diff --git a/model/supervised_finetuning/README.md b/model/supervised_finetuning/README.md new file mode 100644 index 00000000..e223e1cd --- /dev/null +++ b/model/supervised_finetuning/README.md @@ -0,0 +1,38 @@ +# Train using supervised examples + +Requirements + +``` +wandb +evaluate +datasets +transformers +torch +``` + +Start training reward model + +```bash +python trainer.py --configs defaults galactica-125 +``` + +## Dataset + +For now we only support webgpt and summary dataset from OpenAI. Once +open-asisstant dataset are available it will be added here. + +## Model + +TBD + +## Results + +Experimental results in wandb +[here](https://wandb.ai/sanagnos/supervised-finetuning?workspace=user-sanagnos). + +## TODOS + +- decide on a model +- add special token to declare prompt and reply. Do nto freeze the weights for + these +- Merge utils etc with reward model diff --git a/model/supervised_finetuning/configs/config.yaml b/model/supervised_finetuning/configs/config.yaml new file mode 100644 index 00000000..f7164002 --- /dev/null +++ b/model/supervised_finetuning/configs/config.yaml @@ -0,0 +1,37 @@ +defaults: + learning_rate: 1e-5 + gradient_checkpointing: false + gradient_accumulation_steps: 32 + per_device_train_batch_size: 2 + per_device_eval_batch_size: 2 + weight_decay: 0.00 + warmup_steps: 600 + eval_steps: 200 + save_steps: 500 + max_length: 512 + num_train_epochs: 3 + logging_steps: 10 + max_grad_norm: 2.0 + save_total_limit: 4 + eval_accumulation_steps: + freeze_layer: + datasets: + - webgpt + cache_dir: ~/.cache + loss_fn: CrossEntropyLoss + eval_size: + log_dir: "base" + +galactica-125: + learning_rate: 5e-5 + model_name: facebook/galactica-125m + weight_decay: 0.01 + warmup_steps: 600 + gradient_checkpointing: false + gradient_accumulation_steps: 2 + per_device_train_batch_size: 4 + per_device_eval_batch_size: 4 + +debug: + eval_steps: 20 + eval_size: 100 diff --git a/model/supervised_finetuning/custom_datasets/__init__.py b/model/supervised_finetuning/custom_datasets/__init__.py new file mode 100644 index 00000000..fcab8a56 --- /dev/null +++ b/model/supervised_finetuning/custom_datasets/__init__.py @@ -0,0 +1,67 @@ +from datasets import load_dataset +from sklearn.model_selection import train_test_split +from torch.utils.data import Dataset, Subset + + +class SquadV2Dataset(Dataset): + def __init__(self, cache_dir, split): + self.dataset = load_dataset("squad_v2", cache_dir=cache_dir, split=split) + + def __len__(self): + return len(self.dataset) + + def __getitem__(self, idx): + data = self.dataset[idx] + # dummy return first answer + return "".join([data["title"], ". ", data["context"], " " + data["question"]]), data["answers"]["text"][0] + + +class WebGPT(Dataset): + def __init__(self) -> None: + super().__init__() + + dataset = load_dataset("openai/webgpt_comparisons") + questions = {} + # using prompt as our index will allows us + # to add additional generated prompt later + self.index2question = {} + for row in dataset["train"]: + question = row["question"]["full_text"] + if question not in self.index2question: + self.index2question[len(self.index2question)] = question + + # only keep the best answer + questions[question] = row["answer_0" if row["score_0"] > row["score_1"] else "answer_1"] + + self.questions = questions + + def __len__(self): + return len(self.index2question) + + def __getitem__(self, index): + question = self.index2question[index] + answer = self.questions[question] + return [question, answer] + + +def train_val_dataset(dataset, val_split=0.2): + train_idx, val_idx = train_test_split( + list(range(len(dataset))), test_size=val_split, random_state=666, shuffle=True + ) + return Subset(dataset, train_idx), Subset(dataset, val_idx) + + +def get_one_dataset(conf, dataset_name): + dataset_name = dataset_name.lower() + + if dataset_name == "squadv2": + raise ValueError("SquadV2 is not diverse enough for generation .. ") + train = SquadV2Dataset(conf.cache_dir, "train") + eval = SquadV2Dataset(conf.cache_dir, "validation") + elif dataset_name == "webgpt": + dataset = WebGPT() + train, eval = train_val_dataset(dataset, val_split=0.2) + else: + raise ValueError(f"Unknown dataset {dataset_name}") + + return train, eval diff --git a/model/supervised_finetuning/custom_datasets/dialogue_collator.py b/model/supervised_finetuning/custom_datasets/dialogue_collator.py new file mode 100644 index 00000000..17fe1082 --- /dev/null +++ b/model/supervised_finetuning/custom_datasets/dialogue_collator.py @@ -0,0 +1,85 @@ +from dataclasses import dataclass +from typing import Optional, Union + +import numpy as np +import torch +from torch.nn import functional as F +from transformers.tokenization_utils_base import PaddingStrategy, PreTrainedTokenizerBase + + +@dataclass +class DialogueDataCollator: + """ + Expects a list of texts corresponding to a sequence of [question, answer, question, answer, ...] pairs. + """ + + tokenizer: PreTrainedTokenizerBase + padding: Union[bool, str, PaddingStrategy] = True + max_length: Optional[int] = None + pad_to_multiple_of: Optional[int] = None + + def __call__(self, features): + # TODO add special tokens for question and answer here + # additional_special_tokens = ['', ''] + prompt_tokens = ["Question: ", "Answer: "] + + flatten_messages = [] + label_masks = [] + + for messages in features: + assert len(messages) % 2 == 0, "Number of messages must be even" + messages = [ + (prompt_tokens[0] if i % 2 == 0 else "") + x + ((" " + prompt_tokens[1]) if i % 2 == 0 else "") + for i, x in enumerate(messages) + ] + + # Add a way for the model to terminate generation, reinitialize prompter + messages.append(prompt_tokens[0]) + + flatten_messages.append( + self.tokenizer( + "".join(messages), + truncation=True, + max_length=self.max_length, + return_offsets_mapping=True, + ) + ) + + message_change_indices = np.cumsum([len(x) for x in messages[:-1]]) + # for each token an integer indicating the index of the message it belongs to. Just to create the label mask. + # TEXT: Question: Hello, how are you? Answer: I am fine. Question: What is your name? Answer: My name is John. + # MESSAGE_INDICES: 0 0 0 0 0 0 1 1 1 2 2 2 2 2 2 3 3 3 3 + + # If no result in next, we are predicting the last termination token(s) + message_indices = list( + map( + lambda x: next((i for i, val in enumerate(message_change_indices) if val >= x), -2), + list(map(lambda x: x[1], flatten_messages[-1]["offset_mapping"])), + ) + ) + label_mask = np.roll(list(map(lambda x: x % 2 == 1, message_indices)), -1, -1) + try: + label_mask[[i for i in range(len(message_indices)) if message_indices[i] == -2][0] - 1] = True + except IndexError: + # an aftermath of padding + pass + + label_masks.append(label_mask) + flatten_messages[-1].pop("offset_mapping") + + batch = self.tokenizer.pad( + flatten_messages, + padding=self.padding, + max_length=self.max_length, + pad_to_multiple_of=self.pad_to_multiple_of, + return_tensors="pt", + ) + dim = batch["input_ids"].shape[-1] + + batch["label_masks"] = torch.stack([F.pad(torch.tensor(x), (0, dim - len(x))) for x in label_masks]) + + for k in list(batch.keys()): + if k not in ["input_ids", "attention_mask", "label_masks"]: + batch.pop(k) + + return batch diff --git a/model/supervised_finetuning/losses.py b/model/supervised_finetuning/losses.py new file mode 100644 index 00000000..795396b9 --- /dev/null +++ b/model/supervised_finetuning/losses.py @@ -0,0 +1,15 @@ +from torch import nn + + +class CrossEntropyLoss(nn.CrossEntropyLoss): + def __init__(self, weight=None, size_average=None, ignore_index=-100, reduce=None, reduction="mean"): + super(CrossEntropyLoss, self).__init__(weight, size_average, ignore_index, reduce, reduction) + + def forward(self, input, target, mask=None): + if mask is not None: + mask = mask.view(-1) + input = input.view(-1, input.size(-1)) + target = target.view(-1) + input = input[mask] + target = target[mask] + return super(CrossEntropyLoss, self).forward(input, target) diff --git a/model/supervised_finetuning/trainer.py b/model/supervised_finetuning/trainer.py new file mode 100644 index 00000000..b44890df --- /dev/null +++ b/model/supervised_finetuning/trainer.py @@ -0,0 +1,200 @@ +import argparse +import os +from dataclasses import dataclass +from distutils.util import strtobool +from typing import Any, Callable, Dict, List, Optional, Tuple, Union + +import torch +from torch import nn +from torch.utils.data import Dataset +from transformers import ( + DataCollator, + EvalPrediction, + PreTrainedModel, + PreTrainedTokenizerBase, + Trainer, + TrainerCallback, + TrainingArguments, + get_cosine_schedule_with_warmup, +) +from utils import get_dataset, get_loss, get_model, get_tokenizer, read_yamls + +os.environ["WANDB_PROJECT"] = "supervised-finetuning" + + +@dataclass +class CustomTrainingArguments(TrainingArguments): + loss_function: str = "CrossEntropyLoss" + + +def compute_metrics(eval_pred): + pred_ids = eval_pred.predictions + labels = eval_pred.label_ids + + return {"accuracy": (pred_ids[labels > 0] == labels[labels > 0]).mean()} + + +def preprocess_logits_for_metrics(logits, labels): + pred_ids = torch.argmax(logits, dim=-1) + return pred_ids + + +class SFTTrainer(Trainer): + def __init__( + self, + model: Union[PreTrainedModel, nn.Module] = None, + args: TrainingArguments = None, + data_collator: Optional[DataCollator] = None, + train_dataset: Optional[Dataset] = None, + eval_dataset: Optional[Dataset] = None, + tokenizer: Optional[PreTrainedTokenizerBase] = None, + model_init: Callable[[], PreTrainedModel] = None, + compute_metrics: Optional[Callable[[EvalPrediction], Dict]] = None, + callbacks: Optional[List[TrainerCallback]] = None, + optimizers: Tuple[torch.optim.Optimizer, torch.optim.lr_scheduler.LambdaLR] = (None, None), + preprocess_logits_for_metrics: Callable[[torch.Tensor, torch.Tensor], torch.Tensor] = None, + ): + super().__init__( + model, + args, + data_collator, + train_dataset, + eval_dataset, + tokenizer, + model_init, + compute_metrics, + callbacks, + optimizers, + preprocess_logits_for_metrics, + ) + self.loss_fct = get_loss(args.loss_function) + + def fetch_scheduler(self): + return get_cosine_schedule_with_warmup( + self.optimizer, + num_warmup_steps=self.args.warmup_steps, + num_training_steps=self.num_train_steps, + num_cycles=1, + last_epoch=-1, + ) + + def compute_loss(self, model, inputs, return_outputs=False): + labels_mask = inputs.pop("label_masks") + + outputs = model(**inputs) + + loss = self.loss_fct(outputs.get("logits"), torch.roll(inputs["input_ids"], -1, -1), mask=labels_mask) + + return (loss, outputs) if return_outputs else loss + + def _compute_loss(self, model, inputs): + + labels_mask = inputs.pop("label_masks") + + inputs = self._prepare_inputs(inputs) + + outputs = model(**inputs) + + logits = outputs.get("logits") + + targets = torch.roll(inputs["input_ids"], -1, -1) + loss = self.loss_fct(outputs.get("logits"), targets, mask=labels_mask) + + return loss, logits, targets, labels_mask + + def prediction_step( + self, + model: nn.Module, + inputs: Dict[str, Union[torch.Tensor, Any]], + prediction_loss_only: bool, + ignore_keys: Optional[List[str]] = None, + ) -> Tuple[Optional[torch.Tensor], Optional[torch.Tensor], Optional[torch.Tensor]]: + + with torch.no_grad(): + loss, logits, labels, labels_mask = self._compute_loss(model, inputs) + labels[~labels_mask] = -1 + + loss = loss.mean().detach() + + if self.args.prediction_loss_only: + return (loss, None, None) + + return (loss, logits, labels) + + +def _strtobool(x): + return bool(strtobool(x)) + + +def argument_parsing(notebook=False, notebook_args=None): + parser = argparse.ArgumentParser() + parser.add_argument("--configs", nargs="+", required=True) + + if notebook: + args, remaining = parser.parse_known_args(notebook_args) + else: + args, remaining = parser.parse_known_args() + + # Config from YAML + conf = {} + configs = read_yamls("./configs") + for name in args.configs: + if "," in name: + for n in name.split(","): + conf.update(configs[n]) + else: + conf.update(configs[name]) + + # Override config from command-line + parser = argparse.ArgumentParser() + for key, value in conf.items(): + type_ = type(value) if value is not None else str + if type_ == bool: + type_ = _strtobool + parser.add_argument(f"--{key}", type=type_, default=value) + + return parser.parse_args(remaining) + + +if __name__ == "__main__": + training_conf = argument_parsing() + + model = get_model(training_conf) + tokenizer = get_tokenizer(training_conf) + + train, evals, collate_fn = get_dataset(training_conf, tokenizer) + + args = CustomTrainingArguments( + output_dir=f"{training_conf.model_name}-{training_conf.log_dir}-finetuned", + num_train_epochs=training_conf.num_train_epochs, + warmup_steps=training_conf.warmup_steps, + loss_function=training_conf.loss_fn, + learning_rate=float(training_conf.learning_rate), + fp16=True, + gradient_checkpointing=training_conf.gradient_checkpointing, + gradient_accumulation_steps=training_conf.gradient_accumulation_steps, + per_device_train_batch_size=training_conf.per_device_train_batch_size, + per_device_eval_batch_size=training_conf.per_device_eval_batch_size, + weight_decay=training_conf.weight_decay, + max_grad_norm=training_conf.max_grad_norm, + logging_steps=training_conf.logging_steps, + save_total_limit=training_conf.save_total_limit, + evaluation_strategy="steps", + eval_steps=training_conf.eval_steps, + save_steps=training_conf.save_steps, + eval_accumulation_steps=training_conf.eval_accumulation_steps, + report_to="wandb", + ) + + assert len(evals) > 0 + trainer = SFTTrainer( + model, + args, + train_dataset=train, + eval_dataset=evals, + data_collator=collate_fn, + tokenizer=tokenizer, + compute_metrics=compute_metrics, + preprocess_logits_for_metrics=preprocess_logits_for_metrics, + ) + trainer.train() diff --git a/model/supervised_finetuning/utils.py b/model/supervised_finetuning/utils.py new file mode 100644 index 00000000..4a451bed --- /dev/null +++ b/model/supervised_finetuning/utils.py @@ -0,0 +1,111 @@ +from pathlib import Path + +import yaml +from custom_datasets import get_one_dataset +from custom_datasets.dialogue_collator import DialogueDataCollator +from losses import CrossEntropyLoss +from sklearn.model_selection import train_test_split +from torch.utils.data import ConcatDataset, Subset +from transformers import AutoModelForCausalLM, AutoTokenizer + +SUPPORTED_MODELS = ["galactica"] + + +def get_tokenizer(conf): + tokenizer = AutoTokenizer.from_pretrained(conf.model_name, cache_dir=conf.cache_dir) + + if "galactica" in conf.model_name: + tokenizer.add_special_tokens({"pad_token": "", "eos_token": ""}) + + return tokenizer + + +def get_model(conf): + if not any([x in conf.model_name for x in SUPPORTED_MODELS]): + raise ValueError( + f"Model {conf.model_name} not supported. Supported models: {SUPPORTED_MODELS}. " + "To include more make sure the masking is dne correctly... (decoder only supported for now)" + ) + + model = AutoModelForCausalLM.from_pretrained(conf.model_name, cache_dir=conf.cache_dir) + + if conf.freeze_layer: + model = freeze_top_n_layers(model, conf.freeze_layer) + + model_parameters = filter(lambda p: p.requires_grad, model.parameters()) + params = sum([p.numel() for p in model_parameters]) + print("Number of trainable parameters: {}M".format(int(params / 1e6))) + + return model + + +def get_dataset(conf, tokenizer): + train_datasets, evals = [], {} + + for dataset_name in conf.datasets: + train, val = get_one_dataset(conf, dataset_name) + train_datasets.append(train) + evals[dataset_name] = Subset(val, list(range(min(len(val), conf.eval_size)))) if conf.eval_size else val + + train = ConcatDataset(train_datasets) + + collate_fn = DialogueDataCollator(tokenizer, max_length=conf.max_length) + + return train, evals, collate_fn + + +def get_loss(loss): + if loss == "CrossEntropyLoss": + return CrossEntropyLoss() + else: + raise ValueError(f"Loss {loss} not supported") + + +def read_yamls(dir): + conf = {} + no_conf = True + + for config_file in Path(dir).glob("**/*.yaml"): + no_conf = False + with config_file.open("r") as f: + conf.update(yaml.safe_load(f)) + + if no_conf: + print(f"WARNING: No yaml files found in {dir}") + + return conf + + +def train_val_dataset(dataset, val_split=0.2): + train_idx, val_idx = train_test_split( + list(range(len(dataset))), test_size=val_split, random_state=666, shuffle=True + ) + return Subset(dataset, train_idx), Subset(dataset, val_idx) + + +def freeze_top_n_layers(model, target_layers): + # its possible we can simply detect which module is a ModuleList + # and simply freeze the module without doing string parsing + for name, param in model.named_parameters(): + if "embed" in name: + param.requires_grad = False + elif ".layer" in name or ".h." in name: + tokens = name.split(".") + layer_ = None + for token in tokens: + if token.isdigit(): + layer_ = int(token) + break + + if layer_ is not None and layer_ < target_layers: + # print('freeze ', layer_, name) + param.requires_grad = False + return model + + +if __name__ == "__main__": + from transformers import AutoModelForSequenceClassification + + model = AutoModelForSequenceClassification.from_pretrained("bigscience/bloomz-560m") + freeze_top_n_layers(model, 10) + print(model.state_dict().keys()) diff --git a/website/next.config.js b/website/next.config.js index 1cbdb0e0..2c37ebe6 100644 --- a/website/next.config.js +++ b/website/next.config.js @@ -3,7 +3,10 @@ const nextConfig = { output: "standalone", reactStrictMode: true, experimental: { - scrollRestoration: true, + /* Disabling this for now only because it causes a warning in the console that cannot be silenced for eslint + If this can be resolved, we should re-enable this. + */ + // scrollRestoration: true, }, }; diff --git a/website/package-lock.json b/website/package-lock.json index 38f7446e..1803cbca 100644 --- a/website/package-lock.json +++ 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}, + "npm-registry-fetch": { + "version": "14.0.3", + "bundled": true, + "requires": { + "make-fetch-happen": "^11.0.0", + "minipass": "^4.0.0", + "minipass-fetch": "^3.0.0", + "minipass-json-stream": "^1.0.1", + "minizlib": "^2.1.2", + "npm-package-arg": "^10.0.0", + "proc-log": "^3.0.0" + } + }, + "npm-user-validate": { + "version": "1.0.1", + "bundled": true + }, + "npmlog": { + "version": "7.0.1", + "bundled": true, + "requires": { + "are-we-there-yet": "^4.0.0", + "console-control-strings": "^1.1.0", + "gauge": "^5.0.0", + "set-blocking": "^2.0.0" + } + }, + "once": { + "version": "1.4.0", + "bundled": true, + "requires": { + "wrappy": "1" + } + }, + "p-map": { + "version": "4.0.0", + "bundled": true, + "requires": { + "aggregate-error": "^3.0.0" + } + }, + "pacote": { + "version": "15.0.7", + "bundled": true, + "requires": { + "@npmcli/git": "^4.0.0", + "@npmcli/installed-package-contents": "^2.0.1", + "@npmcli/promise-spawn": "^6.0.1", + "@npmcli/run-script": "^6.0.0", + "cacache": "^17.0.0", + "fs-minipass": "^2.1.0", + "minipass": "^4.0.0", + "npm-package-arg": "^10.0.0", + "npm-packlist": "^7.0.0", + "npm-pick-manifest": "^8.0.0", + "npm-registry-fetch": "^14.0.0", + "proc-log": "^3.0.0", + "promise-retry": "^2.0.1", + "read-package-json": "^6.0.0", + "read-package-json-fast": "^3.0.0", + "ssri": "^10.0.0", + "tar": "^6.1.11" + } + }, + "parse-conflict-json": { + "version": "3.0.0", + "bundled": true, + "requires": { + "json-parse-even-better-errors": "^3.0.0", + "just-diff": "^5.0.1", + "just-diff-apply": "^5.2.0" + } + }, + "path-is-absolute": { + "version": "1.0.1", + "bundled": true + }, + "postcss-selector-parser": { + "version": "6.0.10", + "bundled": true, + "requires": { + "cssesc": "^3.0.0", + "util-deprecate": "^1.0.2" + } + }, + "proc-log": { + "version": "3.0.0", + "bundled": true + }, + "process": { + "version": "0.11.10", + "bundled": true + }, + "promise-all-reject-late": { + "version": "1.0.1", + "bundled": true + }, + "promise-call-limit": { + "version": "1.0.1", + "bundled": true + }, + "promise-inflight": { + "version": "1.0.1", + "bundled": true + }, + "promise-retry": { + "version": "2.0.1", + "bundled": true, + "requires": { + "err-code": "^2.0.2", + "retry": "^0.12.0" + } + }, + "promzard": { + "version": "0.3.0", + "bundled": true, + "requires": { + "read": "1" + } + }, + "qrcode-terminal": { + "version": "0.12.0", + "bundled": true + }, + "read": { + "version": "1.0.7", + "bundled": true, + "requires": { + "mute-stream": "~0.0.4" + } + }, + "read-cmd-shim": { + "version": "4.0.0", + "bundled": true + }, + "read-package-json": { + "version": "6.0.0", + "bundled": true, + "requires": { + "glob": "^8.0.1", + "json-parse-even-better-errors": "^3.0.0", + "normalize-package-data": "^5.0.0", + "npm-normalize-package-bin": "^3.0.0" + } + }, + "read-package-json-fast": { + "version": "3.0.1", + "bundled": true, + "requires": { + "json-parse-even-better-errors": "^3.0.0", + "npm-normalize-package-bin": "^3.0.0" + } + }, + "readable-stream": { + "version": "3.6.0", + "bundled": true, + "requires": { + "inherits": "^2.0.3", + "string_decoder": "^1.1.1", + "util-deprecate": "^1.0.1" + } + }, + "retry": { + "version": "0.12.0", + "bundled": true + }, + "rimraf": { + "version": "3.0.2", + "bundled": true, + "requires": { + "glob": "^7.1.3" + }, + "dependencies": { + "brace-expansion": { + "version": "1.1.11", + "bundled": true, + "requires": { + "balanced-match": "^1.0.0", + "concat-map": "0.0.1" + } + }, + "glob": { + "version": "7.2.3", + "bundled": true, + "requires": { + "fs.realpath": "^1.0.0", + "inflight": "^1.0.4", + "inherits": "2", + "minimatch": "^3.1.1", + "once": "^1.3.0", + "path-is-absolute": "^1.0.0" + } + }, + "minimatch": { + "version": "3.1.2", + "bundled": true, + "requires": { + "brace-expansion": "^1.1.7" + } + } + } + }, + "safe-buffer": { + "version": "5.2.1", + "bundled": true + }, + "safer-buffer": { + "version": "2.1.2", + "bundled": true, + "optional": true + }, + "semver": { + "version": "7.3.8", + "bundled": true, + "requires": { + "lru-cache": "^6.0.0" + }, + "dependencies": { + "lru-cache": { + "version": "6.0.0", + "bundled": true, + "requires": { + "yallist": "^4.0.0" + } + } + } + }, + "set-blocking": { + "version": "2.0.0", + "bundled": true + }, + "signal-exit": { + "version": "3.0.7", + "bundled": true + }, + "smart-buffer": { + "version": "4.2.0", + "bundled": true + }, + "socks": { + "version": "2.7.0", + "bundled": true, + "requires": { + "ip": "^2.0.0", + "smart-buffer": "^4.2.0" + } + }, + "socks-proxy-agent": { + "version": "7.0.0", + "bundled": true, + "requires": { + "agent-base": "^6.0.2", + "debug": "^4.3.3", + "socks": "^2.6.2" + } + }, + "spdx-correct": { + "version": "3.1.1", + "bundled": true, + "requires": { + "spdx-expression-parse": "^3.0.0", + "spdx-license-ids": "^3.0.0" + } + }, + "spdx-exceptions": { + "version": "2.3.0", + "bundled": true + }, + "spdx-expression-parse": { + "version": "3.0.1", + "bundled": true, + "requires": { + "spdx-exceptions": "^2.1.0", + "spdx-license-ids": "^3.0.0" + } + }, + "spdx-license-ids": { + "version": "3.0.11", + "bundled": true + }, + "ssri": { + "version": "10.0.1", + "bundled": true, + "requires": { + "minipass": "^4.0.0" + } + }, + "string_decoder": { + "version": "1.3.0", + "bundled": true, + "requires": { + "safe-buffer": "~5.2.0" + } + }, + "string-width": { + "version": "4.2.3", + "bundled": true, + "requires": { + "emoji-regex": "^8.0.0", + "is-fullwidth-code-point": "^3.0.0", + "strip-ansi": "^6.0.1" + } + }, + "strip-ansi": { + "version": "6.0.1", + "bundled": true, + "requires": { + "ansi-regex": "^5.0.1" + } + }, + "supports-color": { + "version": "7.2.0", + "bundled": true, + "requires": { + "has-flag": "^4.0.0" + } + }, + "tar": { + "version": "6.1.13", + "bundled": true, + "requires": { + "chownr": "^2.0.0", + "fs-minipass": "^2.0.0", + "minipass": "^4.0.0", + "minizlib": "^2.1.1", + "mkdirp": "^1.0.3", + "yallist": "^4.0.0" + } + }, + "text-table": { + "version": "0.2.0", + "bundled": true + }, + "tiny-relative-date": { + "version": "1.3.0", + "bundled": true + }, + "treeverse": { + "version": "3.0.0", + "bundled": true + }, + "unique-filename": { + "version": "3.0.0", + "bundled": true, + "requires": { + "unique-slug": "^4.0.0" + } + }, + "unique-slug": { + "version": "4.0.0", + "bundled": true, + "requires": { + "imurmurhash": "^0.1.4" + } + }, + "util-deprecate": { + "version": "1.0.2", + "bundled": true + }, + "validate-npm-package-license": { + "version": "3.0.4", + "bundled": true, + "requires": { + "spdx-correct": "^3.0.0", + "spdx-expression-parse": "^3.0.0" + } + }, + "validate-npm-package-name": { + "version": "5.0.0", + "bundled": true, + "requires": { + "builtins": "^5.0.0" + } + }, + "walk-up-path": { + "version": "1.0.0", + "bundled": true + }, + "wcwidth": { + "version": "1.0.1", + "bundled": true, + "requires": { + "defaults": "^1.0.3" + } + }, + "which": { + "version": "3.0.0", + "bundled": true, + "requires": { + "isexe": "^2.0.0" + } + }, + "wide-align": { + "version": "1.1.5", + "bundled": true, + "requires": { + "string-width": "^1.0.2 || 2 || 3 || 4" + } + }, + "wrappy": { + "version": "1.0.2", + "bundled": true + }, + "write-file-atomic": { + "version": "5.0.0", + "bundled": true, + "requires": { + "imurmurhash": "^0.1.4", + "signal-exit": "^3.0.7" + } + }, + "yallist": { + "version": "4.0.0", + "bundled": true + } + } + }, "npm-run-path": { "version": "4.0.1", "resolved": "https://registry.npmjs.org/npm-run-path/-/npm-run-path-4.0.1.tgz", diff --git a/website/package.json b/website/package.json index 2bd531a0..c1d0c3d2 100644 --- a/website/package.json +++ b/website/package.json @@ -22,6 +22,7 @@ "@dnd-kit/core": "^6.0.6", "@dnd-kit/modifiers": "^6.0.1", "@dnd-kit/sortable": "^7.0.1", + "@dnd-kit/utilities": "^3.2.1", "@emotion/react": "^11.10.5", "@emotion/styled": "^11.10.5", "@headlessui/react": "^1.7.7", @@ -39,9 +40,11 @@ "eslint-plugin-simple-import-sort": "^8.0.0", "focus-visible": "^5.2.0", "framer-motion": "^6.5.1", + "install": "^0.13.0", "next": "13.0.6", "next-auth": "^4.18.6", "nodemailer": "^6.8.0", + "npm": "^9.2.0", "postcss-focus-visible": "^7.1.0", "react": "18.2.0", "react-dom": "18.2.0", diff --git a/website/src/components/AuthLayout.tsx b/website/src/components/AuthLayout.tsx index 3e45dd65..5136e43e 100644 --- a/website/src/components/AuthLayout.tsx +++ b/website/src/components/AuthLayout.tsx @@ -1,11 +1,11 @@ export function AuthLayout({ children }) { return ( -
+
{children}
-
+ ); } diff --git a/website/src/components/CallToAction.tsx b/website/src/components/CallToAction.tsx index 2fd91c79..ee6827eb 100644 --- a/website/src/components/CallToAction.tsx +++ b/website/src/components/CallToAction.tsx @@ -1,16 +1,48 @@ -import { CircleBackground } from "./CircleBackground"; +import { useColorMode } from "@chakra-ui/react"; +import { useId } from "react"; + import { Container } from "./Container"; -export function CallToAction() { +function CircleBackground({ width = 558, height = 558, ...props }) { + const id = useId(); + + const { colorMode } = useColorMode(); + const baseRingColor = colorMode === "light" ? "#777" : "#000"; + const gradStopColor = colorMode === "light" ? "#fff" : "#000"; + return ( -
+ + ); +} + +export function CallToAction() { + const { colorMode } = useColorMode(); + const bgColorClass = colorMode === "light" ? "bg-gray-900" : "bg-gray-50"; + const headingColorClass = colorMode === "light" ? "text-white" : "text-black"; + const textColorClass = colorMode === "light" ? "text-gray-300" : "text-black"; + + return ( +
- +
-

Join Us

-

+

Join Us

+

All open source projects begin with people like you. Open source is the belief that if we collaborate we can together gift our knowledge and technology to the world for the benefit of humanity. Are you in? Find us here: diff --git a/website/src/components/CircleBackground.tsx b/website/src/components/CircleBackground.tsx deleted file mode 100644 index 5851d4ab..00000000 --- a/website/src/components/CircleBackground.tsx +++ /dev/null @@ -1,22 +0,0 @@ -import { useId } from "react"; - -export function CircleBackground({ color, width = 558, height = 558, ...props }) { - const id = useId(); - - return ( - - ); -} diff --git a/website/src/components/Faq.tsx b/website/src/components/Faq.tsx index 8f42b920..b8e5e8f8 100644 --- a/website/src/components/Faq.tsx +++ b/website/src/components/Faq.tsx @@ -1,3 +1,5 @@ +import { useColorMode } from "@chakra-ui/react"; + import { Container } from "./Container"; const faqs = [ @@ -25,11 +27,16 @@ const faqs = [ ]; export function Faq() { + const { colorMode } = useColorMode(); + + const headingColorClass = colorMode === "light" ? "text-gray-900" : "text-white"; + const textColorClass = colorMode === "light" ? "text-gray-700" : "text-gray-100"; + return (

-

+

Frequently Asked Questions

{/*

@@ -52,8 +59,8 @@ export function Faq() {

    {column.map((faq, faqIndex) => (
  • -

    {faq.question}

    -

    {faq.answer}

    +

    {faq.question}

    +

    {faq.answer}

  • ))}
diff --git a/website/src/components/FlaggableElement.tsx b/website/src/components/FlaggableElement.tsx index cae24484..c8fc17ce 100644 --- a/website/src/components/FlaggableElement.tsx +++ b/website/src/components/FlaggableElement.tsx @@ -2,6 +2,7 @@ import { Button, Checkbox, Flex, + Grid, Popover, PopoverAnchor, PopoverArrow, @@ -15,6 +16,7 @@ import { SliderTrack, Spacer, useBoolean, + useId, } from "@chakra-ui/react"; import { FlagIcon, QuestionMarkCircleIcon } from "@heroicons/react/20/solid"; import { useState } from "react"; @@ -65,58 +67,47 @@ export const FlaggableElement = (props) => { isLazy lazyBehavior="keepMounted" > -
+ {props.children} - -
+ - -
- -
    - {TEXT_LABEL_FLAGS.map((option, i) => { - return ( - - ); - })} -
-
- -
-
+
+
+ + {TEXT_LABEL_FLAGS.map((option, i) => ( + + ))} + + + + ); }; -function FlagCheckboxLi(props: { +function FlagCheckbox(props: { option: textFlagLabels; idx: number; checkboxValues: boolean[]; @@ -136,37 +127,35 @@ function FlagCheckboxLi(props: { ); } + const id = useId(); + return ( -
  • - - { - props.checkboxHandler(e.target.checked, props.idx); - }} - /> - - - { - props.sliderHandler(val / 100, props.idx); - }} - > - - - - - - -
  • + + { + props.checkboxHandler(e.target.checked, props.idx); + }} + /> + + + { + props.sliderHandler(val / 100, props.idx); + }} + > + + + + + + ); } interface textFlagLabels { diff --git a/website/src/components/Footer.tsx b/website/src/components/Footer.tsx index 5c774398..cadae07e 100644 --- a/website/src/components/Footer.tsx +++ b/website/src/components/Footer.tsx @@ -1,71 +1,81 @@ +import { useColorMode } from "@chakra-ui/react"; import Image from "next/image"; import Link from "next/link"; -import { Container } from "./Container"; - export function Footer() { - return ( -
    -
    - -
    -
    - - logo - + const { colorMode } = useColorMode(); + const bgColorClass = colorMode === "light" ? "bg-transparent" : "bg-gray-800"; + const borderClass = colorMode === "light" ? "border-slate-200" : "border-transparent"; -
    -

    Open Assistant

    -

    Conversational AI for everyone.

    + return ( +
    +
    +
    + + logo + + +
    +

    Open Assistant

    +

    Conversational AI for everyone.

    +
    +
    + +
    - -
    +
    + + {/*
    */} + +
    ); } diff --git a/website/src/components/Header/Header.stories.jsx b/website/src/components/Header/Header.stories.jsx index 6a8a3866..c3c61018 100644 --- a/website/src/components/Header/Header.stories.jsx +++ b/website/src/components/Header/Header.stories.jsx @@ -22,4 +22,15 @@ const Template = (args) => { }; export const Default = Template.bind({}); -Default.args = { session: { data: { user: { name: "StoryBook user" } }, status: "authenticated" }, transparent: false }; +Default.args = { + session: { + data: { + user: { + name: "StoryBook user", + }, + }, + status: "authenticated", + }, + transparent: false, + borderClass: undefined, +}; diff --git a/website/src/components/Header/Header.tsx b/website/src/components/Header/Header.tsx index e4965807..2d0ef7cc 100644 --- a/website/src/components/Header/Header.tsx +++ b/website/src/components/Header/Header.tsx @@ -1,13 +1,12 @@ -import { Button } from "@chakra-ui/react"; +import { Box, Button, useColorMode } from "@chakra-ui/react"; import { Popover } from "@headlessui/react"; -import clsx from "clsx"; import { AnimatePresence, motion } from "framer-motion"; import Image from "next/image"; import Link from "next/link"; import { useSession } from "next-auth/react"; import { FaUser } from "react-icons/fa"; -import { Container } from "src/components/Container"; +import { ColorModeIconToggle } from "../UI/ColorModeIconToggle"; import { NavLinks } from "./NavLinks"; import { UserMenu } from "./UserMenu"; @@ -55,63 +54,75 @@ function AccountButton() { } export function Header(props) { - const transparent = props.transparent ?? false; + const { colorMode } = useColorMode(); + const borderClass = props.transparent + ? "" + : colorMode === "light" + ? "border-b border-gray-400" + : "border-b border-zinc-800"; + return ( -
    -
    + +
    + + {({ open }) => ( + <> + + {({ open }) => (open ? : )} + + + {open && ( + <> + + +
    + Join Us + FAQs +
    +
    +
    + + )} +
    + + )} +
    + + + +
    + + ); } diff --git a/website/src/components/Header/NavLinks.tsx b/website/src/components/Header/NavLinks.tsx index 3903c8b6..4f559e7e 100644 --- a/website/src/components/Header/NavLinks.tsx +++ b/website/src/components/Header/NavLinks.tsx @@ -1,9 +1,15 @@ +import { useColorMode } from "@chakra-ui/react"; import { AnimatePresence, motion } from "framer-motion"; import Link from "next/link"; import { useState } from "react"; export function NavLinks(): JSX.Element { const [hoveredIndex, setHoveredIndex] = useState(null); + const { colorMode } = useColorMode(); + + const linkColor = colorMode === "light" ? "text-gray-700 hover:text-gray-900" : "text-gray-50 hover:text-white"; + + const hoverBgColor = colorMode === "light" ? "bg-gray-100" : "bg-gray-800"; return ( <> @@ -14,14 +20,14 @@ export function NavLinks(): JSX.Element { setHoveredIndex(index)} onMouseLeave={() => setHoveredIndex(null)} > {hoveredIndex === index && ( ; @@ -26,7 +28,7 @@ export function UserMenu() { {({ open }) => ( <> -
    +
    Profile Picture {open && ( - <> + -
    + {accountOptions.map((item) => ( Sign Out

    -
    + - + )} diff --git a/website/src/components/Hero.tsx b/website/src/components/Hero.tsx index 3ddbc194..1e6b296f 100644 --- a/website/src/components/Hero.tsx +++ b/website/src/components/Hero.tsx @@ -1,3 +1,4 @@ +import { useColorMode } from "@chakra-ui/react"; import Image from "next/image"; import { useId } from "react"; @@ -6,6 +7,10 @@ import { Container } from "./Container"; function BackgroundIllustration(props) { const id = useId(); + const { colorMode } = useColorMode(); + const baseRingColor = colorMode === "light" ? "#d4d4d4" : "#005a69"; + const gradStopColor = colorMode === "light" ? "#06b6d4" : "#00f2ff"; + return (
    - - + + @@ -35,14 +40,14 @@ function BackgroundIllustration(props) { > - - + + @@ -51,17 +56,24 @@ function BackgroundIllustration(props) { } export function Hero() { + const { colorMode } = useColorMode(); + const pTextColor = colorMode === "light" ? "text-gray-600" : "text-white"; + const fancyTextGradientClasses = + colorMode === "light" ? "from-blue-600 via-sky-400 to-blue-700" : "from-blue-500 via-sky-300 to-blue-400"; + return (
    -

    Open Assistant

    -

    +

    Open Assistant

    +

    Conversational AI for everyone.

    -

    We believe we can create a revolution.

    -

    +

    We believe we can create a revolution.

    +

    In the same way that Stable Diffusion helped the world make art and images in new ways, we want to improve the world by providing amazing conversational AI.

    diff --git a/website/src/components/Loading/LoadingScreen.jsx b/website/src/components/Loading/LoadingScreen.jsx index 57323f8c..02aabe7a 100644 --- a/website/src/components/Loading/LoadingScreen.jsx +++ b/website/src/components/Loading/LoadingScreen.jsx @@ -1,12 +1,18 @@ import { Progress } from "@chakra-ui/react"; +import { useColorMode } from "@chakra-ui/react"; -export const LoadingScreen = ({ text }) => ( -
    - - {text && ( -
    -
    {text}
    -
    - )} -
    -); +export const LoadingScreen = ({ text }) => { + const { colorMode } = useColorMode(); + const mainClasses = colorMode === "light" ? "bg-slate-300 text-gray-800" : "bg-slate-900 text-white"; + + return ( +
    + + {text && ( +
    +
    {text}
    +
    + )} +
    + ); +}; diff --git a/website/src/components/Messages.tsx b/website/src/components/Messages.tsx index cc94fcc0..d3d7b3b8 100644 --- a/website/src/components/Messages.tsx +++ b/website/src/components/Messages.tsx @@ -1,3 +1,6 @@ +import { Grid } from "@chakra-ui/react"; +import { useColorMode } from "@chakra-ui/react"; + import { FlaggableElement } from "./FlaggableElement"; export interface Message { @@ -5,23 +8,29 @@ export interface Message { is_assistant: boolean; } -const getColor = (isAssistant: boolean) => (isAssistant ? "bg-slate-800" : "bg-sky-900"); +const getBgColor = (isAssistant: boolean, colorMode: "light" | "dark") => { + if (colorMode === "light") { + return isAssistant ? "bg-slate-800" : "bg-sky-900"; + } else { + return isAssistant ? "bg-black" : "bg-sky-900"; + } +}; export const Messages = ({ messages, post_id }: { messages: Message[]; post_id: string }) => { + const { colorMode } = useColorMode(); + const items = messages.map(({ text, is_assistant }: Message, i: number) => { return ( -
    - -
    - {text} -
    -
    -
    + +
    + {text} +
    +
    ); }); // Maybe also show a legend of the colors? - return <>{items}; + return {items}; }; diff --git a/website/src/components/Sortable/Sortable.tsx b/website/src/components/Sortable/Sortable.tsx index 615b0853..2f63ff27 100644 --- a/website/src/components/Sortable/Sortable.tsx +++ b/website/src/components/Sortable/Sortable.tsx @@ -2,9 +2,9 @@ import { Flex } from "@chakra-ui/react"; import { closestCenter, DndContext, + KeyboardSensor, PointerSensor, TouchSensor, - KeyboardSensor, useSensor, useSensors, } from "@dnd-kit/core"; @@ -23,6 +23,7 @@ import { SortableItem } from "./SortableItem"; export interface SortableProps { items: ReactNode[]; onChange: (newSortedIndices: number[]) => void; + className?: string; } interface SortableItems { @@ -31,18 +32,18 @@ interface SortableItems { item: ReactNode; } -export const Sortable = ({ items, onChange }: SortableProps) => { +export const Sortable = (props: SortableProps) => { const [itemsWithIds, setItemsWithIds] = useState([]); useEffect(() => { setItemsWithIds( - items.map((item, idx) => ({ + props.items.map((item, idx) => ({ item, id: idx + 1, // +1 because dndtoolkit has problem with "falsy" ids originalIndex: idx, })) ); - }, [items]); + }, [props.items]); const sensors = useSensors( useSensor(PointerSensor), @@ -50,6 +51,8 @@ export const Sortable = ({ items, onChange }: SortableProps) => { useSensor(KeyboardSensor, { coordinateGetter: sortableKeyboardCoordinates }) ); + const extraClasses = props.className || ""; + return ( { modifiers={[restrictToVerticalAxis]} > - + {itemsWithIds.map(({ id, item }) => ( {item} @@ -78,7 +81,7 @@ export const Sortable = ({ items, onChange }: SortableProps) => { const oldIndex = items.findIndex((x) => x.id === active.id); const newIndex = items.findIndex((x) => x.id === over.id); const newArray = arrayMove(items, oldIndex, newIndex); - onChange(newArray.map((item) => item.originalIndex)); + props.onChange(newArray.map((item) => item.originalIndex)); return newArray; }); } diff --git a/website/src/components/Sortable/SortableItem.tsx b/website/src/components/Sortable/SortableItem.tsx index 834a854f..da691de3 100644 --- a/website/src/components/Sortable/SortableItem.tsx +++ b/website/src/components/Sortable/SortableItem.tsx @@ -1,8 +1,9 @@ import { Button } from "@chakra-ui/react"; +import { useColorMode } from "@chakra-ui/react"; import { useSortable } from "@dnd-kit/sortable"; import { CSS } from "@dnd-kit/utilities"; -import { RxDragHandleDots2 } from "react-icons/rx"; import { PropsWithChildren } from "react"; +import { RxDragHandleDots2 } from "react-icons/rx"; export const SortableItem = ({ children, id }: PropsWithChildren<{ id: number }>) => { const { attributes, listeners, setNodeRef, transform, transition } = useSortable({ id }); @@ -13,9 +14,15 @@ export const SortableItem = ({ children, id }: PropsWithChildren<{ id: number }> touchAction: "none", }; + const { colorMode } = useColorMode(); + const themedClasses = + colorMode === "light" + ? "bg-slate-600 hover:bg-slate-500 text-white" + : "bg-black hover:bg-slate-900 text-white ring-1 ring-white/30 ring-inset hover:ring-slate-200/50"; + return (
  • diff --git a/website/src/components/Survey/SurveyCard.tsx b/website/src/components/Survey/SurveyCard.tsx new file mode 100644 index 00000000..25699c3f --- /dev/null +++ b/website/src/components/Survey/SurveyCard.tsx @@ -0,0 +1,20 @@ +import { useColorMode } from "@chakra-ui/react"; + +interface SurveyCardProps { + className?: string; + children: React.ReactNode; +} + +export const SurveyCard = (props: SurveyCardProps) => { + const extraClases = props.className || ""; + const { colorMode } = useColorMode(); + + const baseCardClasses = "rounded-lg h-full block p-6"; + const cardClases = + colorMode === "light" + ? `${baseCardClasses} bg-slate-50 text-gray-800 shadow-lg ${extraClases}` + : // `${baseCardClasses} bg-slate-800 text-white shadow-xl${extraClases}`; + `${baseCardClasses} bg-slate-800 text-slate-400 shadow-xl ring-1 ring-white/10 ring-inset ${extraClases}`; + + return
    {props.children}
    ; +}; diff --git a/website/src/components/Survey/TaskControls.tsx b/website/src/components/Survey/TaskControls.tsx new file mode 100644 index 00000000..7847c452 --- /dev/null +++ b/website/src/components/Survey/TaskControls.tsx @@ -0,0 +1,40 @@ +import { useColorMode } from "@chakra-ui/react"; +import { Flex } from "@chakra-ui/react"; +import { SkipButton } from "src/components/Buttons/Skip"; +import { SubmitButton } from "src/components/Buttons/Submit"; +import { TaskInfo } from "src/components/TaskInfo/TaskInfo"; + +interface TaskControlsProps { + // we need a task type + // eslint-disable-next-line @typescript-eslint/no-explicit-any + tasks: any[]; + className?: string; + onSubmitResponse: (task: { id: string }) => void; + onSkip: () => void; +} + +export const TaskControls = (props: TaskControlsProps) => { + const extraClases = props.className || ""; + const { colorMode } = useColorMode(); + + const baseClasses = "flex flex-row justify-items-stretch mb-8 p-4 rounded-lg max-w-7xl mx-auto"; + const taskControlClases = + colorMode === "light" + ? `${baseClasses} bg-white text-gray-800 shadow-lg ${extraClases}` + : `${baseClasses} bg-slate-800 text-slate-400 shadow-xl ring-1 ring-white/10 ring-inset ${extraClases}`; + + const endTask = props.tasks[props.tasks.length - 1]; + return ( +
    + + + Skip + {endTask.task.type !== "task_done" ? ( + props.onSubmitResponse(props.tasks[0])}>Submit + ) : ( + Next Task + )} + +
    + ); +}; diff --git a/website/src/components/Survey/TwoColumnsWithCards.tsx b/website/src/components/Survey/TwoColumnsWithCards.tsx new file mode 100644 index 00000000..55f787ea --- /dev/null +++ b/website/src/components/Survey/TwoColumnsWithCards.tsx @@ -0,0 +1,16 @@ +import { SurveyCard } from "src/components/Survey/SurveyCard"; + +export const TwoColumnsWithCards = ({ children }: { children: React.ReactNode[] }) => { + if (!Array.isArray(children) || children.length !== 2) { + throw new Error("TwoColumns expects 2 children"); + } + + const [first, second] = children; + + return ( +
    + {first} + {second} +
    + ); +}; diff --git a/website/src/components/TaskInfo/TaskInfo.tsx b/website/src/components/TaskInfo/TaskInfo.tsx index d32f7d9d..86fd2d96 100644 --- a/website/src/components/TaskInfo/TaskInfo.tsx +++ b/website/src/components/TaskInfo/TaskInfo.tsx @@ -1,6 +1,6 @@ export const TaskInfo = ({ id, output }: { id: string; output: string }) => { return ( -
    +
    Prompt {id} Output diff --git a/website/src/components/TaskSelection/TaskSelection.tsx b/website/src/components/TaskSelection/TaskSelection.tsx index 7cb216c1..f258a90b 100644 --- a/website/src/components/TaskSelection/TaskSelection.tsx +++ b/website/src/components/TaskSelection/TaskSelection.tsx @@ -1,12 +1,24 @@ import { Flex } from "@chakra-ui/react"; +import { useColorMode } from "@chakra-ui/react"; import React from "react"; import { TaskOption } from "./TaskOption"; import { TaskOptions } from "./TaskOptions"; export const TaskSelection = () => { + const { colorMode } = useColorMode(); + const mainBgClasses = colorMode === "light" ? "bg-slate-300 text-gray-800" : "bg-slate-900 text-white"; + return ( - + {/* { - if (!Array.isArray(children) || children.length !== 2) { - throw new Error("TwoColumns expects 2 children"); - } - - const [first, second] = children; - - return ( -
    -
    {first}
    -
    {second}
    -
    - ); -}; diff --git a/website/src/components/UI/ColorModeIconToggle.tsx b/website/src/components/UI/ColorModeIconToggle.tsx new file mode 100644 index 00000000..de27828c --- /dev/null +++ b/website/src/components/UI/ColorModeIconToggle.tsx @@ -0,0 +1,23 @@ +import { useColorMode } from "@chakra-ui/react"; +import { CiDark } from "react-icons/ci"; +import { CiLight } from "react-icons/ci"; + +export function ColorModeIconToggle(props) { + const { colorMode, toggleColorMode } = useColorMode(); + const propsClassName = props.className ?? ""; + + return ( + + ); +} diff --git a/website/src/components/UI/ColorModeSwitch.tsx b/website/src/components/UI/ColorModeSwitch.tsx new file mode 100644 index 00000000..05c9bde3 --- /dev/null +++ b/website/src/components/UI/ColorModeSwitch.tsx @@ -0,0 +1,16 @@ +import { Switch, useColorMode } from "@chakra-ui/react"; +import React from "react"; + +const ColorModeSwitch = () => { + const { colorMode, toggleColorMode } = useColorMode(); + return ( + + ); +}; + +export default ColorModeSwitch; diff --git a/website/src/pages/_app.tsx b/website/src/pages/_app.tsx index b9cffba1..ab7655cd 100644 --- a/website/src/pages/_app.tsx +++ b/website/src/pages/_app.tsx @@ -1,48 +1,25 @@ import "../styles/globals.css"; import "focus-visible"; -import { ChakraProvider } from "@chakra-ui/react"; -import { extendTheme } from "@chakra-ui/react"; -import { Inter } from "@next/font/google"; import type { AppProps } from "next/app"; import { SessionProvider } from "next-auth/react"; import { getDefaultLayout, NextPageWithLayout } from "src/components/Layout"; -// eslint-disable-next-line @typescript-eslint/no-unused-vars -const inter = Inter({ - subsets: ["latin"], - variable: "--font-inter", -}); - -const theme = extendTheme({ - styles: { - global: { - body: { - bg: "white", - }, - main: { - fontFamily: "Inter", - }, - header: { - fontFamily: "Inter", - }, - }, - }, -}); +import { Chakra, getServerSideProps } from "../styles/Chakra"; type AppPropsWithLayout = AppProps & { Component: NextPageWithLayout; }; -function MyApp({ Component, pageProps: { session, ...pageProps } }: AppPropsWithLayout) { +function MyApp({ Component, pageProps: { session, cookies, ...pageProps } }: AppPropsWithLayout) { const getLayout = Component.getLayout ?? getDefaultLayout; const page = getLayout(); return ( - + {page} - + ); } - +export { getServerSideProps }; export default MyApp; diff --git a/website/src/pages/account/index.tsx b/website/src/pages/account/index.tsx index 51f7ed38..9f8dc4a3 100644 --- a/website/src/pages/account/index.tsx +++ b/website/src/pages/account/index.tsx @@ -2,24 +2,10 @@ import { Button } from "@chakra-ui/react"; import Head from "next/head"; import Link from "next/link"; import { useSession } from "next-auth/react"; -import React, { useState } from "react"; +import React from "react"; export default function Account() { const { data: session } = useSession(); - const [username, setUsername] = useState("null"); - - // eslint-disable-next-line @typescript-eslint/no-unused-vars - const handleUpdate = async () => { - const response = await fetch("../api/update", { - method: "POST", - headers: { - "Content-Type": "application/json", - }, - body: JSON.stringify({ username }), - }); - const { name } = await response.json(); - setUsername(name); - }; if (!session) { return; @@ -34,7 +20,7 @@ export default function Account() { />
    -

    {username}

    +

    {session.user.name || "No username"}

    diff --git a/website/src/pages/api/new_task/[task_type].ts b/website/src/pages/api/new_task/[task_type].ts index 69548b5f..bf2ec5c4 100644 --- a/website/src/pages/api/new_task/[task_type].ts +++ b/website/src/pages/api/new_task/[task_type].ts @@ -63,7 +63,8 @@ const handler = async (req, res) => { message_id: registeredTask.id, }), }); - await ackRes.json(); + + ackRes; // calling this only to get rid of the unused variable warning... not sure if anything is intended to be done with ackRes // Send the results to the client. res.status(200).json(registeredTask); diff --git a/website/src/pages/auth/signin.tsx b/website/src/pages/auth/signin.tsx index 5bfeeb3b..f3c347e6 100644 --- a/website/src/pages/auth/signin.tsx +++ b/website/src/pages/auth/signin.tsx @@ -1,13 +1,16 @@ import { Button, Input, Stack } from "@chakra-ui/react"; +import { useColorMode } from "@chakra-ui/react"; import Head from "next/head"; import Link from "next/link"; import { getCsrfToken, getProviders, signIn } from "next-auth/react"; import React, { useRef } from "react"; import { FaBug, FaDiscord, FaEnvelope, FaGithub } from "react-icons/fa"; import { AuthLayout } from "src/components/AuthLayout"; +import { Footer } from "src/components/Footer"; +import { Header } from "src/components/Header"; // eslint-disable-next-line @typescript-eslint/no-unused-vars -export default function Signin({ csrfToken, providers }) { +function Signin({ csrfToken, providers }) { const { discord, email, github, credentials } = providers; const emailEl = useRef(null); const signinWithEmail = (ev: React.FormEvent) => { @@ -21,8 +24,14 @@ export default function Signin({ csrfToken, providers }) { signIn(credentials.id, { callbackUrl: "/", username: debugUsernameEl.current.value }); } + const { colorMode } = useColorMode(); + const bgColorClass = colorMode === "light" ? "bg-gray-50" : "bg-chakra-gray-900"; + const buttonBgColor = colorMode === "light" ? "#2563eb" : "#2563eb"; + + const buttonColorScheme = colorMode === "light" ? "blue" : "dark-blue-btn"; + return ( - <> +
    Sign Up - Open Assistant @@ -30,11 +39,11 @@ export default function Signin({ csrfToken, providers }) { {credentials && ( -
    - For Debugging Only + + For Debugging Only - @@ -43,13 +52,13 @@ export default function Signin({ csrfToken, providers }) { {email && ( - + @@ -58,7 +67,7 @@ export default function Signin({ csrfToken, providers }) { )} {discord && (
    - +
    ); } -// eslint-disable-next-line @typescript-eslint/no-unused-vars -export async function getServerSideProps(context) { +Signin.getLayout = (page) => ( +
    +
    + {page} +
    +
    +); + +export default Signin; + +export async function getServerSideProps() { const csrfToken = await getCsrfToken(); const providers = await getProviders(); return { diff --git a/website/src/pages/create/assistant_reply.tsx b/website/src/pages/create/assistant_reply.tsx index 4941c106..9a9c062e 100644 --- a/website/src/pages/create/assistant_reply.tsx +++ b/website/src/pages/create/assistant_reply.tsx @@ -1,11 +1,10 @@ -import { Flex, Textarea } from "@chakra-ui/react"; +import { Container, Textarea } from "@chakra-ui/react"; +import { useColorMode } from "@chakra-ui/react"; import { useRef, useState } from "react"; -import { SkipButton } from "src/components/Buttons/Skip"; -import { SubmitButton } from "src/components/Buttons/Submit"; import { LoadingScreen } from "src/components/Loading/LoadingScreen"; import { Messages } from "src/components/Messages"; -import { TaskInfo } from "src/components/TaskInfo/TaskInfo"; -import { TwoColumns } from "src/components/TwoColumns"; +import { TaskControls } from "src/components/Survey/TaskControls"; +import { TwoColumnsWithCards } from "src/components/Survey/TwoColumnsWithCards"; import fetcher from "src/lib/fetcher"; import poster from "src/lib/poster"; import useSWRImmutable from "swr/immutable"; @@ -45,43 +44,31 @@ const AssistantReply = () => { mutate(); }; + const { colorMode } = useColorMode(); + const mainBgClasses = colorMode === "light" ? "bg-slate-300 text-gray-800" : "bg-slate-900 text-white"; + if (isLoading) { return ; } if (tasks.length == 0) { - return
    No tasks found...
    ; + return No tasks found...; } const task = tasks[0].task; - const endTask = tasks[tasks.length - 1]; + return ( -
    - +
    + <>
    Reply as the assistant

    Given the following conversation, provide an adequate reply

    -