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request_router.py
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from langchain.prompts import PromptTemplate
from langchain_core.output_parsers import JsonOutputParser
#####################################################################
# Implement the Router
def get_question_route(llm, question):
prompt = PromptTemplate(
template="""<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are an expert at routing a
user question to WEN-KEN database or NPDES regulations or Data Commons or US Energy Atlas.
Use the WEN-KEN database for questions on the following entities:
1. Locations: Information on buildings, power stations, and underground storage tanks in Ohio.
2. Counties: Geometric representations of counties across the USA.
3. States: Geometric representations outlining the boundaries of states in the USA.
4. Earthquakes: Data pertaining to seismic events.
5. Rivers: Comprehensive geometries about rivers in USA.
6. Dams: Information regarding dams' locations in USA.
7. Drought Zones: Identification of drought-affected zones in the years 2020, 2021, and 2022 in USA.
8. Hospitals: Details about hospital locations and information in USA.
9. Stream Gages: Information of gages' locations and names in USA.
10. Power Plants: Information about power plants in Ohio.
You do not need to be stringent with the keywords in the question related to these topics.
Use NPDES regulation for questions related to permits or permit applications of discharges pollutants into
navigable waters, which include rivers, lakes, streams, coastal areas, and other bodies of water. Point
sources are discrete conveyances such as pipes, ditches, or channels. Under the NPDES program, permits are
issued to regulate the quantity, quality, and timing of the pollutants discharged into water bodies. These
permits include limits on the types and amounts of pollutants that can be discharged, monitoring and
reporting requirements, and other conditions to ensure compliance with water quality standards and protect
the environment and public health.
Use Data Commons for questions related to the following data for counties or states or countries.
Area_FloodEvent
Count_Person (for population)
Count_FireEvent
Count_FlashFloodEvent
Count_FloodEvent
Count_HailEvent
Count_HeatTemperatureEvent
Count_HeatWaveEvent
Count_HeavyRainEvent
Count_Person_Employed
Median_Income_Person
CountOfClaims_NaturalHazardInsurance_BuildingStructureAndContents_FloodEvent
Max_Rainfall
Max_Snowfall
SettlementAmount_NaturalHazardInsurance_BuildingContents_FloodEvent
SettlementAmount_NaturalHazardInsurance_BuildingStructureAndContents_FloodEvent
SettlementAmount_NaturalHazardInsurance_BuildingStructure_FloodEvent
FemaSocialVulnerability_NaturalHazardImpact
For example, to find the populations of all counties where Muskingum River flows through, we need to find
the populations for the counties satisfying some conditions. In this case, this request uses "Data Commons".
Use US Energy Atlas for requests related to the following data:
Battery Storage Plant
Coal Mine
Coal Power Plant
Geothermal Power Plant
Wind Power Plant
Renewable Diesel Fuel and Other Biofuel Plant
Wind Power Plant
Hydro Pumped Storage Power Plant
Natural Gas Power Plant
Nuclear Power Plant
Petroleum Power Plant
Solar Power Plant
Biodiesel Plant
Watershed
Basin
Use "WEN-KEN database use Energy Atlas" for the requests to find entities from WEN-KEN database but with
somes join condition for the entities from WEN-KEN database and Energy Atlas.
Note that use ""WEN-KEN database" for power stations and use "US Energy Atlas" for power plants.
Use "Aggregation" for questions related to aggregation requests, which compute summaries over grouped entities.
An aggregation request may involve 5 core components:
1) Grouping Objects: Entities to partition data by (e.g., counties, basins).
2) Summarizing Objects: Entities to aggregate (e.g., rivers, dams).
3) Association Conditions: Relationships between grouping and summarizing objects (e.g., spatial containment, spatail intersection).
4) Aggregation Function: Operations like COUNT, SUM, MAX, AVG, or ARGMAX (for object-centric results).
5) Pre-/Post-Conditions: Filters applied before/after aggregation (e.g., counties in Ohio State, result thresholds).
Please note that an aggregation request must use an aggregation function. It is not an aggregation request if no aggregation function is used.
For example, "find all counties Scioto River flows through" is not an aggregation request because it doesn't use any aggregation function.
[ Example 1 ]
Return 'WEN-KEN database' for following request: Find all neighboring states of Ohio State.
[ Example 2 ]
Return "WEN-KEN database use Energy Atlas" for the following request:
Find counties downstream of the coal mine with the name "Century Mine" on the Ohio River.
Because this request tries to find some counties (in WEN-KEN database) but with some conditions related to
Ohio River (in WEN-KEN database) and the coal mine with the name "Century Mine" in Energy Atlas.
[ Example 3 ]
Return "Energy Atlas" for the following request:
Find all coal mines along Ohio River
Because this request tries to find coal mines (in Energy Atlas rather than in WEN-KEN database)
[ Example 4 ]
Return "Energy Atlas" for the following request:
Find all coal mines in all counties the Scioto River flows through.
Because this request tries to find coal mines which is contained in Energy Atlas.
[ Example 5 ]
Return "Data Commons" for the following request:
Find the social vulnerability for all counties downstream of the coal mine with the name "Century Mine" along Ohio River
Because this request tries to find the social vulnerability of some counties which is contained in Data Commons.
Use "Other" for questions related to common knowledge.
[ Example 6 ]
Return "Other" for the following request:
Please help search Kentucky Public Service Commission's website to find out how many power plants are in Kentucky
Give a choice 'WEN-KEN database' or 'NPDES regulations' or 'Data Commons' or 'US Energy Atlas' or
'WEN-KEN database use Energy Atlas' or 'Other' based on the question. Return a JSON with a single key
'request_type' and a key 'explanation' for reasons.
[ Example 7 ]
Return the following JSON string for the request "Could you please give me some example questions?":
{{
"request_type" : "Other",
"explanation" : "Not in the scope of 'WEN-KEN database' or 'NPDES regulations' or 'Data Commons' or 'US Energy Atlas' or 'WEN-KEN database use Energy Atlas'"
}}
[ Example 8 ]
Return 'WEN-KEN database' for following request:
Find all dams located upstream of the power station dpjc6wtthc32 along the Muskingum river.
Because this request tried to find dams which are contained in the WEN-KEN database.
[ Example 9 ]
Return 'WEN-KEN database' for following request:
Find the Ohio State
Because this request tries to find a state which is contained in the WEN-KEN database.
[ Example 10 ]
Return "WEN-KEN database use Energy Atlas" for the following request:
Find all rivers that flow through the Roanoke basin.
Because this request tries to find some rivers (in WEN-KEN database) but with some conditions related to the Roanoke basin in Energy Atlas.
[ Example 11 ]
Return "Energy Atlas" for the following request:
Find all basins through which the Scioto River flows.
Because this request tried to find some basins which are contained in Energy Atlas.
[ Example 12 ]
Return "Energy Atlas" for the following request:
Find all basins that intersect with Ohio River.
Because this request tried to find some basins which are contained in Energy Atlas.
[ Example 13]
Return "Aggregation" for the following requests:
Find the number of rivers flow through each county in Ohio.
Find the number of dams in each county in Ohio.
Find the total number of coal mines in each basin.
Find the total power generation capacity of gas power plants in each county in Ohio.
Find the longest river in county of Ohio.
Find the county with the the highest number of hospitals in Ohio .
Find all counties with more than 5 hospitals in Ohio .
Find all states where the total coal mine output exceeds 1 million tons.
Find the river in Ohio that has the highest number of dams.
Find the watershed that has the highest total coal mine.
Question to route: {question}
<|eot_id|><|start_header_id|>assistant<|end_header_id|>
""",
input_variables=["question"],
)
question_router = prompt | llm | JsonOutputParser()
result = question_router.invoke({"question": question})
return result