Update app.py

app.py

@@ -41,6 +41,7 @@ from tempfile import mkdtemp
 from langchain.schema import AIMessage
 from datetime import datetime
 from zoneinfo import ZoneInfo
+from dateutil import parser as date_parser
 import numexpr as ne
 import pandas as pd
 
@@ -53,6 +54,7 @@ from geopy.geocoders import Nominatim
 from timezonefinder import TimezoneFinder
 from langchain_experimental.agents import create_pandas_dataframe_agent
 
+
 session_retriever = None
 session_qa_chain = None
 csv_dataframe = None  # CSV tool will use this
@@ -450,83 +452,148 @@ weather_api_key = os.environ.get("WEATHER_API_KEY")
 
 def weather_agent_tool(query: str) -> str:
     try:
+        from dateutil import parser as date_parser
+        from zoneinfo import ZoneInfo
+
+        weather_api_key = os.environ.get("WEATHER_API_KEY")
+        if not weather_api_key:
+            return "Weather API key not found. Please set WEATHER_API_KEY env variable."
+
+        # GPT get location
         location_prompt = f"""
         You are a location extractor. Given a user's query about weather, return the location mentioned in it. If not found, return "London".
-
         Examples:
         - "What's the weather in Tokyo now?" → Tokyo
         - "紐約天氣如何？" → New York
         - "今天台北下雨嗎？" → Taipei
-        - "Weather" → London
-        - "Is it hot today in ldn?" → London
-
+        - "How's the weather?" → London
+        - "Is it gon rain in ldn" → London
+        
         Now process this query: "{query}"
         """
         location_response = llm_gpt4.invoke(location_prompt)
-        if isinstance(location_response, AIMessage):
-            location = location_response.content.strip()
-        else:
-            location = str(location_response).strip()
-
-        url = f"http://api.weatherapi.com/v1/current.json?key={weather_api_key}&q={location}&aqi=no"
-        response = requests.get(url)
-        data = response.json()
-
-        if "current" not in data:
-            return f"Sorry, I couldn't find the weather info for '{location}'."
+        location = location_response.content.strip() if isinstance(location_response, AIMessage) else str(location_response).strip()
 
-        current = data["current"]
-        condition = current["condition"]["text"]
-        temp_c = current["temp_c"]
-        humidity = current["humidity"]
-        wind_kph = current["wind_kph"]
-        feelslike_c = current["feelslike_c"]
+        # get local time
+        geo = Nominatim(user_agent="weather_agent_demo")
+        loc = geo.geocode(location)
+        tf = TimezoneFinder()
+        tz_str = tf.timezone_at(lat=loc.latitude, lng=loc.longitude) if loc else "Europe/London"
+        local_now = datetime.now(ZoneInfo(tz_str))
+        local_now_str = local_now.strftime("%Y-%m-%d %H:%M:%S")
+
+        # GPT get query time（transfer to Y-M-D）
+        time_prompt = f"""
+        It is currently {local_now_str} in {location}.
+        Based on the query: "{query}", return the intended local date (YYYY-MM-DD).
+        Return only a date like 2025-04-04. If unclear, use today.
+        """
+        date_response = llm_gpt4.invoke(time_prompt)
+        date_str = date_response.content.strip() if isinstance(date_response, AIMessage) else str(date_response).strip()
+        query_date = date_parser.parse(date_str).date()
+        today = local_now.date()
+
+        # choose to use current / forecast / history API according to time
+        if query_date == today:
+            url = f"http://api.weatherapi.com/v1/current.json?key={weather_api_key}&q={location}&aqi=no"
+            data = requests.get(url).json()
+            cur = data["current"]
+            return f"The current weather in {location.title()} is {cur['condition']['text']} with {cur['temp_c']}°C (feels like {cur['feelslike_c']}°C), humidity {cur['humidity']}%, wind {cur['wind_kph']} kph."
+
+        elif query_date > today:
+            url = f"http://api.weatherapi.com/v1/forecast.json?key={weather_api_key}&q={location}&days=3"
+            data = requests.get(url).json()
+            forecast_days = data.get("forecast", {}).get("forecastday", [])
+            for day in forecast_days:
+                if day["date"] == date_str:
+                    d = day["day"]
+                    return f"Forecast for {location.title()} on {query_date.strftime('%A, %B %d')}: {d['condition']['text']}, avg {d['avgtemp_c']}°C, humidity {d['avghumidity']}%, max {d['maxtemp_c']}°C, min {d['mintemp_c']}°C."
+            return f"Forecast unavailable for {query_date} (WeatherAPI supports up to 3 days ahead)."
 
-        return f"The current weather in {location.title()} is {condition} with {temp_c}°C, feels like {feelslike_c}°C, humidity {humidity}%, wind {wind_kph} kph."
+        else:
+            url = f"http://api.weatherapi.com/v1/history.json?key={weather_api_key}&q={location}&dt={date_str}"
+            data = requests.get(url).json()
+            hist = data.get("forecast", {}).get("forecastday", [{}])[0].get("day", {})
+            if not hist:
+                return f"Historical weather not found for {location.title()} on {query_date}."
+            return f"The weather in {location.title()} on {query_date.strftime('%A, %B %d')}: {hist['condition']['text']}, avg {hist['avgtemp_c']}°C, humidity {hist['avghumidity']}%, max {hist['maxtemp_c']}°C, min {hist['mintemp_c']}°C."
 
     except Exception as e:
-        return f"Weather API error: {e}"
+        return f"Weather Agent Error: {e}"
         
+
 @tool("weather")
 def weather_tool(query: str) -> str:
-    """Weather Agent: Provide real-time weather info for any major city."""
+    """Weather Agent: Provide real-time, future, or historical weather info (max 3 days forecast, 7 days history)."""
     try:
+        from dateutil import parser as date_parser
+        from zoneinfo import ZoneInfo
+
+        weather_api_key = os.environ.get("WEATHER_API_KEY")
+        if not weather_api_key:
+            return "Weather API key not found. Please set WEATHER_API_KEY env variable."
+
+        # GPT get location
         location_prompt = f"""
         You are a location extractor. Given a user's query about weather, return the location mentioned in it. If not found, return "London".
-
         Examples:
         - "What's the weather in Tokyo now?" → Tokyo
         - "紐約天氣如何？" → New York
         - "今天台北下雨嗎？" → Taipei
-        - "Weather" → London
-        - "Is it hot today in ldn?" → London
-
+        - "How's the weather?" → London
+        - "Is it gon rain in ldn" → London
+        
         Now process this query: "{query}"
         """
         location_response = llm_gpt4.invoke(location_prompt)
-        if isinstance(location_response, AIMessage):
-            location = location_response.content.strip()
-        else:
-            location = str(location_response).strip()
-
-        url = f"http://api.weatherapi.com/v1/current.json?key={weather_api_key}&q={location}&aqi=no"
-        response = requests.get(url)
-        data = response.json()
-
-        if "current" not in data:
-            return f"Sorry, I couldn't find the weather info for '{location}'."
+        location = location_response.content.strip() if isinstance(location_response, AIMessage) else str(location_response).strip()
 
-        current = data["current"]
-        condition = current["condition"]["text"]
-        temp_c = current["temp_c"]
-        humidity = current["humidity"]
-        wind_kph = current["wind_kph"]
-        feelslike_c = current["feelslike_c"]
+        # get local time
+        geo = Nominatim(user_agent="weather_agent_demo")
+        loc = geo.geocode(location)
+        tf = TimezoneFinder()
+        tz_str = tf.timezone_at(lat=loc.latitude, lng=loc.longitude) if loc else "Europe/London"
+        local_now = datetime.now(ZoneInfo(tz_str))
+        local_now_str = local_now.strftime("%Y-%m-%d %H:%M:%S")
+
+        # GPT get query time（transfer to Y-M-D）
+        time_prompt = f"""
+        It is currently {local_now_str} in {location}.
+        Based on the query: "{query}", return the intended local date (YYYY-MM-DD).
+        Return only a date like 2025-04-04. If unclear, use today.
+        """
+        date_response = llm_gpt4.invoke(time_prompt)
+        date_str = date_response.content.strip() if isinstance(date_response, AIMessage) else str(date_response).strip()
+        query_date = date_parser.parse(date_str).date()
+        today = local_now.date()
+
+        # chose to use current / forecast / history API according to time
+        if query_date == today:
+            url = f"http://api.weatherapi.com/v1/current.json?key={weather_api_key}&q={location}&aqi=no"
+            data = requests.get(url).json()
+            cur = data["current"]
+            return f"The current weather in {location.title()} is {cur['condition']['text']} with {cur['temp_c']}°C (feels like {cur['feelslike_c']}°C), humidity {cur['humidity']}%, wind {cur['wind_kph']} kph."
+
+        elif query_date > today:
+            url = f"http://api.weatherapi.com/v1/forecast.json?key={weather_api_key}&q={location}&days=3"
+            data = requests.get(url).json()
+            forecast_days = data.get("forecast", {}).get("forecastday", [])
+            for day in forecast_days:
+                if day["date"] == date_str:
+                    d = day["day"]
+                    return f"Forecast for {location.title()} on {query_date.strftime('%A, %B %d')}: {d['condition']['text']}, avg {d['avgtemp_c']}°C, humidity {d['avghumidity']}%, max {d['maxtemp_c']}°C, min {d['mintemp_c']}°C."
+            return f"Forecast unavailable for {query_date} (WeatherAPI supports up to 3 days ahead)."
 
-        return f"The current weather in {location.title()} is {condition} with {temp_c}°C, feels like {feelslike_c}°C, humidity {humidity}%, wind {wind_kph} kph."
+        else:
+            url = f"http://api.weatherapi.com/v1/history.json?key={weather_api_key}&q={location}&dt={date_str}"
+            data = requests.get(url).json()
+            hist = data.get("forecast", {}).get("forecastday", [{}])[0].get("day", {})
+            if not hist:
+                return f"Historical weather not found for {location.title()} on {query_date}."
+            return f"The weather in {location.title()} on {query_date.strftime('%A, %B %d')}: {hist['condition']['text']}, avg {hist['avgtemp_c']}°C, humidity {hist['avghumidity']}%, max {hist['maxtemp_c']}°C, min {hist['mintemp_c']}°C."
 
     except Exception as e:
-        return f"Weather API error: {e}"
+        return f"Weather Agent Error: {e}"
         
 @tool("summarise")
 def summarise_tool(query: str) -> str: