feat: 提交热榜评论分析工具 MVP 基线

2026-07-03 11:12:12 +08:00
parent 0231be6338
commit 9bad7b6e63
60 changed files with 4058 additions and 0 deletions
@@ -0,0 +1,140 @@
+import json
+import time
+from dataclasses import dataclass
+from typing import Literal
+
+import httpx
+from pydantic import BaseModel, Field, ValidationError
+
+
+Sentiment = Literal["positive", "negative", "neutral", "unknown"]
+
+
+@dataclass(frozen=True)
+class AIAnalysisResult:
+    comment_id: str
+    sentiment: str
+    labels: list[str]
+    reason: str = ""
+    ai_analysis_status: str = "success"
+
+
+class AIAnalysisItem(BaseModel):
+    comment_id: str
+    sentiment: Sentiment
+    labels: list[str] = Field(default_factory=list, max_length=3)
+    reason: str = ""
+
+
+def build_comment_prompt(comments: list[dict[str, str]]) -> str:
+    payload = [
+        {
+            "comment_id": str(comment["comment_id"]),
+            "content": str(comment.get("content", ""))[:150],
+        }
+        for comment in comments
+    ]
+    return (
+        "只返回 JSON Array，不输出 Markdown 或解释性自然语言。"
+        "请原样回填输入中的 comment_id，不得修改或生成新 ID。"
+        "sentiment 只能是 positive、negative、neutral、unknown；labels 最多 3 个简短中文短语。\n"
+        f"{json.dumps(payload, ensure_ascii=False)}"
+    )
+
+
+def parse_ai_comment_response(response_text: str, *, expected_comment_ids: set[str]) -> list[AIAnalysisResult]:
+    try:
+        raw = json.loads(response_text)
+    except json.JSONDecodeError as exc:
+        raise ValueError("AI response is not valid JSON") from exc
+    if not isinstance(raw, list):
+        raise ValueError("AI response must be a JSON Array")
+
+    results = []
+    for item in raw:
+        try:
+            parsed = AIAnalysisItem.model_validate(item)
+        except ValidationError as exc:
+            raise ValueError("AI response item does not match schema") from exc
+        if parsed.comment_id not in expected_comment_ids:
+            raise ValueError("AI response comment_id does not match input")
+        results.append(
+            AIAnalysisResult(
+                comment_id=parsed.comment_id,
+                sentiment=parsed.sentiment,
+                labels=parsed.labels,
+                reason=parsed.reason,
+            )
+        )
+    return results
+
+
+def calculate_analysis_status(*, success_count: int, total_count: int) -> tuple[float, str]:
+    if total_count <= 0:
+        return 0.0, "insufficient"
+    rate = success_count / total_count
+    return rate, "normal" if rate >= 0.8 else "insufficient"
+
+
+def analyze_comments_with_retry(
+    comments: list[dict[str, str]],
+    *,
+    requester,
+    max_retries: int = 3,
+) -> list[AIAnalysisResult]:
+    expected_ids = {str(comment["comment_id"]) for comment in comments}
+    prompt = build_comment_prompt(comments)
+    for attempt in range(max_retries):
+        try:
+            return parse_ai_comment_response(requester(prompt), expected_comment_ids=expected_ids)
+        except Exception:
+            if attempt >= max_retries - 1:
+                break
+            time.sleep(2**attempt)
+    return [
+        AIAnalysisResult(
+            comment_id=comment_id,
+            sentiment="unknown",
+            labels=[],
+            reason="ai_parse_failed",
+            ai_analysis_status="failed",
+        )
+        for comment_id in expected_ids
+    ]
+
+
+class OpenAICompatibleAIClient:
+    def __init__(
+        self,
+        *,
+        base_url: str,
+        api_key: str,
+        model: str,
+        timeout_seconds: int = 30,
+        http_client: httpx.Client | None = None,
+    ) -> None:
+        self.base_url = base_url.rstrip("/")
+        self.api_key = api_key
+        self.model = model
+        self._http_client = http_client or httpx.Client(timeout=timeout_seconds)
+
+    def request(self, prompt: str) -> str:
+        endpoint = f"{self.base_url}/chat/completions" if self.base_url.endswith("/v1") else f"{self.base_url}/v1/chat/completions"
+        response = self._http_client.post(
+            endpoint,
+            headers={"Authorization": f"Bearer {self.api_key}"},
+            json={
+                "model": self.model,
+                "messages": [
+                    {
+                        "role": "system",
+                        "content": "只返回 JSON Array，不输出 Markdown 或解释性自然语言。",
+                    },
+                    {"role": "user", "content": prompt},
+                ],
+                "temperature": 0,
+            },
+        )
+        response.raise_for_status()
+        payload = response.json()
+        return str(payload["choices"][0]["message"]["content"])