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Add models

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This commit is contained in:
Kwaroran
2025-01-29 05:38:26 +09:00
parent 62ea10cc32
commit 338d1cfec2
6 changed files with 263391 additions and 11 deletions
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119
src/ts/model/modellist.ts
View File

@@ -18,7 +18,10 @@ export enum LLMFlags{
OAICompletionTokens,
DeveloperRole,
geminiThinking,
geminiBlockOff
geminiBlockOff,
deepSeekPrefix,
deepSeekThinkingInput,
deepSeekThinkingOutput,
}
export enum LLMProvider{
@@ -34,7 +37,9 @@ export enum LLMProvider{
WebLLM,
Horde,
AWS,
AI21
AI21,
DeepSeek,
DeepInfra
}
export enum LLMFormat{
@@ -71,7 +76,8 @@ export enum LLMTokenizer{
Gemma,
GoogleCloud,
Cohere,
Local
Local,
DeepSeek
}
export interface LLMModel{
@@ -86,6 +92,8 @@ export interface LLMModel{
parameters: Parameter[],
tokenizer: LLMTokenizer
recommended?: boolean
keyIdentifier?: string
endpoint?: string
}
const ProviderNames = new Map<LLMProvider, string>([
@@ -101,11 +109,31 @@ const ProviderNames = new Map<LLMProvider, string>([
[LLMProvider.WebLLM, 'WebLLM'],
[LLMProvider.Horde, 'Horde'],
[LLMProvider.AWS, 'AWS'],
[LLMProvider.DeepSeek, 'DeepSeek'],
[LLMProvider.DeepInfra, 'DeepInfra']
])
const OpenAIParameters:Parameter[] = ['temperature', 'top_p', 'frequency_penalty', 'presence_penalty']
const ClaudeParameters:Parameter[] = ['temperature', 'top_k', 'top_p']
function makeDeepInfraModels(id:string[]):LLMModel[]{
return id.map((id) => {
return {
id: 'deepinfra_' + id,
name: id,
internalID: id,
provider: LLMProvider.DeepInfra,
format: LLMFormat.OpenAICompatible,
parameters: ['frequency_penalty', 'presence_penalty','temperature', 'top_p'],
flags: [LLMFlags.hasFirstSystemPrompt, LLMFlags.requiresAlternateRole, LLMFlags.mustStartWithUserInput, LLMFlags.hasPrefill, LLMFlags.deepSeekThinkingOutput, LLMFlags.hasStreaming],
tokenizer: LLMTokenizer.DeepSeek,
endpoint: 'https://api.deepinfra.com/v1/openai/chat/completions',
keyIdentifier: 'deepinfra',
recommended: true
} as LLMModel
})
}
export const LLMModels: LLMModel[] = [
{
id: 'gpt35',
@@ -809,7 +837,6 @@ export const LLMModels: LLMModel[] = [
flags: [LLMFlags.geminiBlockOff,LLMFlags.hasImageInput, LLMFlags.hasFirstSystemPrompt, LLMFlags.poolSupported, LLMFlags.hasAudioInput, LLMFlags.hasVideoInput, LLMFlags.hasStreaming, LLMFlags.requiresAlternateRole],
parameters: ['temperature', 'top_k', 'top_p', 'presence_penalty', 'frequency_penalty'],
tokenizer: LLMTokenizer.GoogleCloud,
recommended: true
},
{
name: "Gemini Flash 2.0 Thinking 1219",
@@ -819,6 +846,35 @@ export const LLMModels: LLMModel[] = [
flags: [LLMFlags.hasImageInput, LLMFlags.hasFirstSystemPrompt, LLMFlags.poolSupported, LLMFlags.hasAudioInput, LLMFlags.hasVideoInput, LLMFlags.hasStreaming, LLMFlags.geminiThinking, LLMFlags.requiresAlternateRole],
parameters: ['temperature', 'top_k', 'top_p', 'presence_penalty', 'frequency_penalty'],
tokenizer: LLMTokenizer.GoogleCloud,
},
{
name: "Gemini Flash 2.0",
id: 'gemini-2.0-flash',
provider: LLMProvider.GoogleCloud,
format: LLMFormat.GoogleCloud,
flags: [LLMFlags.geminiBlockOff,LLMFlags.hasImageInput, LLMFlags.hasFirstSystemPrompt, LLMFlags.poolSupported, LLMFlags.hasAudioInput, LLMFlags.hasVideoInput, LLMFlags.hasStreaming, LLMFlags.requiresAlternateRole],
parameters: ['temperature', 'top_k', 'top_p', 'presence_penalty', 'frequency_penalty'],
tokenizer: LLMTokenizer.GoogleCloud,
recommended: true
},
{
name: "Gemini Pro 2.0 Exp 0128",
id: 'gemini-2.0-pro-exp-01-28',
provider: LLMProvider.GoogleCloud,
format: LLMFormat.GoogleCloud,
flags: [LLMFlags.geminiBlockOff,LLMFlags.hasImageInput, LLMFlags.hasFirstSystemPrompt, LLMFlags.poolSupported, LLMFlags.hasAudioInput, LLMFlags.hasVideoInput, LLMFlags.hasStreaming, LLMFlags.requiresAlternateRole],
parameters: ['temperature', 'top_k', 'top_p', 'presence_penalty', 'frequency_penalty'],
tokenizer: LLMTokenizer.GoogleCloud,
recommended: true
},
{
name: "Gemini Flash 2.0 Thinking 0121",
id: 'gemini-2.0-flash-thinking-exp-01-21',
provider: LLMProvider.GoogleCloud,
format: LLMFormat.GoogleCloud,
flags: [LLMFlags.hasImageInput, LLMFlags.hasFirstSystemPrompt, LLMFlags.poolSupported, LLMFlags.hasAudioInput, LLMFlags.hasVideoInput, LLMFlags.hasStreaming, LLMFlags.geminiThinking, LLMFlags.requiresAlternateRole],
parameters: ['temperature', 'top_k', 'top_p', 'presence_penalty', 'frequency_penalty'],
tokenizer: LLMTokenizer.GoogleCloud,
recommended: true
},
{
@@ -1102,6 +1158,59 @@ export const LLMModels: LLMModel[] = [
parameters: OpenAIParameters,
tokenizer: LLMTokenizer.Local
},
{
id: 'deepseek-chat',
name: 'Deepseek Chat',
provider: LLMProvider.DeepSeek,
format: LLMFormat.OpenAICompatible,
flags: [LLMFlags.hasFirstSystemPrompt, LLMFlags.requiresAlternateRole, LLMFlags.mustStartWithUserInput, LLMFlags.hasPrefill, LLMFlags.deepSeekPrefix, LLMFlags.hasStreaming],
parameters: ['frequency_penalty', 'presence_penalty','temperature', 'top_p'],
tokenizer: LLMTokenizer.DeepSeek,
endpoint: 'https://api.deepseek.com/beta',
keyIdentifier: 'deepseek',
recommended: true
},
{
id: 'deepseek-reasoner',
name: 'Deepseek Reasoner',
provider: LLMProvider.DeepSeek,
format: LLMFormat.OpenAICompatible,
flags: [LLMFlags.hasFirstSystemPrompt, LLMFlags.requiresAlternateRole, LLMFlags.mustStartWithUserInput, LLMFlags.hasPrefill, LLMFlags.deepSeekPrefix, LLMFlags.deepSeekThinkingInput, LLMFlags.hasStreaming],
parameters: [],
tokenizer: LLMTokenizer.DeepSeek,
endpoint: 'https://api.deepseek.com/beta/chat/completions',
keyIdentifier: 'deepseek',
recommended: true
},
...makeDeepInfraModels([
'deepseek-ai/DeepSeek-R1',
'deepseek-ai/DeepSeek-R1-Distill-Llama-70B',
'deepseek-ai/DeepSeek-V3',
'meta-llama/Llama-3.3-70B-Instruct-Turbo',
'meta-llama/Llama-3.3-70B-Instruct',
'microsoft/phi-4',
'meta-llama/Meta-Llama-3.1-70B-Instruct',
'meta-llama/Meta-Llama-3.1-8B-Instruct',
'meta-llama/Meta-Llama-3.1-405B-Instruct',
'Qwen/QwQ-32B-Preview',
'meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo',
'meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo',
'Qwen/Qwen2.5-Coder-32B-Instruct',
'nvidia/Llama-3.1-Nemotron-70B-Instruct',
'Qwen/Qwen2.5-72B-Instruct',
'meta-llama/Llama-3.2-90B-Vision-Instruct',
'meta-llama/Llama-3.2-11B-Vision-Instruct',
'microsoft/WizardLM-2-8x22B',
'01-ai/Yi-34B-Chat',
'Austism/chronos-hermes-13b-v2',
'Gryphe/MythoMax-L2-13b',
'Gryphe/MythoMax-L2-13b-turbo',
'Sao10K/L3.3-70B-Euryale-v2.3',
'Sao10K/L3.1-70B-Euryale-v2.2',
'Sao10K/L3-70B-Euryale-v2.1',
'google/gemma-2-27b-it',
'google/gemma-2-9b-it'
]),
{
id: 'custom',
name: "Plugin",
@@ -1121,7 +1230,7 @@ export const LLMModels: LLMModel[] = [
recommended: true,
parameters: ['temperature', 'top_p', 'frequency_penalty', 'presence_penalty', 'repetition_penalty', 'min_p', 'top_a', 'top_k'],
tokenizer: LLMTokenizer.Unknown
}
},
]
for(let model of LLMModels){

83
src/ts/process/request.ts
View File

@@ -287,6 +287,8 @@ export interface OpenAIChatExtra {
attr?:string[]
multimodals?:MultiModal[]
thoughts?:string[]
prefix?:boolean
reasoning_content?:string
}
function reformater(formated:OpenAIChat[],modelInfo:LLMModel){
@@ -476,6 +478,12 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
if(db.newOAIHandle && formatedChat[i].memo && formatedChat[i].memo.startsWith('NewChat')){
formatedChat[i].content = ''
}
if(arg.modelInfo.flags.includes(LLMFlags.deepSeekPrefix) && i === formatedChat.length-1 && formatedChat[i].role === 'assistant'){
formatedChat[i].prefix = true
}
if(arg.modelInfo.flags.includes(LLMFlags.deepSeekThinkingInput) && i === formatedChat.length-1 && formatedChat[i].thoughts && formatedChat[i].thoughts.length > 0 && formatedChat[i].role === 'assistant'){
formatedChat[i].reasoning_content = formatedChat[i].thoughts.join('\n')
}
delete formatedChat[i].memo
delete formatedChat[i].removable
delete formatedChat[i].attr
@@ -796,6 +804,10 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
let replacerURL = aiModel === 'openrouter' ? "https://openrouter.ai/api/v1/chat/completions" :
(aiModel === 'reverse_proxy') ? (arg.customURL) : ('https://api.openai.com/v1/chat/completions')
if(arg.modelInfo?.endpoint){
replacerURL = arg.modelInfo.endpoint
}
let risuIdentify = false
if(replacerURL.startsWith("risu::")){
risuIdentify = true
@@ -824,6 +836,9 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
"Content-Type": "application/json"
}
if(arg.modelInfo?.keyIdentifier){
headers["Authorization"] = "Bearer " + db.OaiCompAPIKeys[arg.modelInfo.keyIdentifier]
}
if(aiModel === 'openrouter'){
headers["X-Title"] = 'RisuAI'
headers["HTTP-Referer"] = 'https://risuai.xyz'
@@ -881,6 +896,7 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
})
let dataUint:Uint8Array|Buffer = new Uint8Array([])
let reasoningContent = ""
const transtream = new TransformStream<Uint8Array, StreamResponseChunk>( {
async transform(chunk, control) {
@@ -894,6 +910,16 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
try {
const rawChunk = data.replace("data: ", "")
if(rawChunk === "[DONE]"){
if(arg.modelInfo.flags.includes(LLMFlags.deepSeekThinkingOutput)){
readed["0"] = readed["0"].replace(/(.*)\<\/think\>/gms, (m, p1) => {
reasoningContent = p1
return ""
})
if(reasoningContent){
reasoningContent = reasoningContent.replace(/\<think\>/gm, '')
}
}
if(arg.extractJson && (db.jsonSchemaEnabled || arg.schema)){
for(const key in readed){
const extracted = extractJSON(readed[key], arg.extractJson)
@@ -902,6 +928,11 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
console.log(JSONreaded)
control.enqueue(JSONreaded)
}
else if(reasoningContent){
control.enqueue({
"0": `<Thoughts>\n${reasoningContent}\n</Thoughts>\n${readed["0"]}`
})
}
else{
control.enqueue(readed)
}
@@ -925,10 +956,27 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
readed["0"] += chunk
}
}
if(choice?.delta?.reasoning_content){
reasoningContent += choice.delta.reasoning_content
}
}
} catch (error) {}
}
}
if(arg.modelInfo.flags.includes(LLMFlags.deepSeekThinkingOutput)){
readed["0"] = readed["0"].replace(/(.*)\<\/think\>/gms, (m, p1) => {
reasoningContent = p1
return ""
})
if(reasoningContent){
reasoningContent = reasoningContent.replace(/\<think\>/gm, '')
}
}
if(arg.extractJson && (db.jsonSchemaEnabled || arg.schema)){
for(const key in readed){
const extracted = extractJSON(readed[key], arg.extractJson)
@@ -937,6 +985,11 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
console.log(JSONreaded)
control.enqueue(JSONreaded)
}
else if(reasoningContent){
control.enqueue({
"0": `<Thoughts>\n${reasoningContent}\n</Thoughts>\n${readed["0"]}`
})
}
else{
control.enqueue(readed)
}
@@ -1031,9 +1084,10 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
}
if(dat?.choices[0]?.text){
let text = dat.choices[0].text as string
if(arg.extractJson && (db.jsonSchemaEnabled || arg.schema)){
try {
const parsed = JSON.parse(dat.choices[0].text)
const parsed = JSON.parse(text)
const extracted = extractJSON(parsed, arg.extractJson)
return {
type: 'success',
@@ -1043,13 +1097,13 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
console.log(error)
return {
type: 'success',
result: dat.choices[0].text
result: text
}
}
}
return {
type: 'success',
result: dat.choices[0].text
result: text
}
}
if(arg.extractJson && (db.jsonSchemaEnabled || arg.schema)){
@@ -1059,9 +1113,30 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
}
}
const msg:OpenAIChatFull = (dat.choices[0].message)
let result = msg.content
if(arg.modelInfo.flags.includes(LLMFlags.deepSeekThinkingOutput)){
console.log("Checking for reasoning content")
let reasoningContent = ""
result = result.replace(/(.*)\<\/think\>/gms, (m, p1) => {
reasoningContent = p1
return ""
})
console.log(`Reasoning Content: ${reasoningContent}`)
if(reasoningContent){
reasoningContent = reasoningContent.replace(/\<think\>/gms, '')
result = `<Thoughts>\n${reasoningContent}\n</Thoughts>\n${result}`
}
}
if(dat?.choices[0]?.reasoning_content){
result = `<Thoughts>\n${dat.choices[0].reasoning_content}\n</Thoughts>\n${result}`
}
return {
type: 'success',
result: msg.content
result: result
}
} catch (error) {
return {

4
src/ts/storage/database.svelte.ts
View File

@@ -470,6 +470,7 @@ export function setDatabase(data:Database){
data.banCharacterset ??= []
data.showPromptComparison ??= false
data.checkCorruption ??= true
data.OaiCompAPIKeys ??= {}
data.hypaV3Settings = {
memoryTokensRatio: data.hypaV3Settings?.memoryTokensRatio ?? 0.2,
extraSummarizationRatio: data.hypaV3Settings?.extraSummarizationRatio ?? 0.2,
@@ -892,7 +893,8 @@ export interface Database{
enableSimilarityCorrection: boolean
preserveOrphanedMemory: boolean
processRegexScript: boolean
}
},
OaiCompAPIKeys: {[key:string]:string}
}
interface SeparateParameters{

13
src/ts/tokenizer.ts
View File

@@ -21,6 +21,7 @@ export const tokenizerList = [
['novellist', 'Novellist'],
['gemma', 'Gemma'],
['cohere', 'Cohere'],
['deepseek', 'DeepSeek'],
] as const
export async function encode(data:string):Promise<(number[]|Uint32Array|Int32Array)>{
@@ -43,6 +44,8 @@ export async function encode(data:string):Promise<(number[]|Uint32Array|Int32Arr
return await gemmaTokenize(data)
case 'cohere':
return await tokenizeWebTokenizers(data, 'cohere')
case 'deepseek':
return await tokenizeWebTokenizers(data, 'DeepSeek')
default:
return await tikJS(data, 'o200k_base')
}
@@ -108,6 +111,9 @@ export async function encode(data:string):Promise<(number[]|Uint32Array|Int32Arr
if(modelInfo.tokenizer === LLMTokenizer.Gemma || modelInfo.tokenizer === LLMTokenizer.GoogleCloud){
return await gemmaTokenize(data)
}
if(modelInfo.tokenizer === LLMTokenizer.DeepSeek){
return await tokenizeWebTokenizers(data, 'DeepSeek')
}
if(modelInfo.tokenizer === LLMTokenizer.Cohere){
return await tokenizeWebTokenizers(data, 'cohere')
}
@@ -115,7 +121,7 @@ export async function encode(data:string):Promise<(number[]|Uint32Array|Int32Arr
return await tikJS(data)
}
type tokenizerType = 'novellist'|'claude'|'novelai'|'llama'|'mistral'|'llama3'|'gemma'|'cohere'|'googleCloud'
type tokenizerType = 'novellist'|'claude'|'novelai'|'llama'|'mistral'|'llama3'|'gemma'|'cohere'|'googleCloud'|'DeepSeek'
let tikParser:Tiktoken = null
let tokenizersTokenizer:Tokenizer = null
@@ -266,6 +272,11 @@ async function tokenizeWebTokenizers(text:string, type:tokenizerType) {
await (await fetch("/token/gemma/tokenizer.model")
).arrayBuffer())
break
case 'DeepSeek':
tokenizersTokenizer = await webTokenizer.Tokenizer.fromJSON(
await (await fetch("/token/deepseek/tokenizer.json")
).arrayBuffer())
break
}
tokenizersType = type