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test/test_julia_to_julia_mix_payload_sender.jl
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238
test/test_julia_to_julia_mix_payload_sender.jl
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#!/usr/bin/env julia
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# Test script for mixed-content message testing
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# Tests sending a mix of text, json, table, image, audio, video, and binary data
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# from Julia serviceA to Julia serviceB using NATSBridge.jl smartsend
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#
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# This test demonstrates that any combination and any number of mixed content
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# can be sent and received correctly.
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using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP, Base64
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# Include the bridge module
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include("../src/NATSBridge.jl")
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using .NATSBridge
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# Configuration
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const SUBJECT = "/NATSBridge_mix_test"
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const NATS_URL = "nats.yiem.cc"
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const FILESERVER_URL = "http://192.168.88.104:8080"
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# Create correlation ID for tracing
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correlation_id = string(uuid4())
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# ------------------------------------------------------------------------------------------------ #
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# test mixed content transfer #
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# ------------------------------------------------------------------------------------------------ #
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# Helper: Log with correlation ID
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function log_trace(message)
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timestamp = Dates.now()
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println("[$timestamp] [Correlation: $correlation_id] $message")
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end
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# File upload handler for plik server
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function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
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# Get upload ID
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url_getUploadID = "$fileserver_url/upload"
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headers = ["Content-Type" => "application/json"]
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body = """{ "OneShot" : true }"""
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httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
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responseJson = JSON.parse(String(httpResponse.body))
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uploadid = responseJson["id"]
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uploadtoken = responseJson["uploadToken"]
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# Upload file
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file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
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url_upload = "$fileserver_url/file/$uploadid"
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headers = ["X-UploadToken" => uploadtoken]
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form = HTTP.Form(Dict("file" => file_multipart))
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httpResponse = HTTP.post(url_upload, headers, form)
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responseJson = JSON.parse(String(httpResponse.body))
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fileid = responseJson["id"]
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url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
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return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
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end
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# Helper: Create sample data for each type
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function create_sample_data()
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# Text data (small - direct transport)
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text_data = "Hello! This is a test chat message. 🎉\nHow are you doing today? 😊"
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# Dictionary/JSON data (medium - could be direct or link)
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dict_data = Dict(
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"type" => "chat",
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"sender" => "serviceA",
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"receiver" => "serviceB",
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"metadata" => Dict(
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"timestamp" => string(Dates.now()),
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"priority" => "high",
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"tags" => ["urgent", "chat", "test"]
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),
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"content" => Dict(
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"text" => "This is a JSON-formatted chat message with nested structure.",
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"format" => "markdown",
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"mentions" => ["user1", "user2"]
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)
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)
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# Table data (DataFrame - small - direct transport)
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table_data_small = DataFrame(
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id = 1:10,
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message = ["msg_$i" for i in 1:10],
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sender = ["sender_$i" for i in 1:10],
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timestamp = [string(Dates.now()) for _ in 1:10],
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priority = rand(1:3, 10)
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)
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# Table data (DataFrame - large - link transport)
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# ~1.5MB of data (150,000 rows) - should trigger link transport
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table_data_large = DataFrame(
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id = 1:150_000,
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message = ["msg_$i" for i in 1:150_000],
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sender = ["sender_$i" for i in 1:150_000],
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timestamp = [string(Dates.now()) for i in 1:150_000],
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priority = rand(1:3, 150_000)
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)
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# Image data (small binary - direct transport)
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# Create a simple 10x10 pixel PNG-like data (128 bytes header + 100 pixels = 112 bytes)
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# Using simple RGB data (10*10*3 = 300 bytes of pixel data)
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image_width = 10
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image_height = 10
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image_data = UInt8[]
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# PNG header (simplified)
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push!(image_data, 0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A)
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# Simple RGB data (RGBRGBRGB...)
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for i in 1:image_width*image_height
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push!(image_data, 0xFF, 0x00, 0x00) # Red pixel
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end
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# Image data (large - link transport)
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# Create a larger image (~1.5MB) to test link transport
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large_image_width = 500
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large_image_height = 1000
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large_image_data = UInt8[]
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# PNG header (simplified for 500x1000)
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push!(large_image_data, 0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A)
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# RGB data (500*1000*3 = 1,500,000 bytes)
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for i in 1:large_image_width*large_image_height
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push!(large_image_data, rand(1:255), rand(1:255), rand(1:255)) # Random color pixels
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end
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# Audio data (small binary - direct transport)
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audio_data = UInt8[rand(1:255) for _ in 1:100]
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# Audio data (large - link transport)
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# ~1.5MB of audio-like data
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large_audio_data = UInt8[rand(1:255) for _ in 1:1_500_000]
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# Video data (small binary - direct transport)
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video_data = UInt8[rand(1:255) for _ in 1:150]
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# Video data (large - link transport)
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# ~1.5MB of video-like data
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large_video_data = UInt8[rand(1:255) for _ in 1:1_500_000]
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# Binary data (small - direct transport)
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binary_data = UInt8[rand(1:255) for _ in 1:200]
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# Binary data (large - link transport)
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# ~1.5MB of binary data
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large_binary_data = UInt8[rand(1:255) for _ in 1:1_500_000]
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return (
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text_data,
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dict_data,
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table_data_small,
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table_data_large,
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image_data,
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large_image_data,
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audio_data,
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large_audio_data,
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video_data,
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large_video_data,
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binary_data,
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large_binary_data
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)
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end
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# Sender: Send mixed content via smartsend
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function test_mix_send()
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# Create sample data
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(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()
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# Create payloads list - mixed content with both small and large data
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# Small data uses direct transport, large data uses link transport
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payloads = [
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# Small data (direct transport) - text, dictionary, small table
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("chat_text", text_data, "text"),
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("chat_json", dict_data, "dictionary"),
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("chat_table_small", table_data_small, "table"),
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# Large data (link transport) - large table, large image, large audio, large video, large binary
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("chat_table_large", table_data_large, "table"),
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("user_image_large", large_image_data, "image"),
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("audio_clip_large", large_audio_data, "audio"),
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("video_clip_large", large_video_data, "video"),
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("binary_file_large", large_binary_data, "binary")
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]
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# Use smartsend with mixed content
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env = NATSBridge.smartsend(
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SUBJECT,
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payloads, # List of (dataname, data, type) tuples
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nats_url = NATS_URL,
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fileserver_url = FILESERVER_URL,
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fileserverUploadHandler = plik_upload_handler,
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size_threshold = 1_000_000, # 1MB threshold
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correlation_id = correlation_id,
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msg_purpose = "chat",
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sender_name = "mix_sender",
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receiver_name = "",
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receiver_id = "",
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reply_to = "",
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reply_to_msg_id = ""
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)
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log_trace("Sent message with $(length(env.payloads)) payloads")
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# Log transport type for each payload
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for (i, payload) in enumerate(env.payloads)
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log_trace("Payload $i ('$payload.dataname'):")
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log_trace(" Transport: $(payload.transport)")
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log_trace(" Type: $(payload.type)")
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log_trace(" Size: $(payload.size) bytes")
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log_trace(" Encoding: $(payload.encoding)")
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if payload.transport == "link"
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log_trace(" URL: $(payload.data)")
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end
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end
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# Summary
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println("\n--- Transport Summary ---")
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direct_count = count(p -> p.transport == "direct", env.payloads)
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link_count = count(p -> p.transport == "link", env.payloads)
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log_trace("Direct transport: $direct_count payloads")
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log_trace("Link transport: $link_count payloads")
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end
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# Run the test
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println("Starting mixed-content transport test...")
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println("Correlation ID: $correlation_id")
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# Run sender
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println("start smartsend for mixed content")
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test_mix_send()
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println("\nTest completed.")
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println("Note: Run test_julia_to_julia_mix_receiver.jl to receive the messages.")
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