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┌─────────────────────────────────────────┐
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│         ADK / Flow / Compose            │  ← upper-layer orchestration
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├─────────────────────────────────────────┤
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│  ChatModel │ Retriever │ Parser │ ...   │  ← component interfaces
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├─────────────────────────────────────────┤
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│  OpenAI │ ARK │ VikingDB │ PDF │ HTML   │  ← concrete implementations
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└─────────────────────────────────────────┘

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Three component categories:
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  Model:     A/B routing (ABRouter) / HTTP logging (CurlRT)
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  Retriever: Multi-Query (rewrite the query) / Router (route across data sources)
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  Parser:    TextParser → ExtParser → CustomParser (dispatch by extension)
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Core pattern: all implement one interface → pluggable in any orchestration

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100% of user requests
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  ├─ 90% → GPT-4o (workhorse, stable)
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  └─ 10% → DeepSeek (experiment, observe)

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import "github.com/cloudwego/eino-examples/components/model/abtest"
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// Prepare two candidate models
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gpt4o, _ := openai.NewChatModel(ctx, &openai.ChatModelConfig{...})
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deepseek, _ := openai.NewChatModel(ctx, &openai.ChatModelConfig{
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    BaseURL: "https://api.deepseek.com/v1",  // point at DeepSeek
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    Model:   "deepseek-chat",
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})
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// Router: split A/B on the last digit of userID
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router := abtest.NewABRouterChatModel(func(
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    ctx context.Context, in []*schema.Message, _ ...model.Option,
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) (string, model.BaseChatModel, error) {
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    // Pull userID out of the context (in a real project, from the request context)
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    userID, _ := ctx.Value("userID").(string)
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    if userID != "" && userID[len(userID)-1] < '5' {  // 50% of traffic
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        return "deepseek", deepseek, nil  // experiment group
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    }
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    return "gpt4o", gpt4o, nil            // control group
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})
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// Used exactly like an ordinary ChatModel!
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msg, _ := router.Generate(ctx, messages)

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client := &http.Client{
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    Transport: httptransport.NewCurlRT(
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        http.DefaultTransport,          // base Transport (the one that actually sends)
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        httptransport.WithLogger(log.Default()),
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        httptransport.WithPrintAuth(false),              // ⚠️ API Key redacted (not printed by default)
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        httptransport.WithMaskHeaders([]string{"X-API-KEY"}),
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        httptransport.WithStreamLogging(true),            // log streaming responses too
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        httptransport.WithMaxStreamLogBytes(8192),
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    ),
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}
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// Inject into the ChatModel — logs print automatically on later calls
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chatModel, _ := openai.NewChatModel(ctx, &openai.ChatModelConfig{
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    HTTPClient: client,
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})

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[curl request] curl -X POST 'https://api.openai.com/v1/chat/completions' \
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  -H 'Content-Type: application/json' \
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  -H 'Authorization: <redacted>' \
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  --data '{"model":"gpt-4o","messages":[{"role":"user","content":"hello"}]}'

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[curl response] HTTP/1.1 200
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{"id":"chatcmpl-xxx","choices":[{"message":{"role":"assistant","content":"Hello! How can I help?"}}]}

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User input: "how do I improve code quality"
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The titles of the relevant docs in the vector store are actually:
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  "Unit Testing Best Practices"
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  "Code Review Process Guidelines"
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  "Static Analysis Tool Configuration Guide"

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User input: "tourist attraction" (too vague)
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    ↓ LLM rewrites automatically
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Variant 1: "best tourist attractions for families"     ← from the "family" angle
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Variant 2: "outdoor sightseeing spots recommendations"  ← from the "outdoor" angle
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Variant 3: "popular travel destinations and landmarks"  ← from the "famous sights" angle
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    ↓ search the same vector store with each
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Result 1: [doc_a, doc_b]
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Result 2: [doc_b, doc_d]     →  FusionFunc merges and dedupes → [doc_a, doc_b, doc_c, doc_d, doc_e, doc_f]
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Result 3: [doc_c, doc_e, doc_f]

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import "github.com/cloudwego/eino/flow/retriever/multiquery"
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mqr, _ := multiquery.NewRetriever(ctx, &multiquery.Config{
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    RewriteHandler: func(ctx context.Context, query string) ([]string, error) {
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        out, _ := llm.Generate(ctx, []*schema.Message{
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            schema.SystemMessage("Generate 3 rewritten search queries, one per line."),
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            schema.UserMessage(query),
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        })
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        return strings.Split(out.Content, "\n"), nil
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    },
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    MaxQueriesNum: 3,        // generate at most 3 variants
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    OrigRetriever: vk,        // underlying vector retrieval engine
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})
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docs, _ := mqr.Retrieve(ctx, "tourist attraction")
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// docs holds the merged result of all variants

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Your system has three vector stores:
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  product_vdb  → product info (name, price, specs)
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  review_vdb   → user reviews (rating, review text)
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  faq_vdb      → FAQs (Q&A pairs)
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User asks "how much is this product?" → search product_vdb
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User asks "is this product any good?"  → search review_vdb
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User asks "how do I return it?"       → search faq_vdb

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rr, _ := router.NewRetriever(ctx, &router.Config{
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    Retrievers: map[string]retriever.Retriever{
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        "product":  productRetriever,   // product vector store
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        "review":   reviewRetriever,    // review vector store
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        "faq":      faqRetriever,       // FAQ vector store
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    },
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    Router: func(ctx context.Context, query string) ([]string, error) {
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        var targets []string
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        // Route to different engines by keyword
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        if strings.Contains(query, "price") || strings.Contains(query, "specs") {
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            targets = append(targets, "product")
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        }
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        if strings.Contains(query, "review") || strings.Contains(query, "good") {
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            targets = append(targets, "review")
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        }
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        if strings.Contains(query, "return") || strings.Contains(query, "how") {
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            targets = append(targets, "faq")
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        }
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        if len(targets) == 0 {
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            targets = []string{"product", "review", "faq"}  // fallback: search all
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        }
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        return targets, nil
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    },
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    FusionFunc: nil,  // nil = default RRF (Reciprocal Rank Fusion) fusion
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})

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import "github.com/cloudwego/eino/components/document/parser"
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textParser := parser.TextParser{}
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docs, _ := textParser.Parse(ctx, strings.NewReader("hello world"))

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extParser, _ := parser.NewExtParser(ctx, &parser.ExtParserConfig{
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    Parsers: map[string]parser.Parser{
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        ".html": htmlParser,     // → extract body content with a CSS selector
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        ".pdf":  pdfParser,      // → extract text with a PDF parsing engine
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    },
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    FallbackParser: textParser,  // unknown format → read as plain text
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})
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file, _ := os.Open("./testdata/test.html")
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docs, _ := extParser.Parse(ctx, file, parser.WithURI(filePath))
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// ↑ WithURI must be passed — ExtParser reads the extension off the file path

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// A/B test routing
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"github.com/cloudwego/eino-examples/components/model/abtest"
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// HTTP transport logging
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"github.com/cloudwego/eino-examples/components/model/httptransport"
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// Retriever augmentation
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"github.com/cloudwego/eino/flow/retriever/multiquery"   // Multi-Query
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"github.com/cloudwego/eino/flow/retriever/router"        // Router
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// Document parsers
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"github.com/cloudwego/eino/components/document/parser"         // Parser interface, TextParser, ExtParser
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"github.com/cloudwego/eino-ext/components/document/parser/html" // HTML
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"github.com/cloudwego/eino-ext/components/document/parser/pdf"  // PDF

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┌──────────────────────────────────────────────────┐
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│  ADK layer (Intro Notes §1~§7)                   │
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│  ChatModelAgent, Runner, Middleware, Interrupt   │
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├──────────────────────────────────────────────────┤
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│  Flow layer (Appendix 1: Flow module)            │
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│  react.NewAgent, host.NewMultiAgent              │
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├──────────────────────────────────────────────────┤
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│  Compose layer (Intro Notes §6.4)                │
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│  Graph, Chain, Workflow, Branch, ProcessState    │
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├──────────────────────────────────────────────────┤
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│  Component layer (this appendix)                 │
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│  ChatModel, Retriever, Parser, Tool              │
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└──────────────────────────────────────────────────┘

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Model:
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  ABRouter = traffic splitter (A/B testing / cost optimization / canary release)
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  CurlRT   = HTTP debugger (cURL-style logs + automatic API Key redaction)
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Retriever:
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  MultiQuery = rewrite the query with an LLM → search one store from several angles → merge and dedupe
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  Router     = analyze the query → dispatch to different stores → fuse the results
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Parser:
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  TextParser → ExtParser (map by extension) → CustomParser (WrapImplSpecificOptFn)