# Preprocessor test cases — Step 1 (Local Agent V2)
#
# Schema per caso:
#   id: "1.N"
#   description: str
#   score_name: str                     # nome score inviato a Langfuse
#
# Sorgente contenuto (una delle due):
#   file: <nome file in data/>          # letto come testo UTF-8
#   generate: binary_noise              # contenuto generato dal runner (per test binari)
#
# Per op=detect:
#   op: detect
#   input_filename: str                 # filename passato a detect_content_type
#   expected_content_type: str
#
# Per op=preprocess:
#   op: preprocess
#   input_content_type: str             # content_type passato a preprocess()
#   assertions:
#     no_html_tags: bool
#     min_length: int
#     compression_ratio_lt: float       # len(clean) / len(raw) < soglia
#     metadata_keys: [str, ...]         # chiavi che devono essere in metadata
#     contains: str | [str, ...]        # substring(s) presenti in clean_text
#     not_contains: str | [str, ...]    # substring(s) assenti da clean_text
#     content_type: str                 # valore atteso di result.content_type

cases:

  # ── Detection tests ────────────────────────────────────────────────

  - id: "1.1"
    description: "Detect email HTML"
    score_name: preprocess.detect_email
    file: email_action.html
    op: detect
    input_filename: email_export.html
    expected_content_type: email_html

  - id: "1.2"
    description: "Detect generic HTML"
    score_name: preprocess.detect_generic
    file: generic_page.html
    op: detect
    input_filename: index.html
    expected_content_type: generic_html

  - id: "1.3"
    description: "Detect plain text"
    score_name: preprocess.detect_text
    file: notes.txt
    op: detect
    input_filename: notes.txt
    expected_content_type: plain_text

  - id: "1.4"
    description: "Detect unknown (binary-like content)"
    score_name: preprocess.detect_unknown
    generate: binary_noise
    op: detect
    input_filename: archive.xyz
    expected_content_type: unknown

  # ── Preprocess tests ───────────────────────────────────────────────

  - id: "1.5"
    description: "Email: strip HTML tags"
    score_name: preprocess.email_strip
    file: email_action.html
    op: preprocess
    input_content_type: email_html
    assertions:
      no_html_tags: true
      min_length: 50
      compression_ratio_lt: 0.8

  - id: "1.6"
    description: "Email: extract metadata (Subject + From)"
    score_name: preprocess.email_metadata
    file: email_action.html
    op: preprocess
    input_content_type: email_html
    assertions:
      metadata_keys: [subject, from]

  - id: "1.7"
    description: "Email: split thread — solo ultimo messaggio"
    score_name: preprocess.email_thread
    file: email_thread.html
    op: preprocess
    input_content_type: email_html
    assertions:
      contains: "Sure, I'll handle the deploy"
      not_contains: "Let's plan the deploy"

  - id: "1.8"
    description: "Email: singolo messaggio senza thread"
    score_name: preprocess.email_single
    file: email_single.html
    op: preprocess
    input_content_type: email_html
    assertions:
      contains: "deploy is done"

  - id: "1.9"
    description: "Email: HTML pesante con table layout"
    score_name: preprocess.email_heavy_html
    file: email_heavy.html
    op: preprocess
    input_content_type: email_html
    assertions:
      no_html_tags: true
      min_length: 30
      not_contains:
        - "border-collapse"
        - "font-size"

  - id: "1.10"
    description: "Fallback: file sconosciuto → testo restituito"
    score_name: preprocess.fallback
    file: fallback.txt
    op: preprocess
    input_content_type: unknown
    assertions:
      min_length: 1
      content_type: unknown