fix: prompt token
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404f40cc23
commit
5382e9666e
@ -332,12 +332,14 @@ export default class llamacpp_extension extends AIEngine {
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)
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// Clear the invalid stored preference
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this.clearStoredBackendType()
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bestAvailableBackendString =
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await this.determineBestBackend(version_backends)
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bestAvailableBackendString = await this.determineBestBackend(
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version_backends
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)
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}
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} else {
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bestAvailableBackendString =
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await this.determineBestBackend(version_backends)
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bestAvailableBackendString = await this.determineBestBackend(
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version_backends
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)
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}
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let settings = structuredClone(SETTINGS)
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@ -2151,7 +2153,12 @@ export default class llamacpp_extension extends AIEngine {
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if (mmprojPath && !this.isAbsolutePath(mmprojPath))
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mmprojPath = await joinPath([await getJanDataFolderPath(), path])
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try {
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const result = await planModelLoadInternal(path, this.memoryMode, mmprojPath, requestedCtx)
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const result = await planModelLoadInternal(
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path,
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this.memoryMode,
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mmprojPath,
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requestedCtx
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)
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return result
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} catch (e) {
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throw new Error(String(e))
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@ -2279,30 +2286,38 @@ export default class llamacpp_extension extends AIEngine {
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}
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// Calculate text tokens
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const messages = JSON.stringify({ messages: opts.messages })
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// Use a direct approach: convert messages to text and tokenize directly
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// This avoids issues with enable_thinking and assistant prefills
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let textToTokenize = ''
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let parseResponse = await fetch(`${baseUrl}/apply-template`, {
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method: 'POST',
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headers: headers,
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body: messages,
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})
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for (const msg of opts.messages) {
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const rolePrefix =
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msg.role === 'user'
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? 'User: '
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: msg.role === 'assistant'
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? 'Assistant: '
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: msg.role === 'system'
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? 'System: '
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: ''
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if (!parseResponse.ok) {
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const errorData = await parseResponse.json().catch(() => null)
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throw new Error(
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`API request failed with status ${
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parseResponse.status
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}: ${JSON.stringify(errorData)}`
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)
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if (typeof msg.content === 'string') {
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textToTokenize += `${rolePrefix}${msg.content}\n`
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} else if (Array.isArray(msg.content)) {
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for (const part of msg.content) {
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if (part.type === 'text' && part.text) {
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textToTokenize += part.text
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}
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// Skip image tokens as they're calculated separately
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}
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textToTokenize += '\n'
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}
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}
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const parsedPrompt = await parseResponse.json()
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const response = await fetch(`${baseUrl}/tokenize`, {
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method: 'POST',
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headers: headers,
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body: JSON.stringify({
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content: parsedPrompt.prompt,
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content: textToTokenize,
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}),
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})
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