add tools for modetoneed and needtodestination

.env

@@ -1,2 +1,3 @@
 SERPAPI_API_KEY="5f1ba2f2179fafad997e2514ccaa634be88cc9d7c5d0382e9e5b528ba0e434c0O"
-OPENWEATHER_API_KEY="e6945bba120fdad7ef7421c5cdbe731c"
+OPENWEATHER_API_KEY="e6945bba120fdad7ef7421c5cdbe731c"
+ANTHROPIC_KEY=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

tools/mood_to_need.py

@@ -0,0 +1,47 @@
+"""Tool to map a user's mood to a vacation need."""
+
+from smolagents.tools import Tool
+
+class MoodToNeedTool(Tool):
+    """
+    A tool that converts user mood descriptions into vacation needs using an LLM.
+
+    Attributes:
+        model: A callable language model used to generate the output.
+    """
+    name = "MoodToNeed"
+    inputs = {
+    "mood": {"type": "string", "description": "User's mood as text"},
+}
+    output_type = "string"
+
+    description = "Converts user mood into a travel-related need."
+
+    def __init__(self, model: callable) -> None:
+        """
+        Args:
+            model: A callable language model with a __call__(str) -> str interface.
+        """
+        self.model = model
+
+    def forward(self, mood: str) -> str:
+        """
+        Generates a vacation need from a user mood string.
+
+        Args:
+            mood: A string describing the user's emotional state.
+
+        Returns:
+            A short string describing the travel-related need.
+        """
+        prompt = (
+            f"Given the user's mood, suggest a travel need.\n"
+            f'Mood: "{mood}"\n'
+            f'Return only the need, no explanation.\n'
+            f'Example:\n'
+            f'Mood: "I am exhausted" → Need: "A calm wellness retreat"\n'
+            f'Mood: "{mood}"\n'
+            f'Need:'
+        )
+        response = self.model(prompt)
+        return response.strip()

tools/need_to_destination.py

@@ -0,0 +1,91 @@
+from smolagents.tools import Tool
+import json
+
+class NeedToDestinationTool(Tool):
+    name = "NeedToDestination"
+    inputs = {
+        "need": {"type": "string", "description": "User's travel need as text"},
+    }
+    output_type = "array"
+    description = "Suggests destinations and flight info based on user need."
+
+    def __init__(self, model: callable, departure_airport: str = "CDG") -> None:
+        super().__init__()
+        self.model = model
+        self.departure_airport = departure_airport
+
+    def forward(self, need: str) -> list[dict]:
+        prompt = f"""
+You are a travel agent AI.
+
+Based on the user's need: "{need}",
+suggest 2-3 travel destinations with round-trip flight information.
+
+Return the output as valid JSON in the following format:
+
+[
+  {{
+    "destination": "DestinationName",
+    "departure": {{
+      "date": "YYYY-MM-DD",
+      "from_airport": "{self.departure_airport}",
+      "to_airport": "XXX"
+    }},
+    "return": {{
+      "date": "YYYY-MM-DD",
+      "from_airport": "XXX",
+      "to_airport": "{self.departure_airport}"
+    }}
+  }},
+  ...
+]
+
+DO NOT add explanations, only return raw JSON.
+"""
+        result = self.model(prompt)
+        try:
+            destinations = json.loads(result.strip())
+        except json.JSONDecodeError:
+            raise ValueError("Could not parse LLM output to JSON.")
+
+        return destinations
+    
+def mock_model(prompt: str) -> str:
+    return """
+    [
+      {
+        "destination": "Nice",
+        "departure": {
+          "date": "2025-07-01",
+          "from_airport": "CDG",
+          "to_airport": "NCE"
+        },
+        "return": {
+          "date": "2025-07-07",
+          "from_airport": "NCE",
+          "to_airport": "CDG"
+        }
+      },
+      {
+        "destination": "Barcelona",
+        "departure": {
+          "date": "2025-07-02",
+          "from_airport": "CDG",
+          "to_airport": "BCN"
+        },
+        "return": {
+          "date": "2025-07-08",
+          "from_airport": "BCN",
+          "to_airport": "CDG"
+        }
+      }
+    ]
+    """
+
+if __name__ == "__main__":
+    tool = NeedToDestinationTool(model=mock_model)
+    test_need = "A relaxing beach holiday"
+    destinations = tool(need=test_need)
+    print("Destinations returned by the tool:")
+    for dest in destinations:
+        print(dest)