from typing import Dict, Any
from datetime import datetime
from src.modules.utils import create_meeting_list, load_meetings_data

TOOLS = [
    {
        "type": "function",
        "function": {
            "name": "search_meetings",
            "description": "Search across all FOMC meeting data for relevant information using keywords or phrases. Searches across date, title, action, rate, magnitude, forward_guidance, economic_outlook, market_impact, and key_economic_factors fields.",
            "parameters": {
                "type": "object",
                "properties": {
                    "query": {
                        "type": "string",
                        "description": "Search term or phrase to look for in meetings. Examples: 'inflation expectations', 'employment concerns', 'rate cuts', 'economic uncertainty'"
                    },
                    "limit": {
                        "type": "integer",
                        "description": "Maximum number of meetings to return. Default is 3, recommend 3-5 for most queries.",
                        "default": 3,
                        "minimum": 1,
                        "maximum": 10
                    }
                },
                "required": ["query"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "get_latest_meeting",
            "description": "Get details of the last N FOMC meetings. Use for quick updates or general information.",
            "parameters": {
                "type": "object",
                "properties": {
                    "last_n": {
                        "type": "integer",
                        "description": "Number of meetings to return. Default is 1 to get the latest meeting.",
                        "default": 1,
                    }
                }
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "get_rate_decision",
            "description": "Get details about a specific FOMC meeting's rate decision by date. Finds exact match or closest meeting within 30 days. Use for date-specific queries or historical lookups.",
            "parameters": {
                "type": "object",
                "properties": {
                    "date": {
                        "type": "string",
                        "description": "Meeting date in YYYY-MM-DD format (e.g., '2024-12-18'). For approximate dates, use typical FOMC meeting dates (usually 3rd Wednesday of month).",
                        "pattern": "^\\d{4}-\\d{2}-\\d{2}$"
                    }
                },
                "required": ["date"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "compare_meetings",
            "description": "Compare two FOMC meetings side by side with detailed analysis of differences, similarities, and factor changes. Use for trend analysis or when user asks about changes over time.",
            "parameters": {
                "type": "object",
                "properties": {
                    "date1": {
                        "type": "string",
                        "description": "First meeting date in YYYY-MM-DD format (e.g., '2024-06-12')",
                        "pattern": "^\\d{4}-\\d{2}-\\d{2}$"
                    },
                    "date2": {
                        "type": "string",
                        "description": "Second meeting date in YYYY-MM-DD format (e.g., '2024-12-18')",
                        "pattern": "^\\d{4}-\\d{2}-\\d{2}$"
                    }
                },
                "required": ["date1", "date2"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "search_meetings_by_date",
            "description": "Search for meetings by date, date can be a string containing YYYY, YYYY-MM, or YYYY-MM-DD or a string containing month name and year (e.g., 'June 2024').",
            "parameters": {
                "type": "object",
                "properties": {
                    "date_str": {
                        "type": "string",
                        "description": "Date search string in various formats"
                    }
                },
                "required": ["date_str"]
            }
        }
    }
]

def search_meetings_by_date(date_str: str) -> Dict[str, Any]:
    """
    Search for meetings by date, date can be a string containing YYYY, YYYY-MM, or YYYY-MM-DD
    or a string containing month name and year (e.g., "June 2024").
    
    Args:
        date_str (str): Date search string in various formats
        
    Returns:
        Dict containing:
        - success (bool): Whether the search succeeded
        - query (str): The original search query
        - results (List[Dict]): List of matching meetings
        - count (int): Number of results returned
        - search_type (str): Type of search performed
    """
    meetings_data = load_meetings_data()
    
    if not meetings_data:
        return {
            "success": False,
            "error": "No meetings data available",
            "results": [],
            "count": 0
        }
    
    if not date_str.strip():
        transformed_results = create_meeting_list(meetings_data)
        return {
            "success": True,
            "query": date_str,
            "results": transformed_results,
            "count": len(transformed_results),
            "search_type": "all"
        }
    
    date_str = date_str.strip()
    matched_meetings = []
    search_type = "unknown"
    
    # Try different date formats
    try:
        # Check for YYYY format (e.g., "2024")
        if len(date_str) == 4 and date_str.isdigit():
            search_type = "year"
            for meeting in meetings_data:
                meeting_date = meeting.get('date', '')
                if meeting_date.startswith(date_str):
                    matched_meetings.append(meeting)
        
        # Check for YYYY-MM format (e.g., "2024-07", "2025-12")
        elif len(date_str) == 7 and date_str[4] == '-':
            search_type = "year_month"
            for meeting in meetings_data:
                meeting_date = meeting.get('date', '')
                if meeting_date.startswith(date_str):
                    matched_meetings.append(meeting)
        
        # Check for YYYY-MM-DD format (e.g., "2024-07-31")
        elif len(date_str) == 10 and date_str[4] == '-' and date_str[7] == '-':
            search_type = "full_date"
            for meeting in meetings_data:
                meeting_date = meeting.get('date', '')
                if meeting_date == date_str:
                    matched_meetings.append(meeting)
        
        # Check for month name and year (e.g., "June 2024", "July 2025")
        else:
            search_type = "month_year"
            date_str_lower = date_str.lower()
            
            # Month name mappings
            month_names = {
                'january': '01', 'jan': '01',
                'february': '02', 'feb': '02',
                'march': '03', 'mar': '03',
                'april': '04', 'apr': '04',
                'may': '05',
                'june': '06', 'jun': '06',
                'july': '07', 'jul': '07',
                'august': '08', 'aug': '08',
                'september': '09', 'sep': '09', 'sept': '09',
                'october': '10', 'oct': '10',
                'november': '11', 'nov': '11',
                'december': '12', 'dec': '12'
            }
            
            # Try to parse month name + year
            parts = date_str_lower.split()
            if len(parts) == 2:
                month_part, year_part = parts
                if month_part in month_names and year_part.isdigit() and len(year_part) == 4:
                    month_num = month_names[month_part]
                    search_pattern = f"{year_part}-{month_num}"
                    for meeting in meetings_data:
                        meeting_date = meeting.get('date', '')
                        if meeting_date.startswith(search_pattern):
                            matched_meetings.append(meeting)
    
    except Exception as e:
        print(f"Error occurred during date parsing: {str(e)}")
        search_type = "fallback"
        for meeting in meetings_data:
            meeting_date = meeting.get('date', '')
            if date_str.lower() in meeting_date.lower():
                matched_meetings.append(meeting)
    
    # Transform results using create_meeting_list
    if matched_meetings:
        transformed_results = create_meeting_list(matched_meetings)
        return {
            "success": True,
            "query": date_str,
            "results": transformed_results,
            "count": len(transformed_results),
            "search_type": search_type
        }
    else:
        return {
            "success": True,
            "query": date_str,
            "results": [],
            "count": 0,
            "search_type": search_type
        }


def search_meetings(query: str, limit: int = 10) -> Dict[str, Any]:
    """
    Search across all FOMC meeting data for relevant information.
    
    Args:
        query (str): Search term or phrase to look for in meetings
        limit (int): Maximum number of meetings to return (default: 3)
        
    Returns:
        Dict containing:
        - success (bool): Whether the search succeeded
        - query (str): The original search query
        - results (List[Dict]): List of matching meetings
        - count (int): Number of results returned
        - total_matches (int): Total number of meetings that matched
    """
    meetings_data = load_meetings_data()

    if not meetings_data:
        return {
            "success": False,
            "error": "No meetings data available",
            "results": [],
            "count": 0
        }

    if not query.strip():
        transformed_results = create_meeting_list(meetings_data)
        return {
            "success": True,
            "query": query,
            "results": transformed_results,
            "match_details": [{"score": 0, "matched_fields": []} for _ in meetings_data],
            "count": len(transformed_results),
            "total_matches": len(meetings_data)
        }
    
    query_lower = query.lower()
    scored_meetings = []
    
    for meeting in meetings_data:
        score = 0
        matched_fields = []
        
        search_fields = {
            'date': 2,
            'title': 1,
            'action': 3,
            'rate': 3,
            'magnitude': 2,
            'forward_guidance': 2,
            'economic_outlook': 1,
            'market_impact': 1,
            'key_economic_factors': 1
        }
        
        for field, weight in search_fields.items():
            field_value = meeting.get(field, '')
            if isinstance(field_value, list):
                field_value = ' '.join(field_value)
            
            if field_value and query_lower in str(field_value).lower():
                score += weight
                matched_fields.append(field)
        
        if score > 0:
            scored_meetings.append({
                'meeting': meeting,
                'score': score,
                'matched_fields': matched_fields
            })
    
    scored_meetings.sort(key=lambda x: x['score'], reverse=True)

    _limit = min(limit, len(scored_meetings))
    top_results = scored_meetings[:_limit]
    
    transformed_results = create_meeting_list(top_results)
    
    return {
        "success": True,
        "query": query,
        "results": transformed_results,
        "match_details": [{'score': r['score'], 'matched_fields': r['matched_fields']} for r in top_results],
        "count": len(top_results),
        "total_matches": len(scored_meetings)
    }

def get_rate_decision(date: str) -> Dict[str, Any]:
    """
    Get details about a specific FOMC meeting's rate decision.
    
    Args:
        date (str): Meeting date in YYYY-MM-DD format (e.g., "2025-06-18")
        
    Returns:
        Dict containing:
        - success (bool): Whether the meeting was found
        - meeting (Dict): Complete meeting data if found
        - exact_match (bool): True if exact date match, False if closest match
        - requested_date (str): The date that was requested
    """
    meetings_data = load_meetings_data()
    
    if not meetings_data:
        return {
            "success": False,
            "error": "No meetings data available"
        }
    
    target_meeting = None
    for meeting in meetings_data:
        if meeting.get('date') == date:
            target_meeting = meeting
            break
    
    if not target_meeting and date:
        try:
            target_date = datetime.strptime(date, '%Y-%m-%d')
            closest_meeting = None
            min_diff = float('inf')
            
            for meeting in meetings_data:
                try:
                    meeting_date = datetime.strptime(meeting.get('date', ''), '%Y-%m-%d')
                    diff = abs((meeting_date - target_date).days)
                    if diff < min_diff and diff <= 30:
                        min_diff = diff
                        closest_meeting = meeting
                except ValueError:
                    continue
            
            target_meeting = closest_meeting
        except ValueError:
            pass
    
    if target_meeting:
        return {
            "success": True,
            "requested_date": date,
            "meeting": target_meeting,
            "exact_match": target_meeting.get('date') == date
        }
    else:
        return {
            "success": False,
            "error": f"No meeting found for date {date}",
            "requested_date": date
        }

def compare_meetings(date1: str, date2: str) -> Dict[str, Any]:
    """
    Compare two FOMC meetings side by side to analyze differences and similarities.
    
    Args:
        date1 (str): First meeting date in YYYY-MM-DD format
        date2 (str): Second meeting date in YYYY-MM-DD format
        
    Returns:
        Dict containing:
        - success (bool): Whether both meetings were found
        - meeting1/meeting2 (Dict): Data for each meeting
        - differences (Dict): Fields that differ between meetings
        - similarities (Dict): Fields that are the same
        - factor_analysis (Dict): Analysis of key economic factors
    """
    meeting1_result = get_rate_decision(date1)
    meeting2_result = get_rate_decision(date2)
    
    if not meeting1_result["success"]:
        return {
            "success": False,
            "error": f"Could not find meeting for {date1}: {meeting1_result.get('error')}"
        }
    
    if not meeting2_result["success"]:
        return {
            "success": False,
            "error": f"Could not find meeting for {date2}: {meeting2_result.get('error')}"
        }
    
    meeting1 = meeting1_result["meeting"]
    meeting2 = meeting2_result["meeting"]
    
    # Compare key fields
    comparison = {
        "success": True,
        "meeting1": {
            "date": meeting1.get('date'),
            "title": meeting1.get('title'),
            "data": meeting1
        },
        "meeting2": {
            "date": meeting2.get('date'), 
            "title": meeting2.get('title'),
            "data": meeting2
        },
        "differences": {},
        "similarities": {}
    }
    
    # Compare specific fields
    compare_fields = ['action', 'rate', 'magnitude', 'forward_guidance', 'economic_outlook', 'market_impact']
    
    for field in compare_fields:
        val1 = meeting1.get(field, '')
        val2 = meeting2.get(field, '')
        
        if val1 != val2:
            comparison["differences"][field] = {
                "meeting1_value": val1,
                "meeting2_value": val2
            }
        else:
            comparison["similarities"][field] = val1
    
    # Compare key economic factors
    factors1 = set(meeting1.get('key_economic_factors', []))
    factors2 = set(meeting2.get('key_economic_factors', []))
    
    comparison["factor_analysis"] = {
        "common_factors": list(factors1.intersection(factors2)),
        "unique_to_meeting1": list(factors1 - factors2),
        "unique_to_meeting2": list(factors2 - factors1)
    }
    
    return comparison

def get_latest_meeting(last_n=1) -> Dict[str, Any]:
    """
    Get the most recent FOMC meeting data.
    
    Returns:
        Dict containing:
        - success (bool): Whether data was retrieved successfully
        - meeting (Dict): The most recent meeting data
        - total_meetings (int): Total number of meetings in database
    """
    meetings_data = load_meetings_data()

    if not meetings_data:
        return {
            "success": False,
            "error": "No meetings data available"
        }

    # Data is already sorted by date (newest first)
    latest_meetings = meetings_data[:last_n]

    return {
        "success": True,
        "meeting": latest_meetings,
        "total_meetings": len(meetings_data)
    }


FED_TOOLS= {
    "search_meetings": search_meetings,
    "get_latest_meeting": get_latest_meeting,
    "get_rate_decision": get_rate_decision,
    "compare_meetings": compare_meetings
}