cleanup

src/router.py

@@ -1,140 +1,3 @@
-# """
-# Stage 1: Query Router - Intelligent Server Selection
-# """
-
-# import json
-# from typing import Dict, Any
-# from openai import OpenAI
-
-
-# class QueryRouter:
-#     """Stage 1: Routes queries to appropriate MCP servers"""
-
-#     def __init__(self, client: OpenAI, registry: Dict[str, Any]):
-#         self.client = client
-#         self.registry = registry
-
-#     def route(self, query: str, location: Dict[str, Any]) -> Dict[str, Any]:
-#         """
-#         Analyze query and determine which MCP servers are needed
-        
-#         Returns:
-#             {
-#                 "intent": str,
-#                 "required_servers": List[str],
-#                 "reasoning": str
-#             }
-#         """
-#         # Create registry summary
-#         registry_text = "Available MCP Servers:\n"
-#         for server_id, info in self.registry.items():
-#             registry_text += f"\n{server_id}:\n"
-#             registry_text += f"  Description: {info['description']}\n"
-#             registry_text += f"  Use for: {', '.join(info['use_for'][:5])}\n"
-
-#         system_prompt = f"""You are a query router for Farmer.chat agricultural system.
-
-# Your task: Analyze the farmer's query and select which MCP servers are needed.
-
-# {registry_text}
-
-# Location: {location['name']} ({location['lat']}°N, {location['lon']}°E)
-
-# CRITICAL RULES:
-# 1. Select ALL servers that provide data relevant to answering the query completely
-# 2. Consider IMPLICIT needs - look for context clues in the query
-# 3. Keywords that trigger elevation: "elevation", "slope", "terrain", "my land", "my field", "drainage", "waterlogged", "frost risk", "wind exposure"
-# 4. For crop decisions: ALWAYS include soil_properties + water + weather (comprehensive assessment)
-# 5. For weather risk questions (wind, frost, flood): Include weather + elevation (terrain affects risk)
-# 6. For pest questions with weather context: Include pests + weather
-# 7. Be generous - better to have extra data than miss critical information
-# 8. When farmer mentions location characteristics (height, slope, elevation), ALWAYS include elevation
-
-# FEW-SHOT EXAMPLES:
-
-# Example 1:
-# Query: "Are strong winds expected at my land elevation?"
-# Required: ["weather", "elevation"]
-# Reasoning: Wind forecast from weather, but elevation affects wind exposure and risk. Farmer explicitly mentions elevation.
-
-# Example 2:
-# Query: "Should I plant rice today?"
-# Required: ["weather", "soil_properties", "water"]
-# Reasoning: Planting decisions need weather conditions, soil suitability, and water availability for comprehensive assessment.
-
-# Example 3:
-# Query: "Is there risk of frost tonight?"
-# Required: ["weather", "elevation"]
-# Reasoning: Frost risk depends on temperature from weather AND elevation (cold air sinks to lower areas).
-
-# Example 4:
-# Query: "What's my soil composition?"
-# Required: ["soil_properties"]
-# Reasoning: Direct soil query, only soil data needed. No implicit needs.
-
-# Example 5:
-# Query: "Can I grow tomatoes here?"
-# Required: ["soil_properties", "water", "weather"]
-# Reasoning: Crop suitability requires soil type, water availability, and climate conditions.
-
-# Example 6:
-# Query: "My field gets waterlogged after rain"
-# Required: ["elevation", "soil_properties", "weather"]
-# Reasoning: Waterlogging relates to drainage (elevation/slope), soil permeability, and rainfall patterns.
-
-# Example 7:
-# Query: "Should I spray pesticides now?"
-# Required: ["pests", "weather"]
-# Reasoning: Need to know pest presence AND weather conditions for optimal application timing.
-
-# Example 8:
-# Query: "How's the weather?"
-# Required: ["weather"]
-# Reasoning: Direct weather query, no implicit needs.
-
-# Example 9:
-# Query: "Give me complete farm status"
-# Required: ["weather", "soil_properties", "water", "elevation", "pests"]
-# Reasoning: Comprehensive assessment requires all available data sources.
-
-# Example 10:
-# Query: "Will it be too windy on my elevated farm?"
-# Required: ["weather", "elevation"]
-# Reasoning: Wind from weather, elevation affects exposure. "Elevated" is explicit context clue.
-
-# Response format (JSON only):
-# {{
-#   "intent": "brief description of farmer's need",
-#   "required_servers": ["server_id1", "server_id2"],
-#   "reasoning": "why these servers"
-# }}
-# """
-
-#         try:
-#             response = self.client.chat.completions.create(
-#                 model="gpt-4o",
-#                 messages=[
-#                     {"role": "system", "content": system_prompt},
-#                     {"role": "user", "content": query}
-#                 ],
-#                 temperature=0.3
-#             )
-
-#             result_text = response.choices[0].message.content.strip()
-#             result_text = result_text.replace("```json", "").replace("```", "").strip()
-
-#             routing_decision = json.loads(result_text)
-#             return routing_decision
-
-#         except Exception as e:
-#             print(f"❌ Routing error: {e}")
-#             # Fallback - include common servers
-#             return {
-#                 "intent": "general_inquiry",
-#                 "required_servers": ["weather", "soil_properties", "water"],
-#                 "reasoning": "Fallback routing due to error"
-#             }
-
 """
 Query Router - Stage 1
 Simple router that always queries all MCP servers for alert generation.