fal-openai-proxy / server.js
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import express from 'express';
import { fal } from '@fal-ai/client';
// 从环境变量读取 Fal AI API Key
const FAL_KEY = process.env.FAL_KEY;
if (!FAL_KEY) {
console.error("Error: FAL_KEY environment variable is not set.");
process.exit(1);
}
// 配置 fal 客户端
fal.config({
credentials: FAL_KEY,
});
const app = express();
app.use(express.json({ limit: '50mb' }));
app.use(express.urlencoded({ extended: true, limit: '50mb' }));
const PORT = process.env.PORT || 3000;
// === 全局定义限制 ===
const PROMPT_LIMIT = 4800;
const SYSTEM_PROMPT_LIMIT = 4800;
// === 限制定义结束 ===
// 定义 fal-ai/any-llm 支持的模型列表
const FAL_SUPPORTED_MODELS = [
"anthropic/claude-3.7-sonnet",
"anthropic/claude-3.5-sonnet",
"anthropic/claude-3-5-haiku",
"anthropic/claude-3-haiku",
"google/gemini-pro-1.5",
"google/gemini-flash-1.5",
"google/gemini-flash-1.5-8b",
"google/gemini-2.0-flash-001",
"meta-llama/llama-3.2-1b-instruct",
"meta-llama/llama-3.2-3b-instruct",
"meta-llama/llama-3.1-8b-instruct",
"meta-llama/llama-3.1-70b-instruct",
"openai/gpt-4o-mini",
"openai/gpt-4o",
"deepseek/deepseek-r1",
"meta-llama/llama-4-maverick",
"meta-llama/llama-4-scout"
];
// Helper function to get owner from model ID
const getOwner = (modelId) => {
if (modelId && modelId.includes('/')) {
return modelId.split('/')[0];
}
return 'fal-ai';
}
// GET /v1/models endpoint
app.get('/v1/models', (req, res) => {
console.log("Received request for GET /v1/models");
try {
const modelsData = FAL_SUPPORTED_MODELS.map(modelId => ({
id: modelId, object: "model", created: 1700000000, owned_by: getOwner(modelId)
}));
res.json({ object: "list", data: modelsData });
console.log("Successfully returned model list.");
} catch (error) {
console.error("Error processing GET /v1/models:", error);
res.status(500).json({ error: "Failed to retrieve model list." });
}
});
// === 修改后的 convertMessagesToFalPrompt 函数 (System置顶 + 分隔符 + 对话历史Recency) ===
function convertMessagesToFalPrompt(messages) {
let fixed_system_prompt_content = "";
const conversation_message_blocks = [];
console.log(`Original messages count: ${messages.length}`);
// 1. 分离 System 消息,格式化 User/Assistant 消息
for (const message of messages) {
let content = (message.content === null || message.content === undefined) ? "" : String(message.content);
switch (message.role) {
case 'system':
fixed_system_prompt_content += `System: ${content}\n\n`;
break;
case 'user':
conversation_message_blocks.push(`Human: ${content}\n\n`);
break;
case 'assistant':
conversation_message_blocks.push(`Assistant: ${content}\n\n`);
break;
default:
console.warn(`Unsupported role: ${message.role}`);
continue;
}
}
// 2. 截断合并后的 system 消息(如果超长)
if (fixed_system_prompt_content.length > SYSTEM_PROMPT_LIMIT) {
const originalLength = fixed_system_prompt_content.length;
fixed_system_prompt_content = fixed_system_prompt_content.substring(0, SYSTEM_PROMPT_LIMIT);
console.warn(`Combined system messages truncated from ${originalLength} to ${SYSTEM_PROMPT_LIMIT}`);
}
// 清理末尾可能多余的空白,以便后续判断和拼接
fixed_system_prompt_content = fixed_system_prompt_content.trim();
// 3. 计算 system_prompt 中留给对话历史的剩余空间
// 注意:这里计算时要考虑分隔符可能占用的长度,但分隔符只在需要时添加
// 因此先计算不含分隔符的剩余空间
let space_occupied_by_fixed_system = 0;
if (fixed_system_prompt_content.length > 0) {
// 如果固定内容不为空,计算其长度 + 后面可能的分隔符的长度(如果需要)
// 暂时只计算内容长度,分隔符在组合时再考虑
space_occupied_by_fixed_system = fixed_system_prompt_content.length + 4; // 预留 \n\n...\n\n 的长度
}
const remaining_system_limit = Math.max(0, SYSTEM_PROMPT_LIMIT - space_occupied_by_fixed_system);
console.log(`Trimmed fixed system prompt length: ${fixed_system_prompt_content.length}. Approx remaining system history limit: ${remaining_system_limit}`);
// 4. 反向填充 User/Assistant 对话历史
const prompt_history_blocks = [];
const system_prompt_history_blocks = [];
let current_prompt_length = 0;
let current_system_history_length = 0;
let promptFull = false;
let systemHistoryFull = (remaining_system_limit <= 0);
console.log(`Processing ${conversation_message_blocks.length} user/assistant messages for recency filling.`);
for (let i = conversation_message_blocks.length - 1; i >= 0; i--) {
const message_block = conversation_message_blocks[i];
const block_length = message_block.length;
if (promptFull && systemHistoryFull) {
console.log(`Both prompt and system history slots full. Omitting older messages from index ${i}.`);
break;
}
// 优先尝试放入 prompt
if (!promptFull) {
if (current_prompt_length + block_length <= PROMPT_LIMIT) {
prompt_history_blocks.unshift(message_block);
current_prompt_length += block_length;
continue;
} else {
promptFull = true;
console.log(`Prompt limit (${PROMPT_LIMIT}) reached. Trying system history slot.`);
}
}
// 如果 prompt 满了,尝试放入 system_prompt 的剩余空间
if (!systemHistoryFull) {
if (current_system_history_length + block_length <= remaining_system_limit) {
system_prompt_history_blocks.unshift(message_block);
current_system_history_length += block_length;
continue;
} else {
systemHistoryFull = true;
console.log(`System history limit (${remaining_system_limit}) reached.`);
}
}
}
// 5. *** 组合最终的 prompt 和 system_prompt (包含分隔符逻辑) ***
const system_prompt_history_content = system_prompt_history_blocks.join('').trim();
const final_prompt = prompt_history_blocks.join('').trim();
// 定义分隔符
const SEPARATOR = "\n\n-------下面是比较早之前的对话内容-----\n\n";
let final_system_prompt = "";
// 检查各部分是否有内容 (使用 trim 后的固定部分)
const hasFixedSystem = fixed_system_prompt_content.length > 0;
const hasSystemHistory = system_prompt_history_content.length > 0;
if (hasFixedSystem && hasSystemHistory) {
// 两部分都有,用分隔符连接
final_system_prompt = fixed_system_prompt_content + SEPARATOR + system_prompt_history_content;
console.log("Combining fixed system prompt and history with separator.");
} else if (hasFixedSystem) {
// 只有固定部分
final_system_prompt = fixed_system_prompt_content;
console.log("Using only fixed system prompt.");
} else if (hasSystemHistory) {
// 只有历史部分 (固定部分为空)
final_system_prompt = system_prompt_history_content;
console.log("Using only history in system prompt slot.");
}
// 如果两部分都为空,final_system_prompt 保持空字符串 ""
// 6. 返回结果
const result = {
system_prompt: final_system_prompt, // 最终结果不需要再 trim
prompt: final_prompt // final_prompt 在组合前已 trim
};
console.log(`Final system_prompt length (Sys+Separator+Hist): ${result.system_prompt.length}`);
console.log(`Final prompt length (Hist): ${result.prompt.length}`);
return result;
}
// === convertMessagesToFalPrompt 函数结束 ===
// POST /v1/chat/completions endpoint (保持不变)
app.post('/v1/chat/completions', async (req, res) => {
const { model, messages, stream = false, reasoning = false, ...restOpenAIParams } = req.body;
console.log(`Received chat completion request for model: ${model}, stream: ${stream}`);
if (!FAL_SUPPORTED_MODELS.includes(model)) {
console.warn(`Warning: Requested model '${model}' is not in the explicitly supported list.`);
}
if (!model || !messages || !Array.isArray(messages) || messages.length === 0) {
console.error("Invalid request parameters:", { model, messages: Array.isArray(messages) ? messages.length : typeof messages });
return res.status(400).json({ error: 'Missing or invalid parameters: model and messages array are required.' });
}
try {
// *** 使用更新后的转换函数 ***
const { prompt, system_prompt } = convertMessagesToFalPrompt(messages);
const falInput = {
model: model,
prompt: prompt,
...(system_prompt && { system_prompt: system_prompt }),
reasoning: !!reasoning,
};
console.log("Fal Input:", JSON.stringify(falInput, null, 2));
console.log("Forwarding request to fal-ai with system-priority + separator + recency input:");
console.log("System Prompt Length:", system_prompt?.length || 0);
console.log("Prompt Length:", prompt?.length || 0);
// 调试时取消注释可以查看具体内容
console.log("--- System Prompt Start ---");
console.log(system_prompt);
console.log("--- System Prompt End ---");
console.log("--- Prompt Start ---");
console.log(prompt);
console.log("--- Prompt End ---");
// --- 流式/非流式处理逻辑 (保持不变) ---
if (stream) {
// ... 流式代码 ...
res.setHeader('Content-Type', 'text/event-stream; charset=utf-8');
res.setHeader('Cache-Control', 'no-cache');
res.setHeader('Connection', 'keep-alive');
res.setHeader('Access-Control-Allow-Origin', '*');
res.flushHeaders();
let previousOutput = '';
const falStream = await fal.stream("fal-ai/any-llm", { input: falInput });
try {
for await (const event of falStream) {
const currentOutput = (event && typeof event.output === 'string') ? event.output : '';
const isPartial = (event && typeof event.partial === 'boolean') ? event.partial : true;
const errorInfo = (event && event.error) ? event.error : null;
if (errorInfo) {
console.error("Error received in fal stream event:", errorInfo);
const errorChunk = { id: `chatcmpl-${Date.now()}-error`, object: "chat.completion.chunk", created: Math.floor(Date.now() / 1000), model: model, choices: [{ index: 0, delta: {}, finish_reason: "error", message: { role: 'assistant', content: `Fal Stream Error: ${JSON.stringify(errorInfo)}` } }] };
res.write(`data: ${JSON.stringify(errorChunk)}\n\n`);
break;
}
let deltaContent = '';
if (currentOutput.startsWith(previousOutput)) {
deltaContent = currentOutput.substring(previousOutput.length);
} else if (currentOutput.length > 0) {
console.warn("Fal stream output mismatch detected. Sending full current output as delta.", { previousLength: previousOutput.length, currentLength: currentOutput.length });
deltaContent = currentOutput;
previousOutput = '';
}
previousOutput = currentOutput;
if (deltaContent || !isPartial) {
const openAIChunk = { id: `chatcmpl-${Date.now()}`, object: "chat.completion.chunk", created: Math.floor(Date.now() / 1000), model: model, choices: [{ index: 0, delta: { content: deltaContent }, finish_reason: isPartial === false ? "stop" : null }] };
res.write(`data: ${JSON.stringify(openAIChunk)}\n\n`);
}
}
res.write(`data: [DONE]\n\n`);
res.end();
console.log("Stream finished.");
} catch (streamError) {
console.error('Error during fal stream processing loop:', streamError);
try {
const errorDetails = (streamError instanceof Error) ? streamError.message : JSON.stringify(streamError);
res.write(`data: ${JSON.stringify({ error: { message: "Stream processing error", type: "proxy_error", details: errorDetails } })}\n\n`);
res.write(`data: [DONE]\n\n`);
res.end();
} catch (finalError) {
console.error('Error sending stream error message to client:', finalError);
if (!res.writableEnded) { res.end(); }
}
}
} else {
// --- 非流式处理 (保持不变) ---
console.log("Executing non-stream request...");
const result = await fal.subscribe("fal-ai/any-llm", { input: falInput, logs: true });
console.log("Received non-stream result from fal-ai:", JSON.stringify(result, null, 2));
if (result && result.error) {
console.error("Fal-ai returned an error in non-stream mode:", result.error);
return res.status(500).json({ object: "error", message: `Fal-ai error: ${JSON.stringify(result.error)}`, type: "fal_ai_error", param: null, code: null });
}
const openAIResponse = {
id: `chatcmpl-${result.requestId || Date.now()}`, object: "chat.completion", created: Math.floor(Date.now() / 1000), model: model,
choices: [{ index: 0, message: { role: "assistant", content: result.output || "" }, finish_reason: "stop" }],
usage: { prompt_tokens: null, completion_tokens: null, total_tokens: null }, system_fingerprint: null,
...(result.reasoning && { fal_reasoning: result.reasoning }),
};
res.json(openAIResponse);
console.log("Returned non-stream response.");
}
} catch (error) {
console.error('Unhandled error in /v1/chat/completions:', error);
if (!res.headersSent) {
const errorMessage = (error instanceof Error) ? error.message : JSON.stringify(error);
res.status(500).json({ error: 'Internal Server Error in Proxy', details: errorMessage });
} else if (!res.writableEnded) {
console.error("Headers already sent, ending response.");
res.end();
}
}
});
// 需要修改成嘅版本 (加咗 '0.0.0.0')
app.listen(PORT, '0.0.0.0', () => {
console.log(`===================================================`);
console.log(` Fal OpenAI Proxy Server (System Top + Separator + Recency)`);
console.log(` Listening on host 0.0.0.0, port: ${PORT}`); // <-- 最好改埋 log 方便確認
console.log(` Using Limits: System Prompt=${SYSTEM_PROMPT_LIMIT}, Prompt=${PROMPT_LIMIT}`);
console.log(` Fal AI Key Loaded: ${FAL_KEY ? 'Yes' : 'No'}`);
console.log(` Chat Completions Endpoint: POST http://localhost:${PORT}/v1/chat/completions`); // Log 顯示 localhost 冇問題,實際監聽係 0.0.0.0
console.log(` Models Endpoint: GET http://localhost:${PORT}/v1/models`);
console.log(`===================================================`);
});
// 根路径响应 (更新信息)
app.get('/', (req, res) => {
res.send('Fal OpenAI Proxy (System Top + Separator + Recency Strategy) is running.');
});