| import express from 'express'; |
| import { fal } from '@fal-ai/client'; |
|
|
| |
| const FAL_KEY = process.env.FAL_KEY; |
| if (!FAL_KEY) { |
| console.error("Error: FAL_KEY environment variable is not set."); |
| process.exit(1); |
| } |
|
|
| |
| 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; |
|
|
| |
| const PROMPT_LIMIT = 4800; |
| const SYSTEM_PROMPT_LIMIT = 4800; |
| |
|
|
| |
| 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" |
| ]; |
|
|
| |
| const getOwner = (modelId) => { |
| if (modelId && modelId.includes('/')) { |
| return modelId.split('/')[0]; |
| } |
| return 'fal-ai'; |
| } |
|
|
| |
| 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." }); |
| } |
| }); |
|
|
|
|
| |
| function convertMessagesToFalPrompt(messages) { |
| let fixed_system_prompt_content = ""; |
| const conversation_message_blocks = []; |
| console.log(`Original messages count: ${messages.length}`); |
|
|
| |
| 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; |
| } |
| } |
|
|
| |
| 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}`); |
| } |
| |
| fixed_system_prompt_content = fixed_system_prompt_content.trim(); |
|
|
|
|
| |
| |
| |
| let space_occupied_by_fixed_system = 0; |
| if (fixed_system_prompt_content.length > 0) { |
| |
| |
| space_occupied_by_fixed_system = fixed_system_prompt_content.length + 4; |
| } |
| 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}`); |
|
|
|
|
| |
| 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 ${i}.`); |
| break; |
| } |
|
|
| |
| if (!promptFull) { |
| if (current_prompt_length + block_length <= PROMPT_LIMIT) { |
| prompt_history_blocks.unshift(message_block); |
| current_prompt_length += block_length; |
| continue; |
| } else { |
| promptFull = true; |
| console.log(`Prompt limit (${PROMPT_LIMIT}) reached. Trying system history slot.`); |
| } |
| } |
|
|
| |
| 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.`); |
| } |
| } |
| } |
|
|
| |
| const system_prompt_history_content = system_prompt_history_blocks.join('').trim(); |
| const final_prompt = prompt_history_blocks.join('').trim(); |
|
|
| |
| const SEPARATOR = "\n\n-------下面是比较早之前的对话内容-----\n\n"; |
|
|
| let final_system_prompt = ""; |
|
|
| |
| const hasFixedSystem = fixed_system_prompt_content.length > 0; |
| const hasSystemHistory = system_prompt_history_content.length > 0; |
|
|
| if (hasFixedSystem && hasSystemHistory) { |
| |
| 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) { |
| |
| final_system_prompt = fixed_system_prompt_content; |
| console.log("Using only fixed system prompt."); |
| } else if (hasSystemHistory) { |
| |
| final_system_prompt = system_prompt_history_content; |
| console.log("Using only history in system prompt slot."); |
| } |
| |
|
|
| |
| const result = { |
| system_prompt: final_system_prompt, |
| prompt: final_prompt |
| }; |
|
|
| console.log(`Final system_prompt length (Sys+Separator+Hist): ${result.system_prompt.length}`); |
| console.log(`Final prompt length (Hist): ${result.prompt.length}`); |
|
|
| return result; |
| } |
| |
|
|
|
|
| |
| 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 { |
| |
| 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); |
| |
| 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 ---"); |
|
|
|
|
| |
| if (stream) { |
| |
| 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 { |
| |
| 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(); |
| } |
| } |
| }); |
|
|
| |
| 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: ${PORT}`); |
| console.log(` Using Limits: System Prompt=${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`); |
| console.log(` Models Endpoint: GET http://localhost:${PORT}/v1/models`); |
| console.log(`===================================================`); |
| }); |
|
|
| |
| app.get('/', (req, res) => { |
| res.send('Fal OpenAI Proxy (System Top + Separator + Recency Strategy) is running.'); |
| }); |
|
|