diff --git a/README.md b/README.md index a0477888..8e3acb10 100644 --- a/README.md +++ b/README.md @@ -102,14 +102,14 @@ Will be updated as i test more models and over time. | Model Name | Type | Notes | |-------------------------------|-----------------|-------------------------------------------------------------------------------------------------------------------| -| [GPT-4](https://platform.openai.com/) | Remote | Still the best for consistency and reasoning, but is heavily censored, while talemate will send a general "decensor" system prompt, depending on the type of content you want to roleplay, there is a chance your key will be banned. **If you do use this make sure to monitor your api usage, talemate tends to send a lot more requests than other roleplaying applications.** | | [Nous Hermes LLama2](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GPTQ) | 13B model | My go-to model for 13B parameters. It's good at roleplay and also smart enough to handle the world state and narrative tools. A 13B model loaded via exllama also allows you run chromadb with the xl instructor embeddings off of a single 4090. | +| [Xwin-LM-13B](https://huggingface.co/TheBloke/Xwin-LM-13B-V0.1-GPTQ) | 13B model | Really strong model, roleplaying capability still needs more testing | | [MythoMax](https://huggingface.co/TheBloke/MythoMax-L2-13B-GPTQ) | 13B model | Similar quality to Hermes LLama2, but a bit more creative. Rarely fails on JSON responses. | | [Synthia v1.2 34B](https://huggingface.co/TheBloke/Synthia-34B-v1.2-GPTQ) | 34B model | Cannot be run at full context together with chromadb instructor models on a single 4090. But a great choice if you're running chromadb with the default embeddings (or on cpu). | -| [Xwin-LM-70B](https://huggingface.co/Xwin-LM/Xwin-LM-70B-V0.1) | 70B model | Great choice if you have the hardware to run it (or can rent it). | +| [Xwin-LM-70B](https://huggingface.co/TheBloke/Xwin-LM-70B-V0.1-GPTQ) | 70B model | Great choice if you have the hardware to run it (or can rent it). | | [Synthia v1.2 70B](https://huggingface.co/TheBloke/Synthia-70B-v1.2-GPTQ) | 70B model | Great choice if you have the hardware to run it (or can rent it). | - -I have not included OpenAI's gpt-3.5-turbo in this list, since it is really inconsistent with JSON responses, plus its probably still just as heavily censored as GPT-4. +| [GPT-4](https://platform.openai.com/) | Remote | Still the best for consistency and reasoning, but is heavily censored. While talemate will send a general "decensor" system prompt, depending on the type of content you want to roleplay, there is a chance your key will be banned. **If you do use this make sure to monitor your api usage, talemate tends to send a lot more requests than other roleplaying applications.** | +| [GPT-3.5-turbo](https://platform.openai.com/) | Remote | It's really inconsistent with JSON responses, plus its probably still just as heavily censored as GPT-4. If you want to run it i'd suggest running it for the conversation agent, and use GPT-4 for the other agents. **If you do use this make sure to monitor your api usage, talemate tends to send a lot more requests than other roleplaying applications.** | I have not tested with Llama 1 models in a while, Lazarus was really good at roleplay, but started failing on JSON requirements. diff --git a/docs/chromadb.md b/docs/chromadb.md index 586c23e0..e8906cf5 100644 --- a/docs/chromadb.md +++ b/docs/chromadb.md @@ -1,7 +1,15 @@ -## ChromaDB +# ChromaDB + +Talemate uses ChromaDB to maintain long-term memory. The default embeddings used are really fast but also not incredibly accurate. If you want to use more accurate embeddings you can use the instructor embeddings or the openai embeddings. See below for instructions on how to enable these. + +In my testing so far, instructor-xl has proved to be the most accurate (even more-so than openai) + +## Local instructor embeddings If you want chromaDB to use the more accurate (but much slower) instructor embeddings add the following to `config.yaml`: +**Note**: The `xl` model takes a while to load even with cuda. Expect a minute of loading time on the first scene you load. + ```yaml chromadb: embeddings: instructor @@ -9,17 +17,23 @@ chromadb: instructor_model: hkunlp/instructor-xl ``` +### Instructor embedding models + +- `hkunlp/instructor-base` (smallest / fastest) +- `hkunlp/instructor-large` +- `hkunlp/instructor-xl` (largest / slowest) - requires about 5GB of memory + You will need to restart the backend for this change to take effect. **NOTE** - The first time you do this it will need to download the instructor model you selected. This may take a while, and the talemate backend will be un-responsive during that time. -Once the download is finished, if talemate is still un-responsive, try reloading the front-end to reconnect. When all fails just restart the backend as well. +Once the download is finished, if talemate is still un-responsive, try reloading the front-end to reconnect. When all fails just restart the backend as well. I'll try to make this more robust in the future. ### GPU support If you want to use the instructor embeddings with GPU support, you will need to install pytorch with CUDA support. -To do this on windows, run `install-pytorch-cuda.bat` from the project root. Then change your device in the config to `cuda`: +To do this on windows, run `install-pytorch-cuda.bat` from the project directory. Then change your device in the config to `cuda`: ```yaml chromadb: @@ -28,8 +42,20 @@ chromadb: instructor_model: hkunlp/instructor-xl ``` -Instructor embedding models: +## OpenAI embeddings -- `hkunlp/instructor-base` (smallest / fastest) -- `hkunlp/instructor-large` -- `hkunlp/instructor-xl` (largest / slowest) - requires about 5GB of GPU memory +First make sure your openai key is specified in the `config.yaml` file + +```yaml +openai: + api_key: +``` + +Then add the following to `config.yaml` for chromadb: + +```yaml +chromadb: + embeddings: openai +``` + +**Note**: As with everything openai, using this isn't free. It's way cheaper than their text completion though. ALSO - if you send super explicit content they may flag / ban your key, so keep that in mind (i hear they usually send warnings first though), and always monitor your usage on their dashboard. \ No newline at end of file diff --git a/poetry.lock b/poetry.lock index 029cb05f..db9e08e0 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. 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(>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)"] +flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] ftfy = ["ftfy"] integrations = ["optuna", "ray[tune]", "sigopt"] -ja = ["fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"] -modelcreation = ["cookiecutter (==1.7.2)"] +ja = ["fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "rhoknp (>=1.1.0,<1.3.1)", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"] +modelcreation = ["cookiecutter (==1.7.3)"] +natten = ["natten (>=0.14.6)"] onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"] onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"] optuna = ["optuna"] -quality = ["GitPython (<3.1.19)", "black (>=22.0,<23.0)", "flake8 (>=3.8.3)", "isort (>=5.5.4)"] +quality = ["GitPython (<3.1.19)", "black (>=23.1,<24.0)", "datasets (!=2.5.0)", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)", "ruff (>=0.0.241,<=0.0.259)", "urllib3 (<2.0.0)"] ray = ["ray[tune]"] -retrieval = ["datasets", "faiss-cpu"] +retrieval = ["datasets (!=2.5.0)", "faiss-cpu"] sagemaker = ["sagemaker (>=2.31.0)"] sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"] -serving = ["fastapi", "pydantic", "starlette", "uvicorn"] +serving = ["fastapi", "pydantic (<2)", "starlette", "uvicorn"] sigopt = ["sigopt"] sklearn = ["scikit-learn"] -speech = ["librosa", "phonemizer", "pyctcdecode (>=0.3.0)", "torchaudio"] -testing = ["GitPython (<3.1.19)", "black (>=22.0,<23.0)", "cookiecutter (==1.7.2)", "datasets", "faiss-cpu", "nltk", "parameterized", "psutil", "pytest", "pytest-timeout", "pytest-xdist", "rouge-score", "sacrebleu (>=1.4.12,<2.0.0)", "timeout-decorator"] -tf = ["onnxconverter-common", "tensorflow (>=2.3)", "tf2onnx"] -tf-cpu = ["onnxconverter-common", "tensorflow-cpu (>=2.3)", "tf2onnx"] -tf-speech = ["librosa", "phonemizer", "pyctcdecode (>=0.3.0)"] +speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] +testing = ["GitPython (<3.1.19)", "beautifulsoup4", "black (>=23.1,<24.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "parameterized", "protobuf", "psutil", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "timeout-decorator"] +tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>=2.6,<2.15)", "tensorflow-text (<2.15)", "tf2onnx"] +tf-cpu = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>=2.6,<2.15)", "tensorflow-text (<2.15)", "tf2onnx"] +tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] timm = ["timm"] -tokenizers = ["tokenizers (>=0.11.1,!=0.11.3)"] -torch = ["torch (>=1.0)"] -torch-speech = ["librosa", "phonemizer", "pyctcdecode (>=0.3.0)", "torchaudio"] -torchhub = ["filelock", "huggingface-hub (>=0.1.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.11.1,!=0.11.3)", "torch (>=1.0)", "tqdm (>=4.27)"] -vision = ["Pillow"] +tokenizers = ["tokenizers (>=0.11.1,!=0.11.3,<0.14)"] +torch = ["accelerate (>=0.20.3)", "torch (>=1.10,!=1.12.0)"] +torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] +torch-vision = ["Pillow (<10.0.0)", "torchvision"] +torchhub = ["filelock", "huggingface-hub (>=0.15.1,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.10,!=1.12.0)", "tqdm (>=4.27)"] +video = ["av (==9.2.0)", "decord (==0.6.0)"] +vision = ["Pillow (<10.0.0)"] [[package]] name = "triton" @@ -3339,14 +3417,35 @@ tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)"] tutorials = ["matplotlib", "pandas", "tabulate"] [[package]] -name = "typing-extensions" -version = "4.7.1" -description = "Backported and Experimental Type Hints for Python 3.7+" +name = "typer" +version = "0.9.0" +description = "Typer, build great CLIs. Easy to code. Based on Python type hints." optional = false -python-versions = ">=3.7" +python-versions = ">=3.6" files = [ - {file = "typing_extensions-4.7.1-py3-none-any.whl", hash = "sha256:440d5dd3af93b060174bf433bccd69b0babc3b15b1a8dca43789fd7f61514b36"}, - {file = "typing_extensions-4.7.1.tar.gz", hash = "sha256:b75ddc264f0ba5615db7ba217daeb99701ad295353c45f9e95963337ceeeffb2"}, + {file = "typer-0.9.0-py3-none-any.whl", hash = "sha256:5d96d986a21493606a358cae4461bd8cdf83cbf33a5aa950ae629ca3b51467ee"}, + {file = "typer-0.9.0.tar.gz", hash = "sha256:50922fd79aea2f4751a8e0408ff10d2662bd0c8bbfa84755a699f3bada2978b2"}, +] + +[package.dependencies] +click = ">=7.1.1,<9.0.0" +typing-extensions = ">=3.7.4.3" + +[package.extras] +all = ["colorama (>=0.4.3,<0.5.0)", "rich (>=10.11.0,<14.0.0)", "shellingham (>=1.3.0,<2.0.0)"] +dev = ["autoflake (>=1.3.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "pre-commit (>=2.17.0,<3.0.0)"] +doc = ["cairosvg (>=2.5.2,<3.0.0)", "mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-material (>=8.1.4,<9.0.0)", "pillow (>=9.3.0,<10.0.0)"] +test = ["black (>=22.3.0,<23.0.0)", "coverage (>=6.2,<7.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.910)", "pytest (>=4.4.0,<8.0.0)", "pytest-cov (>=2.10.0,<5.0.0)", "pytest-sugar (>=0.9.4,<0.10.0)", "pytest-xdist (>=1.32.0,<4.0.0)", "rich (>=10.11.0,<14.0.0)", "shellingham (>=1.3.0,<2.0.0)"] + +[[package]] +name = "typing-extensions" +version = "4.8.0" +description = "Backported and Experimental Type Hints for Python 3.8+" +optional = false +python-versions = ">=3.8" +files = [ + {file = "typing_extensions-4.8.0-py3-none-any.whl", hash = "sha256:8f92fc8806f9a6b641eaa5318da32b44d401efaac0f6678c9bc448ba3605faa0"}, + {file = "typing_extensions-4.8.0.tar.gz", hash = "sha256:df8e4339e9cb77357558cbdbceca33c303714cf861d1eef15e1070055ae8b7ef"}, ] [[package]] @@ -3821,4 +3920,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = ">=3.10,<4.0" -content-hash = "f6fe6fec3163a11f953f03636436795e2ef0e530be943de87c226afe6dc34e94" +content-hash = "64b35172207809793651a70f9bbfd3f5ec53bb1b7424168b5b35a5c46714f8dc" diff --git a/pyproject.toml b/pyproject.toml index 2ee3bb02..217dea2a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.masonry.api" [tool.poetry] name = "talemate" -version = "0.9.0" +version = "0.10.0" description = "AI-backed roleplay and narrative tools" authors = ["FinalWombat"] license = "GNU Affero General Public License v3.0" @@ -35,6 +35,7 @@ websockets = "^11.0.3" structlog = "^23.1.0" runpod = "==1.2.0" nest_asyncio = "^1.5.7" +isodate = ">=0.6.1" # ChromaDB chromadb = ">=0.4,<1" diff --git a/scenes/infinity-quest/infinity-quest.json b/scenes/infinity-quest/infinity-quest.json index 8cd84537..13dcc084 100644 --- a/scenes/infinity-quest/infinity-quest.json +++ b/scenes/infinity-quest/infinity-quest.json @@ -4,7 +4,29 @@ "name": "Infinity Quest", "history": [], "environment": "scene", - "archived_history": [], + "ts": "P1Y", + "archived_history": [ + { + "text": "Captain Elmer and Kaira first met during their rigorous training for the Infinity Quest mission. Their initial interactions were marked by a sense of mutual respect and curiosity.", + "ts": "PT1S" + }, + { + "text": "Over the course of several months, as they trained together, Elmer and Kaira developed a strong bond. They often spent their free time discussing their dreams of exploring the cosmos.", + "ts": "P3M" + }, + { + "text": "During a simulated mission, the Starlight Nomad encountered a sudden system malfunction. Elmer and Kaira worked tirelessly together to resolve the issue and avert a potential disaster. This incident strengthened their trust in each other's abilities.", + "ts": "P6M" + }, + { + "text": "As they ventured further into uncharted space, the crew faced a perilous encounter with a hostile alien species. Elmer and Kaira's coordinated efforts were instrumental in negotiating a peaceful resolution and avoiding conflict.", + "ts": "P8M" + }, + { + "text": "One memorable evening, while gazing at the stars through the ship's observation deck, Elmer and Kaira shared personal stories from their past. This intimate conversation deepened their connection and understanding of each other.", + "ts": "P11M" + } + ], "character_states": {}, "characters": [ { diff --git a/src/talemate/__init__.py b/src/talemate/__init__.py index ab2e0f3f..61860e8d 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 = "0.9.0" \ No newline at end of file +VERSION = "0.10.0" \ No newline at end of file diff --git a/src/talemate/agents/conversation.py b/src/talemate/agents/conversation.py index 05de59b2..2e3c37c6 100644 --- a/src/talemate/agents/conversation.py +++ b/src/talemate/agents/conversation.py @@ -158,23 +158,16 @@ class ConversationAgent(Agent): def clean_result(self, result, character): - log.debug("clean result", result=result) if "#" in result: result = result.split("#")[0] - result = result.replace("\n", "__LINEBREAK__").strip() - - # Removes partial sentence at the end - result = re.sub(r"[^\.\?\!\*]+(\n|$)", "", result) - result = result.replace(" :", ":") result = result.strip().strip('"').strip() result = result.replace("[", "*").replace("]", "*") + result = result.replace("(", "*").replace(")", "*") result = result.replace("**", "*") - - result = result.replace("__LINEBREAK__", "\n") # if there is an uneven number of '*' add one to the end @@ -237,7 +230,10 @@ class ConversationAgent(Agent): total_result = total_result.split("#")[0] # Removes partial sentence at the end - total_result = re.sub(r"[^\.\?\!\*]+(\n|$)", "", total_result) + total_result = util.strip_partial_sentences(total_result) + + # Remove "{character.name}:" - all occurences + total_result = total_result.replace(f"{character.name}:", "") if total_result.count("*") % 2 == 1: total_result += "*" diff --git a/src/talemate/agents/memory.py b/src/talemate/agents/memory.py index 7661c517..9b2afb2d 100644 --- a/src/talemate/agents/memory.py +++ b/src/talemate/agents/memory.py @@ -50,14 +50,13 @@ class MemoryAgent(Agent): def close_db(self): raise NotImplementedError() - async def add(self, text, character=None, uid=None): + async def add(self, text, character=None, uid=None, ts:str=None, **kwargs): if not text: return - log.debug("memory add", text=text, character=character, uid=uid) - await self._add(text, character=character, uid=uid) + await self._add(text, character=character, uid=uid, ts=ts, **kwargs) - async def _add(self, text, character=None): + async def _add(self, text, character=None, ts:str=None, **kwargs): raise NotImplementedError() async def add_many(self, objects: list[dict]): @@ -79,7 +78,7 @@ class MemoryAgent(Agent): return self.db.get(id) def on_archive_add(self, event: events.ArchiveEvent): - asyncio.ensure_future(self.add(event.text, uid=event.memory_id)) + asyncio.ensure_future(self.add(event.text, uid=event.memory_id, ts=event.ts, typ="history")) def on_character_state(self, event: events.CharacterStateEvent): asyncio.ensure_future( @@ -256,7 +255,7 @@ class ChromaDBMemoryAgent(MemoryAgent): self.db_client = chromadb.Client(Settings(anonymized_telemetry=False)) - openai_key = self.config.get("openai").get("api_key") or os.environ.get("OPENAI_API_KEY"), + openai_key = self.config.get("openai").get("api_key") or os.environ.get("OPENAI_API_KEY") if openai_key and self.USE_OPENAI: log.info( @@ -300,25 +299,35 @@ class ChromaDBMemoryAgent(MemoryAgent): except ValueError: pass - async def _add(self, text, character=None, uid=None): + async def _add(self, text, character=None, uid=None, ts:str=None, **kwargs): metadatas = [] ids = [] await self.emit_status(processing=True) if character: - metadatas.append({"character": character.name, "source": "talemate"}) + meta = {"character": character.name, "source": "talemate"} + if ts: + meta["ts"] = ts + meta.update(kwargs) + metadatas.append(meta) self.memory_tracker.setdefault(character.name, 0) self.memory_tracker[character.name] += 1 id = uid or f"{character.name}-{self.memory_tracker[character.name]}" ids = [id] else: - metadatas.append({"character": "__narrator__", "source": "talemate"}) + meta = {"character": "__narrator__", "source": "talemate"} + if ts: + meta["ts"] = ts + meta.update(kwargs) + metadatas.append(meta) self.memory_tracker.setdefault("__narrator__", 0) self.memory_tracker["__narrator__"] += 1 id = uid or f"__narrator__-{self.memory_tracker['__narrator__']}" ids = [id] + log.debug("chromadb agent add", text=text, meta=meta, id=id) + self.db.upsert(documents=[text], metadatas=metadatas, ids=ids) await self.emit_status(processing=False) @@ -341,7 +350,6 @@ class ChromaDBMemoryAgent(MemoryAgent): metadatas.append(meta) uid = obj.get("id", f"{character}-{self.memory_tracker[character]}") ids.append(uid) - self.db.upsert(documents=documents, metadatas=metadatas, ids=ids) await self.emit_status(processing=False) @@ -371,14 +379,27 @@ class ChromaDBMemoryAgent(MemoryAgent): #log.debug("crhomadb agent get", text=text, where=where) _results = self.db.query(query_texts=[text], where=where) - + results = [] for i in range(len(_results["distances"][0])): - await asyncio.sleep(0.001) distance = _results["distances"][0][i] + + doc = _results["documents"][0][i] + meta = _results["metadatas"][0][i] + ts = meta.get("ts") + if distance < 1: - results.append(_results["documents"][0][i]) + + try: + date_prefix = util.iso8601_diff_to_human(ts, self.scene.ts) + except Exception: + log.error("chromadb agent", error="failed to get date prefix", ts=ts, scene_ts=self.scene.ts) + date_prefix = None + + if date_prefix: + doc = f"{date_prefix}: {doc}" + results.append(doc) else: break diff --git a/src/talemate/agents/summarize.py b/src/talemate/agents/summarize.py index 11cd9648..fb79ac12 100644 --- a/src/talemate/agents/summarize.py +++ b/src/talemate/agents/summarize.py @@ -1,12 +1,13 @@ from __future__ import annotations import asyncio +import traceback from typing import TYPE_CHECKING, Callable, List, Optional, Union import talemate.data_objects as data_objects import talemate.util as util from talemate.prompts import Prompt -from talemate.scene_message import DirectorMessage +from talemate.scene_message import DirectorMessage, TimePassageMessage from .base import Agent, set_processing from .registry import register @@ -14,6 +15,7 @@ from .registry import register import structlog import time +import re log = structlog.get_logger("talemate.agents.summarize") @@ -40,6 +42,16 @@ class SummarizeAgent(Agent): super().connect(scene) scene.signals["history_add"].connect(self.on_history_add) + def clean_result(self, result): + if "#" in result: + result = result.split("#")[0] + + # Removes partial sentence at the end + result = re.sub(r"[^\.\?\!]+(\n|$)", "", result) + result = result.strip() + + return result + @set_processing async def build_archive(self, scene): end = None @@ -49,16 +61,36 @@ class SummarizeAgent(Agent): recent_entry = None else: recent_entry = scene.archived_history[-1] - start = recent_entry["end"] + 1 + start = recent_entry.get("end", 0) + 1 - token_threshold = 1300 + token_threshold = 1500 tokens = 0 dialogue_entries = [] + ts = "PT0S" + time_passage_termination = False + + if recent_entry: + ts = recent_entry.get("ts", ts) + for i in range(start, len(scene.history)): dialogue = scene.history[i] if isinstance(dialogue, DirectorMessage): + if i == start: + start += 1 continue + if isinstance(dialogue, TimePassageMessage): + log.debug("build_archive", time_passage_message=dialogue) + if i == start: + ts = util.iso8601_add(ts, dialogue.ts) + log.debug("build_archive", time_passage_message=dialogue, start=start, i=i, ts=ts) + start += 1 + continue + log.debug("build_archive", time_passage_message_termination=dialogue) + time_passage_termination = True + end = i - 1 + break + tokens += util.count_tokens(dialogue) dialogue_entries.append(dialogue) if tokens > token_threshold: # @@ -68,49 +100,65 @@ class SummarizeAgent(Agent): if end is None: # nothing to archive yet return + + log.debug("build_archive", start=start, end=end, ts=ts, time_passage_termination=time_passage_termination) extra_context = None if recent_entry: extra_context = recent_entry["text"] + + # in order to summarize coherently, we need to determine if there is a favorable + # cutoff point (e.g., the scene naturally ends or shifts meaninfully in the middle + # of the dialogue) + # + # One way to do this is to check if the last line is a TimePassageMessage, which + # indicates a scene change or a significant pause. + # + # If not, we can ask the AI to find a good point of + # termination. + + if not time_passage_termination: + + # No TimePassageMessage, so we need to ask the AI to find a good point of termination + + terminating_line = await self.analyze_dialoge(dialogue_entries) - terminating_line = await self.analyze_dialoge(dialogue_entries) + if terminating_line: + adjusted_dialogue = [] + for line in dialogue_entries: + if str(line) in terminating_line: + break + adjusted_dialogue.append(line) + dialogue_entries = adjusted_dialogue + end = start + len(dialogue_entries) + + if dialogue_entries: + summarized = await self.summarize( + "\n".join(map(str, dialogue_entries)), extra_context=extra_context + ) + + else: + # AI has likely identified the first line as a scene change, so we can't summarize + # just use the first line + summarized = str(scene.history[start]) - log.debug("summarize agent build archive", terminating_line=terminating_line) + # determine the appropariate timestamp for the summarization - if terminating_line: - adjusted_dialogue = [] - for line in dialogue_entries: - if str(line) in terminating_line: - break - adjusted_dialogue.append(line) - dialogue_entries = adjusted_dialogue - end = start + len(dialogue_entries) - - summarized = await self.summarize( - "\n".join(map(str, dialogue_entries)), extra_context=extra_context - ) - - scene.push_archive(data_objects.ArchiveEntry(summarized, start, end)) + scene.push_archive(data_objects.ArchiveEntry(summarized, start, end, ts=ts)) return True @set_processing async def analyze_dialoge(self, dialogue): - instruction = "Examine the dialogue from the beginning and find the first line that marks a scene change. Repeat the line back to me exactly as it is written" - - prepare_response = "The first line that marks a scene change is: " - - prompt = dialogue + ["", instruction, f"<|BOT|>{prepare_response}"] - - response = await self.client.send_prompt("\n".join(map(str, prompt)), kind="summarize") - - if prepare_response in response: - response = response.replace(prepare_response, "") - + response = await Prompt.request("summarizer.analyze-dialogue", self.client, "analyze_freeform", vars={ + "dialogue": "\n".join(map(str, dialogue)), + "scene": self.scene, + "max_tokens": self.client.max_token_length, + }) + response = self.clean_result(response) - return response - + @set_processing async def summarize( self, @@ -129,7 +177,7 @@ class SummarizeAgent(Agent): "max_tokens": self.client.max_token_length, }) - self.scene.log.info("summarize", dialogue=text, response=response) + self.scene.log.info("summarize", dialogue_length=len(text), summarized_length=len(response)) return self.clean_result(response) @@ -195,4 +243,52 @@ class SummarizeAgent(Agent): self.scene.log.debug("request_world_state_inline", marked_items=marked_items_response, time=time.time() - t1) - return marked_items_response \ No newline at end of file + return marked_items_response + + @set_processing + async def analyze_time_passage( + self, + text: str, + ): + + response = await Prompt.request( + "summarizer.analyze-time-passage", + self.client, + "analyze_freeform_short", + vars = { + "scene": self.scene, + "max_tokens": self.client.max_token_length, + "text": text, + } + ) + + duration = response.split("\n")[0].split(" ")[0].strip() + + if not duration.startswith("P"): + duration = "P"+duration + + return duration + + + @set_processing + async def analyze_text_and_answer_question( + self, + text: str, + query: str, + ): + + response = await Prompt.request( + "summarizer.analyze-text-and-answer-question", + self.client, + "analyze_freeform", + vars = { + "scene": self.scene, + "max_tokens": self.client.max_token_length, + "text": text, + "query": query, + } + ) + + log.debug("analyze_text_and_answer_question", query=query, text=text, response=response) + + return response \ No newline at end of file diff --git a/src/talemate/client/context.py b/src/talemate/client/context.py index 05506232..1ed795b6 100644 --- a/src/talemate/client/context.py +++ b/src/talemate/client/context.py @@ -4,6 +4,9 @@ Context managers for various client-side operations. from contextvars import ContextVar from pydantic import BaseModel, Field +from copy import deepcopy + +import structlog __all__ = [ 'context_data', @@ -11,6 +14,14 @@ __all__ = [ 'ContextModel', ] +log = structlog.get_logger() + +def model_to_dict_without_defaults(model_instance): + model_dict = model_instance.dict() + for field_name, field in model_instance.__class__.__fields__.items(): + if field.default == model_dict.get(field_name): + del model_dict[field_name] + return model_dict class ConversationContext(BaseModel): talking_character: str = None @@ -47,33 +58,23 @@ class ClientContext: Initialize the context manager with the key-value pairs to be set. """ # Validate the data with the Pydantic model - self.values = ContextModel(**kwargs).dict() - self.tokens = {} + self.values = model_to_dict_without_defaults(ContextModel(**kwargs)) def __enter__(self): """ Set the key-value pairs to the context variable `context_data` when entering the context. """ # Get the current context data - data = context_data.get() - # For each key-value pair, save the current value of the key (if it exists) and set the new value - for key, value in self.values.items(): - self.tokens[key] = data.get(key, None) - data[key] = value + + data = deepcopy(context_data.get()) if context_data.get() else {} + data.update(self.values) + # Update the context data - context_data.set(data) + self.token = context_data.set(data) def __exit__(self, exc_type, exc_val, exc_tb): """ Reset the context variable `context_data` to its previous values when exiting the context. """ - # Get the current context data - data = context_data.get() - # For each key, if a previous value exists, reset it. Otherwise, remove the key - for key in self.values.keys(): - if self.tokens[key] is not None: - data[key] = self.tokens[key] - else: - data.pop(key, None) - # Update the context data - context_data.set(data) \ No newline at end of file + + context_data.reset(self.token) diff --git a/src/talemate/client/textgenwebui.py b/src/talemate/client/textgenwebui.py index 62ae7d7b..2f0c4b3d 100644 --- a/src/talemate/client/textgenwebui.py +++ b/src/talemate/client/textgenwebui.py @@ -491,10 +491,15 @@ class TextGeneratorWebuiClient(RESTTaleMateClient): "chat_prompt_size": self.max_token_length, } - config.update(PRESET_SIMPLE_1) + 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, @@ -606,7 +611,7 @@ class TextGeneratorWebuiClient(RESTTaleMateClient): 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: 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")) @@ -621,6 +626,8 @@ class TextGeneratorWebuiClient(RESTTaleMateClient): 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']}|") response = await self.send_message(message, fn_url()) diff --git a/src/talemate/commands/__init__.py b/src/talemate/commands/__init__.py index 0e8477a8..327c443a 100644 --- a/src/talemate/commands/__init__.py +++ b/src/talemate/commands/__init__.py @@ -22,6 +22,7 @@ from .cmd_save import CmdSave from .cmd_save_as import CmdSaveAs from .cmd_save_characters import CmdSaveCharacters from .cmd_setenv import CmdSetEnvironmentToScene, CmdSetEnvironmentToCreative +from .cmd_time_util import * from .cmd_world_state import CmdWorldState from .cmd_run_helios_test import CmdHeliosTest from .manager import Manager \ No newline at end of file diff --git a/src/talemate/commands/cmd_rebuild_archive.py b/src/talemate/commands/cmd_rebuild_archive.py index 97910703..a5633a54 100644 --- a/src/talemate/commands/cmd_rebuild_archive.py +++ b/src/talemate/commands/cmd_rebuild_archive.py @@ -20,8 +20,11 @@ class CmdRebuildArchive(TalemateCommand): if not summarizer: self.system_message("No summarizer found") return True - - self.scene.archived_history = [] + + # clear out archived history, but keep pre-established history + self.scene.archived_history = [ + ah for ah in self.scene.archived_history if ah.get("end") is None + ] while True: more = await summarizer.agent.build_archive(self.scene) diff --git a/src/talemate/commands/cmd_time_util.py b/src/talemate/commands/cmd_time_util.py new file mode 100644 index 00000000..e5064287 --- /dev/null +++ b/src/talemate/commands/cmd_time_util.py @@ -0,0 +1,50 @@ +""" +Commands to manage scene timescale +""" + +import asyncio +import logging + +from talemate.commands.base import TalemateCommand +from talemate.commands.manager import register +from talemate.prompts.base import set_default_sectioning_handler +from talemate.scene_message import TimePassageMessage +from talemate.util import iso8601_duration_to_human +from talemate.emit import wait_for_input, emit +import isodate + +__all__ = [ + "CmdAdvanceTime", +] + +@register +class CmdAdvanceTime(TalemateCommand): + """ + Command class for the 'advance_time' command + """ + + name = "advance_time" + description = "Advance the scene time by a given amount (expects iso8601 duration))" + aliases = ["time_a"] + + async def run(self): + if not self.args: + self.emit("system", "You must specify an amount of time to advance") + return + + try: + isodate.parse_duration(self.args[0]) + except isodate.ISO8601Error: + self.emit("system", "Invalid duration") + return + + try: + msg = self.args[1] + except IndexError: + msg = iso8601_duration_to_human(self.args[0], suffix=" later") + + message = TimePassageMessage(ts=self.args[0], message=msg) + emit('time', message) + + self.scene.push_history(message) + self.scene.emit_status() \ No newline at end of file diff --git a/src/talemate/data_objects.py b/src/talemate/data_objects.py index fda74ca4..9ed2a4f0 100644 --- a/src/talemate/data_objects.py +++ b/src/talemate/data_objects.py @@ -1,8 +1,12 @@ from dataclasses import dataclass +__all__ = [ + "ArchiveEntry", +] @dataclass class ArchiveEntry: text: str - start: int - end: int + start: int = None + end: int = None + ts: str = None \ No newline at end of file diff --git a/src/talemate/emit/base.py b/src/talemate/emit/base.py index 22194758..02ece2bd 100644 --- a/src/talemate/emit/base.py +++ b/src/talemate/emit/base.py @@ -29,6 +29,7 @@ class AbortCommand(IOError): class Emission: typ: str message: str = None + message_object: SceneMessage = None character: Character = None scene: Scene = None status: str = None @@ -43,12 +44,16 @@ def emit( if typ not in handlers: raise ValueError(f"Unknown message type: {typ}") + if isinstance(message, SceneMessage): kwargs["id"] = message.id + message_object = message message = message.message + else: + message_object = None handlers[typ].send( - Emission(typ=typ, message=message, character=character, scene=scene, **kwargs) + Emission(typ=typ, message=message, character=character, scene=scene, message_object=message_object, **kwargs) ) diff --git a/src/talemate/emit/signals.py b/src/talemate/emit/signals.py index b886d4a2..53c557d2 100644 --- a/src/talemate/emit/signals.py +++ b/src/talemate/emit/signals.py @@ -5,6 +5,7 @@ NarratorMessage = signal("narrator") CharacterMessage = signal("character") PlayerMessage = signal("player") DirectorMessage = signal("director") +TimePassageMessage = signal("time") ClearScreen = signal("clear_screen") @@ -31,6 +32,7 @@ handlers = { "character": CharacterMessage, "player": PlayerMessage, "director": DirectorMessage, + "time": TimePassageMessage, "request_input": RequestInput, "receive_input": ReceiveInput, "client_status": ClientStatus, diff --git a/src/talemate/events.py b/src/talemate/events.py index 40dec145..3800c554 100644 --- a/src/talemate/events.py +++ b/src/talemate/events.py @@ -27,6 +27,7 @@ class HistoryEvent(Event): class ArchiveEvent(Event): text: str memory_id: str = None + ts: str = None @dataclass diff --git a/src/talemate/load.py b/src/talemate/load.py index 219d1b9e..35d4dffa 100644 --- a/src/talemate/load.py +++ b/src/talemate/load.py @@ -6,7 +6,9 @@ from dotenv import load_dotenv import talemate.events as events from talemate import Actor, Character, Player from talemate.config import load_config -from talemate.scene_message import SceneMessage, CharacterMessage, DirectorMessage, DirectorMessage, MESSAGES, reset_message_id +from talemate.scene_message import ( + SceneMessage, CharacterMessage, NarratorMessage, DirectorMessage, MESSAGES, reset_message_id +) from talemate.world_state import WorldState import talemate.instance as instance @@ -144,12 +146,20 @@ async def load_scene_from_data( ) scene.assets.cover_image = scene_data.get("assets", {}).get("cover_image", None) scene.assets.load_assets(scene_data.get("assets", {}).get("assets", {})) - + + scene.sync_time() + log.debug("scene time", ts=scene.ts) + for ah in scene.archived_history: if reset: break + ts = ah.get("ts", "PT1S") + + if not ah.get("ts"): + ah["ts"] = ts + scene.signals["archive_add"].send( - events.ArchiveEvent(scene=scene, event_type="archive_add", text=ah["text"]) + events.ArchiveEvent(scene=scene, event_type="archive_add", text=ah["text"], ts=ts) ) for character_name, cs in scene.character_states.items(): @@ -312,7 +322,7 @@ def _prepare_legacy_history(entry): """ if entry.startswith("*"): - cls = DirectorMessage + cls = NarratorMessage elif entry.startswith("Director instructs"): cls = DirectorMessage else: diff --git a/src/talemate/prompts/base.py b/src/talemate/prompts/base.py index 8f61aef2..cdd279ca 100644 --- a/src/talemate/prompts/base.py +++ b/src/talemate/prompts/base.py @@ -177,6 +177,9 @@ class Prompt: # prompt variables vars: dict = dataclasses.field(default_factory=dict) + # pad prepared response and ai response with a white-space + pad_prepended_response: bool = True + prepared_response: str = "" eval_response: bool = False @@ -282,6 +285,7 @@ class Prompt: env.globals["set_question_eval"] = self.set_question_eval env.globals["query_scene"] = self.query_scene env.globals["query_memory"] = self.query_memory + env.globals["query_text"] = self.query_text env.globals["uuidgen"] = lambda: str(uuid.uuid4()) env.globals["to_int"] = lambda x: int(x) env.globals["config"] = self.config @@ -336,7 +340,15 @@ class Prompt: f"Answer: " + loop.run_until_complete(narrator.narrate_query(query, at_the_end=at_the_end, as_narrative=as_narrative)), ]) - + + def query_text(self, query:str, text:str): + loop = asyncio.get_event_loop() + summarizer = instance.get_agent("summarizer") + query = query.format(**self.vars) + return "\n".join([ + f"Question: {query}", + f"Answer: " + loop.run_until_complete(summarizer.analyze_text_and_answer_question(text, query)), + ]) def query_memory(self, query:str, as_question_answer:bool=True): loop = asyncio.get_event_loop() @@ -524,7 +536,8 @@ class Prompt: response = await client.send_prompt(str(self), kind=kind) if not response.lower().startswith(self.prepared_response.lower()): - response = self.prepared_response.rstrip() + " " + response.strip() + pad = " " if self.pad_prepended_response else "" + response = self.prepared_response.rstrip() + pad + response.strip() if self.eval_response: diff --git a/src/talemate/prompts/templates/conversation/dialogue.jinja2 b/src/talemate/prompts/templates/conversation/dialogue.jinja2 index 515f99a0..03ff0a1a 100644 --- a/src/talemate/prompts/templates/conversation/dialogue.jinja2 +++ b/src/talemate/prompts/templates/conversation/dialogue.jinja2 @@ -7,14 +7,14 @@ {% for character in characters -%} {{ character.name }}: {{ character.filtered_sheet(['name', 'description', 'age', 'gender']) }} -{{ query_memory(character.name+' personality', as_question_answer= False) }} +{{ query_memory("what is "+character.name+"'s personality?", as_question_answer=False) }} {% endfor %} <|CLOSE_SECTION|> <|SECTION:DIALOGUE EXAMPLES|> -{% for dialogue in talking_character.example_dialogue -%} -{{ dialogue }} -{% endfor -%} +{% for example in talking_character.random_dialogue_examples(num=3) -%} +{{ example }} +{% endfor %} <|CLOSE_SECTION|> <|SECTION:TASK|> diff --git a/src/talemate/prompts/templates/summarizer/analyze-dialogue.jinja2 b/src/talemate/prompts/templates/summarizer/analyze-dialogue.jinja2 new file mode 100644 index 00000000..3c060a81 --- /dev/null +++ b/src/talemate/prompts/templates/summarizer/analyze-dialogue.jinja2 @@ -0,0 +1,6 @@ + +{{ dialogue }} +<|SECTION:TASK|> +Examine the dialogue from the beginning and find the last line that marks a scene change. Repeat the line back to me exactly as it is written. +<|CLOSE_SECTION|> +{{ bot_token }}The first line that marks a scene change is: \ No newline at end of file diff --git a/src/talemate/prompts/templates/summarizer/analyze-text-and-answer-question.jinja2 b/src/talemate/prompts/templates/summarizer/analyze-text-and-answer-question.jinja2 new file mode 100644 index 00000000..0aeb7f8f --- /dev/null +++ b/src/talemate/prompts/templates/summarizer/analyze-text-and-answer-question.jinja2 @@ -0,0 +1,7 @@ +{{ text }} + +<|SECTION:TASK|> +Analyze the text above and answer the question. + +Question: {{ query }} +{{ bot_token }}Answer: \ No newline at end of file diff --git a/src/talemate/prompts/templates/summarizer/analyze-time-passage.jinja2 b/src/talemate/prompts/templates/summarizer/analyze-time-passage.jinja2 new file mode 100644 index 00000000..b912b028 --- /dev/null +++ b/src/talemate/prompts/templates/summarizer/analyze-time-passage.jinja2 @@ -0,0 +1,5 @@ +<|SECTION:SCENE|> +{{ text }} +<|SECTION:TASK|> +Question: How much time has passed in the scene above? +{{ bot_token }}Answer (ISO8601 duration): P \ No newline at end of file diff --git a/src/talemate/prompts/templates/summarizer/summarize-dialogue.jinja2 b/src/talemate/prompts/templates/summarizer/summarize-dialogue.jinja2 index 4ba822ea..85388a26 100644 --- a/src/talemate/prompts/templates/summarizer/summarize-dialogue.jinja2 +++ b/src/talemate/prompts/templates/summarizer/summarize-dialogue.jinja2 @@ -5,6 +5,9 @@ <|SECTION:TASK|> Question: What happens within the dialogue? Summarize into narrative description. Content Context: This is a specific scene from {{ scene.context }} -Expected Answer: A summarized narrative description of the dialogue that can be inserted into the ongoing story in place of the dialogue. +Expected Answer: A summarized narrative description of the dialogue that can be inserted into the ongoing story in place of the dialogue. + +Include implied time skips (for example characters plan to meet at a later date and then they meet). + <|CLOSE_SECTION|> Narrator answers: \ No newline at end of file diff --git a/src/talemate/scene_message.py b/src/talemate/scene_message.py index 9fc3bc94..4d4e7972 100644 --- a/src/talemate/scene_message.py +++ b/src/talemate/scene_message.py @@ -1,4 +1,5 @@ from dataclasses import dataclass, field +import isodate _message_id = 0 @@ -11,11 +12,23 @@ def reset_message_id(): global _message_id _message_id = 0 + @dataclass class SceneMessage: + + """ + Base class for all messages that are sent to the scene. + """ + + # the mesage itself message: str + + # the id of the message id: int = field(default_factory=get_message_id) + + # the source of the message (e.g. "ai", "progress_story", "director") source: str = "" + typ = "scene" @@ -83,12 +96,25 @@ class DirectorMessage(SceneMessage): return f"[Story progression instructions for {char_name}: {message}]" - +@dataclass +class TimePassageMessage(SceneMessage): + ts: str = "PT0S" + source: str = "manual" + typ = "time" + + def __dict__(self): + return { + "message": self.message, + "id": self.id, + "typ": "time", + "source": self.source, + "ts": self.ts, + } - MESSAGES = { "scene": SceneMessage, "character": CharacterMessage, "narrator": NarratorMessage, "director": DirectorMessage, + "time": TimePassageMessage, } \ No newline at end of file diff --git a/src/talemate/server/websocket_server.py b/src/talemate/server/websocket_server.py index 6e48c1fa..63327c4f 100644 --- a/src/talemate/server/websocket_server.py +++ b/src/talemate/server/websocket_server.py @@ -292,6 +292,16 @@ class WebsocketHandler(Receiver): } ) + def handle_time(self, emission: Emission): + self.queue_put( + { + "type": "time", + "message": emission.message, + "id": emission.id, + "ts": emission.message_object.ts, + } + ) + def handle_prompt_sent(self, emission: Emission): self.queue_put( { diff --git a/src/talemate/tale_mate.py b/src/talemate/tale_mate.py index 4a3c088a..344596a8 100644 --- a/src/talemate/tale_mate.py +++ b/src/talemate/tale_mate.py @@ -5,6 +5,7 @@ import os import random import traceback import re +import isodate from typing import Dict, List, Optional, Union from blinker import signal @@ -18,7 +19,7 @@ import talemate.util as util import talemate.save as save from talemate.emit import Emitter, emit, wait_for_input from talemate.util import colored_text, count_tokens, extract_metadata, wrap_text -from talemate.scene_message import SceneMessage, CharacterMessage, DirectorMessage, NarratorMessage +from talemate.scene_message import SceneMessage, CharacterMessage, DirectorMessage, NarratorMessage, TimePassageMessage from talemate.exceptions import ExitScene, RestartSceneLoop, ResetScene, TalemateError, TalemateInterrupt, LLMAccuracyError from talemate.world_state import WorldState from talemate.config import SceneConfig @@ -141,6 +142,29 @@ class Character: return random.choice(self.example_dialogue) + def random_dialogue_examples(self, num:int=3): + """ + Get multiple random example dialogue lines for this character. + + Will return up to `num` examples and not have any duplicates. + """ + + if not self.example_dialogue: + return [] + + # create copy of example_dialogue so we dont modify the original + + examples = self.example_dialogue.copy() + + # shuffle the examples so we get a random order + + random.shuffle(examples) + + # now pop examples until we have `num` examples or we run out of examples + + return [examples.pop() for _ in range(min(num, len(examples)))] + + def filtered_sheet(self, attributes: list[str]): """ @@ -260,10 +284,11 @@ class Character: if "color" in metadata: self.color = metadata["color"] if "mes_example" in metadata: + new_line_match = "\r\n" if "\r\n" in metadata["mes_example"] else "\n" for message in metadata["mes_example"].split(""): - if message.strip("\r\n"): + if message.strip(new_line_match): self.example_dialogue.extend( - [m for m in message.split("\r\n") if m] + [m for m in message.split(new_line_match) if m] ) @@ -335,9 +360,9 @@ class Character: } }) - for detail in self.details: + for key, detail in self.details.items(): items.append({ - "text": f"{self.name} details: {detail}", + "text": f"{self.name} - {key}: {detail}", "meta": { "character": self.name, "typ": "details", @@ -522,6 +547,7 @@ class Scene(Emitter): self.environment = "scene" self.goal = None self.world_state = WorldState() + self.ts = "PT0S" self.automated_actions = {} @@ -610,6 +636,10 @@ class Scene(Emitter): def push_history(self, messages: list[SceneMessage]): + """ + Adds one or more messages to the scene history + """ + if isinstance(messages, SceneMessage): messages = [messages] @@ -623,6 +653,9 @@ class Scene(Emitter): if isinstance(self.history[idx], DirectorMessage): self.history.pop(idx) break + + elif isinstance(message, TimePassageMessage): + self.advance_time(message.ts) self.history.extend(messages) self.signals["history_add"].send( @@ -634,19 +667,26 @@ class Scene(Emitter): ) def push_archive(self, entry: data_objects.ArchiveEntry): + + """ + Adds an entry to the archive history. + + The archive history is a list of summarized history entries. + """ + self.archived_history.append(entry.__dict__) self.signals["archive_add"].send( events.ArchiveEvent( scene=self, event_type="archive_add", text=entry.text, + ts=entry.ts, ) ) emit("archived_history", data={ "history":[archived_history["text"] for archived_history in self.archived_history] }) - def edit_message(self, message_id:int, message:str): """ Finds the message in `history` by its id and will update its contents @@ -828,7 +868,7 @@ class Scene(Emitter): # we then take the history from the end index to the end of the history if self.archived_history: - end = self.archived_history[-1]["end"] + end = self.archived_history[-1].get("end", 0) else: end = 0 @@ -865,8 +905,17 @@ class Scene(Emitter): # description at tbe beginning of the context history archive_insert_idx = 0 + + # iterate backwards through archived history and count how many entries + # there are that have an end index + num_archived_entries = 0 + if add_archieved_history: + for i in range(len(self.archived_history) - 1, -1, -1): + if self.archived_history[i].get("end") is None: + break + num_archived_entries += 1 - if len(self.archived_history) <= 2 and add_archieved_history: + if num_archived_entries <= 2 and add_archieved_history: for character in self.characters: @@ -898,6 +947,13 @@ class Scene(Emitter): context_history.insert(archive_insert_idx, "<|CLOSE_SECTION|>") while i >= 0 and limit > 0 and add_archieved_history: + + # we skip predefined history, that should be joined in through + # long term memory queries + + if self.archived_history[i].get("end") is None: + break + text = self.archived_history[i]["text"] if count_tokens(context_history) + count_tokens(text) > budget: break @@ -1038,6 +1094,11 @@ class Scene(Emitter): self.history.pop(i) log.info(f"Deleted message {message_id}") emit("remove_message", "", id=message_id) + + if isinstance(message, TimePassageMessage): + self.sync_time() + self.emit_status() + break def emit_status(self): @@ -1050,6 +1111,7 @@ class Scene(Emitter): "scene_config": self.scene_config, "assets": self.assets.dict(), "characters": [actor.character.serialize for actor in self.actors], + "scene_time": util.iso8601_duration_to_human(self.ts, suffix="") if self.ts else None, }, ) @@ -1059,7 +1121,58 @@ class Scene(Emitter): """ self.environment = environment self.emit_status() - + + def advance_time(self, ts: str): + """ + Accepts an iso6801 duration string and advances the scene's world state by that amount + """ + + self.ts = isodate.duration_isoformat( + isodate.parse_duration(self.ts) + isodate.parse_duration(ts) + ) + + def sync_time(self): + """ + Loops through self.history looking for TimePassageMessage and will + advance the world state by the amount of time passed for each + """ + + # reset time + + self.ts = "PT0S" + + for message in self.history: + if isinstance(message, TimePassageMessage): + self.advance_time(message.ts) + + + self.log.info("sync_time", ts=self.ts) + + # TODO: need to adjust archived_history ts as well + # but removal also probably means the history needs to be regenerated + # anyway. + + def calc_time(self, start_idx:int=0, end_idx:int=None): + """ + Loops through self.history looking for TimePassageMessage and will + return the sum iso8601 duration string + + Defines start and end indexes + """ + + ts = "PT0S" + found = False + + for message in self.history[start_idx:end_idx]: + if isinstance(message, TimePassageMessage): + util.iso8601_add(ts, message.ts) + found = True + + if not found: + return None + + return ts + async def start(self): """ Start the scene @@ -1117,7 +1230,7 @@ class Scene(Emitter): actor = self.get_character(char_name).actor except AttributeError: # If the character is not an actor, then it is the narrator - self.narrator_message(item) + emit(item.typ, item) continue emit("character", item, character=actor.character) if not actor.character.is_player: @@ -1249,6 +1362,7 @@ class Scene(Emitter): "context": scene.context, "world_state": scene.world_state.dict(), "assets": scene.assets.dict(), + "ts": scene.ts, } emit("system", "Saving scene data to: " + filepath) diff --git a/src/talemate/util.py b/src/talemate/util.py index af47f35a..6b1d8ec6 100644 --- a/src/talemate/util.py +++ b/src/talemate/util.py @@ -4,6 +4,8 @@ import json import re import textwrap import structlog +import isodate +import datetime from typing import List from colorama import Back, Fore, Style, init @@ -297,6 +299,26 @@ def pronouns(gender: str) -> tuple[str, str]: return (pronoun, possessive_determiner) +def strip_partial_sentences(text:str) -> str: + # Sentence ending characters + sentence_endings = ['.', '!', '?', '"', "*"] + + # Check if the last character is already a sentence ending + if text[-1] in sentence_endings: + return text + + # Split the text into words + words = text.split() + + # Iterate over the words in reverse order until a sentence ending is found + for i in range(len(words) - 1, -1, -1): + if words[i][-1] in sentence_endings: + return ' '.join(words[:i+1]) + + # If no sentence ending is found, return the original text + return text + + def clean_paragraph(paragraph: str) -> str: """ Cleans up a paragraph of text by: @@ -431,4 +453,145 @@ def fix_faulty_json(data: str) -> str: data = re.sub(r',\s*}', '}', data) data = re.sub(r',\s*]', ']', data) - return data \ No newline at end of file + return data + +def duration_to_timedelta(duration): + """Convert an isodate.Duration object to a datetime.timedelta object.""" + days = int(duration.years) * 365 + int(duration.months) * 30 + int(duration.days) + return datetime.timedelta(days=days) + +def timedelta_to_duration(delta): + """Convert a datetime.timedelta object to an isodate.Duration object.""" + days = delta.days + years = days // 365 + days %= 365 + months = days // 30 + days %= 30 + return isodate.duration.Duration(years=years, months=months, days=days) + +def parse_duration_to_isodate_duration(duration_str): + """Parse ISO 8601 duration string and ensure the result is an isodate.Duration.""" + parsed_duration = isodate.parse_duration(duration_str) + if isinstance(parsed_duration, datetime.timedelta): + days = parsed_duration.days + years = days // 365 + days %= 365 + months = days // 30 + days %= 30 + return isodate.duration.Duration(years=years, months=months, days=days) + return parsed_duration + +def iso8601_diff(duration_str1, duration_str2): + # Parse the ISO 8601 duration strings ensuring they are isodate.Duration objects + duration1 = parse_duration_to_isodate_duration(duration_str1) + duration2 = parse_duration_to_isodate_duration(duration_str2) + + # Convert to timedelta + timedelta1 = duration_to_timedelta(duration1) + timedelta2 = duration_to_timedelta(duration2) + + # Calculate the difference + difference_timedelta = abs(timedelta1 - timedelta2) + + # Convert back to Duration for further processing + difference = timedelta_to_duration(difference_timedelta) + + return difference + +def iso8601_duration_to_human(iso_duration, suffix:str=" ago"): + # Parse the ISO8601 duration string into an isodate duration object + + if isinstance(iso_duration, isodate.Duration): + duration = iso_duration + else: + duration = isodate.parse_duration(iso_duration) + + if isinstance(duration, isodate.Duration): + years = duration.years + months = duration.months + days = duration.days + seconds = duration.tdelta.total_seconds() + else: + years, months = 0, 0 + days = duration.days + seconds = duration.total_seconds() - days * 86400 # Extract time-only part + + hours, seconds = divmod(seconds, 3600) + minutes, seconds = divmod(seconds, 60) + + components = [] + if years: + components.append(f"{years} Year{'s' if years > 1 else ''}") + if months: + components.append(f"{months} Month{'s' if months > 1 else ''}") + if days: + components.append(f"{days} Day{'s' if days > 1 else ''}") + if hours: + components.append(f"{int(hours)} Hour{'s' if hours > 1 else ''}") + if minutes: + components.append(f"{int(minutes)} Minute{'s' if minutes > 1 else ''}") + if seconds: + components.append(f"{int(seconds)} Second{'s' if seconds > 1 else ''}") + + # Construct the human-readable string + if len(components) > 1: + last = components.pop() + human_str = ', '.join(components) + ' and ' + last + elif components: + human_str = components[0] + else: + human_str = "0 Seconds" + + return f"{human_str}{suffix}" + +def iso8601_diff_to_human(start, end): + if not start or not end: + return "" + + diff = iso8601_diff(start, end) + return iso8601_duration_to_human(diff) + + +def iso8601_add(date_a:str, date_b:str) -> str: + """ + Adds two ISO 8601 durations together. + """ + # Validate input + if not date_a or not date_b: + return "PT0S" + + new_ts = isodate.parse_duration(date_a.strip()) + isodate.parse_duration(date_b.strip()) + return isodate.duration_isoformat(new_ts) + +def iso8601_correct_duration(duration: str) -> str: + # Split the string into date and time components using 'T' as the delimiter + parts = duration.split("T") + + # Handle the date component + date_component = parts[0] + time_component = "" + + # If there's a time component, process it + if len(parts) > 1: + time_component = parts[1] + + # Check if the time component has any date values (Y, M, D) and move them to the date component + for char in "YD": # Removed 'M' from this loop + if char in time_component: + index = time_component.index(char) + date_component += time_component[:index+1] + time_component = time_component[index+1:] + + # If the date component contains any time values (H, M, S), move them to the time component + for char in "HMS": + if char in date_component: + index = date_component.index(char) + time_component = date_component[index:] + time_component + date_component = date_component[:index] + + # Combine the corrected date and time components + corrected_duration = date_component + if time_component: + corrected_duration += "T" + time_component + + return corrected_duration \ No newline at end of file diff --git a/talemate_frontend/src/components/SceneMessages.vue b/talemate_frontend/src/components/SceneMessages.vue index bd366703..ae221fbb 100644 --- a/talemate_frontend/src/components/SceneMessages.vue +++ b/talemate_frontend/src/components/SceneMessages.vue @@ -40,6 +40,11 @@ +
+
+ +
+
{{ message.text }}
@@ -51,6 +56,7 @@ import CharacterMessage from './CharacterMessage.vue'; import NarratorMessage from './NarratorMessage.vue'; import DirectorMessage from './DirectorMessage.vue'; +import TimePassageMessage from './TimePassageMessage.vue'; export default { name: 'SceneMessages', @@ -58,6 +64,7 @@ export default { CharacterMessage, NarratorMessage, DirectorMessage, + TimePassageMessage, }, data() { return { @@ -87,6 +94,7 @@ export default { multiSelect: data.data.multi_select, color: data.color, sent: false, + ts: data.ts, }; this.messages.push(message); }, @@ -163,10 +171,12 @@ export default { if (data.message) { if (data.type === 'character') { - const [character, text] = data.message.split(':'); + const parts = data.message.split(':'); + const character = parts.shift(); + const text = parts.join(':'); this.messages.push({ id: data.id, type: data.type, character: character.trim(), text: text.trim(), color: data.color }); // Add color property to the message } else if (data.type != 'request_input' && data.type != 'client_status' && data.type != 'agent_status') { - this.messages.push({ id: data.id, type: data.type, text: data.message, color: data.color, character: data.character, status:data.status }); // Add color property to the message + this.messages.push({ id: data.id, type: data.type, text: data.message, color: data.color, character: data.character, status:data.status, ts:data.ts }); // Add color property to the message } } diff --git a/talemate_frontend/src/components/SceneTools.vue b/talemate_frontend/src/components/SceneTools.vue index 52cbef41..6f6c4103 100644 --- a/talemate_frontend/src/components/SceneTools.vue +++ b/talemate_frontend/src/components/SceneTools.vue @@ -86,6 +86,20 @@ + + + + Advance Time + + {{ option.title }} + + + @@ -154,6 +169,23 @@ export default { return { commandActive: false, commandName: null, + + advanceTimeOptions: [ + {"value" : "P10Y", "title": "10 years"}, + {"value" : "P5Y", "title": "5 years"}, + {"value" : "P1Y", "title": "1 year"}, + {"value" : "P6M", "title": "6 months"}, + {"value" : "P3M", "title": "3 months"}, + {"value" : "P1M", "title": "1 month"}, + {"value" : "P7D:1 Week later", "title": "1 week"}, + {"value" : "P3D", "title": "3 days"}, + {"value" : "P1D", "title": "1 day"}, + {"value" : "PT8H", "title": "8 hours"}, + {"value" : "PT4H", "title": "4 hours"}, + {"Value" : "PT1H", "title": "1 hour"}, + {"value" : "PT30M", "title": "30 minutes"}, + {"value" : "PT15M", "title": "15 minutes"} + ], } }, inject: [ diff --git a/talemate_frontend/src/components/TalemateApp.vue b/talemate_frontend/src/components/TalemateApp.vue index e3cf8ae5..bffe3bb1 100644 --- a/talemate_frontend/src/components/TalemateApp.vue +++ b/talemate_frontend/src/components/TalemateApp.vue @@ -97,6 +97,11 @@ mdi-playlist-starHistory + + mdi-clock + {{ scene.scene_time }} + + Talemate @@ -294,6 +299,7 @@ export default { this.scene = { name: data.name, environment: data.data.environment, + scene_time: data.data.scene_time, } this.sceneActive = true; return; diff --git a/talemate_frontend/src/components/TimePassageMessage.vue b/talemate_frontend/src/components/TimePassageMessage.vue new file mode 100644 index 00000000..e3d740c3 --- /dev/null +++ b/talemate_frontend/src/components/TimePassageMessage.vue @@ -0,0 +1,61 @@ + + + + + \ No newline at end of file diff --git a/templates/llm-prompt/Airoboros.jinja2 b/templates/llm-prompt/Airoboros.jinja2 index bd53c75d..0ef9e87d 100644 --- a/templates/llm-prompt/Airoboros.jinja2 +++ b/templates/llm-prompt/Airoboros.jinja2 @@ -1,2 +1,2 @@ SYSTEM: {{ system_message }} -USER: {{ set_response(prompt, "\nASSISTANT:") }} \ No newline at end of file +USER: {{ set_response(prompt, "\nASSISTANT: ") }} \ No newline at end of file diff --git a/templates/llm-prompt/Speechless-Llama2-Hermes-Orca-Platypus-WizardLM.jinja2 b/templates/llm-prompt/Speechless-Llama2-Hermes-Orca-Platypus-WizardLM.jinja2 new file mode 100644 index 00000000..c68eb6c0 --- /dev/null +++ b/templates/llm-prompt/Speechless-Llama2-Hermes-Orca-Platypus-WizardLM.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/Vicuna.jinja2 b/templates/llm-prompt/Vicuna.jinja2 index bd53c75d..0ef9e87d 100644 --- a/templates/llm-prompt/Vicuna.jinja2 +++ b/templates/llm-prompt/Vicuna.jinja2 @@ -1,2 +1,2 @@ SYSTEM: {{ system_message }} -USER: {{ set_response(prompt, "\nASSISTANT:") }} \ No newline at end of file +USER: {{ set_response(prompt, "\nASSISTANT: ") }} \ No newline at end of file diff --git a/templates/llm-prompt/Xwin-LM.jinja2 b/templates/llm-prompt/Xwin-LM.jinja2 index b9f3762e..f2ec87e7 100644 --- a/templates/llm-prompt/Xwin-LM.jinja2 +++ b/templates/llm-prompt/Xwin-LM.jinja2 @@ -1 +1,2 @@ -{{ system_message }} USER: {{ set_response(prompt, " ASSISTANT:") }} \ No newline at end of file +{{ system_message }} +USER: {{ set_response(prompt, "\nASSISTANT: ") }} \ No newline at end of file