#!/usr/bin/env julia # Test script for mixed-content message testing # Tests sending a mix of text, json, table, image, audio, video, and binary data # from Julia serviceA to Julia serviceB using NATSBridge.jl smartsend # # This test demonstrates that any combination and any number of mixed content # can be sent and received correctly. using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP, Base64 # Include the bridge module include("../src/NATSBridge.jl") using .NATSBridge # Configuration const SUBJECT = "/NATSBridge_mix_test" const NATS_URL = "nats.yiem.cc" const FILESERVER_URL = "http://192.168.88.104:8080" # Create correlation ID for tracing correlation_id = string(uuid4()) # ------------------------------------------------------------------------------------------------ # # test mixed content transfer # # ------------------------------------------------------------------------------------------------ # # Helper: Log with correlation ID function log_trace(message) timestamp = Dates.now() println("[$timestamp] [Correlation: $correlation_id] $message") end # File upload handler for plik server function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any} # Get upload ID url_getUploadID = "$fileserver_url/upload" headers = ["Content-Type" => "application/json"] body = """{ "OneShot" : true }""" httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false) responseJson = JSON.parse(String(httpResponse.body)) uploadid = responseJson["id"] uploadtoken = responseJson["uploadToken"] # Upload file file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream") url_upload = "$fileserver_url/file/$uploadid" headers = ["X-UploadToken" => uploadtoken] form = HTTP.Form(Dict("file" => file_multipart)) httpResponse = HTTP.post(url_upload, headers, form) responseJson = JSON.parse(String(httpResponse.body)) fileid = responseJson["id"] url = "$fileserver_url/file/$uploadid/$fileid/$dataname" return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url) end # Helper: Create sample data for each type function create_sample_data() # Text data (small - direct transport) text_data = "Hello! This is a test chat message. 🎉\nHow are you doing today? 😊" # Dictionary/JSON data (medium - could be direct or link) dict_data = Dict( "type" => "chat", "sender" => "serviceA", "receiver" => "serviceB", "metadata" => Dict( "timestamp" => string(Dates.now()), "priority" => "high", "tags" => ["urgent", "chat", "test"] ), "content" => Dict( "text" => "This is a JSON-formatted chat message with nested structure.", "format" => "markdown", "mentions" => ["user1", "user2"] ) ) # Table data (DataFrame - small - direct transport) table_data_small = DataFrame( id = 1:10, message = ["msg_$i" for i in 1:10], sender = ["sender_$i" for i in 1:10], timestamp = [string(Dates.now()) for _ in 1:10], priority = rand(1:3, 10) ) # Table data (DataFrame - large - link transport) # ~1.5MB of data (150,000 rows) - should trigger link transport table_data_large = DataFrame( id = 1:150_000, message = ["msg_$i" for i in 1:150_000], sender = ["sender_$i" for i in 1:150_000], timestamp = [string(Dates.now()) for i in 1:150_000], priority = rand(1:3, 150_000) ) # Image data (small binary - direct transport) # Create a simple 10x10 pixel PNG-like data (128 bytes header + 100 pixels = 112 bytes) # Using simple RGB data (10*10*3 = 300 bytes of pixel data) image_width = 10 image_height = 10 image_data = UInt8[] # PNG header (simplified) push!(image_data, 0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A) # Simple RGB data (RGBRGBRGB...) for i in 1:image_width*image_height push!(image_data, 0xFF, 0x00, 0x00) # Red pixel end # Image data (large - link transport) # Create a larger image (~1.5MB) to test link transport large_image_width = 500 large_image_height = 1000 large_image_data = UInt8[] # PNG header (simplified for 500x1000) push!(large_image_data, 0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A) # RGB data (500*1000*3 = 1,500,000 bytes) for i in 1:large_image_width*large_image_height push!(large_image_data, rand(1:255), rand(1:255), rand(1:255)) # Random color pixels end # Audio data (small binary - direct transport) audio_data = UInt8[rand(1:255) for _ in 1:100] # Audio data (large - link transport) # ~1.5MB of audio-like data large_audio_data = UInt8[rand(1:255) for _ in 1:1_500_000] # Video data (small binary - direct transport) video_data = UInt8[rand(1:255) for _ in 1:150] # Video data (large - link transport) # ~1.5MB of video-like data large_video_data = UInt8[rand(1:255) for _ in 1:1_500_000] # Binary data (small - direct transport) binary_data = UInt8[rand(1:255) for _ in 1:200] # Binary data (large - link transport) # ~1.5MB of binary data large_binary_data = UInt8[rand(1:255) for _ in 1:1_500_000] return ( text_data, dict_data, table_data_small, table_data_large, image_data, large_image_data, audio_data, large_audio_data, video_data, large_video_data, binary_data, large_binary_data ) end # Sender: Send mixed content via smartsend function test_mix_send() # Create sample data (text_data, dict_data, table_data_small, table_data_large, image_data, large_image_data, audio_data, large_audio_data, video_data, large_video_data, binary_data, large_binary_data) = create_sample_data() # Create payloads list - mixed content with both small and large data # Small data uses direct transport, large data uses link transport payloads = [ # Small data (direct transport) - text, dictionary, small table ("chat_text", text_data, "text"), ("chat_json", dict_data, "dictionary"), ("chat_table_small", table_data_small, "table"), # Large data (link transport) - large table, large image, large audio, large video, large binary ("chat_table_large", table_data_large, "table"), ("user_image_large", large_image_data, "image"), ("audio_clip_large", large_audio_data, "audio"), ("video_clip_large", large_video_data, "video"), ("binary_file_large", large_binary_data, "binary") ] # Use smartsend with mixed content env, env_json_str = NATSBridge.smartsend( SUBJECT, payloads; # List of (dataname, data, type) tuples broker_url = NATS_URL, fileserver_url = FILESERVER_URL, fileserver_upload_handler = plik_upload_handler, size_threshold = 1_000_000, # 1MB threshold correlation_id = correlation_id, msg_purpose = "chat", sender_name = "mix_sender", receiver_name = "", receiver_id = "", reply_to = "", reply_to_msg_id = "", is_publish = true # Publish the message to NATS ) log_trace("Sent message with $(length(env.payloads)) payloads") # Log transport type for each payload for (i, payload) in enumerate(env.payloads) log_trace("Payload $i ('$payload.dataname'):") log_trace(" Transport: $(payload.transport)") log_trace(" Type: $(payload.payload_type)") log_trace(" Size: $(payload.size) bytes") log_trace(" Encoding: $(payload.encoding)") if payload.transport == "link" log_trace(" URL: $(payload.data)") end end # Summary println("\n--- Transport Summary ---") direct_count = count(p -> p.transport == "direct", env.payloads) link_count = count(p -> p.transport == "link", env.payloads) log_trace("Direct transport: $direct_count payloads") log_trace("Link transport: $link_count payloads") end # Run the test println("Starting mixed-content transport test...") println("Correlation ID: $correlation_id") # Run sender println("start smartsend for mixed content") test_mix_send() println("\nTest completed.") println("Note: Run test_julia_to_julia_mix_receiver.jl to receive the messages.")