from dataclasses import dataclass, field
from typing import Dict, Any, List, Optional
from string import Template
import json
@dataclass
class PromptTemplate:
    name: str
    description: str
    template: str
    input_variables: List[str]
    output_format: Optional[str] = None
    examples: List[Dict[str, Any]] = field(default_factory=list)
    category: str = "general"
    version: str = "1.0"
    def format(self, **kwargs) -> str:
        """Format template with provided variables."""
        # Validate all required variables are provided
        missing = [v for v in self.input_variables if v not in kwargs]
        if missing:
            raise ValueError(f"Missing required variables: {missing}")
        # Format template
        prompt = Template(self.template).safe_substitute(**kwargs)
        # Add output format if specified
        if self.output_format:
            prompt += f"\n\nOutput Format:\n{self.output_format}"
        return prompt
    def with_examples(self, n: int = 2) -> str:
        """Return template with few-shot examples."""
        examples_text = ""
        for i, ex in enumerate(self.examples[:n], 1):
            examples_text += f"\nExample {i}:\n"
            examples_text += f"Input: {ex.get('input', '')}\n"
            examples_text += f"Output: {ex.get('output', '')}\n"
        return f"{examples_text}\n{self.template}"
class ConstructionPromptLibrary:
    """Library of construction-specific prompt templates."""
    def __init__(self):
        self.templates: Dict[str, PromptTemplate] = {}
        self._register_defaults()
    def register(self, template: PromptTemplate):
        self.templates[template.name] = template
    def get(self, name: str) -> Optional[PromptTemplate]:
        return self.templates.get(name)
    def list_by_category(self, category: str) -> List[PromptTemplate]:
        return [t for t in self.templates.values() if t.category == category]
    def _register_defaults(self):
        # Register all default templates
        for template in DEFAULT_TEMPLATES:
            self.register(template)

COST_LINE_ITEM_CLASSIFICATION = PromptTemplate(
    name="cost_line_item_classification",
    description="Classify cost estimate line items to CSI MasterFormat divisions",
    category="cost_estimation",
    input_variables=["line_items"],
    template="""You are a construction cost estimator. Classify each line item to its appropriate CSI MasterFormat division.
Line Items to Classify:
$line_items
For each line item, provide:
1. CSI Division (2-digit)
2. CSI Section (6-digit code)
3. Confidence level (high/medium/low)
Use standard CSI MasterFormat 2020 divisions:
- 03: Concrete
- 04: Masonry
- 05: Metals
- 06: Wood, Plastics, Composites
- 07: Thermal and Moisture Protection
- 08: Openings
- 09: Finishes
- 22: Plumbing
- 23: HVAC
- 26: Electrical
- 31: Earthwork
- 32: Exterior Improvements
- 33: Utilities
""",
    output_format="""JSON array with format:
[
  {
    "line_item": "original description",
    "csi_division": "XX",
    "csi_section": "XX XX XX",
    "csi_title": "Section Title",
    "confidence": "high|medium|low"
  }
]""",
    examples=[
        {
            "input": "4000 PSI concrete for foundations",
            "output": '{"csi_division": "03", "csi_section": "03 30 00", "csi_title": "Cast-in-Place Concrete", "confidence": "high"}'
        }
    ]
)

COST_UNIT_PRICE_VALIDATION = PromptTemplate(
    name="cost_unit_price_validation",
    description="Validate unit prices against industry standards",
    category="cost_estimation",
    input_variables=["line_items", "location", "year"],
    template="""You are a construction cost analyst. Review these unit prices for reasonableness.
Project Location: $location
Cost Year: $year
Line Items to Review:
$line_items
For each line item:
1. Assess if the unit price is reasonable for the location and year
2. Flag any outliers (too high or too low)
3. Suggest corrections if needed
Consider regional cost factors, labor rates, and material costs for $location.
""",
    output_format="""JSON array:
[
  {
    "line_item": "description",
    "current_unit_cost": 0.00,
    "assessment": "reasonable|high|low",
    "typical_range": {"low": 0.00, "high": 0.00},
    "suggested_unit_cost": 0.00,
    "notes": "explanation"
  }
]"""
)

COST_ESTIMATE_SUMMARY = PromptTemplate(
    name="cost_estimate_summary",
    description="Generate executive summary from detailed estimate",
    category="cost_estimation",
    input_variables=["project_name", "estimate_data", "gross_area"],
    template="""Generate an executive summary for this construction cost estimate.
Project: $project_name
Gross Area: $gross_area SF
Estimate Data:
$estimate_data
Create a professional summary including:
1. Total project cost and cost per SF
2. Major cost drivers (top 5 divisions)
3. Key assumptions and exclusions
4. Risk factors affecting the estimate
5. Recommendations for cost optimization
Write in a professional tone suitable for owner/stakeholder presentation.
""",
    output_format="""Markdown format with sections:
## Executive Summary
## Cost Breakdown
## Key Assumptions
## Risk Factors
## Recommendations"""
)

SCHEDULE_CRITICAL_PATH = PromptTemplate(
    name="schedule_critical_path_analysis",
    description="Analyze schedule critical path and float",
    category="scheduling",
    input_variables=["schedule_data", "data_date"],
    template="""Analyze the critical path for this construction schedule.
Data Date: $data_date
Schedule Data:
$schedule_data
Provide analysis of:
1. Current critical path activities
2. Near-critical activities (total float < 10 days)
3. Float consumption trends
4. Schedule risk areas
5. Recommendations for protecting the critical path
Focus on activities that could impact the project completion date.
""",
    output_format="""JSON:
{
  "critical_path": [
    {"activity_id": "", "name": "", "duration": 0, "total_float": 0}
  ],
  "near_critical": [...],
  "risk_areas": ["description"],
  "recommendations": ["action item"]
}"""
)

SCHEDULE_DELAY_ANALYSIS = PromptTemplate(
    name="schedule_delay_analysis",
    description="Analyze schedule delays and impacts",
    category="scheduling",
    input_variables=["baseline_schedule", "current_schedule", "delay_events"],
    template="""Perform a delay analysis comparing baseline to current schedule.
Baseline Schedule:
$baseline_schedule
Current Schedule:
$current_schedule
Known Delay Events:
$delay_events
Analyze:
1. Total project delay in calendar days
2. Critical path delays vs non-critical delays
3. Concurrent delays
4. Pacing delays
5. Attribution of delays (owner, contractor, third-party, weather)
Use the Time Impact Analysis (TIA) methodology.
""",
    output_format="""JSON:
{
  "total_delay_days": 0,
  "delay_breakdown": {
    "owner_caused": 0,
    "contractor_caused": 0,
    "concurrent": 0,
    "excusable": 0
  },
  "impacted_milestones": [...],
  "recommendations": [...]
}"""
)

SCHEDULE_RESOURCE_LEVELING = PromptTemplate(
    name="schedule_resource_leveling",
    description="Suggest resource leveling for over-allocated resources",
    category="scheduling",
    input_variables=["schedule_data", "resource_limits"],
    template="""Analyze resource allocation and suggest leveling strategies.
Schedule Data:
$schedule_data
Resource Limits:
$resource_limits
Identify:
1. Over-allocated resources by period
2. Peak demand periods
3. Activities that can be shifted (have float)
4. Recommended activity adjustments
Maintain critical path while optimizing resource usage.
""",
    output_format="""JSON:
{
  "overallocations": [
    {"resource": "", "period": "", "demand": 0, "limit": 0}
  ],
  "recommendations": [
    {"activity_id": "", "action": "shift|split|extend", "days": 0, "reason": ""}
  ],
  "revised_peak_demand": {}
}"""
)

DOC_RFI_RESPONSE = PromptTemplate(
    name="doc_rfi_response",
    description="Generate professional RFI response",
    category="document_processing",
    input_variables=["rfi_number", "question", "context", "spec_references"],
    template="""Generate a professional response to this RFI.
RFI Number: $rfi_number
Question:
$question
Context/Background:
$context
Relevant Specification References:
$spec_references
Write a clear, professional response that:
1. Directly addresses the question
2. References relevant specifications
3. Provides clear direction
4. Notes any cost or schedule implications
5. Identifies if further clarification is needed
Maintain a professional, unambiguous tone.
""",
    output_format="""Response in professional letter format with:
- Direct answer to the question
- Supporting references
- Required actions (if any)
- Disclaimer about cost/schedule (if applicable)"""
)

DOC_SPEC_EXTRACTION = PromptTemplate(
    name="doc_spec_extraction",
    description="Extract key requirements from specifications",
    category="document_processing",
    input_variables=["spec_text", "section_number"],
    template="""Extract key requirements from this specification section.
Section Number: $section_number
Specification Text:
$spec_text
Extract and categorize:
1. Material requirements (products, standards, grades)
2. Performance requirements (strength, ratings, certifications)
3. Submittal requirements (shop drawings, samples, certifications)
4. Installation requirements (methods, tolerances, conditions)
5. Quality control requirements (testing, inspections)
6. Warranty requirements
Flag any ambiguous or conflicting requirements.
""",
    output_format="""JSON:
{
  "section": "XX XX XX",
  "title": "",
  "materials": [...],
  "performance": [...],
  "submittals": [...],
  "installation": [...],
  "quality_control": [...],
  "warranty": {...},
  "ambiguities": [...]
}"""
)

DOC_CHANGE_ORDER = PromptTemplate(
    name="doc_change_order_justification",
    description="Generate change order justification narrative",
    category="document_processing",
    input_variables=["change_description", "cause", "cost_impact", "schedule_impact", "supporting_docs"],
    template="""Generate a professional change order justification.
Change Description:
$change_description
Cause of Change:
$cause
Cost Impact: $cost_impact
Schedule Impact: $schedule_impact
Supporting Documentation:
$supporting_docs
Write a clear justification that:
1. Describes the change and its necessity
2. Explains why this was not included in the original scope
3. Details the cost basis (labor, material, equipment, markup)
4. Explains schedule impact and mitigation
5. References supporting documentation
Maintain a factual, professional tone suitable for owner review.
"""
)

BIM_QTO_EXTRACTION = PromptTemplate(
    name="bim_qto_extraction",
    description="Extract quantities from BIM element data",
    category="bim",
    input_variables=["element_data", "quantity_types"],
    template="""Extract quantities from this BIM element data.
Element Data:
$element_data
Quantity Types Needed:
$quantity_types
For each element:
1. Identify the element type and classification
2. Extract requested quantities
3. Apply appropriate unit conversions
4. Group by classification code
Ensure quantities are in standard construction units (SF, LF, CY, EA, etc.).
""",
    output_format="""JSON:
{
  "summary": [
    {
      "classification": "XX XX XX",
      "description": "",
      "quantity": 0.00,
      "unit": "",
      "element_count": 0
    }
  ],
  "details": [...]
}"""
)

BIM_CLASH_ANALYSIS = PromptTemplate(
    name="bim_clash_analysis",
    description="Summarize and prioritize BIM clash detection results",
    category="bim",
    input_variables=["clash_data", "disciplines"],
    template="""Analyze and summarize these BIM clash detection results.
Clash Data:
$clash_data
Disciplines Involved: $disciplines
Provide:
1. Summary of clash counts by discipline pair
2. Priority ranking of clashes (critical/major/minor)
3. Recommended resolution responsibility
4. Pattern analysis (recurring issues)
5. Suggested coordination meetings
Focus on actionable insights for the coordination team.
""",
    output_format="""JSON:
{
  "total_clashes": 0,
  "by_discipline_pair": {...},
  "by_priority": {"critical": 0, "major": 0, "minor": 0},
  "patterns": [...],
  "recommendations": [...]
}"""
)

# Initialize library
library = ConstructionPromptLibrary()
# Get template
template = library.get("cost_line_item_classification")
# Format with variables
prompt = template.format(
    line_items="""
    1. 4000 PSI structural concrete
    2. #5 rebar
    3. CMU block wall
    4. Steel wide flange beams
    5. Spray foam insulation
    """
)
# Use with LLM
response = llm.generate(prompt)
# With few-shot examples
prompt_with_examples = template.with_examples(n=2)

# Create project-specific template
my_template = PromptTemplate(
    name="my_project_template",
    description="Custom template for specific project needs",
    category="custom",
    input_variables=["var1", "var2"],
    template="""
    Your custom prompt here with $var1 and $var2 placeholders.
    """,
    output_format="JSON or other format specification"
)
# Register to library
library.register(my_template)