_dialogue"].enabled:
return return
narrate_on_ai_chance = self.actions["narrate_dialogue"].config["ai_dialog"].value
narrate_on_player_chance = self.actions["narrate_dialogue"].config["player_dialog"].value
narrate_on_ai = random.random() < narrate_on_ai_chance
narrate_on_player = random.random() < narrate_on_player_chance
log.debug(
"narrate on dialog",
narrate_on_ai=narrate_on_ai,
narrate_on_ai_chance=narrate_on_ai_chance,
narrate_on_player=narrate_on_player,
narrate_on_player_chance=narrate_on_player_chance,
)
narrate_on_ai_chance = random.random() < self.actions["narrate_dialogue"].config["ai_dialog"].value if event.actor.character.is_player and not narrate_on_player:
narrate_on_player_chance = random.random() < self.actions["narrate_dialogue"].config["player_dialog"].value
log.debug("narrate on dialog", narrate_on_ai_chance=narrate_on_ai_chance, narrate_on_player_chance=narrate_on_player_chance)
if event.actor.character.is_player and not narrate_on_player_chance:
return return
if not event.actor.character.is_player and not narrate_on_ai_chance: if not event.actor.character.is_player and not narrate_on_ai:
return return
response = await self.narrate_after_dialogue(event.actor.character) response = await self.narrate_after_dialogue(event.actor.character)
@@ -183,6 +219,7 @@ class NarratorAgent(Agent):
vars = { vars = {
"scene": self.scene, "scene": self.scene,
"max_tokens": self.client.max_token_length, "max_tokens": self.client.max_token_length,
"extra_instructions": self.extra_instructions,
} }
) )
@@ -200,22 +237,11 @@ class NarratorAgent(Agent):
""" """
scene = self.scene scene = self.scene
director = scene.get_helper("director").agent
pc = scene.get_player_character() pc = scene.get_player_character()
npcs = list(scene.get_npc_characters()) npcs = list(scene.get_npc_characters())
npc_names= ", ".join([npc.name for npc in npcs]) npc_names= ", ".join([npc.name for npc in npcs])
#summarized_history = await scene.summarized_dialogue_history(
# budget = self.client.max_token_length - 300,
# min_dialogue = 50,
#)
#augmented_context = await self.augment_context()
if narrative_direction is None: if narrative_direction is None:
#narrative_direction = await director.direct_narrative(
# scene.context_history(budget=self.client.max_token_length - 500, min_dialogue=20),
#)
narrative_direction = "Slightly move the current scene forward." narrative_direction = "Slightly move the current scene forward."
self.scene.log.info("narrative_direction", narrative_direction=narrative_direction) self.scene.log.info("narrative_direction", narrative_direction=narrative_direction)
@@ -226,13 +252,12 @@ class NarratorAgent(Agent):
"narrate", "narrate",
vars = { vars = {
"scene": self.scene, "scene": self.scene,
#"summarized_history": summarized_history,
#"augmented_context": augmented_context,
"max_tokens": self.client.max_token_length, "max_tokens": self.client.max_token_length,
"narrative_direction": narrative_direction, "narrative_direction": narrative_direction,
"player_character": pc, "player_character": pc,
"npcs": npcs, "npcs": npcs,
"npc_names": npc_names, "npc_names": npc_names,
"extra_instructions": self.extra_instructions,
} }
) )
@@ -263,6 +288,7 @@ class NarratorAgent(Agent):
"query": query, "query": query,
"at_the_end": at_the_end, "at_the_end": at_the_end,
"as_narrative": as_narrative, "as_narrative": as_narrative,
"extra_instructions": self.extra_instructions,
} }
) )
log.info("narrate_query", response=response) log.info("narrate_query", response=response)
@@ -299,6 +325,7 @@ class NarratorAgent(Agent):
"character": character, "character": character,
"max_tokens": self.client.max_token_length, "max_tokens": self.client.max_token_length,
"memory": memory_context, "memory": memory_context,
"extra_instructions": self.extra_instructions,
} }
) )
@@ -323,6 +350,7 @@ class NarratorAgent(Agent):
vars = { vars = {
"scene": self.scene, "scene": self.scene,
"max_tokens": self.client.max_token_length, "max_tokens": self.client.max_token_length,
"extra_instructions": self.extra_instructions,
} }
) )
@@ -343,6 +371,7 @@ class NarratorAgent(Agent):
"max_tokens": self.client.max_token_length, "max_tokens": self.client.max_token_length,
"memory": memory_context, "memory": memory_context,
"questions": questions, "questions": questions,
"extra_instructions": self.extra_instructions,
} }
) )
@@ -368,6 +397,7 @@ class NarratorAgent(Agent):
"max_tokens": self.client.max_token_length, "max_tokens": self.client.max_token_length,
"duration": duration, "duration": duration,
"narrative": narrative, "narrative": narrative,
"extra_instructions": self.extra_instructions,
} }
) )
@@ -393,7 +423,8 @@ class NarratorAgent(Agent):
"scene": self.scene, "scene": self.scene,
"max_tokens": self.client.max_token_length, "max_tokens": self.client.max_token_length,
"character": character, "character": character,
"last_line": str(self.scene.history[-1]) "last_line": str(self.scene.history[-1]),
"extra_instructions": self.extra_instructions,
} }
) )
@@ -401,5 +432,28 @@ class NarratorAgent(Agent):
response = self.clean_result(response.strip().strip("*")) response = self.clean_result(response.strip().strip("*"))
response = f"*{response}*" response = f"*{response}*"
allow_dialogue = self.actions["narrate_dialogue"].config["generate_dialogue"].value
if not allow_dialogue:
response = response.split('"')[0].strip()
response = response.replace("*", "")
response = util.strip_partial_sentences(response)
response = f"*{response}*"
return response return response
# LLM client related methods. These are called during or after the client
def inject_prompt_paramters(self, prompt_param: dict, kind: str, agent_function_name: str):
log.debug("inject_prompt_paramters", prompt_param=prompt_param, kind=kind, agent_function_name=agent_function_name)
character_names = [f"\n{c.name}:" for c in self.scene.get_characters()]
if prompt_param.get("extra_stopping_strings") is None:
prompt_param["extra_stopping_strings"] = []
prompt_param["extra_stopping_strings"] += character_names
def allow_repetition_break(self, kind: str, agent_function_name: str, auto:bool=False):
if auto and not self.actions["auto_break_repetition"].enabled:
return False
return True

View File

@@ -15,7 +15,9 @@ from nltk.tokenize import sent_tokenize
import talemate.config as config import talemate.config as config
import talemate.emit.async_signals import talemate.emit.async_signals
import talemate.instance as instance
from talemate.emit import emit from talemate.emit import emit
from talemate.emit.signals import handlers
from talemate.events import GameLoopNewMessageEvent from talemate.events import GameLoopNewMessageEvent
from talemate.scene_message import CharacterMessage, NarratorMessage from talemate.scene_message import CharacterMessage, NarratorMessage
@@ -38,7 +40,6 @@ if not TTS:
# so we don't want to require it unless the user wants to use it # so we don't want to require it unless the user wants to use it
log.info("TTS (local) requires the TTS package, please install with `pip install TTS` if you want to use the local api") log.info("TTS (local) requires the TTS package, please install with `pip install TTS` if you want to use the local api")
nltk.download("punkt")
def parse_chunks(text): def parse_chunks(text):
@@ -56,10 +57,25 @@ def parse_chunks(text):
for i, chunk in enumerate(cleaned_chunks): for i, chunk in enumerate(cleaned_chunks):
chunk = chunk.replace("__ellipsis__", "...") chunk = chunk.replace("__ellipsis__", "...")
cleaned_chunks[i] = chunk cleaned_chunks[i] = chunk
return cleaned_chunks return cleaned_chunks
def clean_quotes(chunk:str):
# if there is an uneven number of quotes, remove the last one if its
# at the end of the chunk. If its in the middle, add a quote to the end
if chunk.count('"') % 2 == 1:
if chunk.endswith('"'):
chunk = chunk[:-1]
else:
chunk += '"'
return chunk
def rejoin_chunks(chunks:list[str], chunk_size:int=250): def rejoin_chunks(chunks:list[str], chunk_size:int=250):
""" """
@@ -74,14 +90,13 @@ def rejoin_chunks(chunks:list[str], chunk_size:int=250):
for chunk in chunks: for chunk in chunks:
if len(current_chunk) + len(chunk) > chunk_size: if len(current_chunk) + len(chunk) > chunk_size:
joined_chunks.append(current_chunk) joined_chunks.append(clean_quotes(current_chunk))
current_chunk = "" current_chunk = ""
current_chunk += chunk current_chunk += chunk
if current_chunk: if current_chunk:
joined_chunks.append(current_chunk) joined_chunks.append(clean_quotes(current_chunk))
return joined_chunks return joined_chunks
@@ -104,7 +119,7 @@ class TTSAgent(Agent):
""" """
agent_type = "tts" agent_type = "tts"
verbose_name = "Text to speech" verbose_name = "Voice"
requires_llm_client = False requires_llm_client = False
@classmethod @classmethod
@@ -121,6 +136,7 @@ class TTSAgent(Agent):
def __init__(self, **kwargs): def __init__(self, **kwargs):
self.is_enabled = False self.is_enabled = False
nltk.download("punkt", quiet=True)
self.voices = { self.voices = {
"elevenlabs": VoiceLibrary(api="elevenlabs"), "elevenlabs": VoiceLibrary(api="elevenlabs"),
@@ -175,7 +191,7 @@ class TTSAgent(Agent):
), ),
"generate_chunks": AgentActionConfig( "generate_chunks": AgentActionConfig(
type="bool", type="bool",
value=True, value=False,
label="Split generation", label="Split generation",
description="Generate audio chunks for each sentence - will be much more responsive but may loose context to inform inflection", description="Generate audio chunks for each sentence - will be much more responsive but may loose context to inform inflection",
) )
@@ -184,6 +200,7 @@ class TTSAgent(Agent):
} }
self.actions["_config"].model_dump() self.actions["_config"].model_dump()
handlers["config_saved"].connect(self.on_config_saved)
@property @property
@@ -274,6 +291,7 @@ class TTSAgent(Agent):
if self.api == "tts": if self.api == "tts":
if not TTS: if not TTS:
return "error" return "error"
return "uninitialized"
@property @property
def max_generation_length(self): def max_generation_length(self):
@@ -309,12 +327,17 @@ class TTSAgent(Agent):
super().connect(scene) super().connect(scene)
talemate.emit.async_signals.get("game_loop_new_message").connect(self.on_game_loop_new_message) talemate.emit.async_signals.get("game_loop_new_message").connect(self.on_game_loop_new_message)
def on_config_saved(self, event):
config = event.data
self.config = config
instance.emit_agent_status(self.__class__, self)
async def on_game_loop_new_message(self, emission:GameLoopNewMessageEvent): async def on_game_loop_new_message(self, emission:GameLoopNewMessageEvent):
""" """
Called when a conversation is generated Called when a conversation is generated
""" """
if not self.enabled: if not self.enabled or not self.ready:
return return
if not isinstance(emission.message, (CharacterMessage, NarratorMessage)): if not isinstance(emission.message, (CharacterMessage, NarratorMessage)):
@@ -362,21 +385,20 @@ class TTSAgent(Agent):
library = self.voices[self.api] library = self.voices[self.api]
log.info("Listing voices", api=self.api, last_synced=library.last_synced)
# TODO: allow re-syncing voices # TODO: allow re-syncing voices
if library.last_synced: if library.last_synced:
return library.voices return library.voices
list_fn = getattr(self, f"_list_voices_{self.api}") list_fn = getattr(self, f"_list_voices_{self.api}")
log.info("Listing voices", api=self.api) log.info("Listing voices", api=self.api)
library.voices = await list_fn() library.voices = await list_fn()
library.last_synced = time.time() library.last_synced = time.time()
# if the current voice cannot be found, reset it # if the current voice cannot be found, reset it
if not self.voice(self.default_voice_id): if not self.voice(self.default_voice_id):
self.actions["_config"].config["voice_id"].value = "" self.actions["_config"].config["voice_id"].value = ""
# set loading to false # set loading to false
return library.voices return library.voices
@@ -471,7 +493,7 @@ class TTSAgent(Agent):
} }
data = { data = {
"text": text, "text": text,
"model_id": "eleven_monolingual_v1", "model_id": self.config.get("elevenlabs",{}).get("model"),
"voice_settings": { "voice_settings": {
"stability": 0.5, "stability": 0.5,
"similarity_boost": 0.5 "similarity_boost": 0.5

View File

@@ -17,7 +17,7 @@ import talemate.client.system_prompts as system_prompts
import talemate.util as util import talemate.util as util
from talemate.client.context import client_context_attribute from talemate.client.context import client_context_attribute
from talemate.client.model_prompts import model_prompt from talemate.client.model_prompts import model_prompt
from talemate.agents.context import active_agent
# Set up logging level for httpx to WARNING to suppress debug logs. # Set up logging level for httpx to WARNING to suppress debug logs.
logging.getLogger('httpx').setLevel(logging.WARNING) logging.getLogger('httpx').setLevel(logging.WARNING)
@@ -37,10 +37,10 @@ class ClientBase:
enabled: bool = True enabled: bool = True
current_status: str = None current_status: str = None
max_token_length: int = 4096 max_token_length: int = 4096
randomizable_inference_parameters: list[str] = ["temperature"]
processing: bool = False processing: bool = False
connected: bool = False connected: bool = False
conversation_retries: int = 5 conversation_retries: int = 5
auto_break_repetition_enabled: bool = True
client_type = "base" client_type = "base"
@@ -74,6 +74,17 @@ class ClientBase:
return model_prompt(self.model_name, sys_msg, prompt) return model_prompt(self.model_name, sys_msg, prompt)
def has_prompt_template(self):
if not self.model_name:
return False
return model_prompt.exists(self.model_name)
def prompt_template_example(self):
if not self.model_name:
return None
return model_prompt(self.model_name, "sysmsg", "prompt<|BOT|>{LLM coercion}")
def reconfigure(self, **kwargs): def reconfigure(self, **kwargs):
""" """
@@ -142,6 +153,8 @@ class ClientBase:
return system_prompts.EDITOR return system_prompts.EDITOR
if "world_state" in kind: if "world_state" in kind:
return system_prompts.WORLD_STATE return system_prompts.WORLD_STATE
if "analyze_freeform" in kind:
return system_prompts.ANALYST_FREEFORM
if "analyst" in kind: if "analyst" in kind:
return system_prompts.ANALYST return system_prompts.ANALYST
if "analyze" in kind: if "analyze" in kind:
@@ -181,6 +194,10 @@ class ClientBase:
id=self.name, id=self.name,
details=model_name, details=model_name,
status=status, status=status,
data={
"prompt_template_example": self.prompt_template_example(),
"has_prompt_template": self.has_prompt_template(),
}
) )
if status_change: if status_change:
@@ -244,6 +261,10 @@ class ClientBase:
fn_tune_kind = getattr(self, f"tune_prompt_parameters_{kind}", None) fn_tune_kind = getattr(self, f"tune_prompt_parameters_{kind}", None)
if fn_tune_kind: if fn_tune_kind:
fn_tune_kind(parameters) fn_tune_kind(parameters)
agent_context = active_agent.get()
if agent_context.agent:
agent_context.agent.inject_prompt_paramters(parameters, kind, agent_context.action)
def tune_prompt_parameters_conversation(self, parameters:dict): def tune_prompt_parameters_conversation(self, parameters:dict):
conversation_context = client_context_attribute("conversation") conversation_context = client_context_attribute("conversation")
@@ -275,7 +296,7 @@ class ClientBase:
return "" return ""
async def send_prompt( async def send_prompt(
self, prompt: str, kind: str = "conversation", finalize: Callable = lambda x: x self, prompt: str, kind: str = "conversation", finalize: Callable = lambda x: x, retries:int=2
) -> str: ) -> str:
""" """
Send a prompt to the AI and return its response. Send a prompt to the AI and return its response.
@@ -298,8 +319,14 @@ class ClientBase:
time_start = time.time() time_start = time.time()
extra_stopping_strings = prompt_param.pop("extra_stopping_strings", []) extra_stopping_strings = prompt_param.pop("extra_stopping_strings", [])
self.log.debug("send_prompt", token_length=token_length, max_token_length=self.max_token_length, parameters=prompt_param) self.log.debug("send_prompt", token_length=token_length, max_token_length=self.max_token_length, parameters=prompt_param)
response = await self.generate(finalized_prompt, prompt_param, kind) response = await self.generate(
self.repetition_adjustment(finalized_prompt),
prompt_param,
kind
)
response, finalized_prompt = await self.auto_break_repetition(finalized_prompt, prompt_param, response, kind, retries)
time_end = time.time() time_end = time.time()
@@ -325,6 +352,125 @@ class ClientBase:
finally: finally:
self.emit_status(processing=False) self.emit_status(processing=False)
async def auto_break_repetition(
self,
finalized_prompt:str,
prompt_param:dict,
response:str,
kind:str,
retries:int,
pad_max_tokens:int=32,
) -> str:
"""
If repetition breaking is enabled, this will retry the prompt if its
response is too similar to other messages in the prompt
This requires the agent to have the allow_repetition_break method
and the jiggle_enabled_for method and the client to have the
auto_break_repetition_enabled attribute set to True
Arguments:
- finalized_prompt: the prompt that was sent
- prompt_param: the parameters that were used
- response: the response that was received
- kind: the kind of generation
- retries: the number of retries left
- pad_max_tokens: increase response max_tokens by this amount per iteration
Returns:
- the response
"""
if not self.auto_break_repetition_enabled:
return response, finalized_prompt
agent_context = active_agent.get()
if self.jiggle_enabled_for(kind, auto=True):
# check if the response is a repetition
# using the default similarity threshold of 98, meaning it needs
# to be really similar to be considered a repetition
is_repetition, similarity_score, matched_line = util.similarity_score(
response,
finalized_prompt.split("\n"),
)
if not is_repetition:
# not a repetition, return the response
self.log.debug("send_prompt no similarity", similarity_score=similarity_score)
return response, finalized_prompt
while is_repetition and retries > 0:
# it's a repetition, retry the prompt with adjusted parameters
self.log.warn(
"send_prompt similarity retry",
agent=agent_context.agent.agent_type,
similarity_score=similarity_score,
retries=retries
)
# first we apply the client's randomness jiggle which will adjust
# parameters like temperature and repetition_penalty, depending
# on the client
#
# this is a cumulative adjustment, so it will add to the previous
# iteration's adjustment, this also means retries should be kept low
# otherwise it will get out of hand and start generating nonsense
self.jiggle_randomness(prompt_param, offset=0.5)
# then we pad the max_tokens by the pad_max_tokens amount
prompt_param["max_tokens"] += pad_max_tokens
# send the prompt again
# we use the repetition_adjustment method to further encourage
# the AI to break the repetition on its own as well.
finalized_prompt = self.repetition_adjustment(finalized_prompt, is_repetitive=True)
response = retried_response = await self.generate(
finalized_prompt,
prompt_param,
kind
)
self.log.debug("send_prompt dedupe sentences", response=response, matched_line=matched_line)
# a lot of the times the response will now contain the repetition + something new
# so we dedupe the response to remove the repetition on sentences level
response = util.dedupe_sentences(response, matched_line, similarity_threshold=85, debug=True)
self.log.debug("send_prompt dedupe sentences (after)", response=response)
# deduping may have removed the entire response, so we check for that
if not util.strip_partial_sentences(response).strip():
# if the response is empty, we set the response to the original
# and try again next loop
response = retried_response
# check if the response is a repetition again
is_repetition, similarity_score, matched_line = util.similarity_score(
response,
finalized_prompt.split("\n"),
)
retries -= 1
return response, finalized_prompt
def count_tokens(self, content:str): def count_tokens(self, content:str):
return util.count_tokens(content) return util.count_tokens(content)
@@ -338,12 +484,35 @@ class ClientBase:
min_offset = offset * 0.3 min_offset = offset * 0.3
prompt_config["temperature"] = random.uniform(temp + min_offset, temp + offset) prompt_config["temperature"] = random.uniform(temp + min_offset, temp + offset)
def jiggle_enabled_for(self, kind:str): def jiggle_enabled_for(self, kind:str, auto:bool=False) -> bool:
if kind in ["conversation", "story"]: agent_context = active_agent.get()
return True agent = agent_context.agent
if kind.startswith("narrate"): if not agent:
return True return False
return False return agent.allow_repetition_break(kind, agent_context.action, auto=auto)
def repetition_adjustment(self, prompt:str, is_repetitive:bool=False):
"""
Breaks the prompt into lines and checkse each line for a match with
[$REPETITION|{repetition_adjustment}].
On match and if is_repetitive is True, the line is removed from the prompt and
replaced with the repetition_adjustment.
On match and if is_repetitive is False, the line is removed from the prompt.
"""
lines = prompt.split("\n")
new_lines = []
for line in lines:
if line.startswith("[$REPETITION|"):
if is_repetitive:
new_lines.append(line.split("|")[1][:-1])
else:
new_lines.append(line)
return "\n".join(new_lines)

View File

@@ -39,6 +39,9 @@ class ModelPrompt:
"set_response" : self.set_response "set_response" : self.set_response
}) })
def exists(self, model_name:str):
return bool(self.get_template(model_name))
def set_response(self, prompt:str, response_str:str): def set_response(self, prompt:str, response_str:str):
prompt = prompt.strip("\n").strip() prompt = prompt.strip("\n").strip()

View File

@@ -6,7 +6,10 @@ from openai import AsyncOpenAI
from talemate.client.base import ClientBase from talemate.client.base import ClientBase
from talemate.client.registry import register from talemate.client.registry import register
from talemate.emit import emit from talemate.emit import emit
from talemate.emit.signals import handlers
import talemate.emit.async_signals as async_signals
from talemate.config import load_config from talemate.config import load_config
import talemate.instance as instance
import talemate.client.system_prompts as system_prompts import talemate.client.system_prompts as system_prompts
import structlog import structlog
import tiktoken import tiktoken
@@ -75,39 +78,40 @@ class OpenAIClient(ClientBase):
client_type = "openai" client_type = "openai"
conversation_retries = 0 conversation_retries = 0
auto_break_repetition_enabled = False
def __init__(self, model="gpt-4-1106-preview", **kwargs): def __init__(self, model="gpt-4-1106-preview", **kwargs):
self.model_name = model self.model_name = model
self.api_key_status = None
self.config = load_config() self.config = load_config()
super().__init__(**kwargs) super().__init__(**kwargs)
# if os.environ.get("OPENAI_API_KEY") is not set, look in the config file
# and set it
if not os.environ.get("OPENAI_API_KEY"):
if self.config.get("openai", {}).get("api_key"):
os.environ["OPENAI_API_KEY"] = self.config["openai"]["api_key"]
self.set_client() self.set_client()
handlers["config_saved"].connect(self.on_config_saved)
@property @property
def openai_api_key(self): def openai_api_key(self):
return os.environ.get("OPENAI_API_KEY") return self.config.get("openai",{}).get("api_key")
def emit_status(self, processing: bool = None): def emit_status(self, processing: bool = None):
if processing is not None: if processing is not None:
self.processing = processing self.processing = processing
if os.environ.get("OPENAI_API_KEY"): if self.openai_api_key:
status = "busy" if self.processing else "idle" status = "busy" if self.processing else "idle"
model_name = self.model_name or "No model loaded" model_name = self.model_name
else: else:
status = "error" status = "error"
model_name = "No API key set" model_name = "No API key set"
if not self.model_name:
status = "error"
model_name = "No model loaded"
self.current_status = status self.current_status = status
emit( emit(
@@ -121,12 +125,17 @@ class OpenAIClient(ClientBase):
def set_client(self, max_token_length:int=None): def set_client(self, max_token_length:int=None):
if not self.openai_api_key: if not self.openai_api_key:
self.client = AsyncOpenAI(api_key="sk-1111")
log.error("No OpenAI API key set") log.error("No OpenAI API key set")
if self.api_key_status:
self.api_key_status = False
emit('request_client_status')
emit('request_agent_status')
return return
model = self.model_name model = self.model_name
self.client = AsyncOpenAI() self.client = AsyncOpenAI(api_key=self.openai_api_key)
if model == "gpt-3.5-turbo": if model == "gpt-3.5-turbo":
self.max_token_length = min(max_token_length or 4096, 4096) self.max_token_length = min(max_token_length or 4096, 4096)
elif model == "gpt-4": elif model == "gpt-4":
@@ -138,12 +147,27 @@ class OpenAIClient(ClientBase):
else: else:
self.max_token_length = max_token_length or 2048 self.max_token_length = max_token_length or 2048
if not self.api_key_status:
if self.api_key_status is False:
emit('request_client_status')
emit('request_agent_status')
self.api_key_status = True
log.info("openai set client")
def reconfigure(self, **kwargs): def reconfigure(self, **kwargs):
if "model" in kwargs: if "model" in kwargs:
self.model_name = kwargs["model"] self.model_name = kwargs["model"]
self.set_client(kwargs.get("max_token_length")) self.set_client(kwargs.get("max_token_length"))
def on_config_saved(self, event):
config = event.data
self.config = config
self.set_client()
def count_tokens(self, content: str): def count_tokens(self, content: str):
if not self.model_name:
return 0
return num_tokens_from_messages([{"content": content}], model=self.model_name) return num_tokens_from_messages([{"content": content}], model=self.model_name)
async def status(self): async def status(self):
@@ -179,6 +203,9 @@ class OpenAIClient(ClientBase):
Generates text from the given prompt and parameters. Generates text from the given prompt and parameters.
""" """
if not self.openai_api_key:
raise Exception("No OpenAI API key set")
# only gpt-4-1106-preview supports json_object response coersion # only gpt-4-1106-preview supports json_object response coersion
supports_json_object = self.model_name in ["gpt-4-1106-preview"] supports_json_object = self.model_name in ["gpt-4-1106-preview"]
right = None right = None
@@ -187,7 +214,7 @@ class OpenAIClient(ClientBase):
expected_response = right.strip() expected_response = right.strip()
if expected_response.startswith("{") and supports_json_object: if expected_response.startswith("{") and supports_json_object:
parameters["response_format"] = {"type": "json_object"} parameters["response_format"] = {"type": "json_object"}
except IndexError: except (IndexError, ValueError):
pass pass
human_message = {'role': 'user', 'content': prompt.strip()} human_message = {'role': 'user', 'content': prompt.strip()}
@@ -208,5 +235,4 @@ class OpenAIClient(ClientBase):
return response return response
except Exception as e: except Exception as e:
self.log.error("generate error", e=e) raise
return ""

View File

@@ -6,6 +6,8 @@ import os
from pydantic import BaseModel from pydantic import BaseModel
from typing import Optional, Dict, Union from typing import Optional, Dict, Union
from talemate.emit import emit
log = structlog.get_logger("talemate.config") log = structlog.get_logger("talemate.config")
class Client(BaseModel): class Client(BaseModel):
@@ -20,7 +22,7 @@ class Client(BaseModel):
class AgentActionConfig(BaseModel): class AgentActionConfig(BaseModel):
value: Union[int, float, str, bool] value: Union[int, float, str, bool, None] = None
class AgentAction(BaseModel): class AgentAction(BaseModel):
enabled: bool = True enabled: bool = True
@@ -42,17 +44,17 @@ class Agent(BaseModel):
return super().model_dump(exclude_none=True) return super().model_dump(exclude_none=True)
class GamePlayerCharacter(BaseModel): class GamePlayerCharacter(BaseModel):
name: str name: str = ""
color: str color: str = "#3362bb"
gender: str gender: str = ""
description: Optional[str] description: Optional[str] = ""
class Config: class Config:
extra = "ignore" extra = "ignore"
class Game(BaseModel): class Game(BaseModel):
default_player_character: GamePlayerCharacter default_player_character: GamePlayerCharacter = GamePlayerCharacter()
class Config: class Config:
extra = "ignore" extra = "ignore"
@@ -68,6 +70,7 @@ class RunPodConfig(BaseModel):
class ElevenLabsConfig(BaseModel): class ElevenLabsConfig(BaseModel):
api_key: Union[str,None]=None api_key: Union[str,None]=None
model: str = "eleven_turbo_v2"
class CoquiConfig(BaseModel): class CoquiConfig(BaseModel):
api_key: Union[str,None]=None api_key: Union[str,None]=None
@@ -157,4 +160,6 @@ def save_config(config, file_path: str = "./config.yaml"):
return None return None
with open(file_path, "w") as file: with open(file_path, "w") as file:
yaml.dump(config, file) yaml.dump(config, file)
emit("config_saved", data=config)

View File

@@ -13,7 +13,9 @@ RequestInput = signal("request_input")
ReceiveInput = signal("receive_input") ReceiveInput = signal("receive_input")
ClientStatus = signal("client_status") ClientStatus = signal("client_status")
RequestClientStatus = signal("request_client_status")
AgentStatus = signal("agent_status") AgentStatus = signal("agent_status")
RequestAgentStatus = signal("request_agent_status")
ClientBootstraps = signal("client_bootstraps") ClientBootstraps = signal("client_bootstraps")
PromptSent = signal("prompt_sent") PromptSent = signal("prompt_sent")
@@ -28,6 +30,8 @@ AudioQueue = signal("audio_queue")
MessageEdited = signal("message_edited") MessageEdited = signal("message_edited")
ConfigSaved = signal("config_saved")
handlers = { handlers = {
"system": SystemMessage, "system": SystemMessage,
"narrator": NarratorMessage, "narrator": NarratorMessage,
@@ -38,7 +42,9 @@ handlers = {
"request_input": RequestInput, "request_input": RequestInput,
"receive_input": ReceiveInput, "receive_input": ReceiveInput,
"client_status": ClientStatus, "client_status": ClientStatus,
"request_client_status": RequestClientStatus,
"agent_status": AgentStatus, "agent_status": AgentStatus,
"request_agent_status": RequestAgentStatus,
"client_bootstraps": ClientBootstraps, "client_bootstraps": ClientBootstraps,
"clear_screen": ClearScreen, "clear_screen": ClearScreen,
"remove_message": RemoveMessage, "remove_message": RemoveMessage,
@@ -49,4 +55,5 @@ handlers = {
"message_edited": MessageEdited, "message_edited": MessageEdited,
"prompt_sent": PromptSent, "prompt_sent": PromptSent,
"audio_queue": AudioQueue, "audio_queue": AudioQueue,
"config_saved": ConfigSaved,
} }

View File

@@ -1,10 +1,11 @@
""" """
Keep track of clients and agents Keep track of clients and agents
""" """
import asyncio
import talemate.agents as agents import talemate.agents as agents
import talemate.client as clients import talemate.client as clients
from talemate.emit import emit from talemate.emit import emit
from talemate.emit.signals import handlers
import talemate.client.bootstrap as bootstrap import talemate.client.bootstrap as bootstrap
import structlog import structlog
@@ -14,6 +15,8 @@ AGENTS = {}
CLIENTS = {} CLIENTS = {}
def get_agent(typ: str, *create_args, **create_kwargs): def get_agent(typ: str, *create_args, **create_kwargs):
agent = AGENTS.get(typ) agent = AGENTS.get(typ)
@@ -94,11 +97,19 @@ async def emit_clients_status():
""" """
Will emit status of all clients Will emit status of all clients
""" """
#log.debug("emit", type="client status")
for client in CLIENTS.values(): for client in CLIENTS.values():
if client: if client:
await client.status() await client.status()
def _sync_emit_clients_status(*args, **kwargs):
"""
Will emit status of all clients
in synchronous mode
"""
loop = asyncio.get_event_loop()
loop.run_until_complete(emit_clients_status())
handlers["request_client_status"].connect(_sync_emit_clients_status)
def emit_client_bootstraps(): def emit_client_bootstraps():
emit( emit(
@@ -144,11 +155,13 @@ def emit_agent_status(cls, agent=None):
) )
def emit_agents_status(): def emit_agents_status(*args, **kwargs):
""" """
Will emit status of all agents Will emit status of all agents
""" """
#log.debug("emit", type="agent status")
for typ, cls in agents.AGENT_CLASSES.items(): for typ, cls in agents.AGENT_CLASSES.items():
agent = AGENTS.get(typ) agent = AGENTS.get(typ)
emit_agent_status(cls, agent) emit_agent_status(cls, agent)
handlers["request_agent_status"].connect(emit_agents_status)

View File

@@ -343,7 +343,7 @@ class Prompt:
parsed_text = env.from_string(prompt_text).render(self.vars) parsed_text = env.from_string(prompt_text).render(self.vars)
if self.dedupe_enabled: if self.dedupe_enabled:
parsed_text = dedupe_string(parsed_text, debug=True) parsed_text = dedupe_string(parsed_text, debug=False)
parsed_text = remove_extra_linebreaks(parsed_text) parsed_text = remove_extra_linebreaks(parsed_text)
@@ -395,7 +395,7 @@ class Prompt:
f"Answer: " + loop.run_until_complete(memory.query(query, **kwargs)), f"Answer: " + loop.run_until_complete(memory.query(query, **kwargs)),
]) ])
else: else:
return loop.run_until_complete(memory.multi_query(query.split("\n"), **kwargs)) return loop.run_until_complete(memory.multi_query([q for q in query.split("\n") if q.strip()], **kwargs))
def instruct_text(self, instruction:str, text:str): def instruct_text(self, instruction:str, text:str):
loop = asyncio.get_event_loop() loop = asyncio.get_event_loop()
@@ -516,7 +516,7 @@ class Prompt:
log.warning("parse_json_response error on first attempt - sending to AI to fix", response=response, error=e) log.warning("parse_json_response error on first attempt - sending to AI to fix", response=response, error=e)
fixed_response = await self.client.send_prompt( fixed_response = await self.client.send_prompt(
f"fix the syntax errors in this JSON string, but keep the structure as is.\n\nError:{e}\n\n```json\n{response}\n```<|BOT|>"+"{", f"fix the syntax errors in this JSON string, but keep the structure as is. Remove any comments.\n\nError:{e}\n\n```json\n{response}\n```<|BOT|>"+"{",
kind="analyze_long", kind="analyze_long",
) )
log.warning("parse_json_response error on first attempt - sending to AI to fix", response=response, error=e) log.warning("parse_json_response error on first attempt - sending to AI to fix", response=response, error=e)

View File

@@ -33,8 +33,7 @@ You may chose to have {{ talking_character.name}} respond to the conversation, o
Use an informal and colloquial register with a conversational tone. Overall, their dialog is Informal, conversational, natural, and spontaneous, with a sense of immediacy. Use an informal and colloquial register with a conversational tone. Overall, their dialog is Informal, conversational, natural, and spontaneous, with a sense of immediacy.
Spoken word should be enclosed in double quotes, e.g. "Hello, how are you?" Spoken words MUST be enclosed in double quotes, e.g. {{ talking_character.name}}: "spoken words.".
Narration and actions should be enclosed in asterisks, e.g. *She smiles.*
{{ extra_instructions }} {{ extra_instructions }}
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
{% if memory -%} {% if memory -%}

View File

@@ -8,12 +8,19 @@ Scenario Premise: {{ scene.description }}
{% endfor %} {% endfor %}
{% endblock -%} {% endblock -%}
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
{% for scene_context in scene.context_history(budget=max_tokens-200-count_tokens(self.rendered_context())) -%} {% for scene_context in scene.context_history(budget=max_tokens-200-count_tokens(self.rendered_context()), min_dialogue=25) -%}
{{ scene_context }} {{ scene_context }}
{% endfor %} {% endfor %}
<|SECTION:TASK|> <|SECTION:TASK|>
Based on the previous line '{{ last_line }}', create the next line of narration. This line should focus solely on describing sensory details (like sounds, sights, smells, tactile sensations) or external actions that move the story forward. Avoid including any character's internal thoughts, feelings, or dialogue. Your narration should directly respond to '{{ last_line }}', either by elaborating on the immediate scene or by subtly advancing the plot. Generate exactly one sentence of new narration. If the character is trying to determine some state, truth or situation, try to answer as part of the narration. Based on the previous line '{{ last_line }}', create the next line of narration. This line should focus solely on describing sensory details (like sounds, sights, smells, tactile sensations) or external actions that move the story forward. Avoid including any character's internal thoughts, feelings, or dialogue. Your narration should directly respond to '{{ last_line }}', either by elaborating on the immediate scene or by subtly advancing the plot. Generate exactly one sentence of new narration. If the character is trying to determine some state, truth or situation, try to answer as part of the narration.
Be creative and generate something new and interesting, but stay true to the setting and context of the story so far. Be creative and generate something new and interesting, but stay true to the setting and context of the story so far.
Use an informal and colloquial register with a conversational tone. Overall, the narrative is Informal, conversational, natural, and spontaneous, with a sense of immediacy.
Narration style should be that of a 90s point and click adventure game. You are omniscient and can describe the scene in detail.
Only generate new narration. {{ extra_instructions }}
[$REPETITION|Narration is getting repetitive. Try to choose different words to break up the repetitive text.]
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
{{ set_prepared_response('*') }} {{ set_prepared_response('*') }}

View File

@@ -8,23 +8,23 @@ Last time we checked on {{ character.name }}:
{% endfor %} {% endfor %}
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
{% for scene_context in scene.context_history(budget=max_tokens-300, min_dialogue=30) -%} {% for scene_context in scene.context_history(budget=max_tokens-300, min_dialogue=20) -%}
{{ scene_context }} {{ scene_context }}
{% endfor %} {% endfor %}
<|SECTION:INFORMATION|> <|SECTION:INFORMATION|>
{{ query_memory("How old is {character.name}?") }} {{ query_memory("How old is {character.name}?") }}
{{ query_scene("Where is {character.name}?") }} {{ query_scene("Where is {character.name} and what is {character.name} doing?") }}
{{ query_scene("what is {character.name} doing?") }} {{ query_scene("what is {character.name} wearing? Be explicit.") }}
{{ query_scene("what is {character.name} wearing?") }}
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
<|SECTION:TASK|> <|SECTION:TASK|>
Last line of dialogue: {{ scene.history[-1] }} Last line of dialogue: {{ scene.history[-1] }}
Questions: Where is {{ character.name}} currently and what are they doing? What is {{ character.name }}'s appearance at the end of the dialogue? What is {{ character.pronoun_2 }} wearing? What position is {{ character.pronoun_2 }} in? Questions: Where is {{ character.name}} currently and what are they doing? What is {{ character.name }}'s appearance at the end of the dialogue? What is {{ character.pronoun_2 }} wearing? What position is {{ character.pronoun_2 }} in?
Instruction: Answer the questions to describe {{ character.name }}'s appearance at the end of the dialogue and summarize into narrative description. Use the whole dialogue for context. Instruction: Answer the questions to describe {{ character.name }}'s appearance at the end of the dialogue and summarize into narrative description. Use the whole dialogue for context. You must fill in gaps using imagination as long as it fits the existing context. You will provide a confident and decisive answer to the question.
Content Context: This is a specific scene from {{ scene.context }} Content Context: This is a specific scene from {{ scene.context }}
Narration style: point and click adventure game from the 90s Narration style: point and click adventure game from the 90s
Expected Answer: A summarized visual description of {{ character.name }}'s appearance at the dialogue. Expected Answer: A brief summarized visual description of {{ character.name }}'s appearance at the end of the dialogue. NEVER break the fourth wall. (2 to 3 sentences)
{{ extra_instructions }}
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
Narrator answers: {{ bot_token }}At the end of the dialogue, {{ bot_token }}At the end of the dialogue,

View File

@@ -1,3 +1,4 @@
{% block extra_context -%}
<|SECTION:CONTEXT|> <|SECTION:CONTEXT|>
Scenario Premise: {{ scene.description }} Scenario Premise: {{ scene.description }}
@@ -9,19 +10,24 @@ NPCs: {{ npc_names }}
Player Character: {{ player_character.name }} Player Character: {{ player_character.name }}
Content Context: {{ scene.context }} Content Context: {{ scene.context }}
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
{% endblock -%}
{% for scene_context in scene.context_history(budget=max_tokens-300, min_dialogue=30, sections=False, dialogue_negative_offset=10) -%} {% for scene_context in scene.context_history(budget=max_tokens-300, min_dialogue=20, sections=False) -%}
{{ scene_context }} {{ scene_context }}
{% endfor %} {% endfor %}
<|SECTION:TASK|> <|SECTION:TASK|>
Continue the current dialogue by narrating the progression of the scene Continue the current dialogue by narrating the progression of the scene.
Narration style: point and click adventure game from the 90s
If the scene is over, narrate the beginning of the next scene. If the scene is over, narrate the beginning of the next scene.
Be creative and generate something new and interesting, but stay true to the setting and context of the story so far.
Use an informal and colloquial register with a conversational tone. Overall, the narrative is informal, conversational, natural, and spontaneous, with a sense of immediacy.
Narration style should be that of a 90s point and click adventure game. You are omniscient and can describe the scene in detail.
Only generate new narration. Avoid including any character's internal thoughts or dialogue.
Write 2 to 4 sentences. {{ extra_instructions }}
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
{{ bot_token }}
{% for row in scene.history[-10:] -%}
{{ row }}
{% endfor %}
{{ {{
set_prepared_response_random( set_prepared_response_random(
npc_names.split(", ") + [ npc_names.split(", ") + [

View File

@@ -6,15 +6,22 @@
{% endfor %} {% endfor %}
<|SECTION:TASK|> <|SECTION:TASK|>
{% if query.endswith("?") -%} {% if query.endswith("?") -%}
Question: {{ query }}
Extra context: {{ query_memory(query, as_question_answer=False) }} Extra context: {{ query_memory(query, as_question_answer=False) }}
Instruction: Analyze Context, History and Dialogue. When evaluating both story and memory, story is more important. You can fill in gaps using imagination as long as it is based on the existing context. Respect the scene progression and answer in the context of the end of the dialogue. Instruction: Analyze Context, History and Dialogue and then answer the question: "{{ query }}".
When evaluating both story and context, story is more important. You can fill in gaps using imagination as long as it is based on the existing context.
Respect the scene progression and answer in the context of the end of the dialogue.
Use your imagination to fill in gaps in order to answer the question in a confident and decisive manner. Avoid uncertainty and vagueness.
{% else -%} {% else -%}
Instruction: {{ query }} Instruction: {{ query }}
Extra context: {{ query_memory(query, as_question_answer=False) }} Extra context: {{ query_memory(query, as_question_answer=False) }}
Answer based on Context, History and Dialogue. When evaluating both story and memory, story is more important. You can fill in gaps using imagination as long as it is based on the existing context. Answer based on Context, History and Dialogue.
When evaluating both story and context, story is more important. You can fill in gaps using imagination as long as it is based on the existing context.
{% endif -%} {% endif -%}
Content Context: This is a specific scene from {{ scene.context }} Content Context: This is a specific scene from {{ scene.context }}
Your answer should be in the style of short narration that fits the context of the scene. Your answer should be in the style of short, concise narration that fits the context of the scene. (1 to 2 sentences)
{{ extra_instructions }}
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
Narrator answers: {% if at_the_end %}{{ bot_token }}At the end of the dialogue, {% endif %} {% if at_the_end %}{{ bot_token }}At the end of the dialogue, {% endif %}

View File

@@ -8,5 +8,6 @@ Scenario Premise: {{ scene.description }}
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
<|SECTION:TASK|> <|SECTION:TASK|>
Provide a visual description of what is currently happening in the scene. Don't progress the scene. Provide a visual description of what is currently happening in the scene. Don't progress the scene.
{{ extra_instructions }}
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
{{ bot_token }}At the end of the scene we currently see: {{ bot_token }}At the end of the scene we currently see:

View File

@@ -12,5 +12,6 @@ Content Context: {{ scene.context }}
<|SECTION:TASK|> <|SECTION:TASK|>
Narrate the passage of time that just occured, subtly move the story forward, and set up the next scene. Narrate the passage of time that just occured, subtly move the story forward, and set up the next scene.
Write 1 to 3 sentences. Write 1 to 3 sentences.
{{ extra_instructions }}
<|CLOSE_SECTION|> <|CLOSE_SECTION|>
{{ bot_token }}{{ narrative }}: {{ bot_token }}{{ narrative }}:

View File

@@ -1,6 +1,6 @@
{% set questions = instruct_text("Ask the narrator three (3) questions to gather more context from the past for the continuation of this conversation. If a character is asking about a state, location or information about an item or another character, make sure to include question(s) that help gather context for this.", text) %}
<|SECTION:CONTEXT|> <|SECTION:CONTEXT|>
{% for memory in query_memory(text, as_question_answer=False, max_tokens=max_tokens-500, iterate=20) -%} {% for memory in query_memory(questions, as_question_answer=False, max_tokens=max_tokens-500, iterate=10) -%}
{{ memory }} {{ memory }}
{% endfor -%} {% endfor -%}
@@ -8,7 +8,7 @@
<|SECTION:TASK|> <|SECTION:TASK|>
Answer the following questions: Answer the following questions:
{{ instruct_text("Ask the narrator three (3) questions to gather more context from the past for the continuation of this conversation. If a character is asking about a state, location or information about an item or another character, make sure to include question(s) that help gather context for this.", text) }} {{ questions }}
You answers should be precise, truthful and short. Pay close attention to timestamps when retrieving information from the context. You answers should be precise, truthful and short. Pay close attention to timestamps when retrieving information from the context.

View File

@@ -1 +1 @@
Instructions for a talented story analyst. The analyst will analyze parts of a story or dialogue and give truthful answers based on the dialogue or events given to him. The analyst will never make up facts or lie in his answers and will use crude, lewd and strong language if the content requires it. Instructions for a talented story analyst. The analyst will analyze parts of a story or dialogue and give truthful answers based on the dialogue or events given to him. The analyst will never make up facts or lie in his answers and will use crude, lewd and strong language if the context requires it.

View File

@@ -56,7 +56,7 @@ async def websocket_endpoint(websocket, path):
await instance.sync_client_bootstraps() await instance.sync_client_bootstraps()
except Exception as e: except Exception as e:
log.error("send_client_bootstraps", error=e, traceback=traceback.format_exc()) log.error("send_client_bootstraps", error=e, traceback=traceback.format_exc())
await asyncio.sleep(60) await asyncio.sleep(15)
send_client_bootstraps_task = asyncio.create_task(send_client_bootstraps()) send_client_bootstraps_task = asyncio.create_task(send_client_bootstraps())

View File

@@ -1,5 +1,6 @@
import pydantic import pydantic
import structlog import structlog
from talemate import VERSION
from talemate.config import Config as AppConfigData, load_config, save_config from talemate.config import Config as AppConfigData, load_config, save_config
@@ -8,6 +9,12 @@ log = structlog.get_logger("talemate.server.config")
class ConfigPayload(pydantic.BaseModel): class ConfigPayload(pydantic.BaseModel):
config: AppConfigData config: AppConfigData
class DefaultCharacterPayload(pydantic.BaseModel):
name: str
gender: str
description: str
color: str = "#3362bb"
class ConfigPlugin: class ConfigPlugin:
router = "config" router = "config"
@@ -36,8 +43,38 @@ class ConfigPlugin:
save_config(current_config) save_config(current_config)
self.websocket_handler.config = current_config self.websocket_handler.config = current_config
self.websocket_handler.queue_put({
"type": "app_config",
"data": load_config(),
"version": VERSION
})
self.websocket_handler.queue_put({ self.websocket_handler.queue_put({
"type": "config", "type": "config",
"action": "save_complete", "action": "save_complete",
}) })
async def handle_save_default_character(self, data):
log.info("Saving default character", data=data["data"])
payload = DefaultCharacterPayload(**data["data"])
current_config = load_config()
current_config["game"]["default_player_character"] = payload.model_dump()
log.info("Saving default character", character=current_config["game"]["default_player_character"])
save_config(current_config)
self.websocket_handler.config = current_config
self.websocket_handler.queue_put({
"type": "app_config",
"data": load_config(),
"version": VERSION
})
self.websocket_handler.queue_put({
"type": "config",
"action": "save_default_character_complete",
})

View File

@@ -6,10 +6,11 @@ import textwrap
import structlog import structlog
import isodate import isodate
import datetime import datetime
from typing import List from typing import List, Union
from thefuzz import fuzz from thefuzz import fuzz
from colorama import Back, Fore, Style, init from colorama import Back, Fore, Style, init
from PIL import Image from PIL import Image
from nltk.tokenize import sent_tokenize
from talemate.scene_message import SceneMessage from talemate.scene_message import SceneMessage
log = structlog.get_logger("talemate.util") log = structlog.get_logger("talemate.util")
@@ -497,13 +498,9 @@ def duration_to_timedelta(duration):
if isinstance(duration, datetime.timedelta): if isinstance(duration, datetime.timedelta):
return duration return duration
# Check if the duration is an isodate.Duration object with a tdelta attribute
if hasattr(duration, 'tdelta'):
return duration.tdelta
# If it's an isodate.Duration object with separate year, month, day, hour, minute, second attributes # If it's an isodate.Duration object with separate year, month, day, hour, minute, second attributes
days = int(duration.years) * 365 + int(duration.months) * 30 + int(duration.days) days = int(duration.years) * 365 + int(duration.months) * 30 + int(duration.days)
seconds = int(duration.hours) * 3600 + int(duration.minutes) * 60 + int(duration.seconds) seconds = duration.tdelta.seconds
return datetime.timedelta(days=days, seconds=seconds) return datetime.timedelta(days=days, seconds=seconds)
def timedelta_to_duration(delta): def timedelta_to_duration(delta):
@@ -737,12 +734,91 @@ def extract_json(s):
json_object = json.loads(json_string) json_object = json.loads(json_string)
return json_string, json_object return json_string, json_object
def similarity_score(line: str, lines: list[str], similarity_threshold: int = 95) -> tuple[bool, int, str]:
"""
Checks if a line is similar to any of the lines in the list of lines.
Arguments:
line (str): The line to check.
lines (list): The list of lines to check against.
threshold (int): The similarity threshold to use when comparing lines.
Returns:
bool: Whether a similar line was found.
int: The similarity score of the line. If no similar line was found, the highest similarity score is returned.
str: The similar line that was found. If no similar line was found, None is returned.
"""
highest_similarity = 0
for existing_line in lines:
similarity = fuzz.ratio(line, existing_line)
highest_similarity = max(highest_similarity, similarity)
#print("SIMILARITY", similarity, existing_line[:32]+"...")
if similarity >= similarity_threshold:
return True, similarity, existing_line
return False, highest_similarity, None
def dedupe_sentences(line_a:str, line_b:str, similarity_threshold:int=95, debug:bool=False, split_on_comma:bool=True) -> str:
"""
Will split both lines into sentences and then compare each sentence in line_a
against similar sentences in line_b. If a similar sentence is found, it will be
removed from line_a.
The similarity threshold is used to determine if two sentences are similar.
Arguments:
line_a (str): The first line.
line_b (str): The second line.
similarity_threshold (int): The similarity threshold to use when comparing sentences.
debug (bool): Whether to log debug messages.
split_on_comma (bool): Whether to split line_b sentences on commas as well.
Returns:
str: the cleaned line_a.
"""
line_a_sentences = sent_tokenize(line_a)
line_b_sentences = sent_tokenize(line_b)
cleaned_line_a_sentences = []
if split_on_comma:
# collect all sentences from line_b that contain a comma
line_b_sentences_with_comma = []
for line_b_sentence in line_b_sentences:
if "," in line_b_sentence:
line_b_sentences_with_comma.append(line_b_sentence)
# then split all sentences in line_b_sentences_with_comma on the comma
# and extend line_b_sentences with the split sentences, making sure
# to strip whitespace from the beginning and end of each sentence
for line_b_sentence in line_b_sentences_with_comma:
line_b_sentences.extend([s.strip() for s in line_b_sentence.split(",")])
for line_a_sentence in line_a_sentences:
similar_found = False
for line_b_sentence in line_b_sentences:
similarity = fuzz.ratio(line_a_sentence, line_b_sentence)
if similarity >= similarity_threshold:
if debug:
log.debug("DEDUPE SENTENCE", similarity=similarity, line_a_sentence=line_a_sentence, line_b_sentence=line_b_sentence)
similar_found = True
break
if not similar_found:
cleaned_line_a_sentences.append(line_a_sentence)
return " ".join(cleaned_line_a_sentences)
def dedupe_string(s: str, min_length: int = 32, similarity_threshold: int = 95, debug: bool = False) -> str: def dedupe_string(s: str, min_length: int = 32, similarity_threshold: int = 95, debug: bool = False) -> str:
""" """
Removes duplicate lines from a string. Removes duplicate lines from a string.
Parameters: Arguments:
s (str): The input string. s (str): The input string.
min_length (int): The minimum length of a line to be checked for duplicates. min_length (int): The minimum length of a line to be checked for duplicates.
similarity_threshold (int): The similarity threshold to use when comparing lines. similarity_threshold (int): The similarity threshold to use when comparing lines.
@@ -861,6 +937,15 @@ def ensure_dialog_line_format(line:str):
elif segment_open is not None and segment_open != c: elif segment_open is not None and segment_open != c:
# open segment is not the same as the current character # open segment is not the same as the current character
# opening - close the current segment and open a new one # opening - close the current segment and open a new one
# if we are at the last character we append the segment
if i == len(line)-1 and segment.strip():
segment += c
segments += [segment.strip()]
segment_open = None
segment = None
continue
segments += [segment.strip()] segments += [segment.strip()]
segment_open = c segment_open = c
segment = c segment = c
@@ -876,14 +961,15 @@ def ensure_dialog_line_format(line:str):
segment += c segment += c
if segment is not None: if segment is not None:
segments += [segment.strip()] if segment.strip().strip("*").strip('"'):
segments += [segment.strip()]
for i in range(len(segments)): for i in range(len(segments)):
segment = segments[i] segment = segments[i]
if segment in ['"', '*']: if segment in ['"', '*']:
if i > 0: if i > 0:
prev_segment = segments[i-1] prev_segment = segments[i-1]
if prev_segment[-1] not in ['"', '*']: if prev_segment and prev_segment[-1] not in ['"', '*']:
segments[i-1] = f"{prev_segment}{segment}" segments[i-1] = f"{prev_segment}{segment}"
segments[i] = "" segments[i] = ""
continue continue
@@ -924,4 +1010,27 @@ def ensure_dialog_line_format(line:str):
elif next_segment and next_segment[0] == '*': elif next_segment and next_segment[0] == '*':
segments[i] = f"\"{segment}\"" segments[i] = f"\"{segment}\""
return " ".join(segment for segment in segments if segment) for i in range(len(segments)):
segments[i] = clean_uneven_markers(segments[i], '"')
segments[i] = clean_uneven_markers(segments[i], '*')
return " ".join(segment for segment in segments if segment).strip()
def clean_uneven_markers(chunk:str, marker:str):
# if there is an uneven number of quotes, remove the last one if its
# at the end of the chunk. If its in the middle, add a quote to the endc
count = chunk.count(marker)
if count % 2 == 1:
if chunk.endswith(marker):
chunk = chunk[:-1]
elif chunk.startswith(marker):
chunk = chunk[1:]
elif count == 1:
chunk = chunk.replace(marker, "")
else:
chunk += marker
return chunk

View File

@@ -64,12 +64,13 @@
} }
}, },
"node_modules/@babel/code-frame": { "node_modules/@babel/code-frame": {
"version": "7.22.5", "version": "7.23.5",
"resolved": "https://registry.npmmirror.com/@babel/code-frame/-/code-frame-7.22.5.tgz", "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.23.5.tgz",
"integrity": "sha512-Xmwn266vad+6DAqEB2A6V/CcZVp62BbwVmcOJc2RPuwih1kw02TjQvWVWlcKGbBPd+8/0V5DEkOcizRGYsspYQ==", "integrity": "sha512-CgH3s1a96LipHCmSUmYFPwY7MNx8C3avkq7i4Wl3cfa662ldtUe4VM1TPXX70pfmrlWTb6jLqTYrZyT2ZTJBgA==",
"dev": true, "dev": true,
"dependencies": { "dependencies": {
"@babel/highlight": "^7.22.5" "@babel/highlight": "^7.23.4",
"chalk": "^2.4.2"
}, },
"engines": { "engines": {
"node": ">=6.9.0" "node": ">=6.9.0"
@@ -129,12 +130,12 @@
} }
}, },
"node_modules/@babel/generator": { "node_modules/@babel/generator": {
"version": "7.22.7", "version": "7.23.5",
"resolved": "https://registry.npmmirror.com/@babel/generator/-/generator-7.22.7.tgz", "resolved": "https://registry.npmjs.org/@babel/generator/-/generator-7.23.5.tgz",
"integrity": "sha512-p+jPjMG+SI8yvIaxGgeW24u7q9+5+TGpZh8/CuB7RhBKd7RCy8FayNEFNNKrNK/eUcY/4ExQqLmyrvBXKsIcwQ==", "integrity": "sha512-BPssCHrBD+0YrxviOa3QzpqwhNIXKEtOa2jQrm4FlmkC2apYgRnQcmPWiGZDlGxiNtltnUFolMe8497Esry+jA==",
"dev": true, "dev": true,
"dependencies": { "dependencies": {
"@babel/types": "^7.22.5", "@babel/types": "^7.23.5",
"@jridgewell/gen-mapping": "^0.3.2", "@jridgewell/gen-mapping": "^0.3.2",
"@jridgewell/trace-mapping": "^0.3.17", "@jridgewell/trace-mapping": "^0.3.17",
"jsesc": "^2.5.1" "jsesc": "^2.5.1"
@@ -243,22 +244,22 @@
} }
}, },
"node_modules/@babel/helper-environment-visitor": { "node_modules/@babel/helper-environment-visitor": {
"version": "7.22.5", "version": "7.22.20",
"resolved": "https://registry.npmmirror.com/@babel/helper-environment-visitor/-/helper-environment-visitor-7.22.5.tgz", "resolved": "https://registry.npmjs.org/@babel/helper-environment-visitor/-/helper-environment-visitor-7.22.20.tgz",
"integrity": "sha512-XGmhECfVA/5sAt+H+xpSg0mfrHq6FzNr9Oxh7PSEBBRUb/mL7Kz3NICXb194rCqAEdxkhPT1a88teizAFyvk8Q==", "integrity": "sha512-zfedSIzFhat/gFhWfHtgWvlec0nqB9YEIVrpuwjruLlXfUSnA8cJB0miHKwqDnQ7d32aKo2xt88/xZptwxbfhA==",
"dev": true, "dev": true,
"engines": { "engines": {
"node": ">=6.9.0" "node": ">=6.9.0"
} }
}, },
"node_modules/@babel/helper-function-name": { "node_modules/@babel/helper-function-name": {
"version": "7.22.5", "version": "7.23.0",
"resolved": "https://registry.npmmirror.com/@babel/helper-function-name/-/helper-function-name-7.22.5.tgz", "resolved": "https://registry.npmjs.org/@babel/helper-function-name/-/helper-function-name-7.23.0.tgz",
"integrity": "sha512-wtHSq6jMRE3uF2otvfuD3DIvVhOsSNshQl0Qrd7qC9oQJzHvOL4qQXlQn2916+CXGywIjpGuIkoyZRRxHPiNQQ==", "integrity": "sha512-OErEqsrxjZTJciZ4Oo+eoZqeW9UIiOcuYKRJA4ZAgV9myA+pOXhhmpfNCKjEH/auVfEYVFJ6y1Tc4r0eIApqiw==",
"dev": true, "dev": true,
"dependencies": { "dependencies": {
"@babel/template": "^7.22.5", "@babel/template": "^7.22.15",
"@babel/types": "^7.22.5" "@babel/types": "^7.23.0"
}, },
"engines": { "engines": {
"node": ">=6.9.0" "node": ">=6.9.0"
@@ -412,18 +413,18 @@
} }
}, },
"node_modules/@babel/helper-string-parser": { "node_modules/@babel/helper-string-parser": {
"version": "7.22.5", "version": "7.23.4",
"resolved": "https://registry.npmmirror.com/@babel/helper-string-parser/-/helper-string-parser-7.22.5.tgz", "resolved": "https://registry.npmjs.org/@babel/helper-string-parser/-/helper-string-parser-7.23.4.tgz",
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"integrity": "sha512-SaPHK1A01VrNthlix6h1hq4uJu7S/z0kdLUb6klubo738NeQoLbS6V9/d8Pv19tU0XdQKju3D1HSKuI8wJ5wMA==", "integrity": "sha512-0iw4VchYLePqJfJu9s62ACWUXeSqM30SQqlIftbYWM3C+jpPcEHKSPUZBLjSF9au4HTHQ/naF6OGnO3Q/qGR3Q==",
"dev": true, "dev": true,
"requires": { "requires": {
"@vue/component-compiler-utils": "^3.1.0", "@vue/component-compiler-utils": "^3.1.0",
@@ -17572,9 +17591,9 @@
} }
}, },
"postcss": { "postcss": {
"version": "8.4.25", "version": "8.4.31",
"resolved": "https://registry.npmmirror.com/postcss/-/postcss-8.4.25.tgz", "resolved": "https://registry.npmjs.org/postcss/-/postcss-8.4.31.tgz",
"integrity": "sha512-7taJ/8t2av0Z+sQEvNzCkpDynl0tX3uJMCODi6nT3PfASC7dYCWV9aQ+uiCf+KBD4SEFcu+GvJdGdwzQ6OSjCw==", "integrity": "sha512-PS08Iboia9mts/2ygV3eLpY5ghnUcfLV/EXTOW1E2qYxJKGGBUtNjN76FYHnMs36RmARn41bC0AZmn+rR0OVpQ==",
"requires": { "requires": {
"nanoid": "^3.3.6", "nanoid": "^3.3.6",
"picocolors": "^1.0.0", "picocolors": "^1.0.0",

View File

@@ -19,7 +19,7 @@
<v-chip v-if="agent.data.experimental" color="warning" size="x-small">experimental</v-chip> <v-chip v-if="agent.data.experimental" color="warning" size="x-small">experimental</v-chip>
</v-list-item> </v-list-item>
</v-list> </v-list>
<AgentModal :dialog="dialog" :formTitle="formTitle" @save="saveAgent" @update:dialog="updateDialog"></AgentModal> <AgentModal :dialog="state.dialog" :formTitle="state.formTitle" @save="saveAgent" @update:dialog="updateDialog"></AgentModal>
</div> </div>
</template> </template>

View File

@@ -21,7 +21,7 @@
{{ client.type }} {{ client.type }}
<v-chip label size="x-small" variant="outlined" class="ml-1">ctx {{ client.max_token_length }}</v-chip> <v-chip label size="x-small" variant="outlined" class="ml-1">ctx {{ client.max_token_length }}</v-chip>
</v-list-item-subtitle> </v-list-item-subtitle>
<v-list-item-content density="compact"> <div density="compact">
<v-slider <v-slider
hide-details hide-details
v-model="client.max_token_length" v-model="client.max_token_length"
@@ -32,9 +32,15 @@
@click.stop @click.stop
density="compact" density="compact"
></v-slider> ></v-slider>
</v-list-item-content> </div>
<v-list-item-subtitle class="text-center"> <v-list-item-subtitle class="text-center">
<v-tooltip text="No LLM prompt template for this model. Using default. Templates can be added in ./templates/llm-prompt" v-if="client.status === 'idle' && client.data && !client.data.has_prompt_template" max-width="200">
<template v-slot:activator="{ props }">
<v-icon x-size="14" class="mr-1" v-bind="props" color="orange">mdi-alert</v-icon>
</template>
</v-tooltip>
<v-tooltip text="Edit client"> <v-tooltip text="Edit client">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn size="x-small" class="mr-1" v-bind="props" variant="tonal" density="comfortable" rounded="sm" @click.stop="editClient(index)" icon="mdi-cogs"></v-btn> <v-btn size="x-small" class="mr-1" v-bind="props" variant="tonal" density="comfortable" rounded="sm" @click.stop="editClient(index)" icon="mdi-cogs"></v-btn>
@@ -56,7 +62,7 @@
</v-list-item-subtitle> </v-list-item-subtitle>
</v-list-item> </v-list-item>
</v-list> </v-list>
<ClientModal :dialog="dialog" :formTitle="formTitle" @save="saveClient" @update:dialog="updateDialog"></ClientModal> <ClientModal :dialog="state.dialog" :formTitle="state.formTitle" @save="saveClient" @error="propagateError" @update:dialog="updateDialog"></ClientModal>
<v-alert type="warning" variant="tonal" v-if="state.clients.length === 0">You have no LLM clients configured. Add one.</v-alert> <v-alert type="warning" variant="tonal" v-if="state.clients.length === 0">You have no LLM clients configured. Add one.</v-alert>
<v-btn @click="openModal" prepend-icon="mdi-plus-box">Add client</v-btn> <v-btn @click="openModal" prepend-icon="mdi-plus-box">Add client</v-btn>
</div> </div>
@@ -81,6 +87,9 @@ export default {
apiUrl: '', apiUrl: '',
model_name: '', model_name: '',
max_token_length: 2048, max_token_length: 2048,
data: {
has_prompt_template: false,
}
}, // Add a new field to store the model name }, // Add a new field to store the model name
formTitle: '' formTitle: ''
} }
@@ -90,7 +99,6 @@ export default {
'getWebsocket', 'getWebsocket',
'registerMessageHandler', 'registerMessageHandler',
'isConnected', 'isConnected',
'chekcingStatus',
'getAgents', 'getAgents',
], ],
provide() { provide() {
@@ -123,10 +131,16 @@ export default {
apiUrl: 'http://localhost:5000', apiUrl: 'http://localhost:5000',
model_name: '', model_name: '',
max_token_length: 4096, max_token_length: 4096,
data: {
has_prompt_template: false,
}
}; };
this.state.formTitle = 'Add Client'; this.state.formTitle = 'Add Client';
this.state.dialog = true; this.state.dialog = true;
}, },
propagateError(error) {
this.$emit('error', error);
},
saveClient(client) { saveClient(client) {
const index = this.state.clients.findIndex(c => c.name === client.name); const index = this.state.clients.findIndex(c => c.name === client.name);
if (index === -1) { if (index === -1) {
@@ -153,10 +167,13 @@ export default {
let agents = this.getAgents(); let agents = this.getAgents();
let client = this.state.clients[index]; let client = this.state.clients[index];
this.saveClient(client);
for (let i = 0; i < agents.length; i++) { for (let i = 0; i < agents.length; i++) {
agents[i].client = client.name; agents[i].client = client.name;
this.$emit('client-assigned', agents); console.log("Assigning client", client.name, "to agent", agents[i].name);
} }
this.$emit('client-assigned', agents);
}, },
updateDialog(newVal) { updateDialog(newVal) {
this.state.dialog = newVal; this.state.dialog = newVal;
@@ -175,6 +192,7 @@ export default {
client.status = data.status; client.status = data.status;
client.max_token_length = data.max_token_length; client.max_token_length = data.max_token_length;
client.apiUrl = data.apiUrl; client.apiUrl = data.apiUrl;
client.data = data.data;
} else { } else {
console.log("Adding new client", data); console.log("Adding new client", data);
this.state.clients.push({ this.state.clients.push({
@@ -184,6 +202,7 @@ export default {
status: data.status, status: data.status,
max_token_length: data.max_token_length, max_token_length: data.max_token_length,
apiUrl: data.apiUrl, apiUrl: data.apiUrl,
data: data.data,
}); });
// sort the clients by name // sort the clients by name
this.state.clients.sort((a, b) => (a.name > b.name) ? 1 : -1); this.state.clients.sort((a, b) => (a.name > b.name) ? 1 : -1);

View File

@@ -1,73 +1,209 @@
<template> <template>
<v-dialog v-model="dialog" scrollable max-width="50%"> <v-dialog v-model="dialog" scrollable max-width="960px">
<v-card v-if="app_config !== null"> <v-card v-if="app_config !== null">
<v-card-title><v-icon class="mr-1">mdi-cog</v-icon>Settings</v-card-title>
<v-tabs color="primary" v-model="tab"> <v-tabs color="primary" v-model="tab">
<v-tab value="game"> <v-tab value="game">
<v-icon start>mdi-gamepad-square</v-icon> <v-icon start>mdi-gamepad-square</v-icon>
Game Game
</v-tab> </v-tab>
<v-tab value="application">
<v-icon start>mdi-application</v-icon>
Application
</v-tab>
<v-tab value="creator"> <v-tab value="creator">
<v-icon start>mdi-palette-outline</v-icon> <v-icon start>mdi-palette-outline</v-icon>
Creator Creator
</v-tab> </v-tab>
</v-tabs> </v-tabs>
<v-window v-model="tab"> <v-window v-model="tab">
<!-- GAME -->
<v-window-item value="game"> <v-window-item value="game">
<v-card flat> <v-card flat>
<v-card-title>
Default player character
<v-tooltip location="top" max-width="500" text="This will be default player character that will be added to a game if the game does not come with a defined player character. Essentially this is relevant for when you load character-cards that aren't in the talemate scene format.">
<template v-slot:activator="{ props }">
<v-icon size="x-small" v-bind="props" v-on="on">mdi-help</v-icon>
</template>
</v-tooltip>
</v-card-title>
<v-card-text> <v-card-text>
<v-row> <v-row>
<v-col cols="6"> <v-col cols="4">
<v-text-field v-model="app_config.game.default_player_character.name" label="Name"></v-text-field> <v-list>
<v-list-item @click="gamePageSelected=item.value" :prepend-icon="item.icon" v-for="(item, index) in navigation.game" :key="index">
<v-list-item-title>{{ item.title }}</v-list-item-title>
</v-list-item>
</v-list>
</v-col> </v-col>
<v-col cols="6"> <v-col cols="8">
<v-text-field v-model="app_config.game.default_player_character.gender" label="Gender"></v-text-field> <div v-if="gamePageSelected === 'character'">
</v-col> <v-alert color="white" variant="text" icon="mdi-human-edit" density="compact">
</v-row> <v-alert-title>Default player character</v-alert-title>
<v-row> <div class="text-grey">
<v-col> This will be default player character that will be added to a game if the game does not come with a defined player character. Essentially this is relevant for when you load character-cards that aren't in the talemate scene format.
<v-textarea v-model="app_config.game.default_player_character.description" auto-grow label="Description"></v-textarea>
</v-col>
<v-col>
<v-color-picker v-model="app_config.game.default_player_character.color" hide-inputs label="Color" elevation="0"></v-color-picker>
</div>
</v-alert>
<v-divider class="mb-2"></v-divider>
<v-row>
<v-col cols="6">
<v-text-field v-model="app_config.game.default_player_character.name"
label="Name"></v-text-field>
</v-col>
<v-col cols="6">
<v-text-field v-model="app_config.game.default_player_character.gender"
label="Gender"></v-text-field>
</v-col>
</v-row>
<v-row>
<v-col cols="12">
<v-textarea v-model="app_config.game.default_player_character.description"
auto-grow label="Description"></v-textarea>
</v-col>
</v-row>
</div>
</v-col> </v-col>
</v-row> </v-row>
</v-card-text> </v-card-text>
</v-card> </v-card>
</v-window-item> </v-window-item>
<!-- APPLICATION -->
<v-window-item value="application">
<v-card flat>
<v-card-text>
<v-row>
<v-col cols="4">
<v-list>
<v-list-subheader>Third Party APIs</v-list-subheader>
<v-list-item @click="applicationPageSelected=item.value" :prepend-icon="item.icon" v-for="(item, index) in navigation.application" :key="index">
<v-list-item-title>{{ item.title }}</v-list-item-title>
</v-list-item>
</v-list>
</v-col>
<v-col cols="8">
<!-- OPENAI API -->
<div v-if="applicationPageSelected === 'openai_api'">
<v-alert color="white" variant="text" icon="mdi-api" density="compact">
<v-alert-title>OpenAI</v-alert-title>
<div class="text-grey">
Configure your OpenAI API key here. You can get one from <a href="https://platform.openai.com/" target="_blank">https://platform.openai.com/</a>
</div>
</v-alert>
<v-divider class="mb-2"></v-divider>
<v-row>
<v-col cols="12">
<v-text-field type="password" v-model="app_config.openai.api_key"
label="OpenAI API Key"></v-text-field>
</v-col>
</v-row>
</div>
<!-- ELEVENLABS API -->
<div v-if="applicationPageSelected === 'elevenlabs_api'">
<v-alert color="white" variant="text" icon="mdi-api" density="compact">
<v-alert-title>ElevenLabs</v-alert-title>
<div class="text-grey">
<p class="mb-1">Generate realistic speech with the most advanced AI voice model ever.</p>
Configure your ElevenLabs API key here. You can get one from <a href="https://elevenlabs.io/?from=partnerewing2048" target="_blank">https://elevenlabs.io</a> <span class="text-caption">(affiliate link)</span>
</div>
</v-alert>
<v-divider class="mb-2"></v-divider>
<v-row>
<v-col cols="12">
<v-text-field type="password" v-model="app_config.elevenlabs.api_key"
label="ElevenLabs API Key"></v-text-field>
</v-col>
</v-row>
</div>
<!-- COQUI API -->
<div v-if="applicationPageSelected === 'coqui_api'">
<v-alert color="white" variant="text" icon="mdi-api" density="compact">
<v-alert-title>Coqui Studio</v-alert-title>
<div class="text-grey">
<p class="mb-1">Realistic, emotive text-to-speech through generative AI.</p>
Configure your Coqui API key here. You can get one from <a href="https://app.coqui.ai/account" target="_blank">https://app.coqui.ai/account</a>
</div>
</v-alert>
<v-divider class="mb-2"></v-divider>
<v-row>
<v-col cols="12">
<v-text-field type="password" v-model="app_config.coqui.api_key"
label="Coqui API Key"></v-text-field>
</v-col>
</v-row>
</div>
<!-- RUNPOD API -->
<div v-if="applicationPageSelected === 'runpod_api'">
<v-alert color="white" variant="text" icon="mdi-api" density="compact">
<v-alert-title>RunPod</v-alert-title>
<div class="text-grey">
<p class="mb-1">Launch a GPU instance in seconds.</p>
Configure your RunPod API key here. You can get one from <a href="https://runpod.io?ref=gma8kdu0" target="_blank">https://runpod.io/</a> <span class="text-caption">(affiliate link)</span>
</div>
</v-alert>
<v-divider class="mb-2"></v-divider>
<v-row>
<v-col cols="12">
<v-text-field type="password" v-model="app_config.runpod.api_key"
label="RunPod API Key"></v-text-field>
</v-col>
</v-row>
</div>
</v-col>
</v-row>
</v-card-text>
</v-card>
</v-window-item>
<!-- CREATOR -->
<v-window-item value="creator"> <v-window-item value="creator">
<v-card flat> <v-card flat>
<v-card-title> <v-card-text>
Content context <v-row>
<v-tooltip location="top" max-width="500" text="Available choices when generating characters or scenarios within talemate."> <v-col cols="4">
<template v-slot:activator="{ props }"> <v-list>
<v-icon size="x-small" v-bind="props" v-on="on">mdi-help</v-icon> <v-list-item @click="creatorPageSelected=item.value" :prepend-icon="item.icon" v-for="(item, index) in navigation.creator" :key="index">
</template> <v-list-item-title>{{ item.title }}</v-list-item-title>
</v-tooltip> </v-list-item>
</v-card-title> </v-list>
<v-card-text style="max-height:600px; overflow-y:scroll;"> </v-col>
<v-list density="compact"> <v-col cols="8">
<v-list-item v-for="(value, index) in app_config.creator.content_context" :key="index"> <div v-if="creatorPageSelected === 'content_context'">
<v-list-item-title><v-icon color="red">mdi-delete</v-icon>{{ value }}</v-list-item-title> <!-- Content for Content context will go here -->
</v-list-item> <v-alert color="white" variant="text" icon="mdi-cube-scan" density="compact">
</v-list> <v-alert-title>Content context</v-alert-title>
<v-text-field v-model="content_context_input" label="Add content context" @keyup.enter="app_config.creator.content_context.push(content_context_input); app_config.creator.content_context_input = ''"></v-text-field> <div class="text-grey">
Available content-context choices when generating characters or scenarios. This can strongly influence the content that is generated.
</div>
</v-alert>
<v-divider class="mb-2"></v-divider>
<v-row>
<v-col cols="12">
<v-list density="compact">
<v-list-item v-for="(value, index) in app_config.creator.content_context" :key="index">
<v-list-item-title><v-icon color="red" class="mr-2" @click="contentContextRemove(index)">mdi-delete</v-icon>{{ value }}</v-list-item-title>
</v-list-item>
</v-list>
<v-divider></v-divider>
<v-text-field v-model="content_context_input" label="Add content context (Press enter to add)"
@keyup.enter="app_config.creator.content_context.push(content_context_input); content_context_input = ''"></v-text-field>
</v-col>
</v-row>
</div>
</v-col>
</v-row>
</v-card-text> </v-card-text>
</v-card> </v-card>
</v-window-item> </v-window-item>
</v-window> </v-window>
<v-card-actions> <v-card-actions>
<v-btn color="primary" text @click="saveConfig">Save</v-btn> <v-spacer></v-spacer>
<v-btn color="primary" text @click="saveConfig" prepend-icon="mdi-check-circle-outline">Save</v-btn>
</v-card-actions> </v-card-actions>
</v-card> </v-card>
<v-card v-else> <v-card v-else>
@@ -78,7 +214,7 @@
<v-progress-circular indeterminate color="primary" size="20"></v-progress-circular> <v-progress-circular indeterminate color="primary" size="20"></v-progress-circular>
</v-card-text> </v-card-text>
</v-card> </v-card>
</v-dialog> </v-dialog>
</template> </template>
<script> <script>
@@ -90,6 +226,23 @@ export default {
dialog: false, dialog: false,
app_config: null, app_config: null,
content_context_input: '', content_context_input: '',
navigation: {
game: [
{title: 'Default Character', icon: 'mdi-human-edit', value: 'character'},
],
application: [
{title: 'OpenAI', icon: 'mdi-api', value: 'openai_api'},
{title: 'ElevenLabs', icon: 'mdi-api', value: 'elevenlabs_api'},
{title: 'Coqui Studio', icon: 'mdi-api', value: 'coqui_api'},
{title: 'RunPod', icon: 'mdi-api', value: 'runpod_api'},
],
creator: [
{title: 'Content Context', icon: 'mdi-cube-scan', value: 'content_context'},
]
},
gamePageSelected: 'character',
applicationPageSelected: 'openai_api',
creatorPageSelected: 'content_context',
} }
}, },
inject: ['getWebsocket', 'registerMessageHandler', 'setWaitingForInput', 'requestSceneAssets', 'requestAppConfig'], inject: ['getWebsocket', 'registerMessageHandler', 'setWaitingForInput', 'requestSceneAssets', 'requestAppConfig'],
@@ -104,6 +257,10 @@ export default {
this.dialog = false this.dialog = false
}, },
contentContextRemove(index) {
this.app_config.creator.content_context.splice(index, 1);
},
handleMessage(message) { handleMessage(message) {
if (message.type == "app_config") { if (message.type == "app_config") {
this.app_config = message.data; this.app_config = message.data;
@@ -111,7 +268,7 @@ export default {
} }
if (message.type == 'config') { if (message.type == 'config') {
if(message.action == 'save_complete') { if (message.action == 'save_complete') {
this.exit(); this.exit();
} }
} }
@@ -138,5 +295,4 @@ export default {
</script> </script>
<style scoped> <style scoped></style>
</style>

View File

@@ -44,10 +44,10 @@
<v-window-item value="details"> <v-window-item value="details">
<v-card-text style="max-height:600px; overflow-y:scroll;"> <v-card-text style="max-height:600px; overflow-y:scroll;">
<v-list-item v-for="(value, key) in base_attributes" :key="key"> <v-list-item v-for="(value, key) in base_attributes" :key="key">
<v-list-item-content> <div>
<v-list-item-title>{{ key }}</v-list-item-title> <v-list-item-title>{{ key }}</v-list-item-title>
<v-list-item-subtitle>{{ value }}</v-list-item-subtitle> <v-list-item-subtitle>{{ value }}</v-list-item-subtitle>
</v-list-item-content> </div>
</v-list-item> </v-list-item>
</v-card-text> </v-card-text>
</v-window-item> </v-window-item>

View File

@@ -2,36 +2,48 @@
<v-dialog v-model="localDialog" persistent max-width="600px"> <v-dialog v-model="localDialog" persistent max-width="600px">
<v-card> <v-card>
<v-card-title> <v-card-title>
<span class="headline">{{ formTitle }}</span> <v-icon>mdi-network-outline</v-icon>
<span class="headline">{{ title() }}</span>
</v-card-title> </v-card-title>
<v-card-text> <v-card-text>
<v-container> <v-container>
<v-row> <v-row>
<v-col cols="6"> <v-col cols="6">
<v-select v-model="client.type" :disabled="!typeEditable()" :items="['openai', 'textgenwebui', 'lmstudio']" label="Client Type"></v-select> <v-select v-model="client.type" :disabled="!typeEditable()" :items="['openai', 'textgenwebui', 'lmstudio']" label="Client Type" @update:model-value="resetToDefaults"></v-select>
</v-col> </v-col>
<v-col cols="6"> <v-col cols="6">
<v-text-field v-model="client.name" label="Client Name"></v-text-field> <v-text-field v-model="client.name" label="Client Name"></v-text-field>
</v-col> </v-col>
</v-row> </v-row>
<v-row> <v-row>
<v-col cols="12"> <v-col cols="12">
<v-text-field v-model="client.apiUrl" v-if="isLocalApiClient(client)" label="API URL"></v-text-field> <v-text-field v-model="client.apiUrl" v-if="isLocalApiClient(client)" label="API URL"></v-text-field>
<v-select v-model="client.model" v-if="client.type === 'openai'" :items="['gpt-4-1106-preview', 'gpt-4', 'gpt-3.5-turbo', 'gpt-3.5-turbo-16k']" label="Model"></v-select> <v-select v-model="client.model" v-if="client.type === 'openai'" :items="['gpt-4-1106-preview', 'gpt-4', 'gpt-3.5-turbo', 'gpt-3.5-turbo-16k']" label="Model"></v-select>
</v-col> </v-col>
</v-row> </v-row>
<v-row> <v-row>
<v-col cols="6"> <v-col cols="4">
<v-text-field v-model="client.max_token_length" v-if="isLocalApiClient(client)" type="number" label="Context Length"></v-text-field> <v-text-field v-model="client.max_token_length" v-if="isLocalApiClient(client)" type="number" label="Context Length"></v-text-field>
</v-col> </v-col>
</v-row> <v-col cols="8" v-if="!typeEditable() && client.data && client.data.prompt_template_example !== null">
<v-card elevation="3" :color="(client.data.has_prompt_template ? 'primary' : 'warning')" variant="tonal">
<v-card-title>Prompt Template</v-card-title>
<v-card-text>
<div class="text-caption" v-if="!client.data.has_prompt_template">No matching LLM prompt template found. Using default.</div>
<pre>{{ client.data.prompt_template_example }}</pre>
</v-card-text>
</v-card>
</v-col>
</v-row>
</v-container> </v-container>
</v-card-text> </v-card-text>
<v-card-actions> <v-card-actions>
<v-spacer></v-spacer> <v-spacer></v-spacer>
<v-btn color="blue darken-1" text @click="close">Close</v-btn> <v-btn color="primary" text @click="close" prepend-icon="mdi-cancel">Cancel</v-btn>
<v-btn color="blue darken-1" text @click="save">Save</v-btn> <v-btn color="primary" text @click="save" prepend-icon="mdi-check-circle-outline">Save</v-btn>
</v-card-actions> </v-card-actions>
</v-card> </v-card>
</v-dialog> </v-dialog>
@@ -47,7 +59,25 @@ export default {
data() { data() {
return { return {
localDialog: this.state.dialog, localDialog: this.state.dialog,
client: { ...this.state.currentClient } // Define client data property client: { ...this.state.currentClient },
defaultValuesByCLientType: {
// when client type is changed in the modal, these values will be used
// to populate the form
'textgenwebui': {
apiUrl: 'http://localhost:5000',
max_token_length: 4096,
name_prefix: 'TextGenWebUI',
},
'openai': {
model: 'gpt-4-1106-preview',
name_prefix: 'OpenAI',
},
'lmstudio': {
apiUrl: 'http://localhost:1234',
max_token_length: 4096,
name_prefix: 'LMStudio',
}
}
}; };
}, },
watch: { watch: {
@@ -68,13 +98,48 @@ export default {
} }
}, },
methods: { methods: {
resetToDefaults() {
const defaults = this.defaultValuesByCLientType[this.client.type];
if (defaults) {
this.client.model = defaults.model || '';
this.client.apiUrl = defaults.apiUrl || '';
this.client.max_token_length = defaults.max_token_length || 4096;
// loop and build name from prefix, checking against current clients
let name = defaults.name_prefix;
let i = 2;
while (this.state.clients.find(c => c.name === name)) {
name = `${defaults.name_prefix} ${i}`;
i++;
}
this.client.name = name;
this.client.data = {};
}
},
validateName() {
// if we are editing a client, we should exclude the current client from the check
if(!this.typeEditable()) {
return this.state.clients.findIndex(c => c.name === this.client.name && c.name !== this.state.currentClient.name) === -1;
}
return this.state.clients.findIndex(c => c.name === this.client.name) === -1;
},
typeEditable() { typeEditable() {
return this.state.formTitle === 'Add Client'; return this.state.formTitle === 'Add Client';
}, },
title() {
return this.typeEditable() ? 'Add Client' : 'Edit Client';
},
close() { close() {
this.$emit('update:dialog', false); this.$emit('update:dialog', false);
}, },
save() { save() {
if(!this.validateName()) {
this.$emit('error', 'Client name already exists');
return;
}
this.$emit('save', this.client); // Emit save event with client object this.$emit('save', this.client); // Emit save event with client object
this.close(); this.close();
}, },

View File

@@ -0,0 +1,92 @@
<template>
<v-dialog v-model="showModal" max-width="800px">
<v-card>
<v-card-title class="headline">Your Character</v-card-title>
<v-card-text>
<v-alert type="info" variant="tonal" v-if="defaultCharacter.name === ''" density="compact">You have not yet
configured a default player character. This character will be used when a scenario is loaded that does not come
with a pre-defined player character.</v-alert>
<v-container>
<v-row>
<v-col cols="12" sm="6">
<v-text-field v-model="defaultCharacter.name" label="Name" :rules="[rules.required]"></v-text-field>
</v-col>
<v-col cols="12" sm="6">
<v-text-field v-model="defaultCharacter.gender" label="Gender" :rules="[rules.required]"></v-text-field>
</v-col>
</v-row>
<v-row>
<v-col cols="12">
<v-textarea v-model="defaultCharacter.description" label="Description" auto-grow></v-textarea>
</v-col>
</v-row>
</v-container>
</v-card-text>
<v-card-actions>
<v-spacer></v-spacer>
<v-btn color="primary" v-if="!saving" text @click="cancel" prepend-icon="mdi-cancel">Cancel</v-btn>
<v-progress-circular v-else indeterminate color="primary" size="20"></v-progress-circular>
<v-btn color="primary" text :disabled="saving" @click="saveDefaultCharacter" prepend-icon="mdi-check-circle-outline">Continue</v-btn>
</v-card-actions>
</v-card>
</v-dialog>
</template>
<script>
export default {
name: 'DefaultCharacter',
inject: ['getWebsocket', 'registerMessageHandler'],
data() {
return {
showModal: false,
saving: false,
defaultCharacter: {
name: '',
gender: '',
description: '',
color: '#3362bb'
},
rules: {
required: value => !!value || 'Required.'
}
};
},
methods: {
saveDefaultCharacter() {
// Send the new default character data to the server
this.saving = true;
this.getWebsocket().send(JSON.stringify({
type: 'config',
action: 'save_default_character',
data: this.defaultCharacter
}));
},
cancel() {
this.$emit("cancel");
this.closeModal();
},
open() {
this.saving = false;
this.showModal = true;
},
closeModal() {
this.showModal = false;
},
handleMessage(message) {
if (message.type == 'config') {
if (message.action == 'save_default_character_complete') {
this.closeModal();
this.$emit("save");
}
}
},
},
created() {
this.registerMessageHandler(this.handleMessage);
},
};
</script>
<style scoped>
/* Add any specific styles for your DefaultCharacter modal here */
</style>

View File

@@ -1,12 +1,15 @@
<template> <template>
<v-list-subheader @click="toggle()" class="text-uppercase"><v-icon>mdi-script-text-outline</v-icon> Load <v-list-subheader v-if="appConfig !== null" @click="toggle()" class="text-uppercase"><v-icon>mdi-script-text-outline</v-icon> Load
<v-progress-circular v-if="loading" indeterminate color="primary" size="20"></v-progress-circular> <v-progress-circular v-if="loading" indeterminate color="primary" size="20"></v-progress-circular>
<v-icon v-if="expanded" icon="mdi-chevron-down"></v-icon> <v-icon v-if="expanded" icon="mdi-chevron-down"></v-icon>
<v-icon v-else icon="mdi-chevron-up"></v-icon> <v-icon v-else icon="mdi-chevron-up"></v-icon>
</v-list-subheader> </v-list-subheader>
<v-list-item-group v-if="!loading && isConnected() && expanded && !configurationRequired()"> <v-list-subheader class="text-uppercase" v-else>
<v-progress-circular indeterminate color="primary" size="20"></v-progress-circular> Waiting for config...
</v-list-subheader>
<div v-if="!loading && isConnected() && expanded && !configurationRequired() && appConfig !== null">
<v-list-item> <v-list-item>
<v-list-item-content class="mb-3"> <div class="mb-3">
<!-- Toggle buttons for switching between file upload and path input --> <!-- Toggle buttons for switching between file upload and path input -->
<v-btn-toggle density="compact" class="mb-3" v-model="inputMethod" mandatory> <v-btn-toggle density="compact" class="mb-3" v-model="inputMethod" mandatory>
<v-btn value="file"> <v-btn value="file">
@@ -37,18 +40,24 @@
<v-icon left>mdi-palette-outline</v-icon> <v-icon left>mdi-palette-outline</v-icon>
Creative Mode Creative Mode
</v-btn> </v-btn>
</v-list-item-content> </div>
</v-list-item> </v-list-item>
</v-list-item-group> </div>
<div v-else-if="configurationRequired()"> <div v-else-if="configurationRequired()">
<v-alert type="warning" variant="tonal">You need to configure a Talemate client before you can load scenes.</v-alert> <v-alert type="warning" variant="tonal">You need to configure a Talemate client before you can load scenes.</v-alert>
</div> </div>
<DefaultCharacter ref="defaultCharacterModal" @save="loadScene" @cancel="loadCanceled"></DefaultCharacter>
</template> </template>
<script> <script>
import DefaultCharacter from './DefaultCharacter.vue';
export default { export default {
name: 'LoadScene', name: 'LoadScene',
components: {
DefaultCharacter,
},
data() { data() {
return { return {
loading: false, loading: false,
@@ -60,10 +69,19 @@ export default {
sceneSearchLoading: false, sceneSearchLoading: false,
sceneSaved: null, sceneSaved: null,
expanded: true, expanded: true,
appConfig: null, // Store the app configuration
} }
}, },
emits: {
loading: null,
},
inject: ['getWebsocket', 'registerMessageHandler', 'isConnected', 'configurationRequired'], inject: ['getWebsocket', 'registerMessageHandler', 'isConnected', 'configurationRequired'],
methods: { methods: {
// Method to show the DefaultCharacter modal
showDefaultCharacterModal() {
this.$refs.defaultCharacterModal.open();
},
toggle() { toggle() {
this.expanded = !this.expanded; this.expanded = !this.expanded;
}, },
@@ -89,6 +107,12 @@ export default {
this.loading = true; this.loading = true;
this.getWebsocket().send(JSON.stringify({ type: 'load_scene', file_path: "environment:creative" })); this.getWebsocket().send(JSON.stringify({ type: 'load_scene', file_path: "environment:creative" }));
}, },
loadCanceled() {
console.log("Load canceled");
this.loading = false;
this.sceneFile = [];
},
loadScene() { loadScene() {
if(this.sceneSaved === false) { if(this.sceneSaved === false) {
@@ -97,13 +121,26 @@ export default {
} }
} }
this.loading = true; this.sceneSaved = null;
if (this.inputMethod === 'file' && this.sceneFile.length > 0) { // Check if the input method is "file" and there is at least one file if (this.inputMethod === 'file' && this.sceneFile.length > 0) { // Check if the input method is "file" and there is at least one file
// if file is image check if default character is set
if(this.sceneFile[0].type.startsWith("image/")) {
if(!this.appConfig.game.default_player_character.name) {
this.showDefaultCharacterModal();
return;
}
}
this.loading = true;
// Convert the uploaded file to base64 // Convert the uploaded file to base64
const reader = new FileReader(); const reader = new FileReader();
reader.readAsDataURL(this.sceneFile[0]); // Access the first file in the array reader.readAsDataURL(this.sceneFile[0]); // Access the first file in the array
reader.onload = () => { reader.onload = () => {
//const base64File = reader.result.split(',')[1]; //const base64File = reader.result.split(',')[1];
this.$emit("loading", true)
this.getWebsocket().send(JSON.stringify({ this.getWebsocket().send(JSON.stringify({
type: 'load_scene', type: 'load_scene',
scene_data: reader.result, scene_data: reader.result,
@@ -112,11 +149,28 @@ export default {
this.sceneFile = []; this.sceneFile = [];
}; };
} else if (this.inputMethod === 'path' && this.sceneInput) { // Check if the input method is "path" and the scene input is not empty } else if (this.inputMethod === 'path' && this.sceneInput) { // Check if the input method is "path" and the scene input is not empty
// if path ends with .png/jpg/webp check if default character is set
if(this.sceneInput.endsWith(".png") || this.sceneInput.endsWith(".jpg") || this.sceneInput.endsWith(".webp")) {
if(!this.appConfig.game.default_player_character.name) {
this.showDefaultCharacterModal();
return;
}
}
this.loading = true;
this.$emit("loading", true)
this.getWebsocket().send(JSON.stringify({ type: 'load_scene', file_path: this.sceneInput })); this.getWebsocket().send(JSON.stringify({ type: 'load_scene', file_path: this.sceneInput }));
this.sceneInput = ''; this.sceneInput = '';
} }
}, },
handleMessage(data) { handleMessage(data) {
// Handle app configuration
if (data.type === 'app_config') {
this.appConfig = data.data;
console.log("App config", this.appConfig);
}
// Scene loaded // Scene loaded
if (data.type === "system") { if (data.type === "system") {
@@ -139,10 +193,11 @@ export default {
return; return;
} }
} },
}, },
created() { created() {
this.registerMessageHandler(this.handleMessage); this.registerMessageHandler(this.handleMessage);
//this.getWebsocket().send(JSON.stringify({ type: 'request_config' })); // Request the current app configuration
}, },
mounted() { mounted() {
console.log("Websocket", this.getWebsocket()); // Check if websocket is available console.log("Websocket", this.getWebsocket()); // Check if websocket is available

View File

@@ -18,7 +18,7 @@
<v-tooltip v-if="isEnvironment('scene')" :disabled="isInputDisabled()" location="top" <v-tooltip v-if="isEnvironment('scene')" :disabled="isInputDisabled()" location="top"
text="Redo most recent AI message"> text="Redo most recent AI message">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey" v-bind="props" v-on="on" :disabled="isInputDisabled()" <v-btn class="hotkey" v-bind="props" :disabled="isInputDisabled()"
@click="sendHotButtonMessage('!rerun')" color="primary" icon> @click="sendHotButtonMessage('!rerun')" color="primary" icon>
<v-icon>mdi-refresh</v-icon> <v-icon>mdi-refresh</v-icon>
</v-btn> </v-btn>
@@ -28,7 +28,7 @@
<v-tooltip v-if="isEnvironment('scene')" :disabled="isInputDisabled()" location="top" <v-tooltip v-if="isEnvironment('scene')" :disabled="isInputDisabled()" location="top"
text="Redo most recent AI message (Nuke Option - use this to attempt to break out of repetition)"> text="Redo most recent AI message (Nuke Option - use this to attempt to break out of repetition)">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey" v-bind="props" v-on="on" :disabled="isInputDisabled()" <v-btn class="hotkey" v-bind="props" :disabled="isInputDisabled()"
@click="sendHotButtonMessage('!rerun:0.5')" color="primary" icon> @click="sendHotButtonMessage('!rerun:0.5')" color="primary" icon>
<v-icon>mdi-nuke</v-icon> <v-icon>mdi-nuke</v-icon>
</v-btn> </v-btn>
@@ -39,7 +39,7 @@
<v-tooltip v-if="commandActive" location="top" <v-tooltip v-if="commandActive" location="top"
text="Abort / end action."> text="Abort / end action.">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey mr-3" v-bind="props" v-on="on" :disabled="!isWaitingForInput()" <v-btn class="hotkey mr-3" v-bind="props" :disabled="!isWaitingForInput()"
@click="sendHotButtonMessage('!abort')" color="primary" icon> @click="sendHotButtonMessage('!abort')" color="primary" icon>
<v-icon>mdi-cancel</v-icon> <v-icon>mdi-cancel</v-icon>
@@ -56,7 +56,7 @@
<v-card-actions> <v-card-actions>
<v-tooltip :disabled="isInputDisabled()" location="top" text="Narrate: Progress Story"> <v-tooltip :disabled="isInputDisabled()" location="top" text="Narrate: Progress Story">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey mx-3" v-bind="props" v-on="on" :disabled="isInputDisabled()" <v-btn class="hotkey mx-3" v-bind="props" :disabled="isInputDisabled()"
@click="sendHotButtonMessage('!narrate_progress')" color="primary" icon> @click="sendHotButtonMessage('!narrate_progress')" color="primary" icon>
<v-icon>mdi-script-text-play</v-icon> <v-icon>mdi-script-text-play</v-icon>
</v-btn> </v-btn>
@@ -64,7 +64,7 @@
</v-tooltip> </v-tooltip>
<v-tooltip :disabled="isInputDisabled()" location="top" text="Narrate: Scene"> <v-tooltip :disabled="isInputDisabled()" location="top" text="Narrate: Scene">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey mx-3" v-bind="props" v-on="on" :disabled="isInputDisabled()" <v-btn class="hotkey mx-3" v-bind="props" :disabled="isInputDisabled()"
@click="sendHotButtonMessage('!narrate')" color="primary" icon> @click="sendHotButtonMessage('!narrate')" color="primary" icon>
<v-icon>mdi-script-text</v-icon> <v-icon>mdi-script-text</v-icon>
</v-btn> </v-btn>
@@ -72,7 +72,7 @@
</v-tooltip> </v-tooltip>
<v-tooltip :disabled="isInputDisabled()" location="top" text="Narrate: Character"> <v-tooltip :disabled="isInputDisabled()" location="top" text="Narrate: Character">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey mx-3" v-bind="props" v-on="on" :disabled="isInputDisabled()" <v-btn class="hotkey mx-3" v-bind="props" :disabled="isInputDisabled()"
@click="sendHotButtonMessage('!narrate_c')" color="primary" icon> @click="sendHotButtonMessage('!narrate_c')" color="primary" icon>
<v-icon>mdi-account-voice</v-icon> <v-icon>mdi-account-voice</v-icon>
</v-btn> </v-btn>
@@ -80,7 +80,7 @@
</v-tooltip> </v-tooltip>
<v-tooltip :disabled="isInputDisabled()" location="top" text="Narrate: Query"> <v-tooltip :disabled="isInputDisabled()" location="top" text="Narrate: Query">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey mx-3" v-bind="props" v-on="on" :disabled="isInputDisabled()" <v-btn class="hotkey mx-3" v-bind="props" :disabled="isInputDisabled()"
@click="sendHotButtonMessage('!narrate_q')" color="primary" icon> @click="sendHotButtonMessage('!narrate_q')" color="primary" icon>
<v-icon>mdi-crystal-ball</v-icon> <v-icon>mdi-crystal-ball</v-icon>
</v-btn> </v-btn>
@@ -103,7 +103,7 @@
<v-divider vertical></v-divider> <v-divider vertical></v-divider>
<v-tooltip :disabled="isInputDisabled()" location="top" text="Direct a character"> <v-tooltip :disabled="isInputDisabled()" location="top" text="Direct a character">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey mx-3" v-bind="props" v-on="on" :disabled="isInputDisabled()" <v-btn class="hotkey mx-3" v-bind="props" :disabled="isInputDisabled()"
@click="sendHotButtonMessage('!director')" color="primary" icon> @click="sendHotButtonMessage('!director')" color="primary" icon>
<v-icon>mdi-bullhorn</v-icon> <v-icon>mdi-bullhorn</v-icon>
</v-btn> </v-btn>
@@ -118,7 +118,7 @@
<v-tooltip :disabled="isInputDisabled()" location="top" text="Save"> <v-tooltip :disabled="isInputDisabled()" location="top" text="Save">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey mx-3" v-bind="props" v-on="on" :disabled="isInputDisabled()" <v-btn class="hotkey mx-3" v-bind="props" :disabled="isInputDisabled()"
@click="sendHotButtonMessage('!save')" color="primary" icon> @click="sendHotButtonMessage('!save')" color="primary" icon>
<v-icon>mdi-content-save</v-icon> <v-icon>mdi-content-save</v-icon>
</v-btn> </v-btn>
@@ -127,7 +127,7 @@
<v-tooltip :disabled="isInputDisabled()" location="top" text="Save As"> <v-tooltip :disabled="isInputDisabled()" location="top" text="Save As">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey mx-3" v-bind="props" v-on="on" :disabled="isInputDisabled()" <v-btn class="hotkey mx-3" v-bind="props" :disabled="isInputDisabled()"
@click="sendHotButtonMessage('!save_as')" color="primary" icon> @click="sendHotButtonMessage('!save_as')" color="primary" icon>
<v-icon>mdi-content-save-all</v-icon> <v-icon>mdi-content-save-all</v-icon>
</v-btn> </v-btn>
@@ -136,7 +136,7 @@
<v-tooltip v-if="isEnvironment('scene')" :disabled="isInputDisabled()" location="top" text="Switch to creative mode"> <v-tooltip v-if="isEnvironment('scene')" :disabled="isInputDisabled()" location="top" text="Switch to creative mode">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey mx-3" v-bind="props" v-on="on" :disabled="isInputDisabled()" <v-btn class="hotkey mx-3" v-bind="props" :disabled="isInputDisabled()"
@click="sendHotButtonMessage('!setenv_creative')" color="primary" icon> @click="sendHotButtonMessage('!setenv_creative')" color="primary" icon>
<v-icon>mdi-palette-outline</v-icon> <v-icon>mdi-palette-outline</v-icon>
</v-btn> </v-btn>
@@ -145,7 +145,7 @@
<v-tooltip v-else-if="isEnvironment('creative')" :disabled="isInputDisabled()" location="top" text="Switch to game mode"> <v-tooltip v-else-if="isEnvironment('creative')" :disabled="isInputDisabled()" location="top" text="Switch to game mode">
<template v-slot:activator="{ props }"> <template v-slot:activator="{ props }">
<v-btn class="hotkey mx-3" v-bind="props" v-on="on" :disabled="isInputDisabled()" <v-btn class="hotkey mx-3" v-bind="props" :disabled="isInputDisabled()"
@click="sendHotButtonMessage('!setenv_scene')" color="primary" icon> @click="sendHotButtonMessage('!setenv_scene')" color="primary" icon>
<v-icon>mdi-gamepad-square</v-icon> <v-icon>mdi-gamepad-square</v-icon>
</v-btn> </v-btn>

View File

@@ -11,7 +11,7 @@
Make sure the backend process is running. Make sure the backend process is running.
</p> </p>
</v-alert> </v-alert>
<LoadScene ref="loadScene" /> <LoadScene ref="loadScene" @loading="sceneStartedLoading" />
<v-divider></v-divider> <v-divider></v-divider>
<div :style="(sceneActive && scene.environment === 'scene' ? 'display:block' : 'display:none')"> <div :style="(sceneActive && scene.environment === 'scene' ? 'display:block' : 'display:none')">
<!-- <GameOptions v-if="sceneActive" ref="gameOptions" /> --> <!-- <GameOptions v-if="sceneActive" ref="gameOptions" /> -->
@@ -37,18 +37,14 @@
<v-list> <v-list>
<v-list-subheader class="text-uppercase"><v-icon>mdi-network-outline</v-icon> <v-list-subheader class="text-uppercase"><v-icon>mdi-network-outline</v-icon>
Clients</v-list-subheader> Clients</v-list-subheader>
<v-list-item-group> <v-list-item>
<v-list-item> <AIClient ref="aiClient" @save="saveClients" @error="uxErrorHandler" @clients-updated="saveClients" @client-assigned="saveAgents"></AIClient>
<AIClient ref="aiClient" @save="saveClients" @clients-updated="saveClients" @client-assigned="saveAgents"></AIClient> </v-list-item>
</v-list-item>
</v-list-item-group>
<v-divider></v-divider> <v-divider></v-divider>
<v-list-subheader class="text-uppercase"><v-icon>mdi-transit-connection-variant</v-icon> Agents</v-list-subheader> <v-list-subheader class="text-uppercase"><v-icon>mdi-transit-connection-variant</v-icon> Agents</v-list-subheader>
<v-list-item-group> <v-list-item>
<v-list-item> <AIAgent ref="aiAgent" @save="saveAgents" @agents-updated="saveAgents"></AIAgent>
<AIAgent ref="aiAgent" @save="saveAgents" @agents-updated="saveAgents"></AIAgent> </v-list-item>
</v-list-item>
</v-list-item-group>
<!-- More sections can be added here --> <!-- More sections can be added here -->
</v-list> </v-list>
</v-navigation-drawer> </v-navigation-drawer>
@@ -97,13 +93,12 @@
<v-chip size="x-small" v-else-if="scene.environment === 'scene'" class="ml-1"><v-icon text="Play" size="14" <v-chip size="x-small" v-else-if="scene.environment === 'scene'" class="ml-1"><v-icon text="Play" size="14"
class="mr-1">mdi-gamepad-square</v-icon>Game Mode</v-chip> class="mr-1">mdi-gamepad-square</v-icon>Game Mode</v-chip>
<v-btn v-if="scene.environment === 'scene'" class="ml-1" @click="openSceneHistory()"><v-icon size="14" <v-tooltip :text="scene.scene_time" v-if="scene.scene_time !== undefined">
class="mr-1">mdi-playlist-star</v-icon>History</v-btn> <template v-slot:activator="{ props }">
<v-btn v-bind="props" v-if="scene.environment === 'scene'" class="ml-1" @click="openSceneHistory()"><v-icon size="14"
<v-chip size="x-small" v-if="scene.scene_time !== undefined"> class="mr-1">mdi-clock</v-icon>History</v-btn>
<v-icon>mdi-clock</v-icon> </template>
{{ scene.scene_time }} </v-tooltip>
</v-chip>
</v-toolbar-title> </v-toolbar-title>
<v-toolbar-title v-else> <v-toolbar-title v-else>
@@ -429,7 +424,7 @@ export default {
let agent = this.$refs.aiAgent.getActive(); let agent = this.$refs.aiAgent.getActive();
if (agent) { if (agent) {
return agent.name; return agent.label;
} }
return null; return null;
}, },
@@ -448,6 +443,14 @@ export default {
openAppConfig() { openAppConfig() {
this.$refs.appConfig.show(); this.$refs.appConfig.show();
}, },
uxErrorHandler(error) {
this.errorNotification = true;
this.errorMessage = error;
},
sceneStartedLoading() {
this.loading = true;
this.sceneActive = false;
}
} }
} }
</script> </script>

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@@ -2,10 +2,8 @@
<v-list-subheader class="text-uppercase"> <v-list-subheader class="text-uppercase">
<v-icon class="mr-1">mdi-earth</v-icon>World <v-icon class="mr-1">mdi-earth</v-icon>World
<v-progress-circular class="ml-1 mr-3" size="14" v-if="requesting" indeterminate color="primary"></v-progress-circular> <v-progress-circular class="ml-1 mr-3" size="14" v-if="requesting" indeterminate color="primary"></v-progress-circular>
<v-btn v-else size="x-small" class="mr-1" v-bind="props" variant="tonal" density="comfortable" rounded="sm" @click.stop="refresh()" icon="mdi-refresh"></v-btn> <v-btn v-else :disabled="isInputDisabled()" size="x-small" class="mr-1" variant="tonal" density="comfortable" rounded="sm" @click.stop="refresh()" icon="mdi-refresh"></v-btn>
</v-list-subheader> </v-list-subheader>
<div ref="charactersContainer"> <div ref="charactersContainer">
<v-expansion-panels density="compact" v-for="(character,name) in characters" :key="name"> <v-expansion-panels density="compact" v-for="(character,name) in characters" :key="name">
@@ -85,6 +83,7 @@ export default {
items: {}, items: {},
location: null, location: null,
requesting: false, requesting: false,
sceneTime: null,
} }
}, },
@@ -94,6 +93,7 @@ export default {
'setWaitingForInput', 'setWaitingForInput',
'openCharacterSheet', 'openCharacterSheet',
'characterSheet', 'characterSheet',
'isInputDisabled',
], ],
methods: { methods: {
@@ -127,6 +127,8 @@ export default {
this.items = data.data.items; this.items = data.data.items;
this.location = data.data.location; this.location = data.data.location;
this.requesting = (data.status==="requested") this.requesting = (data.status==="requested")
} else if (data.type == "scene_status") {
this.sceneTime = data.data.scene_time;
} }
}, },
}, },

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@@ -0,0 +1,2 @@
SYSTEM: {{ system_message }}
USER: {{ set_response(prompt, "\nASSISTANT: ") }}

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@@ -0,0 +1,4 @@
{{ system_message }}
### Instruction:
{{ set_response(prompt, "\n\n### Response:\n") }}

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@@ -0,0 +1,4 @@
<|im_start|>system
{{ system_message }}<|im_end|>
<|im_start|>user
{{ set_response(prompt, "<|im_end|>\n<|im_start|>assistant\n") }}

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@@ -0,0 +1,2 @@
SYSTEM: {{ system_message }}
USER: {{ set_response(prompt, "\nASSISTANT: ") }}

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@@ -0,0 +1,2 @@
SYSTEM: {{ system_message }}
USER: {{ set_response(prompt, "\nASSISTANT: ") }}

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@@ -0,0 +1,4 @@
{{ system_message }}
### Instruction:
{{ set_response(prompt, "\n\n### Response:\n") }}

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@@ -0,0 +1 @@
User: {{ system_message }} {{ set_response(prompt, "\nAssistant: ") }}

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@@ -0,0 +1 @@
GPT4 Correct System: {{ system_message }}<|end_of_turn|>GPT4 Correct User: {{ set_response(prompt, "<|end_of_turn|>GPT4 Correct Assistant:") }}

0
tests/conftest.py Normal file
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@@ -0,0 +1,21 @@
import pytest
from talemate.util import ensure_dialog_format
@pytest.mark.parametrize("input, expected", [
('Hello how are you?', 'Hello how are you?'),
('"Hello how are you?"', '"Hello how are you?"'),
('"Hello how are you?" he asks "I am fine"', '"Hello how are you?" *he asks* "I am fine"'),
('Hello how are you? *he asks* I am fine', '"Hello how are you?" *he asks* "I am fine"'),
('Hello how are you?" *he asks* I am fine', '"Hello how are you?" *he asks* "I am fine"'),
('Hello how are you?" *he asks I am fine', '"Hello how are you?" *he asks I am fine*'),
('Hello how are you?" *he asks* "I am fine" *', '"Hello how are you?" *he asks* "I am fine"'),
('"Hello how are you *he asks* I am fine"', '"Hello how are you" *he asks* "I am fine"'),
('This is a string without any markers', 'This is a string without any markers'),
('This is a string with an ending quote"', '"This is a string with an ending quote"'),
('This is a string with an ending asterisk*', '*This is a string with an ending asterisk*'),
('"Mixed markers*', '*Mixed markers*'),
])
def test_dialogue_cleanup(input, expected):
assert ensure_dialog_format(input) == expected

38
tests/test_isodate.py Normal file
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@@ -0,0 +1,38 @@
from talemate.util import (
iso8601_add,
iso8601_correct_duration,
iso8601_diff,
iso8601_diff_to_human,
iso8601_duration_to_human,
parse_duration_to_isodate_duration,
timedelta_to_duration,
duration_to_timedelta,
isodate
)
def test_isodate_utils():
date1 = "P11MT15M"
date2 = "PT1S"
duration1= parse_duration_to_isodate_duration(date1)
assert duration1.months == 11
assert duration1.tdelta.seconds == 900
duration2 = parse_duration_to_isodate_duration(date2)
assert duration2.seconds == 1
timedelta1 = duration_to_timedelta(duration1)
assert timedelta1.seconds == 900
assert timedelta1.days == 11*30, timedelta1.days
timedelta2 = duration_to_timedelta(duration2)
assert timedelta2.seconds == 1
parsed = parse_duration_to_isodate_duration("P11MT14M59S")
assert iso8601_diff(date1, date2) == parsed, parsed
assert iso8601_duration_to_human(date1) == "11 Months and 15 Minutes ago", iso8601_duration_to_human(date1)
assert iso8601_duration_to_human(date2) == "1 Second ago", iso8601_duration_to_human(date2)
assert iso8601_duration_to_human(iso8601_diff(date1, date2)) == "11 Months, 14 Minutes and 59 Seconds ago", iso8601_duration_to_human(iso8601_diff(date1, date2))