@llumiverse/drivers
Version:
LLM driver implementations. Currently supported are: openai, huggingface, bedrock, replicate.
131 lines • 5.21 kB
JavaScript
;
// This file is used by multiple drivers
// to format prompts in a way that is compatible with OpenAI's API.
Object.defineProperty(exports, "__esModule", { value: true });
exports.formatOpenAILikeTextPrompt = formatOpenAILikeTextPrompt;
exports.formatOpenAILikeMultimodalPrompt = formatOpenAILikeMultimodalPrompt;
const common_1 = require("@llumiverse/common");
const core_1 = require("@llumiverse/core");
/**
* OpenAI text only prompts
* @param segments
* @returns
*/
function formatOpenAILikeTextPrompt(segments) {
const system = [];
const safety = [];
const user = [];
for (const msg of segments) {
if (msg.role === common_1.PromptRole.system) {
system.push({ content: msg.content, role: "system" });
}
else if (msg.role === common_1.PromptRole.safety) {
safety.push({ content: "IMPORTANT: " + msg.content, role: "system" });
}
else if (msg.role !== common_1.PromptRole.negative && msg.role !== common_1.PromptRole.mask && msg.role !== common_1.PromptRole.tool) {
user.push({
content: msg.content,
role: msg.role || 'user',
});
}
}
// put system messages first and safety last
return system.concat(user).concat(safety);
}
async function formatOpenAILikeMultimodalPrompt(segments, opts) {
const system = [];
const safety = [];
const others = [];
for (const msg of segments) {
const parts = [];
//generate the parts based on PromptSegment
if (msg.files) {
for (const file of msg.files) {
const stream = await file.getStream();
const data = await (0, core_1.readStreamAsBase64)(stream);
parts.push({
type: "input_image",
image_url: `data:${file.mime_type || "image/jpeg"};base64,${data}`,
detail: "auto",
});
}
}
if (msg.content) {
parts.push({
type: "input_text",
text: msg.content,
});
}
if (msg.role === common_1.PromptRole.system) {
// For system messages, filter to only text parts
const textParts = parts.filter((part) => part.type === 'input_text');
const textContent = textParts.length === 1 && !msg.files ? textParts[0].text : textParts;
const systemMsg = {
role: "system",
content: textContent,
};
system.push(systemMsg);
if (opts.useToolForFormatting && opts.schema) {
system.forEach(s => {
if (s.role === 'system') {
const sysMsg = s;
if (typeof sysMsg.content === 'string') {
sysMsg.content = "TOOL: " + sysMsg.content;
}
else if (Array.isArray(sysMsg.content)) {
sysMsg.content.forEach((c) => {
if (c.type === "input_text")
c.text = "TOOL: " + c.text;
});
}
}
});
}
}
else if (msg.role === common_1.PromptRole.safety) {
const textParts = parts.filter((part) => part.type === 'input_text');
const safetyMsg = {
role: "system",
content: textParts,
};
if (Array.isArray(safetyMsg.content)) {
safetyMsg.content.forEach((c) => {
if (c.type === "input_text")
c.text = "DO NOT IGNORE - IMPORTANT: " + c.text;
});
}
system.push(safetyMsg);
}
else if (msg.role === common_1.PromptRole.tool) {
if (!msg.tool_use_id) {
throw new Error("Tool use id is required for tool messages");
}
const toolOutputMsg = {
type: "function_call_output",
call_id: msg.tool_use_id,
output: msg.content || ""
};
others.push(toolOutputMsg);
}
else if (msg.role !== common_1.PromptRole.negative && msg.role !== common_1.PromptRole.mask) {
const inputMsg = {
role: msg.role === 'assistant' ? 'assistant' : 'user',
content: parts,
};
others.push(inputMsg);
}
}
if (opts.result_schema && !opts.useToolForFormatting) {
const schemaMsg = {
role: "system",
content: [{
type: "input_text",
text: "IMPORTANT: only answer using JSON, and respecting the schema included below, between the <response_schema> tags. " + `<response_schema>${JSON.stringify(opts.result_schema)}</response_schema>`
}]
};
system.push(schemaMsg);
}
// put system messages first and safety last
return [].concat(system).concat(others).concat(safety);
}
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