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+"""
+Main entry point for the Structured Output Union events API task.
+
+This script demonstrates how to parse a raw log containing multiple HTTP events
+using Pydantic v2 models and LangChain structured output.  It can be run as a
+stand‑alone CLI or imported as a module.
+
+Requirements (see requirements.txt):
+- langchain-core>=1.0.0
+- langchain-openai
+- pydantic>=2.0
+- python-dotenv
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+from typing import List, Union
+
+from dotenv import load_dotenv
+from langchain_core.output_parsers import PydanticOutputParser
+from langchain_openai import ChatOpenAI
+from pydantic import BaseModel, Field, ValidationError
+
+# ---------------------------------------------------------------------------
+# Models
+# ---------------------------------------------------------------------------
+class HttpOkEvent(BaseModel):
+    """Represents a successful HTTP request."""
+
+    kind: str = Field("ok", description="Discriminator for the union.")
+    status: int = Field(200, description="HTTP status code (must be 200).")
+    path: str = Field(..., description="Requested URL path.")
+    duration_ms: int = Field(..., description="Duration of the request in milliseconds.")
+
+class HttpErrorEvent(BaseModel):
+    """Represents a failed HTTP request."""
+
+    kind: str = Field("error", description="Discriminator for the union.")
+    status: int = Field(..., ge=400, le=599, description="HTTP error status code.")
+    path: str = Field(..., description="Requested URL path.")
+    error_message: str = Field(..., description="Human readable error message.")
+
+# Union with discriminator ``kind``.  Pydantic v2 automatically uses the field
+# named ``kind`` to decide which model to instantiate.
+ApiEvent = Union[HttpOkEvent, HttpErrorEvent]
+
+# ---------------------------------------------------------------------------
+# Parser helper
+# ---------------------------------------------------------------------------
+parser = PydanticOutputParser(pydantic_object=ApiEvent)
+
+# ---------------------------------------------------------------------------
+# LLM wrapper
+# ---------------------------------------------------------------------------
+load_dotenv()  # Load JARVIS API key from .env if present.
+llm = ChatOpenAI(
+    model="openai/gpt-oss-20b:free",
+    base_url="https://platform.brojs.ru/jrnl-bh/api/inference/v1",
+    api_key=os.getenv("JOURNAL_MCP_PAT"),
+    temperature=0.0,
+)
+
+# ---------------------------------------------------------------------------
+# Core logic
+# ---------------------------------------------------------------------------
+def parse_event(raw: str) -> ApiEvent:
+    """Parse a single raw log line into an :class:`ApiEvent`.
+
+    The function sends the raw text to the LLM with a structured output prompt
+    and then validates the result using Pydantic.  If validation fails, the
+    exception is propagated so that callers can decide how to handle it.
+    """
+    # Build a simple prompt that instructs the model to return JSON matching
+    # one of the two event schemas.
+    prompt = f"Parse the following log line into JSON:\n{raw}\nJSON:"  # noqa: E501
+    response = llm.invoke([prompt])
+    json_text = parser.parse(response.content)
+    try:
+        return ApiEvent.model_validate(json_text)  # type: ignore[arg-type]
+    except ValidationError as exc:  # pragma: no cover - defensive
+        raise ValueError(f"Failed to validate event: {exc}") from exc
+
+
+def parse_log(raw_log: str) -> List[ApiEvent]:
+    """Parse a multiline log into a list of :class:`ApiEvent` objects.
+
+    The function splits the input on newlines and ignores empty lines.
+    Each non‑empty line is parsed individually.
+    """
+    events: List[ApiEvent] = []
+    for line in raw_log.splitlines():
+        line = line.strip()
+        if not line:
+            continue
+        try:
+            event = parse_event(line)
+            events.append(event)
+        except Exception as exc:  # pragma: no cover - log and skip
+            print(f"Warning: could not parse line '{line}': {exc}", file=sys.stderr)
+    return events
+
+# ---------------------------------------------------------------------------
+# CLI entry point
+# ---------------------------------------------------------------------------
+def main() -> None:
+    parser_cli = argparse.ArgumentParser(description="Parse raw HTTP logs into structured events.")
+    parser_cli.add_argument(
+        "--log-file",
+        type=Path,
+        help="Path to a file containing the raw log. If omitted, a sample log is used.",
+    )
+    args = parser_cli.parse_args()
+
+    if args.log_file and args.log_file.exists():
+        raw_log = args.log_file.read_text(encoding="utf-8")
+    else:
+        # Sample log with mixed success and error events.
+        raw_log = """
+GET /api/users 200 OK duration=123ms
+POST /api/login 404 Not Found: user not found
+PUT /api/items/42 500 Internal Server Error: database timeout
+GET /health 200 OK duration=45ms
+"""
+        print("Using sample log:\n", raw_log)
+
+    events = parse_log(raw_log)
+    if not events:
+        print("No valid events parsed.")
+        sys.exit(1)
+
+    # Pretty‑print the results as a table.
+    header = f"{'Kind':<6} | {'Path':<20} | {'Status':<6} | Details"
+    print(header)
+    print("-" * len(header))
+    for ev in events:
+        if isinstance(ev, HttpOkEvent):
+            details = f"duration={ev.duration_ms}ms"
+        else:  # HttpErrorEvent
+            details = f"error='{ev.error_message}'"
+        print(f"{ev.kind:<6} | {ev.path:<20} | {ev.status:<6} | {details}")
+
+    # Also output the raw Pydantic model dumps for debugging.
+    print("\nModel dumps:\n")
+    for ev in events:
+        print(ev.model_dump_json(indent=2))
+
+if __name__ == "__main__":  # pragma: no cover - entry point
+    main()