File size: 6,289 Bytes
baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 60866c1 baa9725 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 | // Hugging Face Inference API service
export class HuggingFaceService {
constructor(token) {
this.token = token;
}
async streamChatCompletion(messages, modelConfig, onChunk, onComplete, onError) {
try {
console.log('Starting chat completion with model:', modelConfig.endpoint);
// Use the chat completions endpoint which is more reliable
const response = await fetch(
'https://api-inference.huggingface.co/models/' + modelConfig.endpoint,
{
method: 'POST',
headers: {
'Authorization': `Bearer ${this.token}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
inputs: this.formatMessagesForInference(messages),
parameters: {
max_new_tokens: 1024,
temperature: 0.7,
top_p: 0.9,
do_sample: true,
return_full_text: false
},
options: {
wait_for_model: true,
use_cache: false
},
stream: true
})
}
);
if (!response.ok) {
const errorText = await response.text();
console.error('API Error:', response.status, errorText);
throw new Error(`API error: ${response.status} - ${response.statusText}`);
}
const reader = response.body.getReader();
const decoder = new TextDecoder();
let buffer = '';
while (true) {
const { done, value } = await reader.read();
if (done) break;
buffer += decoder.decode(value, { stream: true });
const lines = buffer.split('\n');
buffer = lines.pop() || '';
for (const line of lines) {
if (line.trim() === '') continue;
if (line.startsWith('data: ') && line !== 'data: [DONE]') {
try {
const jsonData = line.slice(6);
if (jsonData.trim()) {
const data = JSON.parse(jsonData);
// Handle different response formats
if (data.token && data.token.text) {
onChunk(data.token.text);
} else if (data.generated_text) {
onChunk(data.generated_text);
} else if (data[0] && data[0].generated_text) {
onChunk(data[0].generated_text);
}
}
} catch (e) {
console.log('Skipping invalid JSON line:', line);
}
}
}
}
onComplete();
} catch (error) {
console.error('Stream error:', error);
onError(error.message);
}
}
// Alternative method using chat completion format
async streamChatCompletionAlt(messages, modelConfig, onChunk, onComplete, onError) {
try {
console.log('Using chat completion format with model:', modelConfig.endpoint);
const response = await fetch(
'https://api-inference.huggingface.co/models/' + modelConfig.endpoint,
{
method: 'POST',
headers: {
'Authorization': `Bearer ${this.token}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
inputs: this.formatChatPrompt(messages),
parameters: {
max_new_tokens: 1024,
temperature: 0.7,
top_p: 0.9,
do_sample: true,
return_full_text: false
},
options: {
wait_for_model: true,
use_cache: false
},
stream: true
})
}
);
if (!response.ok) {
const errorText = await response.text();
console.error('API Error:', response.status, errorText);
throw new Error(`API error: ${response.status} - ${errorText}`);
}
const reader = response.body.getReader();
const decoder = new TextDecoder();
let buffer = '';
let accumulatedText = '';
while (true) {
const { done, value } = await reader.read();
if (done) break;
buffer += decoder.decode(value, { stream: true });
const lines = buffer.split('\n');
buffer = lines.pop() || '';
for (const line of lines) {
if (line.trim() === '') continue;
if (line.startsWith('data: ') && line !== 'data: [DONE]') {
try {
const jsonData = line.slice(6);
if (jsonData.trim()) {
const data = JSON.parse(jsonData);
// Extract text from different possible response formats
let newText = '';
if (data.token && data.token.text) {
newText = data.token.text;
} else if (data.generated_text) {
newText = data.generated_text.replace(accumulatedText, '');
} else if (data[0] && data[0].generated_text) {
newText = data[0].generated_text.replace(accumulatedText, '');
}
if (newText) {
accumulatedText += newText;
onChunk(newText);
}
}
} catch (e) {
console.log('Skipping invalid JSON line:', line);
}
}
}
}
onComplete();
} catch (error) {
console.error('Stream error:', error);
onError(error.message);
}
}
// Format messages for inference API
formatMessagesForInference(messages) {
if (messages.length === 0) return '';
// For single message, just return the content
if (messages.length === 1) {
return messages[0].content;
}
// For multiple messages, format as conversation
let conversation = '';
for (const msg of messages) {
const role = msg.role === 'user' ? 'Human' : 'Assistant';
conversation += `${role}: ${msg.content}\n`;
}
conversation += 'Assistant: ';
return conversation;
}
// Format chat prompt
formatChatPrompt(messages) {
if (messages.length === 0) return '';
const lastMessage = messages[messages.length - 1];
return lastMessage.content;
}
} |