diff --git a/install.bat b/install.bat index a7289e3d..b4c1f910 100644 --- a/install.bat +++ b/install.bat @@ -7,10 +7,10 @@ REM activate the virtual environment call talemate_env\Scripts\activate REM install poetry -python -m pip install poetry "rapidfuzz>=3" -U +python -m pip install "poetry==1.7.1" "rapidfuzz>=3" -U REM use poetry to install dependencies -poetry install +python -m poetry install REM copy config.example.yaml to config.yaml only if config.yaml doesn't exist IF NOT EXIST config.yaml copy config.example.yaml config.yaml diff --git a/poetry.lock b/poetry.lock index 14e3509c..4293a491 100644 --- a/poetry.lock +++ b/poetry.lock @@ -344,17 +344,17 @@ files = [ [[package]] name = "boto3" -version = "1.28.83" +version = "1.28.84" description = "The AWS SDK for Python" optional = false python-versions = ">= 3.7" files = [ - {file = "boto3-1.28.83-py3-none-any.whl", hash = "sha256:1d10691911c4b8b9443d3060257ba32b68b6e3cad0eebbb9f69fd1c52a78417f"}, - {file = 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"!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7" +files = [ + {file = "pyasn1_modules-0.3.0-py2.py3-none-any.whl", hash = "sha256:d3ccd6ed470d9ffbc716be08bd90efbd44d0734bc9303818f7336070984a162d"}, + {file = "pyasn1_modules-0.3.0.tar.gz", hash = "sha256:5bd01446b736eb9d31512a30d46c1ac3395d676c6f3cafa4c03eb54b9925631c"}, +] + +[package.dependencies] +pyasn1 = ">=0.4.6,<0.6.0" + [[package]] name = "pydantic" version = "2.4.2" @@ -2488,6 +2733,24 @@ urllib3 = ">=1.21.1,<3" socks = ["PySocks (>=1.5.6,!=1.5.7)"] use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] +[[package]] +name = "requests-oauthlib" +version = "1.3.1" +description = "OAuthlib authentication support for Requests." +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +files = [ + {file = "requests-oauthlib-1.3.1.tar.gz", hash = "sha256:75beac4a47881eeb94d5ea5d6ad31ef88856affe2332b9aafb52c6452ccf0d7a"}, + {file = "requests_oauthlib-1.3.1-py2.py3-none-any.whl", hash = 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succeeds" +optional = false +python-versions = ">=3.7" +files = [ + {file = "tenacity-8.2.3-py3-none-any.whl", hash = "sha256:ce510e327a630c9e1beaf17d42e6ffacc88185044ad85cf74c0a8887c6a0f88c"}, + {file = "tenacity-8.2.3.tar.gz", hash = "sha256:5398ef0d78e63f40007c1fb4c0bff96e1911394d2fa8d194f77619c05ff6cc8a"}, +] + +[package.extras] +doc = ["reno", "sphinx", "tornado (>=4.5)"] + [[package]] name = "thefuzz" version = "0.20.0" @@ -3415,20 +3706,19 @@ files = [ [[package]] name = "urllib3" -version = "2.0.7" +version = "1.26.18" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false -python-versions = ">=3.7" +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" files = [ - {file = "urllib3-2.0.7-py3-none-any.whl", hash = "sha256:fdb6d215c776278489906c2f8916e6e7d4f5a9b602ccbcfdf7f016fc8da0596e"}, - {file = "urllib3-2.0.7.tar.gz", hash = "sha256:c97dfde1f7bd43a71c8d2a58e369e9b2bf692d1334ea9f9cae55add7d0dd0f84"}, + 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API options" +optional = false +python-versions = ">=3.8" +files = [ + {file = "websocket-client-1.6.4.tar.gz", hash = "sha256:b3324019b3c28572086c4a319f91d1dcd44e6e11cd340232978c684a7650d0df"}, + {file = "websocket_client-1.6.4-py3-none-any.whl", hash = "sha256:084072e0a7f5f347ef2ac3d8698a5e0b4ffbfcab607628cadabc650fc9a83a24"}, +] + +[package.extras] +docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"] +optional = ["python-socks", "wsaccel"] +test = ["websockets"] + [[package]] name = "websockets" version = "11.0.3" @@ -3832,7 +4138,22 @@ files = [ idna = ">=2.0" multidict = ">=4.0" +[[package]] +name = "zipp" +version = "3.17.0" +description = "Backport of pathlib-compatible object wrapper for zip files" +optional = false +python-versions = ">=3.8" +files = [ + {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"}, + {file = "zipp-3.17.0.tar.gz", hash = "sha256:84e64a1c28cf7e91ed2078bb8cc8c259cb19b76942096c8d7b84947690cabaf0"}, +] + +[package.extras] +docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"] +testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"] + [metadata] lock-version = "2.0" python-versions = ">=3.10,<4.0" -content-hash = "13dc0c939ece1591caa09211c5a29a839cb63b5a921797ab225fc723b66e0d67" +content-hash = "8d77eeb6bba3c389345f461840b5257716a397e3ecaebc735a26b06e27361a1a" diff --git a/pyproject.toml b/pyproject.toml index 8db2864e..99c25be6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.masonry.api" [tool.poetry] name = "talemate" -version = "0.12.0" +version = "0.13.0" description = "AI-backed roleplay and narrative tools" authors = ["FinalWombat"] license = "GNU Affero General Public License v3.0" @@ -39,9 +39,9 @@ thefuzz = ">=0.20.0" tiktoken = ">=0.5.1" # ChromaDB -chromadb = ">=0.4,<1" +chromadb = ">=0.4.17,<1" InstructorEmbedding = "^1.0.1" -torch = ">=2.0.0, !=2.0.1" +torch = ">=2.1.0" sentence-transformers="^2.2.2" [tool.poetry.dev-dependencies] diff --git a/reinstall.bat b/reinstall.bat index 7fa86d6a..8db95527 100644 --- a/reinstall.bat +++ b/reinstall.bat @@ -9,7 +9,7 @@ REM activate the virtual environment call talemate_env\Scripts\activate REM install poetry -python -m pip install poetry "rapidfuzz>=3" -U +python -m pip install "poetry==1.7.1" "rapidfuzz>=3" -U REM use poetry to install dependencies python -m poetry install diff --git a/src/talemate/__init__.py b/src/talemate/__init__.py index 3407e433..379b832d 100644 --- a/src/talemate/__init__.py +++ b/src/talemate/__init__.py @@ -2,4 +2,4 @@ from .agents import Agent from .client import TextGeneratorWebuiClient from .tale_mate import * -VERSION = "0.12.0" +VERSION = "0.13.0" diff --git a/src/talemate/agents/memory.py b/src/talemate/agents/memory.py index 356a961b..51a4edd4 100644 --- a/src/talemate/agents/memory.py +++ b/src/talemate/agents/memory.py @@ -328,9 +328,13 @@ class ChromaDBMemoryAgent(MemoryAgent): model_name=instructor_model, device=instructor_device ) + log.info("chromadb", status="embedding function ready") + self.db = self.db_client.get_or_create_collection( collection_name, embedding_function=ef ) + + log.info("chromadb", status="instructor db ready") else: log.info("chromadb", status="using default embeddings") self.db = self.db_client.get_or_create_collection(collection_name) @@ -461,6 +465,7 @@ class ChromaDBMemoryAgent(MemoryAgent): #import json #print(json.dumps(_results["ids"], indent=2)) + #print(json.dumps(_results["distances"], indent=2)) results = [] diff --git a/src/talemate/agents/narrator.py b/src/talemate/agents/narrator.py index 931ebde7..8d4eb069 100644 --- a/src/talemate/agents/narrator.py +++ b/src/talemate/agents/narrator.py @@ -2,6 +2,7 @@ from __future__ import annotations from typing import TYPE_CHECKING, Callable, List, Optional, Union import structlog +import random import talemate.util as util from talemate.emit import emit import talemate.emit.async_signals @@ -9,14 +10,23 @@ from talemate.prompts import Prompt from talemate.agents.base import set_processing, Agent, AgentAction, AgentActionConfig from talemate.agents.world_state import TimePassageEmission from talemate.scene_message import NarratorMessage +from talemate.events import GameLoopActorIterEvent import talemate.client as client from .registry import register +if TYPE_CHECKING: + from talemate.tale_mate import Actor, Player, Character + log = structlog.get_logger("talemate.agents.narrator") @register() class NarratorAgent(Agent): + + """ + Handles narration of the story + """ + agent_type = "narrator" verbose_name = "Narrator" @@ -27,31 +37,78 @@ class NarratorAgent(Agent): ): self.client = client + # agent actions + self.actions = { - "narrate_time_passage": AgentAction(enabled=False, 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( + enabled=True, + label="Narrate Dialogue", + description="Narrator will get a chance to narrate after every line of dialogue", + config = { + "ai_dialog": AgentActionConfig( + type="number", + label="AI Dialogue", + description="Chance to narrate after every line of dialogue, 1 = always, 0 = never", + value=0.3, + min=0.0, + max=1.0, + step=0.1, + ), + "player_dialog": AgentActionConfig( + type="number", + label="Player Dialogue", + description="Chance to narrate after every line of dialogue, 1 = always, 0 = never", + value=0.3, + min=0.0, + max=1.0, + step=0.1, + ), + } + ), } def clean_result(self, result): + """ + Cleans the result of a narration + """ + result = result.strip().strip(":").strip() if "#" in result: result = result.split("#")[0] + + character_names = [c.name for c in self.scene.get_characters()] + cleaned = [] for line in result.split("\n"): - if ":" in line.strip(): - break + for character_name in character_names: + if line.startswith(f"{character_name}:"): + break cleaned.append(line) - return "\n".join(cleaned) + result = "\n".join(cleaned) + #result = util.strip_partial_sentences(result) + return result def connect(self, scene): + + """ + Connect to signals + """ + super().connect(scene) talemate.emit.async_signals.get("agent.world_state.time").connect(self.on_time_passage) + talemate.emit.async_signals.get("game_loop_actor_iter").connect(self.on_dialog) async def on_time_passage(self, event:TimePassageEmission): + """ + Handles time passage narration, if enabled + """ + if not self.actions["narrate_time_passage"].enabled: return @@ -59,6 +116,31 @@ class NarratorAgent(Agent): narrator_message = NarratorMessage(response, source=f"narrate_time_passage:{event.duration};{event.narrative}") emit("narrator", narrator_message) self.scene.push_history(narrator_message) + + async def on_dialog(self, event:GameLoopActorIterEvent): + + """ + Handles dialogue narration, if enabled + """ + + if not self.actions["narrate_dialogue"].enabled: + return + + narrate_on_ai_chance = random.random() < self.actions["narrate_dialogue"].config["ai_dialog"].value + 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 + + if not event.actor.character.is_player and not narrate_on_ai_chance: + return + + response = await self.narrate_after_dialogue(event.actor.character) + narrator_message = NarratorMessage(response, source=f"narrate_dialogue:{event.actor.character.name}") + emit("narrator", narrator_message) + self.scene.push_history(narrator_message) @set_processing async def narrate_scene(self): @@ -155,8 +237,9 @@ class NarratorAgent(Agent): "as_narrative": as_narrative, } ) - + log.info("narrate_query", response=response) response = self.clean_result(response.strip()) + log.info("narrate_query (after clean)", response=response) if as_narrative: response = f"*{response}*" @@ -265,4 +348,30 @@ class NarratorAgent(Agent): response = self.clean_result(response.strip()) response = f"*{response}*" + return response + + + @set_processing + async def narrate_after_dialogue(self, character:Character): + """ + Narrate after a line of dialogue + """ + + response = await Prompt.request( + "narrator.narrate-after-dialogue", + self.client, + "narrate", + vars = { + "scene": self.scene, + "max_tokens": self.client.max_token_length, + "character": character, + "last_line": str(self.scene.history[-1]) + } + ) + + log.info("narrate_after_dialogue", response=response) + + response = self.clean_result(response.strip().strip("*")) + response = f"*{response}*" + return response \ No newline at end of file diff --git a/src/talemate/agents/world_state.py b/src/talemate/agents/world_state.py index c7f51bfd..2161697e 100644 --- a/src/talemate/agents/world_state.py +++ b/src/talemate/agents/world_state.py @@ -8,6 +8,7 @@ import talemate.util as util from talemate.prompts import Prompt from talemate.scene_message import DirectorMessage, TimePassageMessage from talemate.emit import emit +from talemate.events import GameLoopEvent from .base import Agent, set_processing, AgentAction, AgentActionConfig, AgentEmission from .registry import register @@ -16,9 +17,6 @@ import structlog import isodate import time -if TYPE_CHECKING: - from talemate.agents.conversation import ConversationAgentEmission - log = structlog.get_logger("talemate.agents.world_state") @@ -74,7 +72,7 @@ class WorldStateAgent(Agent): def connect(self, scene): super().connect(scene) - talemate.emit.async_signals.get("agent.conversation.generated").connect(self.on_conversation_generated) + talemate.emit.async_signals.get("game_loop").connect(self.on_game_loop) async def advance_time(self, duration:str, narrative:str=None): """ @@ -96,7 +94,7 @@ class WorldStateAgent(Agent): ) - async def on_conversation_generated(self, emission:ConversationAgentEmission): + async def on_game_loop(self, emission:GameLoopEvent): """ Called when a conversation is generated """ @@ -104,8 +102,7 @@ class WorldStateAgent(Agent): if not self.enabled: return - for _ in emission.generation: - await self.update_world_state() + await self.update_world_state() async def update_world_state(self): @@ -230,7 +227,7 @@ class WorldStateAgent(Agent): ): response = await Prompt.request( - "world_state.analyze-and-follow-instruction", + "world_state.analyze-text-and-follow-instruction", self.client, "analyze_freeform", vars = { diff --git a/src/talemate/client/__init__.py b/src/talemate/client/__init__.py index 062e9b1e..3173210f 100644 --- a/src/talemate/client/__init__.py +++ b/src/talemate/client/__init__.py @@ -1,4 +1,6 @@ +import os from talemate.client.openai import OpenAIClient from talemate.client.registry import CLIENT_CLASSES, get_client_class, register from talemate.client.textgenwebui import TextGeneratorWebuiClient -import talemate.client.runpod \ No newline at end of file +from talemate.client.lmstudio import LMStudioClient +import talemate.client.runpod diff --git a/src/talemate/client/base.py b/src/talemate/client/base.py new file mode 100644 index 00000000..dd3a8c13 --- /dev/null +++ b/src/talemate/client/base.py @@ -0,0 +1,349 @@ +""" +A unified client base, based on the openai API +""" +import copy +import random +import time +from typing import Callable + +import structlog +import logging +from openai import AsyncOpenAI + +from talemate.emit import emit +import talemate.instance as instance +import talemate.client.presets as presets +import talemate.client.system_prompts as system_prompts +import talemate.util as util +from talemate.client.context import client_context_attribute +from talemate.client.model_prompts import model_prompt + + +# Set up logging level for httpx to WARNING to suppress debug logs. +logging.getLogger('httpx').setLevel(logging.WARNING) + +REMOTE_SERVICES = [ + # TODO: runpod.py should add this to the list + ".runpod.net" +] + +STOPPING_STRINGS = ["<|im_end|>", ""] + +class ClientBase: + + api_url: str + model_name: str + name:str = None + enabled: bool = True + current_status: str = None + max_token_length: int = 4096 + randomizable_inference_parameters: list[str] = ["temperature"] + processing: bool = False + connected: bool = False + conversation_retries: int = 5 + + client_type = "base" + + + def __init__( + self, + api_url: str, + name = None, + **kwargs, + ): + self.api_url = api_url + self.name = name or self.client_type + self.log = structlog.get_logger(f"client.{self.client_type}") + self.set_client() + + def __str__(self): + return f"{self.client_type}Client[{self.api_url}][{self.model_name or ''}]" + + def set_client(self): + self.client = AsyncOpenAI(base_url=self.api_url, api_key="sk-1111") + + def prompt_template(self, sys_msg, prompt): + + """ + Applies the appropriate prompt template for the model. + """ + + if not self.model_name: + self.log.warning("prompt template not applied", reason="no model loaded") + return f"{sys_msg}\n{prompt}" + + return model_prompt(self.model_name, sys_msg, prompt) + + def reconfigure(self, **kwargs): + + """ + Reconfigures the client. + + Keyword Arguments: + + - api_url: the API URL to use + - max_token_length: the max token length to use + - enabled: whether the client is enabled + """ + + if "api_url" in kwargs: + self.api_url = kwargs["api_url"] + + if "max_token_length" in kwargs: + self.max_token_length = kwargs["max_token_length"] + + if "enabled" in kwargs: + self.enabled = bool(kwargs["enabled"]) + + + def toggle_disabled_if_remote(self): + + """ + If the client is targeting a remote recognized service, this + will disable the client. + """ + + for service in REMOTE_SERVICES: + if service in self.api_url: + if self.enabled: + self.log.warn("remote service unreachable, disabling client", client=self.name) + self.enabled = False + + return True + + return False + + + def get_system_message(self, kind: str) -> str: + + """ + Returns the appropriate system message for the given kind of generation + + Arguments: + + - kind: the kind of generation + """ + + # TODO: make extensible + + if "narrate" in kind: + return system_prompts.NARRATOR + if "story" in kind: + return system_prompts.NARRATOR + if "director" in kind: + return system_prompts.DIRECTOR + if "create" in kind: + return system_prompts.CREATOR + if "roleplay" in kind: + return system_prompts.ROLEPLAY + if "conversation" in kind: + return system_prompts.ROLEPLAY + if "editor" in kind: + return system_prompts.EDITOR + if "world_state" in kind: + return system_prompts.WORLD_STATE + if "analyst" in kind: + return system_prompts.ANALYST + if "analyze" in kind: + return system_prompts.ANALYST + + return system_prompts.BASIC + + + def emit_status(self, processing: bool = None): + + """ + Sets and emits the client status. + """ + + if processing is not None: + self.processing = processing + + if not self.enabled: + status = "disabled" + model_name = "Disabled" + elif not self.connected: + status = "error" + model_name = "Could not connect" + elif self.model_name: + status = "busy" if self.processing else "idle" + model_name = self.model_name + else: + model_name = "No model loaded" + status = "warning" + + status_change = status != self.current_status + self.current_status = status + + emit( + "client_status", + message=self.client_type, + id=self.name, + details=model_name, + status=status, + ) + + if status_change: + instance.emit_agent_status_by_client(self) + + + async def get_model_name(self): + models = await self.client.models.list() + try: + return models.data[0].id + except IndexError: + return None + + async def status(self): + """ + Send a request to the API to retrieve the loaded AI model name. + Raises an error if no model name is returned. + :return: None + """ + if self.processing: + return + + if not self.enabled: + self.connected = False + self.emit_status() + return + + try: + self.model_name = await self.get_model_name() + except Exception as e: + self.log.warning("client status error", e=e, client=self.name) + self.model_name = None + self.connected = False + self.toggle_disabled_if_remote() + self.emit_status() + return + + self.connected = True + + if not self.model_name or self.model_name == "None": + self.log.warning("client model not loaded", client=self) + self.emit_status() + return + + self.emit_status() + + + def generate_prompt_parameters(self, kind:str): + parameters = {} + self.tune_prompt_parameters( + presets.configure(parameters, kind, self.max_token_length), + kind + ) + return parameters + + def tune_prompt_parameters(self, parameters:dict, kind:str): + parameters["stream"] = False + if client_context_attribute("nuke_repetition") > 0.0 and self.jiggle_enabled_for(kind): + self.jiggle_randomness(parameters, offset=client_context_attribute("nuke_repetition")) + + fn_tune_kind = getattr(self, f"tune_prompt_parameters_{kind}", None) + if fn_tune_kind: + fn_tune_kind(parameters) + + def tune_prompt_parameters_conversation(self, parameters:dict): + conversation_context = client_context_attribute("conversation") + parameters["max_tokens"] = conversation_context.get("length", 96) + + dialog_stopping_strings = [ + f"{character}:" for character in conversation_context["other_characters"] + ] + + if "extra_stopping_strings" in parameters: + parameters["extra_stopping_strings"] += dialog_stopping_strings + else: + parameters["extra_stopping_strings"] = dialog_stopping_strings + + + async def generate(self, prompt:str, parameters:dict, kind:str): + + """ + Generates text from the given prompt and parameters. + """ + + self.log.debug("generate", prompt=prompt[:128]+" ...", parameters=parameters) + + try: + response = await self.client.completions.create(prompt=prompt.strip(), **parameters) + return response.get("choices", [{}])[0].get("text", "") + except Exception as e: + self.log.error("generate error", e=e) + return "" + + async def send_prompt( + self, prompt: str, kind: str = "conversation", finalize: Callable = lambda x: x + ) -> str: + """ + Send a prompt to the AI and return its response. + :param prompt: The text prompt to send. + :return: The AI's response text. + """ + + try: + self.emit_status(processing=True) + await self.status() + + prompt_param = self.generate_prompt_parameters(kind) + + finalized_prompt = self.prompt_template(self.get_system_message(kind), prompt).strip() + prompt_param = finalize(prompt_param) + + token_length = self.count_tokens(finalized_prompt) + + + time_start = time.time() + 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) + response = await self.generate(finalized_prompt, prompt_param, kind) + + time_end = time.time() + + # stopping strings sometimes get appended to the end of the response anyways + # split the response by the first stopping string and take the first part + + + for stopping_string in STOPPING_STRINGS + extra_stopping_strings: + if stopping_string in response: + response = response.split(stopping_string)[0] + break + + emit("prompt_sent", data={ + "kind": kind, + "prompt": finalized_prompt, + "response": response, + "prompt_tokens": token_length, + "response_tokens": self.count_tokens(response), + "time": time_end - time_start, + }) + + return response + finally: + self.emit_status(processing=False) + + def count_tokens(self, content:str): + return util.count_tokens(content) + + def jiggle_randomness(self, prompt_config:dict, offset:float=0.3) -> dict: + """ + adjusts temperature and repetition_penalty + by random values using the base value as a center + """ + + temp = prompt_config["temperature"] + min_offset = offset * 0.3 + prompt_config["temperature"] = random.uniform(temp + min_offset, temp + offset) + + def jiggle_enabled_for(self, kind:str): + + if kind in ["conversation", "story"]: + return True + + if kind.startswith("narrate"): + return True + + return False \ No newline at end of file diff --git a/src/talemate/client/lmstudio.py b/src/talemate/client/lmstudio.py new file mode 100644 index 00000000..4a546afb --- /dev/null +++ b/src/talemate/client/lmstudio.py @@ -0,0 +1,56 @@ +from talemate.client.base import ClientBase +from talemate.client.registry import register + +from openai import AsyncOpenAI + + +@register() +class LMStudioClient(ClientBase): + + client_type = "lmstudio" + conversation_retries = 5 + + def set_client(self): + self.client = AsyncOpenAI(base_url=self.api_url+"/v1", api_key="sk-1111") + + def tune_prompt_parameters(self, parameters:dict, kind:str): + super().tune_prompt_parameters(parameters, kind) + + keys = list(parameters.keys()) + + valid_keys = ["temperature", "top_p"] + + for key in keys: + if key not in valid_keys: + del parameters[key] + + + async def get_model_name(self): + model_name = await super().get_model_name() + + # model name comes back as a file path, so we need to extract the model name + # the path could be windows or linux so it needs to handle both backslash and forward slash + + if model_name: + model_name = model_name.replace("\\", "/").split("/")[-1] + + return model_name + + async def generate(self, prompt:str, parameters:dict, kind:str): + + """ + Generates text from the given prompt and parameters. + """ + human_message = {'role': 'user', 'content': prompt.strip()} + + self.log.debug("generate", prompt=prompt[:128]+" ...", parameters=parameters) + + try: + response = await self.client.chat.completions.create( + model=self.model_name, messages=[human_message], **parameters + ) + + return response.choices[0].message.content + except Exception as e: + self.log.error("generate error", e=e) + return "" \ No newline at end of file diff --git a/src/talemate/client/openai.py b/src/talemate/client/openai.py index f7290fd7..ea3bb60e 100644 --- a/src/talemate/client/openai.py +++ b/src/talemate/client/openai.py @@ -1,10 +1,9 @@ -import asyncio import os -import time -from typing import Callable - +import json from openai import AsyncOpenAI + +from talemate.client.base import ClientBase from talemate.client.registry import register from talemate.emit import emit from talemate.config import load_config @@ -15,10 +14,9 @@ import tiktoken __all__ = [ "OpenAIClient", ] - log = structlog.get_logger("talemate") -def num_tokens_from_messages(messages, model="gpt-3.5-turbo-0613"): +def num_tokens_from_messages(messages:list[dict], model:str="gpt-3.5-turbo-0613"): """Return the number of tokens used by a list of messages.""" try: encoding = tiktoken.encoding_for_model(model) @@ -70,7 +68,7 @@ def num_tokens_from_messages(messages, model="gpt-3.5-turbo-0613"): return num_tokens @register() -class OpenAIClient: +class OpenAIClient(ClientBase): """ OpenAI client for generating text. """ @@ -79,13 +77,10 @@ class OpenAIClient: conversation_retries = 0 def __init__(self, model="gpt-4-1106-preview", **kwargs): - self.name = kwargs.get("name", "openai") + self.model_name = model - self.last_token_length = 0 - self.max_token_length = 2048 - self.processing = False - self.current_status = "idle" self.config = load_config() + super().__init__(**kwargs) # if os.environ.get("OPENAI_API_KEY") is not set, look in the config file # and set it @@ -94,7 +89,7 @@ class OpenAIClient: if self.config.get("openai", {}).get("api_key"): os.environ["OPENAI_API_KEY"] = self.config["openai"]["api_key"] - self.set_client(model) + self.set_client() @property @@ -123,12 +118,14 @@ class OpenAIClient: status=status, ) - def set_client(self, model:str, max_token_length:int=None): + def set_client(self, max_token_length:int=None): if not self.openai_api_key: log.error("No OpenAI API key set") return + model = self.model_name + self.client = AsyncOpenAI() if model == "gpt-3.5-turbo": self.max_token_length = min(max_token_length or 4096, 4096) @@ -144,89 +141,72 @@ class OpenAIClient: def reconfigure(self, **kwargs): if "model" in kwargs: self.model_name = kwargs["model"] - self.set_client(self.model_name, kwargs.get("max_token_length")) + self.set_client(kwargs.get("max_token_length")) + + def count_tokens(self, content: str): + return num_tokens_from_messages([{"content": content}], model=self.model_name) async def status(self): self.emit_status() - def get_system_message(self, kind: str) -> str: - - if "narrate" in kind: - return system_prompts.NARRATOR - if "story" in kind: - return system_prompts.NARRATOR - if "director" in kind: - return system_prompts.DIRECTOR - if "create" in kind: - return system_prompts.CREATOR - if "roleplay" in kind: - return system_prompts.ROLEPLAY - if "conversation" in kind: - return system_prompts.ROLEPLAY - if "editor" in kind: - return system_prompts.EDITOR - if "world_state" in kind: - return system_prompts.WORLD_STATE - if "analyst" in kind: - return system_prompts.ANALYST - if "analyze" in kind: - return system_prompts.ANALYST - - return system_prompts.BASIC - - async def send_prompt( - self, prompt: str, kind: str = "conversation", finalize: Callable = lambda x: x - ) -> str: - - right = "" - opts = {} - + + def prompt_template(self, system_message:str, prompt:str): # only gpt-4-1106-preview supports json_object response coersion - supports_json_object = self.model_name in ["gpt-4-1106-preview"] if "<|BOT|>" in prompt: _, right = prompt.split("<|BOT|>", 1) if right: prompt = prompt.replace("<|BOT|>", "\nContinue this response: ") - expected_response = prompt.split("\nContinue this response: ")[1].strip() - if expected_response.startswith("{") and supports_json_object: - opts["response_format"] = {"type": "json_object"} else: prompt = prompt.replace("<|BOT|>", "") - self.emit_status(processing=True) - await asyncio.sleep(0.1) + return prompt - sys_message = {'role': 'system', 'content': self.get_system_message(kind)} + def tune_prompt_parameters(self, parameters:dict, kind:str): + super().tune_prompt_parameters(parameters, kind) - human_message = {'role': 'user', 'content': prompt} + keys = list(parameters.keys()) + + valid_keys = ["temperature", "top_p"] + + for key in keys: + if key not in valid_keys: + del parameters[key] - log.debug("openai send", kind=kind, sys_message=sys_message, opts=opts) - - time_start = time.time() - - response = await self.client.chat.completions.create(model=self.model_name, messages=[sys_message, human_message], **opts) + async def generate(self, prompt:str, parameters:dict, kind:str): - time_end = time.time() + """ + Generates text from the given prompt and parameters. + """ - response = response.choices[0].message.content + # only gpt-4-1106-preview supports json_object response coersion + supports_json_object = self.model_name in ["gpt-4-1106-preview"] + right = None + try: + _, right = prompt.split("\nContinue this response: ") + expected_response = right.strip() + if expected_response.startswith("{") and supports_json_object: + parameters["response_format"] = {"type": "json_object"} + except IndexError: + pass - if right and response.startswith(right): - response = response[len(right):].strip() + human_message = {'role': 'user', 'content': prompt.strip()} + system_message = {'role': 'system', 'content': self.get_system_message(kind)} + + self.log.debug("generate", prompt=prompt[:128]+" ...", parameters=parameters) + + try: + response = await self.client.chat.completions.create( + model=self.model_name, messages=[system_message, human_message], **parameters + ) - if kind == "conversation": - response = response.replace("\n", " ").strip() - - log.debug("openai response", response=response) - - emit("prompt_sent", data={ - "kind": kind, - "prompt": prompt, - "response": response, - "prompt_tokens": num_tokens_from_messages([sys_message, human_message], model=self.model_name), - "response_tokens": num_tokens_from_messages([{"role": "assistant", "content": response}], model=self.model_name), - "time": time_end - time_start, - }) - - self.emit_status(processing=False) - return response + response = response.choices[0].message.content + + if right and response.startswith(right): + response = response[len(right):].strip() + + return response + + except Exception as e: + self.log.error("generate error", e=e) + return "" \ No newline at end of file diff --git a/src/talemate/client/presets.py b/src/talemate/client/presets.py new file mode 100644 index 00000000..3e9f8959 --- /dev/null +++ b/src/talemate/client/presets.py @@ -0,0 +1,163 @@ +__all__ = [ + "configure", + "set_max_tokens", + "set_preset", + "preset_for_kind", + "max_tokens_for_kind", + "PRESET_TALEMATE_CONVERSATION", + "PRESET_TALEMATE_CREATOR", + "PRESET_LLAMA_PRECISE", + "PRESET_DIVINE_INTELLECT", + "PRESET_SIMPLE_1", +] + +PRESET_TALEMATE_CONVERSATION = { + "temperature": 0.65, + "top_p": 0.47, + "top_k": 42, + "repetition_penalty": 1.18, + "repetition_penalty_range": 2048, +} + +PRESET_TALEMATE_CREATOR = { + "temperature": 0.7, + "top_p": 0.9, + "top_k": 20, + "repetition_penalty": 1.15, + "repetition_penalty_range": 512, +} + +PRESET_LLAMA_PRECISE = { + 'temperature': 0.7, + 'top_p': 0.1, + 'top_k': 40, + 'repetition_penalty': 1.18, +} + +PRESET_DIVINE_INTELLECT = { + 'temperature': 1.31, + 'top_p': 0.14, + 'top_k': 49, + "repetition_penalty_range": 1024, + 'repetition_penalty': 1.17, +} + +PRESET_SIMPLE_1 = { + "temperature": 0.7, + "top_p": 0.9, + "top_k": 20, + "repetition_penalty": 1.15, +} + +def configure(config:dict, kind:str, total_budget:int): + """ + Sets the config based on the kind of text to generate. + """ + set_preset(config, kind) + set_max_tokens(config, kind, total_budget) + return config + +def set_max_tokens(config:dict, kind:str, total_budget:int): + """ + Sets the max_tokens in the config based on the kind of text to generate. + """ + config["max_tokens"] = max_tokens_for_kind(kind, total_budget) + return config + +def set_preset(config:dict, kind:str): + """ + Sets the preset in the config based on the kind of text to generate. + """ + config.update(preset_for_kind(kind)) + +def preset_for_kind(kind: str): + if kind == "conversation": + return PRESET_TALEMATE_CONVERSATION + elif kind == "conversation_old": + return PRESET_TALEMATE_CONVERSATION # Assuming old conversation uses the same preset + elif kind == "conversation_long": + return PRESET_TALEMATE_CONVERSATION # Assuming long conversation uses the same preset + elif kind == "conversation_select_talking_actor": + return PRESET_TALEMATE_CONVERSATION # Assuming select talking actor uses the same preset + elif kind == "summarize": + return PRESET_LLAMA_PRECISE + elif kind == "analyze": + return PRESET_SIMPLE_1 + elif kind == "analyze_creative": + return PRESET_DIVINE_INTELLECT + elif kind == "analyze_long": + return PRESET_SIMPLE_1 # Assuming long analysis uses the same preset as simple + elif kind == "analyze_freeform": + return PRESET_LLAMA_PRECISE + elif kind == "analyze_freeform_short": + return PRESET_LLAMA_PRECISE # Assuming short freeform analysis uses the same preset as precise + elif kind == "narrate": + return PRESET_LLAMA_PRECISE + elif kind == "story": + return PRESET_DIVINE_INTELLECT + elif kind == "create": + return PRESET_TALEMATE_CREATOR + elif kind == "create_concise": + return PRESET_TALEMATE_CREATOR # Assuming concise creation uses the same preset as creator + elif kind == "create_precise": + return PRESET_LLAMA_PRECISE + elif kind == "director": + return PRESET_SIMPLE_1 + elif kind == "director_short": + return PRESET_SIMPLE_1 # Assuming short direction uses the same preset as simple + elif kind == "director_yesno": + return PRESET_SIMPLE_1 # Assuming yes/no direction uses the same preset as simple + elif kind == "edit_dialogue": + return PRESET_DIVINE_INTELLECT + elif kind == "edit_add_detail": + return PRESET_DIVINE_INTELLECT # Assuming adding detail uses the same preset as divine intellect + elif kind == "edit_fix_exposition": + return PRESET_DIVINE_INTELLECT # Assuming fixing exposition uses the same preset as divine intellect + else: + return PRESET_SIMPLE_1 # Default preset if none of the kinds match + +def max_tokens_for_kind(kind: str, total_budget: int): + if kind == "conversation": + return 75 # Example value, adjust as needed + elif kind == "conversation_old": + return 75 # Example value, adjust as needed + elif kind == "conversation_long": + return 300 # Example value, adjust as needed + elif kind == "conversation_select_talking_actor": + return 30 # Example value, adjust as needed + elif kind == "summarize": + return 500 # Example value, adjust as needed + elif kind == "analyze": + return 500 # Example value, adjust as needed + elif kind == "analyze_creative": + return 1024 # Example value, adjust as needed + elif kind == "analyze_long": + return 2048 # Example value, adjust as needed + elif kind == "analyze_freeform": + return 500 # Example value, adjust as needed + elif kind == "analyze_freeform_short": + return 10 # Example value, adjust as needed + elif kind == "narrate": + return 500 # Example value, adjust as needed + elif kind == "story": + return 300 # Example value, adjust as needed + elif kind == "create": + return min(1024, int(total_budget * 0.35)) # Example calculation, adjust as needed + elif kind == "create_concise": + return min(400, int(total_budget * 0.25)) # Example calculation, adjust as needed + elif kind == "create_precise": + return min(400, int(total_budget * 0.25)) # Example calculation, adjust as needed + elif kind == "director": + return min(600, int(total_budget * 0.25)) # Example calculation, adjust as needed + elif kind == "director_short": + return 25 # Example value, adjust as needed + elif kind == "director_yesno": + return 2 # Example value, adjust as needed + elif kind == "edit_dialogue": + return 100 # Example value, adjust as needed + elif kind == "edit_add_detail": + return 200 # Example value, adjust as needed + elif kind == "edit_fix_exposition": + return 1024 # Example value, adjust as needed + else: + return 150 # Default value if none of the kinds match \ No newline at end of file diff --git a/src/talemate/client/runpod.py b/src/talemate/client/runpod.py index 7d5bede9..ec594bb4 100644 --- a/src/talemate/client/runpod.py +++ b/src/talemate/client/runpod.py @@ -67,9 +67,9 @@ def _client_bootstrap(client_type: ClientType, pod): id = pod["id"] if client_type == ClientType.textgen: - api_url = f"https://{id}-5000.proxy.runpod.net/api" + api_url = f"https://{id}-5000.proxy.runpod.net" elif client_type == ClientType.automatic1111: - api_url = f"https://{id}-5000.proxy.runpod.net/api" + api_url = f"https://{id}-5000.proxy.runpod.net" return ClientBootstrap( client_type=client_type, diff --git a/src/talemate/client/textgenwebui.py b/src/talemate/client/textgenwebui.py index c96e96a6..31377dd4 100644 --- a/src/talemate/client/textgenwebui.py +++ b/src/talemate/client/textgenwebui.py @@ -1,735 +1,61 @@ -import asyncio -import random -import json -import copy -import structlog -import time -import httpx -from abc import ABC, abstractmethod -from typing import Callable, Union -import logging -import talemate.util as util +from talemate.client.base import ClientBase, STOPPING_STRINGS from talemate.client.registry import register -import talemate.client.system_prompts as system_prompts -from talemate.emit import Emission, emit -from talemate.client.context import client_context_attribute -from talemate.client.model_prompts import model_prompt - -import talemate.instance as instance - -log = structlog.get_logger(__name__) - -__all__ = [ - "TaleMateClient", - "RestApiTaleMateClient", - "TextGeneratorWebuiClient", -] - -# Set up logging level for httpx to WARNING to suppress debug logs. -logging.getLogger('httpx').setLevel(logging.WARNING) - -class DefaultContext(int): - pass - - -PRESET_TALEMATE_LEGACY = { - "temperature": 0.72, - "top_p": 0.73, - "top_k": 0, - "top_a": 0, - "repetition_penalty": 1.18, - "repetition_penalty_range": 2048, - "encoder_repetition_penalty": 1, - #"encoder_repetition_penalty": 1.2, - #"no_repeat_ngram_size": 2, - "do_sample": True, - "length_penalty": 1, -} - -PRESET_TALEMATE_CONVERSATION = { - "temperature": 0.65, - "top_p": 0.47, - "top_k": 42, - "typical_p": 1, - "top_a": 0, - "tfs": 1, - "epsilon_cutoff": 0, - "eta_cutoff": 0, - "repetition_penalty": 1.18, - "repetition_penalty_range": 2048, - "no_repeat_ngram_size": 0, - "penalty_alpha": 0, - "num_beams": 1, - "length_penalty": 1, - "min_length": 0, - "encoder_rep_pen": 1, - "do_sample": True, - "early_stopping": False, - "mirostat_mode": 0, - "mirostat_tau": 5, - "mirostat_eta": 0.1 -} - -PRESET_TALEMATE_CREATOR = { - "temperature": 0.7, - "top_p": 0.9, - "repetition_penalty": 1.15, - "repetition_penalty_range": 512, - "top_k": 20, - "do_sample": True, - "length_penalty": 1, -} - -PRESET_LLAMA_PRECISE = { - 'temperature': 0.7, - 'top_p': 0.1, - 'repetition_penalty': 1.18, - 'top_k': 40 -} - -PRESET_KOBOLD_GODLIKE = { - 'temperature': 0.7, - 'top_p': 0.5, - 'typical_p': 0.19, - 'repetition_penalty': 1.1, - "repetition_penalty_range": 1024, -} - -PRESET_DIVINE_INTELLECT = { - 'temperature': 1.31, - 'top_p': 0.14, - "repetition_penalty_range": 1024, - 'repetition_penalty': 1.17, - 'top_k': 49, - "mirostat_mode": 0, - "mirostat_tau": 5, - "mirostat_eta": 0.1, - "tfs": 1, -} - -PRESET_SIMPLE_1 = { - "temperature": 0.7, - "top_p": 0.9, - "repetition_penalty": 1.15, - "top_k": 20, -} - -def jiggle_randomness(prompt_config:dict, offset:float=0.3) -> dict: - """ - adjusts temperature and repetition_penalty - by random values using the base value as a center - """ - - temp = prompt_config["temperature"] - rep_pen = prompt_config["repetition_penalty"] - - copied_config = copy.deepcopy(prompt_config) - - min_offset = offset * 0.3 - - copied_config["temperature"] = random.uniform(temp + min_offset, temp + offset) - copied_config["repetition_penalty"] = random.uniform(rep_pen + min_offset * 0.3, rep_pen + offset * 0.3) - - return copied_config - - -class TaleMateClient: - """ - An abstract TaleMate client that can be implemented for different communication methods with the AI. - """ - def __init__( - self, - api_url: str, - max_token_length: Union[int, DefaultContext] = int.__new__( - DefaultContext, 2048 - ), - ): - self.api_url = api_url - self.name = "generic_client" - self.model_name = None - self.last_token_length = 0 - self.max_token_length = max_token_length - self.original_max_token_length = max_token_length - self.enabled = True - self.current_status = None - - @abstractmethod - def send_message(self, message: dict) -> str: - """ - Sends a message to the AI. Needs to be implemented by the subclass. - :param message: The message to be sent. - :return: The AI's response text. - """ - pass - - @abstractmethod - def send_prompt(self, prompt: str) -> str: - """ - Sends a prompt to the AI. Needs to be implemented by the subclass. - :param prompt: The text prompt to send. - :return: The AI's response text. - """ - pass - - def reconfigure(self, **kwargs): - if "api_url" in kwargs: - self.api_url = kwargs["api_url"] - - if "max_token_length" in kwargs: - self.max_token_length = kwargs["max_token_length"] - - if "enabled" in kwargs: - self.enabled = bool(kwargs["enabled"]) - - def remaining_tokens(self, context: Union[str, list]) -> int: - return self.max_token_length - util.count_tokens(context) - - - def prompt_template(self, sys_msg, prompt): - return model_prompt(self.model_name, sys_msg, prompt) - -class RESTTaleMateClient(TaleMateClient, ABC): - """ - A RESTful TaleMate client that connects to the REST API endpoint. - """ - - async def send_message(self, message: dict, url: str) -> str: - """ - Sends a message to the REST API and returns the AI's response. - :param message: The message to be sent. - :return: The AI's response text. - """ - - try: - async with httpx.AsyncClient() as client: - response = await client.post(url, json=message, timeout=None) - response_data = response.json() - return response_data["results"][0]["text"] - except KeyError: - return response_data["results"][0]["history"]["visible"][0][-1] +from openai import AsyncOpenAI +import httpx +import copy +import random @register() -class TextGeneratorWebuiClient(RESTTaleMateClient): - """ - Client that connects to the text-generatior-webui api - """ - +class TextGeneratorWebuiClient(ClientBase): + client_type = "textgenwebui" - conversation_retries = 5 + + def tune_prompt_parameters(self, parameters:dict, kind:str): + super().tune_prompt_parameters(parameters, kind) + parameters["stopping_strings"] = STOPPING_STRINGS + parameters.get("extra_stopping_strings", []) + # is this needed? + parameters["max_new_tokens"] = parameters["max_tokens"] - def __init__(self, api_url: str, max_token_length: int = 2048, **kwargs): + def set_client(self): + self.client = AsyncOpenAI(base_url=self.api_url+"/v1", api_key="sk-1111") + + async def get_model_name(self): + async with httpx.AsyncClient() as client: + response = await client.get(f"{self.api_url}/v1/internal/model/info", timeout=2) + if response.status_code == 404: + raise Exception("Could not find model info (wrong api version?)") + response_data = response.json() + model_name = response_data.get("model_name") + return model_name + + + async def generate(self, prompt:str, parameters:dict, kind:str): - api_url = self.cleanup_api_url(api_url) - - self.api_url_base = api_url - api_url = f"{api_url}/v1/chat" - super().__init__(api_url, max_token_length=max_token_length) - self.model_name = None - self.limited_ram = False - self.name = kwargs.get("name", "textgenwebui") - self.processing = False - self.connected = False - - def __str__(self): - return f"TextGeneratorWebuiClient[{self.api_url_base}][{self.model_name or ''}]" - - def cleanup_api_url(self, api_url:str): """ - Strips trailing / and ensures endpoint is /api + Generates text from the given prompt and parameters. """ - if api_url.endswith("/"): - api_url = api_url[:-1] - - if not api_url.endswith("/api"): - api_url = api_url + "/api" - - return api_url - - def reconfigure(self, **kwargs): - super().reconfigure(**kwargs) - if "api_url" in kwargs: - log.debug("reconfigure", api_url=kwargs["api_url"]) - api_url = kwargs["api_url"] - api_url = self.cleanup_api_url(api_url) - self.api_url_base = api_url - self.api_url = api_url + headers = {} + headers["Content-Type"] = "application/json" - def toggle_disabled_if_remote(self): + parameters["prompt"] = prompt.strip() - remote_servies = [ - ".runpod.net" - ] - - for service in remote_servies: - if service in self.api_url_base: - self.enabled = False - return - - def emit_status(self, processing: bool = None): - if processing is not None: - self.processing = processing - - if not self.enabled: - status = "disabled" - model_name = "Disabled" - elif not self.connected: - status = "error" - model_name = "Could not connect" - elif self.model_name: - status = "busy" if self.processing else "idle" - model_name = self.model_name - else: - model_name = "No model loaded" - status = "warning" - - status_change = status != self.current_status - self.current_status = status - - emit( - "client_status", - message=self.client_type, - id=self.name, - details=model_name, - status=status, - ) - - - if status_change: - instance.emit_agent_status_by_client(self) - - - # Add the 'status' method - async def status(self): - """ - Send a request to the API to retrieve the loaded AI model name. - Raises an error if no model name is returned. - :return: None - """ - - if not self.enabled: - self.connected = False - self.emit_status() - return - - try: - - async with httpx.AsyncClient() as client: - response = await client.get(f"{self.api_url_base}/v1/model", timeout=2) - - except ( - httpx.TimeoutException, - httpx.NetworkError, - ): - self.model_name = None - self.connected = False - self.toggle_disabled_if_remote() - self.emit_status() - return - - self.connected = True - - try: + async with httpx.AsyncClient() as client: + response = await client.post(f"{self.api_url}/v1/completions", json=parameters, timeout=None, headers=headers) response_data = response.json() - self.enabled = True - except json.decoder.JSONDecodeError as e: - self.connected = False - self.toggle_disabled_if_remote() - if not self.enabled: - log.warn("remote service unreachable, disabling client", name=self.name) - else: - log.error("client response error", name=self.name, e=e) - - self.emit_status() - return - - model_name = response_data.get("result") - - if not model_name or model_name == "None": - log.warning("client model not loaded", client=self.name) - self.emit_status() - return - - model_changed = model_name != self.model_name - - self.model_name = model_name - - if model_changed: - self.auto_context_length() - - log.info(f"{self} [{self.max_token_length} ctx]: ready") - self.emit_status() - - def auto_context_length(self): + return response_data["choices"][0]["text"] + + def jiggle_randomness(self, prompt_config:dict, offset:float=0.3) -> dict: """ - Automaticalle sets context length based on LLM - """ - - if not isinstance(self.max_token_length, DefaultContext): - # context length was specified manually - return - - model_name = self.model_name.lower() - - if "longchat" in model_name: - self.max_token_length = 16000 - elif "8k" in model_name: - if not self.limited_ram or "13b" in model_name: - self.max_token_length = 6000 - else: - self.max_token_length = 4096 - elif "4k" in model_name: - self.max_token_length = 4096 - else: - self.max_token_length = self.original_max_token_length - - @property - def instruction_template(self): - if "vicuna" in self.model_name.lower(): - return "Vicuna-v1.1" - if "camel" in self.model_name.lower(): - return "Vicuna-v1.1" - return "" - - def prompt_url(self): - return self.api_url_base + "/v1/generate" - - def prompt_config_conversation_old(self, prompt: str) -> dict: - prompt = self.prompt_template( - system_prompts.BASIC, - prompt, - ) - - config = { - "prompt": prompt, - "max_new_tokens": 75, - "truncation_length": self.max_token_length, - } - config.update(PRESET_TALEMATE_CONVERSATION) - return config - - - def prompt_config_conversation(self, prompt: str) -> dict: - prompt = self.prompt_template( - system_prompts.ROLEPLAY, - prompt, - ) - - stopping_strings = ["<|end_of_turn|>"] - - conversation_context = client_context_attribute("conversation") - - stopping_strings += [ - f"{character}:" for character in conversation_context["other_characters"] - ] - - max_new_tokens = conversation_context.get("length", 96) - log.debug("prompt_config_conversation", stopping_strings=stopping_strings, conversation_context=conversation_context, max_new_tokens=max_new_tokens) - - config = { - "prompt": prompt, - "max_new_tokens": max_new_tokens, - "truncation_length": self.max_token_length, - "stopping_strings": stopping_strings, - } - config.update(PRESET_TALEMATE_CONVERSATION) - - jiggle_randomness(config) - - return config - - def prompt_config_conversation_long(self, prompt: str) -> dict: - config = self.prompt_config_conversation(prompt) - config["max_new_tokens"] = 300 - return config - - def prompt_config_conversation_select_talking_actor(self, prompt: str) -> dict: - config = self.prompt_config_conversation(prompt) - config["max_new_tokens"] = 30 - config["stopping_strings"] += [":"] - return config - - - def prompt_config_summarize(self, prompt: str) -> dict: - prompt = self.prompt_template( - system_prompts.NARRATOR, - prompt, - ) - - config = { - "prompt": prompt, - "max_new_tokens": 500, - "truncation_length": self.max_token_length, - } - - config.update(PRESET_LLAMA_PRECISE) - return config - - def prompt_config_analyze(self, prompt: str) -> dict: - prompt = self.prompt_template( - system_prompts.ANALYST, - prompt, - ) - - config = { - "prompt": prompt, - "max_new_tokens": 500, - "truncation_length": self.max_token_length, - } - - config.update(PRESET_SIMPLE_1) - return config - - def prompt_config_analyze_creative(self, prompt: str) -> dict: - prompt = self.prompt_template( - system_prompts.ANALYST, - prompt, - ) - - config = {} - config.update(PRESET_DIVINE_INTELLECT) - config.update({ - "prompt": prompt, - "max_new_tokens": 1024, - "repetition_penalty_range": 1024, - "truncation_length": self.max_token_length - }) - - return config - - def prompt_config_analyze_long(self, prompt: str) -> dict: - config = self.prompt_config_analyze(prompt) - config["max_new_tokens"] = 2048 - return config - - def prompt_config_analyze_freeform(self, prompt: str) -> dict: - prompt = self.prompt_template( - system_prompts.ANALYST_FREEFORM, - prompt, - ) - - config = { - "prompt": prompt, - "max_new_tokens": 500, - "truncation_length": self.max_token_length, - } - - config.update(PRESET_LLAMA_PRECISE) - return config - - - def prompt_config_analyze_freeform_short(self, prompt: str) -> dict: - config = self.prompt_config_analyze_freeform(prompt) - config["max_new_tokens"] = 10 - return config - - def prompt_config_narrate(self, prompt: str) -> dict: - prompt = self.prompt_template( - system_prompts.NARRATOR, - prompt, - ) - - config = { - "prompt": prompt, - "max_new_tokens": 500, - "truncation_length": self.max_token_length, - } - config.update(PRESET_LLAMA_PRECISE) - return config - - def prompt_config_story(self, prompt: str) -> dict: - prompt = self.prompt_template( - system_prompts.NARRATOR, - prompt, - ) - - config = { - "prompt": prompt, - "max_new_tokens": 300, - "seed": random.randint(0, 1000000000), - "truncation_length": self.max_token_length - } - config.update(PRESET_DIVINE_INTELLECT) - config.update({ - "repetition_penalty": 1.3, - "repetition_penalty_range": 2048, - }) - return config - - def prompt_config_create(self, prompt: str) -> dict: - prompt = self.prompt_template( - system_prompts.CREATOR, - prompt, - ) - config = { - "prompt": prompt, - "max_new_tokens": min(1024, self.max_token_length * 0.35), - "truncation_length": self.max_token_length, - } - config.update(PRESET_TALEMATE_CREATOR) - return config - - def prompt_config_create_concise(self, prompt: str) -> dict: - prompt = self.prompt_template( - system_prompts.CREATOR, - prompt, - ) - - config = { - "prompt": prompt, - "max_new_tokens": min(400, self.max_token_length * 0.25), - "truncation_length": self.max_token_length, - "stopping_strings": ["<|DONE|>", "\n\n"] - } - config.update(PRESET_TALEMATE_CREATOR) - return config - - def prompt_config_create_precise(self, prompt: str) -> dict: - config = self.prompt_config_create_concise(prompt) - config.update(PRESET_LLAMA_PRECISE) - return config - - def prompt_config_director(self, prompt: str) -> dict: - prompt = self.prompt_template( - system_prompts.DIRECTOR, - prompt, - ) - - config = { - "prompt": prompt, - "max_new_tokens": min(600, self.max_token_length * 0.25), - "truncation_length": self.max_token_length, - } - config.update(PRESET_SIMPLE_1) - return config - - - def prompt_config_director_short(self, prompt: str) -> dict: - config = self.prompt_config_director(prompt) - config.update(max_new_tokens=25) - return config - - def prompt_config_director_yesno(self, prompt: str) -> dict: - config = self.prompt_config_director(prompt) - config.update(max_new_tokens=2) - return config - - def prompt_config_edit_dialogue(self, prompt:str) -> dict: - prompt = self.prompt_template( - system_prompts.EDITOR, - prompt, - ) - - conversation_context = client_context_attribute("conversation") - - stopping_strings = [ - f"{character}:" for character in conversation_context["other_characters"] - ] - - config = { - "prompt": prompt, - "max_new_tokens": 100, - "truncation_length": self.max_token_length, - "stopping_strings": stopping_strings, - } - - config.update(PRESET_DIVINE_INTELLECT) - - return config - - def prompt_config_edit_add_detail(self, prompt:str) -> dict: - - config = self.prompt_config_edit_dialogue(prompt) - config.update(max_new_tokens=200) - return config - - - def prompt_config_edit_fix_exposition(self, prompt:str) -> dict: - - config = self.prompt_config_edit_dialogue(prompt) - config.update(max_new_tokens=1024) - return config - - - async def send_prompt( - self, prompt: str, kind: str = "conversation", finalize: Callable = lambda x: x - ) -> str: - """ - Send a prompt to the AI and return its response. - :param prompt: The text prompt to send. - :return: The AI's response text. + adjusts temperature and repetition_penalty + by random values using the base value as a center """ - #prompt = prompt.replace("<|BOT|>", "<|BOT|>Certainly! ") - - await self.status() - self.emit_status(processing=True) - - await asyncio.sleep(0.01) - - fn_prompt_config = getattr(self, f"prompt_config_{kind}") - fn_url = self.prompt_url - message = fn_prompt_config(prompt) - - if client_context_attribute("nuke_repetition") > 0.0 and kind in ["conversation", "story"]: - log.info("nuke repetition", offset=client_context_attribute("nuke_repetition"), temperature=message["temperature"], repetition_penalty=message["repetition_penalty"]) - message = jiggle_randomness(message, offset=client_context_attribute("nuke_repetition")) - log.info("nuke repetition (applied)", offset=client_context_attribute("nuke_repetition"), temperature=message["temperature"], repetition_penalty=message["repetition_penalty"]) + temp = prompt_config["temperature"] + rep_pen = prompt_config["repetition_penalty"] - message = finalize(message) + min_offset = offset * 0.3 - token_length = int(len(message["prompt"]) / 3.6) - - self.last_token_length = token_length - - log.debug("send_prompt", token_length=token_length, max_token_length=self.max_token_length) - - message["prompt"] = message["prompt"].strip() - - #print(f"prompt: |{message['prompt']}|") - - # add <|im_end|> to stopping strings - if "stopping_strings" in message: - message["stopping_strings"] += ["<|im_end|>", ""] - else: - message["stopping_strings"] = ["<|im_end|>", ""] - - #message["seed"] = -1 - - #for k,v in message.items(): - # if k == "prompt": - # continue - # print(f"{k}: {v}") - - time_start = time.time() - - response = await self.send_message(message, fn_url()) - - time_end = time.time() - - response = response.split("#")[0] - self.emit_status(processing=False) - - emit("prompt_sent", data={ - "kind": kind, - "prompt": message["prompt"], - "response": response, - "prompt_tokens": token_length, - "response_tokens": int(len(response) / 3.6), - "time": time_end - time_start, - }) - - return response - - -class OpenAPIClient(RESTTaleMateClient): - pass - - -class GPT3Client(OpenAPIClient): - pass - - -class GPT4Client(OpenAPIClient): - pass + prompt_config["temperature"] = random.uniform(temp + min_offset, temp + offset) + prompt_config["repetition_penalty"] = random.uniform(rep_pen + min_offset * 0.3, rep_pen + offset * 0.3) \ No newline at end of file diff --git a/src/talemate/client/utils.py b/src/talemate/client/utils.py new file mode 100644 index 00000000..63f91b7e --- /dev/null +++ b/src/talemate/client/utils.py @@ -0,0 +1,32 @@ +import copy +import random + +def jiggle_randomness(prompt_config:dict, offset:float=0.3) -> dict: + """ + adjusts temperature and repetition_penalty + by random values using the base value as a center + """ + + temp = prompt_config["temperature"] + rep_pen = prompt_config["repetition_penalty"] + + copied_config = copy.deepcopy(prompt_config) + + min_offset = offset * 0.3 + + copied_config["temperature"] = random.uniform(temp + min_offset, temp + offset) + copied_config["repetition_penalty"] = random.uniform(rep_pen + min_offset * 0.3, rep_pen + offset * 0.3) + + return copied_config + + +def jiggle_enabled_for(kind:str): + + if kind in ["conversation", "story"]: + return True + + if kind.startswith("narrate"): + return True + + return False + diff --git a/src/talemate/commands/cmd_rename.py b/src/talemate/commands/cmd_rename.py index 105f43dd..023c834f 100644 --- a/src/talemate/commands/cmd_rename.py +++ b/src/talemate/commands/cmd_rename.py @@ -17,7 +17,26 @@ class CmdRename(TalemateCommand): aliases = [] async def run(self): + # collect list of characters in the scene + + if self.args: + character_name = self.args[0] + else: + character_names = self.scene.character_names + character_name = await wait_for_input("Which character do you want to rename?", data={ + "input_type": "select", + "choices": character_names, + }) + + character = self.scene.get_character(character_name) + + if not character: + self.system_message(f"Character {character_name} not found") + return True + name = await wait_for_input("Enter new name: ") - self.scene.main_character.character.rename(name) + character.rename(name) await asyncio.sleep(0) + + return True diff --git a/src/talemate/events.py b/src/talemate/events.py index 8a257a2e..28eb8984 100644 --- a/src/talemate/events.py +++ b/src/talemate/events.py @@ -4,7 +4,7 @@ from dataclasses import dataclass from typing import TYPE_CHECKING if TYPE_CHECKING: - from talemate.tale_mate import Scene + from talemate.tale_mate import Scene, Actor __all__ = [ "Event", @@ -42,4 +42,8 @@ class GameLoopEvent(Event): @dataclass class GameLoopStartEvent(GameLoopEvent): - pass \ No newline at end of file + pass + +@dataclass +class GameLoopActorIterEvent(GameLoopEvent): + actor: Actor \ No newline at end of file diff --git a/src/talemate/prompts/base.py b/src/talemate/prompts/base.py index 4ebd4bc7..524388cd 100644 --- a/src/talemate/prompts/base.py +++ b/src/talemate/prompts/base.py @@ -290,6 +290,7 @@ class Prompt: env.globals["query_scene"] = self.query_scene env.globals["query_memory"] = self.query_memory env.globals["query_text"] = self.query_text + env.globals["instruct_text"] = self.instruct_text env.globals["retrieve_memories"] = self.retrieve_memories env.globals["uuidgen"] = lambda: str(uuid.uuid4()) env.globals["to_int"] = lambda x: int(x) @@ -394,9 +395,14 @@ class Prompt: f"Answer: " + loop.run_until_complete(memory.query(query, **kwargs)), ]) else: - return loop.run_until_complete(memory.multi_query([query], **kwargs)) - + return loop.run_until_complete(memory.multi_query(query.split("\n"), **kwargs)) + def instruct_text(self, instruction:str, text:str): + loop = asyncio.get_event_loop() + world_state = instance.get_agent("world_state") + instruction = instruction.format(**self.vars) + + return loop.run_until_complete(world_state.analyze_and_follow_instruction(text, instruction)) def retrieve_memories(self, lines:list[str], goal:str=None): diff --git a/src/talemate/prompts/templates/narrator/narrate-after-dialogue.jinja2 b/src/talemate/prompts/templates/narrator/narrate-after-dialogue.jinja2 new file mode 100644 index 00000000..d49939e2 --- /dev/null +++ b/src/talemate/prompts/templates/narrator/narrate-after-dialogue.jinja2 @@ -0,0 +1,19 @@ +{% block rendered_context -%} +<|SECTION:CONTEXT|> +Content Context: This is a specific scene from {{ scene.context }} +Scenario Premise: {{ scene.description }} +{% for memory in query_memory(last_line, as_question_answer=False, iterate=10) -%} +{{ memory }} + +{% endfor %} +{% endblock -%} +<|CLOSE_SECTION|> +{% for scene_context in scene.context_history(budget=max_tokens-200-count_tokens(self.rendered_context())) -%} +{{ scene_context }} +{% endfor %} +<|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. + +Be creative and generate something new and interesting. +<|CLOSE_SECTION|> +{{ set_prepared_response('*') }} \ No newline at end of file diff --git a/src/talemate/prompts/templates/narrator/narrate-query.jinja2 b/src/talemate/prompts/templates/narrator/narrate-query.jinja2 index 35adc863..158efb23 100644 --- a/src/talemate/prompts/templates/narrator/narrate-query.jinja2 +++ b/src/talemate/prompts/templates/narrator/narrate-query.jinja2 @@ -8,13 +8,13 @@ {% if query.endswith("?") -%} Question: {{ query }} Extra context: {{ query_memory(query, as_question_answer=False) }} -Instruction: Analyze Context, History and Dialogue. Be factual and truthful. 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. 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. {% else -%} Instruction: {{ query }} Extra context: {{ query_memory(query, as_question_answer=False) }} -Answer based on Context, History and Dialogue. Be factual and truthful. 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 memory, story is more important. You can fill in gaps using imagination as long as it is based on the existing context. {% endif -%} Content Context: This is a specific scene from {{ scene.context }} -Narration style: point and click adventure game from the 90s +Your answer should be in the style of short narration that fits the context of the scene. <|CLOSE_SECTION|> Narrator answers: {% if at_the_end %}{{ bot_token }}At the end of the dialogue, {% endif %} \ No newline at end of file diff --git a/src/talemate/prompts/templates/world_state/analyze-text-and-extract-context.jinja2 b/src/talemate/prompts/templates/world_state/analyze-text-and-extract-context.jinja2 index 90a41746..afd1e074 100644 --- a/src/talemate/prompts/templates/world_state/analyze-text-and-extract-context.jinja2 +++ b/src/talemate/prompts/templates/world_state/analyze-text-and-extract-context.jinja2 @@ -8,9 +8,10 @@ <|SECTION:TASK|> Answer the following questions: -{{ query_text("What are 1 to 3 questions to ask the narrator of the story to gather more context from the past for the continuation of this conversation? If a character is asking about a status, location or information about an item or another character, make sure to include question(s) that help gather context for this. Don't explain your reasoning. Don't ask the actors directly.", text, as_question_answer=False) }} +{{ 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) }} -You answers should be precise, truthful and short. +You answers should be precise, truthful and short. Pay close attention to timestamps when retrieving information from the context. <|CLOSE_SECTION|> -<|SECTION:RELEVANT CONTEXT|> \ No newline at end of file +<|SECTION:RELEVANT CONTEXT|> +{{ bot_token }}Answers: \ No newline at end of file diff --git a/src/talemate/prompts/templates/world_state/analyze-text-and-follow-instruction.jinja2 b/src/talemate/prompts/templates/world_state/analyze-text-and-follow-instruction.jinja2 new file mode 100644 index 00000000..efdea681 --- /dev/null +++ b/src/talemate/prompts/templates/world_state/analyze-text-and-follow-instruction.jinja2 @@ -0,0 +1,5 @@ + +{{ text }} + +<|SECTION:TASK|> +{{ instruction }} \ No newline at end of file diff --git a/src/talemate/prompts/templates/world_state/request-world-state-v2.jinja2 b/src/talemate/prompts/templates/world_state/request-world-state-v2.jinja2 index fc88e641..72f82fbf 100644 --- a/src/talemate/prompts/templates/world_state/request-world-state-v2.jinja2 +++ b/src/talemate/prompts/templates/world_state/request-world-state-v2.jinja2 @@ -34,7 +34,7 @@ No dialogue so far {% endif -%} <|CLOSE_SECTION|> <|SECTION:SCENE PROGRESS|> -{% for scene_context in scene.context_history(budget=300, min_dialogue=5, add_archieved_history=False, max_dialogue=5) -%} +{% for scene_context in scene.context_history(budget=500, min_dialogue=5, add_archieved_history=False, max_dialogue=5) -%} {{ scene_context }} {% endfor -%} <|CLOSE_SECTION|> diff --git a/src/talemate/server/run.py b/src/talemate/server/run.py index bb782a66..cd580f9a 100644 --- a/src/talemate/server/run.py +++ b/src/talemate/server/run.py @@ -1,3 +1,5 @@ +import os + import argparse import asyncio import sys diff --git a/src/talemate/server/websocket_server.py b/src/talemate/server/websocket_server.py index ae4e91a0..33f3a434 100644 --- a/src/talemate/server/websocket_server.py +++ b/src/talemate/server/websocket_server.py @@ -167,14 +167,14 @@ class WebsocketHandler(Receiver): log.info("Configuring clients", clients=clients) for client in clients: - if client["type"] == "textgenwebui": + if client["type"] in ["textgenwebui", "lmstudio"]: try: max_token_length = int(client.get("max_token_length", 2048)) except ValueError: continue self.llm_clients[client["name"]] = { - "type": "textgenwebui", + "type": client["type"], "api_url": client["apiUrl"], "name": client["name"], "max_token_length": max_token_length, @@ -385,7 +385,7 @@ class WebsocketHandler(Receiver): "status": emission.status, "data": emission.data, "max_token_length": client.max_token_length if client else 2048, - "apiUrl": getattr(client, "api_url_base", None) if client else None, + "apiUrl": getattr(client, "api_url", None) if client else None, } ) diff --git a/src/talemate/tale_mate.py b/src/talemate/tale_mate.py index d6c97581..b9783da4 100644 --- a/src/talemate/tale_mate.py +++ b/src/talemate/tale_mate.py @@ -43,6 +43,10 @@ __all__ = [ log = structlog.get_logger("talemate") +async_signals.register("game_loop_start") +async_signals.register("game_loop") +async_signals.register("game_loop_actor_iter") + class Character: """ @@ -523,8 +527,6 @@ class Player(Actor): return message -async_signals.register("game_loop_start") -async_signals.register("game_loop") class Scene(Emitter): """ @@ -575,6 +577,7 @@ class Scene(Emitter): "character_state": signal("character_state"), "game_loop": async_signals.get("game_loop"), "game_loop_start": async_signals.get("game_loop_start"), + "game_loop_actor_iter": async_signals.get("game_loop_actor_iter"), } self.setup_emitter(scene=self) @@ -1066,7 +1069,9 @@ class Scene(Emitter): new_message = await narrator.agent.narrate_character(character) elif source == "narrate_query": new_message = await narrator.agent.narrate_query(arg) - + elif source == "narrate_dialogue": + character = self.get_character(arg) + new_message = await narrator.agent.narrate_after_dialogue(character) else: fn = getattr(narrator.agent, source, None) if not fn: @@ -1339,6 +1344,10 @@ class Scene(Emitter): if await command.execute(message): break await self.call_automated_actions() + + await self.signals["game_loop_actor_iter"].send( + events.GameLoopActorIterEvent(scene=self, event_type="game_loop_actor_iter", actor=actor) + ) continue self.saved = False @@ -1350,6 +1359,10 @@ class Scene(Emitter): emit( "character", item, character=actor.character ) + + await self.signals["game_loop_actor_iter"].send( + events.GameLoopActorIterEvent(scene=self, event_type="game_loop_actor_iter", actor=actor) + ) self.emit_status() diff --git a/src/talemate/util.py b/src/talemate/util.py index a3c18d78..cc124fad 100644 --- a/src/talemate/util.py +++ b/src/talemate/util.py @@ -303,6 +303,9 @@ def strip_partial_sentences(text:str) -> str: # Sentence ending characters sentence_endings = ['.', '!', '?', '"', "*"] + if not text: + return text + # Check if the last character is already a sentence ending if text[-1] in sentence_endings: return text @@ -779,7 +782,11 @@ def ensure_dialog_format(line:str, talking_character:str=None) -> str: lines = [] for _line in line.split("\n"): - _line = ensure_dialog_line_format(_line) + try: + _line = ensure_dialog_line_format(_line) + except Exception as exc: + log.error("ensure_dialog_format", msg="Error ensuring dialog line format", line=_line, exc_info=exc) + pass lines.append(_line) diff --git a/talemate_frontend/src/components/AIClient.vue b/talemate_frontend/src/components/AIClient.vue index 29696d62..3e44d552 100644 --- a/talemate_frontend/src/components/AIClient.vue +++ b/talemate_frontend/src/components/AIClient.vue @@ -120,7 +120,7 @@ export default { this.state.currentClient = { name: 'TextGenWebUI', type: 'textgenwebui', - apiUrl: 'http://localhost:5000/api', + apiUrl: 'http://localhost:5000', model_name: '', max_token_length: 4096, }; diff --git a/talemate_frontend/src/components/ClientModal.vue b/talemate_frontend/src/components/ClientModal.vue index 3be857ef..b60265af 100644 --- a/talemate_frontend/src/components/ClientModal.vue +++ b/talemate_frontend/src/components/ClientModal.vue @@ -8,7 +8,7 @@ - + @@ -17,13 +17,13 @@ - + - + @@ -74,6 +74,9 @@ export default { save() { this.$emit('save', this.client); // Emit save event with client object this.close(); + }, + isLocalApiClient(client) { + return client.type === 'textgenwebui' || client.type === 'lmstudio'; } } } diff --git a/templates/llm-prompt/Cat.jinja2 b/templates/llm-prompt/Cat.jinja2 new file mode 100644 index 00000000..c68eb6c0 --- /dev/null +++ b/templates/llm-prompt/Cat.jinja2 @@ -0,0 +1,4 @@ +{{ system_message }} + +### Instruction: +{{ set_response(prompt, "\n\n### Response:\n") }} \ No newline at end of file diff --git a/templates/llm-prompt/Nous-Capybara.jinja2 b/templates/llm-prompt/Nous-Capybara.jinja2 new file mode 100644 index 00000000..8f78b90d --- /dev/null +++ b/templates/llm-prompt/Nous-Capybara.jinja2 @@ -0,0 +1,3 @@ +USER: +{{ system_message }} +{{ set_response(prompt, "\nASSISTANT:") }} \ No newline at end of file diff --git a/templates/llm-prompt/Psyfighter2.jinja2 b/templates/llm-prompt/Psyfighter2.jinja2 new file mode 100644 index 00000000..c68eb6c0 --- /dev/null +++ b/templates/llm-prompt/Psyfighter2.jinja2 @@ -0,0 +1,4 @@ +{{ system_message }} + +### Instruction: +{{ set_response(prompt, "\n\n### Response:\n") }} \ No newline at end of file diff --git a/templates/llm-prompt/Tess-Medium.jinja2 b/templates/llm-prompt/Tess-Medium.jinja2 new file mode 100644 index 00000000..0ef9e87d --- /dev/null +++ b/templates/llm-prompt/Tess-Medium.jinja2 @@ -0,0 +1,2 @@ +SYSTEM: {{ system_message }} +USER: {{ set_response(prompt, "\nASSISTANT: ") }} \ No newline at end of file diff --git a/templates/llm-prompt/dolphin-2.2.1-mistral.jinja2 b/templates/llm-prompt/dolphin-2.2.1-mistral.jinja2 new file mode 100644 index 00000000..bef1036f --- /dev/null +++ b/templates/llm-prompt/dolphin-2.2.1-mistral.jinja2 @@ -0,0 +1,4 @@ +<|im_start|>system +{{ system_message }}<|im_end|> +<|im_start|>user +{{ set_response(prompt, "<|im_end|>\n<|im_start|>assistant\n") }} \ No newline at end of file diff --git a/templates/llm-prompt/dolphin-2_2-yi.jinja2 b/templates/llm-prompt/dolphin-2_2-yi.jinja2 new file mode 100644 index 00000000..bef1036f --- /dev/null +++ b/templates/llm-prompt/dolphin-2_2-yi.jinja2 @@ -0,0 +1,4 @@ +<|im_start|>system +{{ system_message }}<|im_end|> +<|im_start|>user +{{ set_response(prompt, "<|im_end|>\n<|im_start|>assistant\n") }} \ No newline at end of file diff --git a/update.bat b/update.bat index 8b9fd5ed..ce304fd1 100644 --- a/update.bat +++ b/update.bat @@ -6,5 +6,5 @@ call talemate_env\Scripts\activate REM use poetry to install dependencies python -m poetry install -echo Virtual environment re-created. +echo Virtual environment updated pause