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feat: Implement AI analysis and integrate with the bot listener.

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This commit is contained in:
2569718930@qq.com
2026-02-27 00:14:32 +08:00
parent be0784ea53
commit 3aee0e7832
2 changed files with 16 additions and 19 deletions
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bot_listener.py
+15 -18
View File
@@ -300,39 +300,40 @@ def analyze_weather_trend(weather_data, temp_symbol):
# 兜底默认值
first_peak_h, last_peak_h = 13, 15
# --- 简化的 AI 特征提取 ---
# --- 简化的 AI 特征提取 (不对用户双重显示，仅供 AI 使用) ---
ai_features = list(insights)
# 不再生成死板的分析文案，仅保留核心事实描述
# 1. 气温节奏特征
if local_hour > last_peak_h:
insights.append(f"⏱️ 状态: 预报峰值时段已过 ({window})。")
ai_features.append(f"⏱️ 状态: 预报峰值时段已过 ({window})。")
elif first_peak_h <= local_hour <= last_peak_h:
insights.append(f"⏱️ 状态: 正处于预报最热窗口 ({window})内。")
ai_features.append(f"⏱️ 状态: 正处于预报最热窗口 ({window})内。")
else:
insights.append(f"⏱️ 状态: 距最热时段还有 {first_peak_h - local_hour}h ({window})。")
ai_features.append(f"⏱️ 状态: 距最热时段还有 {first_peak_h - local_hour}h ({window})。")
# 2. 气温偏差特征
if max_so_far is not None and forecast_high is not None:
gap = max_so_far - forecast_high
if gap > 0.5:
insights.append(f"🚨 异常: 实测已冲破所有预报上限 ({max_so_far}{temp_symbol} vs {forecast_high}{temp_symbol})。")
ai_features.append(f"🚨 异常: 实测已冲破所有预报上限 ({max_so_far}{temp_symbol} vs {forecast_high}{temp_symbol})。")
elif abs(gap) <= 1.0:
insights.append(f"⚖️ 状态: 实测已极度接近预报峰值。")
ai_features.append(f"⚖️ 状态: 实测已极度接近预报峰值。")
# 3. 气象动力特征描述 (无主观推测)
humidity = metar.get("current", {}).get("humidity")
if humidity and humidity > 80:
insights.append(f"💦 湿度极高 ({humidity}%)。")
ai_features.append(f"💦 湿度极高 ({humidity}%)。")
clouds = metar.get("current", {}).get("clouds", [])
if clouds:
cover = clouds[-1].get("cover", "")
c_desc = {"OVC": "全阴", "BKN": "多云", "SCT": "散云", "FEW": "少云"}.get(cover, cover)
insights.append(f"☁️ 天空状况: {c_desc}。")
ai_features.append(f"☁️ 天空状况: {c_desc}。")
wx_desc = metar.get("current", {}).get("wx_desc")
if wx_desc:
insights.append(f"🌧️ 天气现象: {wx_desc}。")
ai_features.append(f"🌧️ 天气现象: {wx_desc}。")
# 4. 暖平流事实提取
max_temp_time_str = metar.get("current", {}).get("max_temp_time", "")
@@ -346,7 +347,7 @@ def analyze_weather_trend(weather_data, temp_symbol):
max_temp_rad = rad if rad is not None else 0.0
break
if max_temp_rad < 50:
insights.append(f"🌙 动力事实: 最高温出现在低辐射时段 ({max_temp_time_str}, 辐射{max_temp_rad:.0f}W/m²)。")
ai_features.append(f"🌙 动力事实: 最高温出现在低辐射时段 ({max_temp_time_str}, 辐射{max_temp_rad:.0f}W/m²)。")
except: pass
# 5. 结算判定
@@ -354,12 +355,10 @@ def analyze_weather_trend(weather_data, temp_symbol):
settled = round(max_so_far)
fractional = max_so_far - int(max_so_far)
if abs(fractional - 0.5) <= 0.2:
insights.append(f"⚖️ 结算事实: 当前最高 {max_so_far}{temp_symbol} 处于进位关键点 ({settled}{temp_symbol})。")
ai_features.append(f"⚖️ 结算事实: 当前最高 {max_so_far}{temp_symbol} 处于进位关键点 ({settled}{temp_symbol})。")
if not insights:
return ""
return "\n".join(insights)
display_str = "\n".join(insights) if insights else ""
return display_str, "\n".join(ai_features)
def start_bot():
config = load_config()
@@ -705,7 +704,7 @@ def start_bot():
msg_lines.append(f" {prefix} {cloud_desc} | 👁️ {vis or 10}mi | 💨 {wind or 0}kt")
# --- 5. 态势特征提取 ---
feature_str = analyze_weather_trend(weather_data, temp_symbol)
feature_str, ai_context = analyze_weather_trend(weather_data, temp_symbol)
if feature_str:
# 仅将最核心的信息展示给用户作为"态势分析"
# 但后面会把更全的数据传给 AI
@@ -718,8 +717,6 @@ def start_bot():
try:
from src.analysis.ai_analyzer import get_ai_analysis
# 构建更全的背景数据给 AI
# 包含风力、能见度、多源分歧等原始结论
ai_context = feature_str
# 补充多模型分歧
mm = weather_data.get("multi_model", {})
src/analysis/ai_analyzer.py
+1 -1
View File
@@ -39,7 +39,7 @@ def get_ai_analysis(weather_insights: str, city_name: str, temp_symbol: str) ->
🤖 <b>Groq AI 决策</b>
- 💡 逻辑: [简述动力来源/阻碍因子。例如：暖平流强势推高，且辐射极低时段创新高，极大概率超预报。]
- ⏰ 时机: [理想 / 较好 / 谨慎 / 不建议] (信心: [1-10]/10)
- 🎯 信心: [1-10]/10
"""
payload = {