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7ac2545 afef44c 7ac2545 afef44c 7ac2545 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 | import { useState, useRef, useCallback, useEffect } from "react";
import {
AutoModelForCausalLM,
AutoTokenizer,
TextStreamer,
} from "@huggingface/transformers";
const MODEL_ID = "shreyask/Maincoder-1B-ONNX-web";
interface LLMState {
isLoading: boolean;
isReady: boolean;
error: string | null;
progress: number;
}
interface LLMInstance {
model: any;
tokenizer: any;
}
let cachedInstance: LLMInstance | null = null;
let loadingPromise: Promise<LLMInstance> | null = null;
export const useLLM = () => {
const [state, setState] = useState<LLMState>({
isLoading: false,
isReady: false,
error: null,
progress: 0,
});
const instanceRef = useRef<LLMInstance | null>(null);
const pastKeyValuesRef = useRef<any>(null);
const loadModel = useCallback(async () => {
if (instanceRef.current || cachedInstance) {
const instance = instanceRef.current || cachedInstance;
instanceRef.current = instance;
cachedInstance = instance;
setState((prev) => ({ ...prev, isReady: true, isLoading: false }));
return instance;
}
if (loadingPromise) {
const instance = await loadingPromise;
instanceRef.current = instance;
cachedInstance = instance;
setState((prev) => ({ ...prev, isReady: true, isLoading: false }));
return instance;
}
setState((prev) => ({
...prev,
isLoading: true,
error: null,
progress: 0,
}));
loadingPromise = (async () => {
try {
const progress_callback = (progress: any) => {
if (
progress.status === "progress" &&
(progress.file?.endsWith(".onnx") ||
progress.file?.endsWith(".onnx_data"))
) {
const percentage = Math.round(
(progress.loaded / progress.total) * 100,
);
setState((prev) => ({ ...prev, progress: percentage }));
}
};
const tokenizer = await AutoTokenizer.from_pretrained(MODEL_ID, {
progress_callback,
});
const model = await AutoModelForCausalLM.from_pretrained(MODEL_ID, {
dtype: "q4",
device: "webgpu",
progress_callback,
});
const instance = { model, tokenizer };
instanceRef.current = instance;
cachedInstance = instance;
loadingPromise = null;
setState({
isLoading: false,
isReady: true,
error: null,
progress: 100,
});
return instance;
} catch (error) {
loadingPromise = null;
const message =
error instanceof Error ? error.message : "Failed to load model";
setState((prev) => ({
...prev,
isLoading: false,
error: message,
}));
throw error;
}
})();
return loadingPromise;
}, []);
const generateResponse = useCallback(
async (
messages: Array<{ role: string; content: string }>,
onToken?: (token: string) => void,
): Promise<string> => {
const instance = instanceRef.current;
if (!instance) {
throw new Error("Model not loaded. Call loadModel() first.");
}
const { model, tokenizer } = instance;
const input = tokenizer.apply_chat_template(messages, {
add_generation_prompt: true,
return_dict: true,
});
const streamer = onToken
? new TextStreamer(tokenizer, {
skip_prompt: true,
skip_special_tokens: true,
callback_function: onToken,
})
: undefined;
const { sequences, past_key_values } = await model.generate({
...input,
past_key_values: pastKeyValuesRef.current,
max_new_tokens: 1024,
do_sample: false,
repetition_penalty: 1.2,
eos_token_id: [151643, 151645], // <|endoftext|> and <|im_end|>
streamer,
return_dict_in_generate: true,
});
pastKeyValuesRef.current = past_key_values;
const response = tokenizer
.batch_decode(sequences.slice(null, [input.input_ids.dims[1], null]), {
skip_special_tokens: true,
})[0];
return response;
},
[],
);
const clearHistory = useCallback(() => {
pastKeyValuesRef.current = null;
}, []);
useEffect(() => {
if (cachedInstance) {
instanceRef.current = cachedInstance;
setState((prev) => ({ ...prev, isReady: true }));
}
}, []);
return {
...state,
loadModel,
generateResponse,
clearHistory,
};
};
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