107 lines
1.9 KiB
V
107 lines
1.9 KiB
V
module openai
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import json
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@[params]
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pub struct CompletionArgs {
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pub mut:
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model string
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messages []Message // optional because we can use message, which means we just pass a string
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message string
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temperature f64 = 0.2
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max_completion_tokens int = 32000
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}
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struct Message {
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mut:
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role RoleType
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content string
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}
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pub enum RoleType {
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system
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user
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assistant
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function
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}
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fn roletype_str(x RoleType) string {
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return match x {
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.system {
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'system'
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}
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.user {
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'user'
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}
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.assistant {
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'assistant'
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}
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.function {
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'function'
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}
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}
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}
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struct Usage {
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mut:
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prompt_tokens int
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completion_tokens int
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total_tokens int
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}
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struct ChatCompletion {
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mut:
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id string
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created u32
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result string
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usage Usage
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}
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// creates a new chat completion given a list of messages
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// each message consists of message content and the role of the author
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pub fn (mut f OpenAI) chat_completion(args_ CompletionArgs) !ChatCompletion {
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mut args := args_
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if args.model == '' {
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args.model = f.model_default
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}
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mut m := ChatMessagesRaw{
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model: args.model
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temperature: args.temperature
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max_completion_tokens: args.max_completion_tokens
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}
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for msg in args.messages {
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mr := MessageRaw{
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role: roletype_str(msg.role)
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content: msg.content
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}
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m.messages << mr
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}
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if args.message != '' {
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mr := MessageRaw{
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role: 'user'
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content: args.message
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}
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m.messages << mr
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}
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data := json.encode(m)
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// println('data: ${data}')
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mut conn := f.connection()!
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r := conn.post_json_str(prefix: 'chat/completions', data: data)!
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res := json.decode(ChatCompletionRaw, r)!
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mut result := ''
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for choice in res.choices {
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result += choice.message.content
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}
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mut chat_completion_result := ChatCompletion{
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id: res.id
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created: res.created
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result: result
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usage: res.usage
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}
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return chat_completion_result
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}
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