@adaline/azure/dist/index.mjs

Adaline Azure

import { z as z$1 } from 'zod';

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With a setting of 0, the model strictly picks the most probable next word.     For endeavors that benefit from a dash of inventiveness, consider dialing it up to 0.7 or higher, enabling the model to produce text     that's unexpectedly fresh."},Qa={type:"range",title:"Max tokens",description:"Specify the total tokens for generation, where one token approximates four English characters.     Setting this to 0 defaults to the model's maximum capacity."},es={type:"range",title:"Max reasoning tokens",description:"Specify the total tokens for reasoning, where one token approximates four English characters."},ts=e=>({type:"multi",title:"Stop sequence",description:`Enter up to ${e} sequences that will halt additional text output.       The generated text will exclude these sequences.`}),os={type:"range",title:"Top A",description:"Considers only the top tokens that have 'sufficiently high' probabilities relative to the most likely token,     functioning like a dynamic Top-P.     A lower Top-A value narrows down the token choices based on the highest probability token,     while a higher Top-A value refines the filtering without necessarily impacting the creativity of the output."},ns={type:"range",title:"Top P",description:"Selects a subset of likely tokens for generation, restricting choices to the top-P fraction of possibilities,     such as the top 10% when P=0.1.     This approach can limit the variety of the output. By default, it's set to 1, indicating no restriction.     It's advised to adjust this parameter or temperature to modulate output diversity, but not to modify both simultaneously."},as={type:"range",title:"Top K",description:"Select only from the highest K probabilities for each following word, effectively eliminating the less likely 'long tail' options."},ss={type:"range",title:"Min P",description:"Specifies the minimum probability a token must have to be considered, in relation to the probability of the most likely token.     (This value varies based on the confidence level of the top token.)     For example, if Min-P is set to 0.1, only tokens with at least 1/10th the probability of the highest-ranked token will be considered."},is={type:"range",title:"Frequency penalty",description:"Minimize redundancy.    By assigning a penalty to frequently used tokens within the text, the likelihood of repeating identical phrases is reduced.     The default setting for this penalty is zero."},rs={type:"range",title:"Presence penalty",description:"Enhance the introduction of novel subjects by reducing the preference for tokens that have already appeared in the text,     thus boosting the chances of exploring fresh topics.     The standard setting for this is zero."},ls={type:"range",title:"Seed",description:"When seed is fixed to a specific value, the model makes a best effort to provide the same response for repeated requests.     Deterministic output isn't guaranteed.     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e.reduce((t,n)=>t+n.content.map(s=>s.modality==="text"?s.value:"").join(" ").length,0)}transformModelRequest(e){let t=Ks.safeParse(e);if(!t.success)throw new ae({info:"Invalid model request",cause:t.error});let n=t.data,s=n.model;if(n.tool_choice&&(!n.tools||n.tools.length===0))throw new ae({info:`Invalid model request for model : '${this.modelName}'`,cause:new Error("'tools' are required when 'tool_choice' is specified")});let i={};n.response_format&&(i.responseFormat=n.response_format.type,n.response_format.type==="json_schema"&&(i.responseSchema={name:n.response_format.json_schema.name,description:n.response_format.json_schema.description||"",strict:n.response_format.json_schema.strict,schema:n.response_format.json_schema.schema})),n.tool_choice&&(typeof n.tool_choice=="string"?i.toolChoice=n.tool_choice:i.toolChoice=n.tool_choice.function.name),i.seed=n.seed,i.maxTokens=n.max_completion_tokens,i.temperature=n.temperature,i.topP=n.top_p,i.presencePenalty=n.presence_penalty,i.frequencyPenalty=n.frequency_penalty,i.stop=n.stop,i.logProbs=n.logprobs,i.topLogProbs=n.top_logprobs;let l=$e().parse(Xe(i)),r=[],d={};n.messages.forEach(u=>{let M=u.role;switch(M){case"system":{let b=u.content;if(typeof b=="string")r.push({role:M,content:[{modality:E,value:b}]});else {let k=b.map(y=>({modality:E,value:y.text}));r.push({role:M,content:k});}}break;case"user":{let b=u.content;if(typeof b=="string")r.push({role:M,content:[{modality:E,value:b}]});else {let k=b.map(y=>y.type==="text"?{modality:E,value:y.text}:y.image_url.url.startsWith("data:")?{modality:L,detail:y.image_url.detail||"auto",value:{type:je,base64:y.image_url.url,mediaType:ko(y.image_url.url)}}:{modality:L,detail:y.image_url.detail||"auto",value:{type:Ae,url:y.image_url.url}});r.push({role:M,content:k});}}break;case"assistant":{let b=[];if(!u.content&&!u.tool_calls)throw new ae({info:`Invalid model request for model : '${this.modelName}'`,cause:new Error("one of'content' or 'tool_calls' must be provided")});if(u.content){let k=u.content;typeof k=="string"?b.push({modality:E,value:k}):k.forEach(y=>{b.push({modality:E,value:y.text});});}u.tool_calls&&u.tool_calls.forEach((k,y)=>{let I={modality:G,id:k.id,index:y,name:k.function.name,arguments:k.function.arguments};b.push(I),d[I.id]=I;}),r.push({role:M,content:b});}break;case"tool":{let b=u;r.push({role:M,content:[{modality:N,id:b.tool_call_id,index:d[b.tool_call_id].index,name:d[b.tool_call_id].name,data:b.content}]});}break}});let c=[];return n.tools&&n.tools.forEach(u=>{c.push({type:"function",definition:{schema:{name:u.function.name,description:u.function.description||"",strict:u.function.strict,parameters:u.function.parameters}}});}),{modelName:s,config:l,messages:r,tools:c.length>0?c:void 0}}transformConfig(e,t,n){let s=e.toolChoice;delete e.toolChoice;let i=this.modelSchema.config.schema.safeParse(e);if(!i.success)throw new K({info:`Invalid config for model : '${this.modelName}'`,cause:i.error});let l=i.data;s!==void 0&&(l.toolChoice=s),Object.keys(l).forEach(d=>{if(!(d in this.modelSchema.config.def))throw new K({info:`Invalid config for model : '${this.modelName}'`,cause:new Error(`Invalid config key : '${d}', 
            available keys : [${Object.keys(this.modelSchema.config.def).join(", ")}]`)})});let r=Object.keys(l).reduce((d,c)=>{let u=this.modelSchema.config.def[c],M=u.param,b=l[c];return M==="max_completion_tokens"&&u.type==="range"&&b===0?d[M]=u.max:d[M]=b,d},{});if(r.top_logprobs&&!r.logprobs)throw new K({info:`Invalid config for model : '${this.modelName}'`,cause:new Error("'logprobs' must be 'true' when 'top_logprobs' is specified")});if("tool_choice"in r&&r.tool_choice!==void 0){let d=r.tool_choice;if(!n||n&&n.length===0)throw new K({info:`Invalid config for model : '${this.modelName}'`,cause:new Error("'tools' are required when 'toolChoice' is specified")});if(n&&n.length>0){let c=this.modelSchema.config.def.toolChoice;if(!c.choices.includes(d))if(n.map(u=>u.definition.schema.name).includes(d))r.tool_choice={type:"function",function:{name:d}};else throw new K({info:`Invalid config for model : '${this.modelName}'`,cause:new Error(`toolChoice : '${d}' is not part of provided 'tools' names or 
                one of [${c.choices.join(", ")}]`)})}}if("response_format"in r&&r.response_format!==void 0){let d=r.response_format;if(d==="json_schema")if("response_schema"in r)r.response_format={type:"json_schema",json_schema:r.response_schema},delete r.response_schema;else throw new K({info:`Invalid config for model : '${this.modelName}'`,cause:new Error("'responseSchema' is required in config when 'responseFormat' is 'json_schema'")});else r.response_format={type:d};}return r}transformMessages(e){if(!e||e&&e.length===0)return {messages:[]};let t=e.map(n=>{let s=Ue().safeParse(n);if(!s.success)throw new j({info:"Invalid messages",cause:s.error});return s.data});return t.forEach(n=>{n.content.forEach(s=>{if(!this.modelSchema.modalities.includes(s.modality))throw new j({info:`Invalid message content for model : '${this.modelName}'`,cause:new Error(`model : '${this.modelName}' does not support modality : '${s.modality}', 
              available modalities : [${this.modelSchema.modalities.join(", ")}]`)})});}),t.forEach(n=>{if(!Object.keys(this.modelSchema.roles).includes(n.role))throw new j({info:`Invalid message content for model : '${this.modelName}'`,cause:new Error(`model : '${this.modelName}' does not support role : '${n.role}', 
            available roles : [${Object.keys(this.modelSchema.roles).join(", ")}]`)})}),{messages:t.map(n=>{switch(n.role){case ee:{let s=[];return n.content.forEach(i=>{if(i.modality===E)s.push({type:"text",text:i.value});else throw new j({info:`Invalid message 'role' and 'modality' combination for model : ${this.modelName}`,cause:new Error(`role : '${n.role}' cannot have content with modality : '${i.modality}'`)})}),{role:this.modelSchema.roles[n.role],content:s}}case A:{let s=[],i=[];return n.content.forEach(l=>{if(l.modality===E)s.push({type:"text",text:l.value});else if(l.modality===G)i.push({id:l.id,type:"function",function:{name:l.name,arguments:l.arguments}});else throw new j({info:`Invalid message 'role' and 'modality' combination for model : ${this.modelName}`,cause:new Error(`role : '${n.role}' cannot have content with modality : '${l.modality}'`)})}),w({role:this.modelSchema.roles[n.role],content:s},i.length>0?{tool_calls:i}:{})}case te:{let s=[],i=[];n.content.forEach(r=>{if(r.modality===E)s.push({type:"text",text:r.value});else if(r.modality===L)i.push({type:"image_url",image_url:{url:r.value.type==="url"?r.value.url:r.value.base64,detail:r.detail}});else throw new j({info:`Invalid message 'role' and 'modality' combination for model : ${this.modelName}`,cause:new Error(`role : '${n.role}' cannot have content with modality : '${r.modality}'`)})});let l=[...s,...i];return {role:this.modelSchema.roles[n.role],content:l}}case oe:{if(n.content.length!==1)throw new j({info:`Invalid message for role : '${n.role}'`,cause:new Error(`role : '${n.role}' must have exactly one content item`)});if(n.content[0].modality!==N)throw new j({info:`Invalid message 'role' and 'modality' combination for model : ${this.modelName}`,cause:new Error(`role : '${n.role}' must have content with modality : '${N}'`)});let s=n.content[0];return {role:this.modelSchema.roles[n.role],tool_call_id:s.id,content:s.data}}default:throw new j({info:`Invalid message 'role' for model : ${this.modelName}`,cause:new Error(`role : '${n.role}' is not supported, 
              available roles : [${Object.keys(this.modelSchema.roles).join(", ")}]`)})}})}}transformTools(e){if(!this.modelSchema.modalities.includes(G))throw new He({info:`Invalid tool 'modality' for model : ${this.modelName}`,cause:new Error(`model : '${this.modelName}' does not support tool modality : '${G}'`)});return !e||e&&e.length===0?{tools:[]}:{tools:e.map(t=>{let n=Jt().safeParse(t);if(!n.success)throw new He({info:"Invalid tools",cause:n.error});return n.data}).map(t=>({type:"function",function:t.definition.schema}))}}getCompleteChatUrl(e,t,n){return R(this,null,function*(){return new Promise(s=>{s(this.completeChatUrl);})})}getCompleteChatHeaders(e,t,n){return R(this,null,function*(){return new Promise(s=>{s(this.getDefaultHeaders());})})}getCompleteChatData(e,t,n){return R(this,null,function*(){let s=this.transformConfig(e,t,n),i=this.transformMessages(t);if(i.messages&&i.messages.length===0)throw new j({info:"Messages are required",cause:new Error("Messages are required")});let l=n?this.transformTools(n):{};return new Promise(r=>{r(w(w(w(w({},this.getDefaultParams()),s),i),l));})})}transformCompleteChatResponse(e){let t=Is.safeParse(e);if(t.success){if(t.data.choices.length===0)throw new F({info:"Invalid response from model",cause:new Error(`No choices in response : ${JSON.stringify(t.data)}`)});let n=t.data,s=[{role:A,content:[]}],i=n.choices[0].message;i.content&&s[0].content.push(ze(i.content)),i.refusal&&s[0].content.push(ze(i.refusal)),i.tool_calls&&i.tool_calls.forEach((c,u)=>{s[0].content.push(Wt(u,c.id,c.function.name,c.function.arguments));});let l={promptTokens:n.usage.prompt_tokens,completionTokens:n.usage.completion_tokens,totalTokens:n.usage.total_tokens},r=[],d=n.choices[0].logprobs;return d&&(d.content&&r.push(...d.content.map(