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import { createParser } from 'eventsource-parser'; | |
export const OPENAI_API_HOST = process.env.OPENAI_API_HOST || "https://api.openai.com"; | |
export const OPENAI_API_TYPE = process.env.OPENAI_API_TYPE || "openai"; | |
export class LLMError extends Error { | |
constructor(message, type, param, code) { | |
super(message); | |
this.name = 'LLMError'; | |
this.type = type; | |
this.param = param; | |
this.code = code; | |
} | |
} | |
export const LLMStream = async ( | |
model, | |
systemPrompt, | |
temperature, | |
messages, | |
functions | |
) => { | |
let url = `${OPENAI_API_HOST}/v1/chat/completions`; | |
const res = await fetch(url, { | |
headers: { | |
'Content-Type': 'application/json', | |
...(OPENAI_API_TYPE === 'openai' && { | |
Authorization: `Bearer ${process.env.OPENAI_API_KEY}` | |
}) | |
}, | |
method: 'POST', | |
body: JSON.stringify({ | |
...(OPENAI_API_TYPE === 'openai' && {model: model.id}), | |
messages: [ | |
{ | |
role: 'system', | |
content: systemPrompt, | |
}, | |
...messages, | |
], | |
max_tokens: 1000, | |
temperature: temperature, | |
functions: [functions['googleCustomSearch']['googleCustomSearchSchema']], | |
stream: true, | |
}), | |
}); | |
const encoder = new TextEncoder(); | |
const decoder = new TextDecoder(); | |
if (res.status !== 200) { | |
const result = await res.json(); | |
if (result.error) { | |
throw new LLMError( | |
result.error.message, | |
result.error.type, | |
result.error.param, | |
result.error.code, | |
); | |
} else { | |
throw new Error( | |
`OpenAI API returned an error: ${ | |
decoder.decode(result?.value) || result.statusText | |
}`, | |
); | |
} | |
} | |
const stream = new ReadableStream({ | |
async start(controller) { | |
let func_call = { | |
"name": null, | |
"arguments": "", | |
}; | |
const onParse = async (event) => { | |
if (event.type === 'event') { | |
const data = event.data; | |
try { | |
if (data === "[DONE]" || !data) { | |
return; | |
} | |
const json = JSON.parse(data); | |
if (Array.isArray(json.choices) && json.choices.length > 0) { | |
const choice = json.choices[0]; | |
const delta = choice.delta; | |
if (choice.finish_reason === "stop") { | |
controller.close(); | |
return; | |
} | |
if (delta.hasOwnProperty("function_call")) { | |
if (delta.function_call.hasOwnProperty("name")) { | |
func_call["name"] = delta.function_call["name"]; | |
} | |
if (delta.function_call.hasOwnProperty("arguments")) { | |
func_call["arguments"] += delta.function_call["arguments"]; | |
} | |
} | |
if (choice.finish_reason === "function_call") { | |
// function call here using func_call | |
const fn = functions[func_call.name][func_call.name]; | |
const funcResult = await fn(func_call.arguments); | |
const serpQueue = encoder.encode(funcResult); | |
controller.enqueue(serpQueue); | |
} | |
if (delta && 'content' in delta) { | |
const text = delta.content; | |
const queue = encoder.encode(text); | |
controller.enqueue(queue); | |
} | |
} else { | |
console.error('No choices found in json'); | |
} | |
} catch (e) { | |
console.log(e); | |
controller.error(e); | |
} | |
} | |
}; | |
const parser = createParser(onParse); | |
for await (const chunk of res.body) { | |
parser.feed(decoder.decode(chunk)); | |
} | |
}, | |
}); | |
return stream; | |
}; | |