app.py

import json
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from dotenv import load_dotenv
from google.adk.agents import Agent
from google.adk.sessions import InMemorySessionService
from google.adk.runners import Runner
from google.genai import types
import os
import re
from tools import (
    db_tool,
    tavily_tool,
    predictor_tool,
    mentor_tool,
    add_query_to_sheet
)
import warnings
warnings.filterwarnings("ignore")

# === LOAD ENV ===
load_dotenv()
HF_TOKEN = os.getenv("HUGGINGFACE_TOKEN")
GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")

# === PREPROCESSING DICTIONARY ===
INSTITUTE_MAPPING = {
    "iit": ["indian institute of technology"],
    "IIT": ["indian institute of technology"],
    "i.i.t": ["indian institute of technology"],
    "I.I.T": ["indian institute of technology"],
    "i i t": ["indian institute of technology"],
    "I I T": ["indian institute of technology"],
    "indian institute of technology": ["indian institute of technology"],
    "Indian Institute of Technology": ["indian institute of technology"],
    "nit": ["national institute of technology"],
    "NIT": ["national institute of technology"],
    "n.i.t": ["national institute of technology"],
    "N.I.T": ["national institute of technology"],
    "n i t": ["national institute of technology"],
    "N I T": ["national institute of technology"],
    "national institute of technology": ["national institute of technology"],
    "National Institute of Technology": ["national institute of technology"],
    "iiit": ["indian institute of information technology"],
    "IIIT": ["indian institute of information technology"],
    "i.i.i.t": ["indian institute of information technology"],
    "I.I.I.T": ["indian institute of information technology"],
    "i i i t": ["indian institute of information technology"],
    "I I I T": ["indian institute of information technology"],
    "indian institute of information technology": ["indian institute of information technology"],
    "Indian Institute of Information Technology": ["indian institute of information technology"],
    "bit": ["birla institute of technology"],
    "BIT": ["birla institute of technology"],
    "b.i.t": ["birla institute of technology"],
    "B.I.T": ["birla institute of technology"],
    "b i t": ["birla institute of technology"],
    "B I T": ["birla institute of technology"],
    "birla institute of technology": ["birla institute of technology"],
    "Birla Institute of Technology": ["birla institute of technology"],
    "bits": ["birla institute of technology and science"],
    "BITS": ["birla institute of technology and science"],
    "b.i.t.s": ["birla institute of technology and science"],
    "B.I.T.S": ["birla institute of technology and science"],
    "b i t s": ["birla institute of technology and science"],
    "B I T S": ["birla institute of technology and science"],
    "birla institute of technology and science": ["birla institute of technology and science"],
    "Birla Institute of Technology and Science": ["birla institute of technology and science"],
    "dtu": ["delhi technological university"],
    "DTU": ["delhi technological university"],
    "nsut": ["netaji subhas university of technology"],
    "NSUT": ["netaji subhas university of technology"],
    "iiitd": ["indraprastha institute of information technology delhi"],
    "IIITD": ["indraprastha institute of information technology delhi"],
    "iiith": ["international institute of information technology hyderabad"],
    "IIITH": ["international institute of information technology hyderabad"],
    "iiitb": ["international institute of information technology bangalore"],
    "IIITB": ["international institute of information technology bangalore"],
    "vit": ["vellore institute of technology"],
    "VIT": ["vellore institute of technology"],
    "srm": ["srm institute of science and technology"],
    "SRM": ["srm institute of science and technology"],
    "mit": ["manipal institute of technology"],
    "MIT": ["manipal institute of technology"],
    "pes": ["pes university"],
    "PES": ["pes university"],
    "bms": ["bms college of engineering"],
    "BMS": ["bms college of engineering"],
    "rv": ["rv college of engineering"],
    "RV": ["rv college of engineering"],
    "ramaiah": ["ms ramaiah institute of technology"],
    "RAMAIAH": ["ms ramaiah institute of technology"],
    "thapar": ["thapar institute of engineering and technology"],
    "THAPAR": ["thapar institute of engineering and technology"],
    "ism": ["indian school of mines"],
    "ISM": ["indian school of mines"],
    "spa": ["school of planning & architecture"],
    "SPA": ["school of planning & architecture"],
    "vnit": ["visvesvaraya national institute of technology"],
    "VNIT": ["visvesvaraya national institute of technology"],
    "manit": ["maulana azad national institute of technology"],
    "MANIT": ["maulana azad national institute of technology"],
    "svnit": ["sardar vallabhbhai national institute of technology"],
    "SVNIT": ["sardar vallabhbhai national institute of technology"],
    "mnit": ["malaviya national institute of technology"],
    "MNIT": ["malaviya national institute of technology"],
    "mnnit": ["motilal nehru national institute of technology"],
    "MNNIT": ["motilal nehru national institute of technology"],
    "sliet": ["sant longowal institute of engineering and technology"],
    "SLIET": ["sant longowal institute of engineering and technology"],
    "iiest": ["indian institute of engineering science and technology"],
    "IIEST": ["indian institute of engineering science and technology"],
    "cusat": ["cochin university of science and technology"],
    "CUSAT": ["cochin university of science and technology"],
    "niftem": ["national institute of food technology entrepreneurship and management"],
    "NIFTEM": ["national institute of food technology entrepreneurship and management"],
    "iiht": ["indian institute of handloom technology"],
    "IIHT": ["indian institute of handloom technology"],
    "ict": ["institute of chemical technology"],
    "ICT": ["institute of chemical technology"],
    "iitram": ["institute of infrastructure, technology, research and management"],
    "IITRAM": ["institute of infrastructure, technology, research and management"],
    "csvtu": ["chhattisgarh swami vivekanada technical university"],
    "CSVTU": ["chhattisgarh swami vivekanada technical university"],
    "gkc": ["ghani khan choudhary institute of engineering and technology"],
    "GKC": ["ghani khan choudhary institute of engineering and technology"],
    "nerist": ["north eastern regional institute of science and technology"],
    "NERIST": ["north eastern regional institute of science and technology"],
    "cit": ["central institute of technology"],
    "CIT": ["central institute of technology"],
    "tezu": ["tezpur university"],
    "TEZU": ["tezpur university"],
    "nehu": ["north-eastern hill university"],
    "NEHU": ["north-eastern hill university"],
    "mizoram": ["mizoram university"],
    "MIZORAM": ["mizoram university"],
    "assam": ["assam university"],
    "ASSAM": ["assam university"],
    "smvdu": ["shri mata vaishno devi university"],
    "SMVDU": ["shri mata vaishno devi university"],
    "pu": ["puducherry university"],
    "PU": ["puducherry university"],
    "ptu": ["puducherry technological university"],
    "PTU": ["puducherry technological university"],
    "jnu": ["jawaharlal nehru university"],
    "JNU": ["jawaharlal nehru university"],
    "uoh": ["university of hyderabad"],
    "UOH": ["university of hyderabad"],
    "ggu": ["guru ghasidas vishwavidyalaya"],
    "GGU": ["guru ghasidas vishwavidyalaya"],
    "cu": ["central university"],
    "CU": ["central university"],
    "gsv": ["gati shakti vishwavidyalaya"],
    "GSV": ["gati shakti vishwavidyalaya"],
    "gkv": ["gurukula kangri vishwavidyalaya"],
    "GKV": ["gurukula kangri vishwavidyalaya"]
}
BRANCH_MAPPING = {
    "cse": "computer science and engineering",
    "CSE": "computer science and engineering",
    "cs": "computer science and engineering",
    "CS": "computer science and engineering",
    "ece": "electronics and communication engineering",
    "ECE": "electronics and communication engineering",
    "ee": "electrical engineering",
    "EE": "electrical engineering",
    "MECH": "mechanical engineering",
    "mech": "mechanical engineering",
    "ce": "civil engineering",
    "CE": "civil engineering",
    "che": "chemical engineering",
    "CHE": "chemical engineering",
    # "it": "information technology",
    # "IT": "information technology",
    "aero": "aerospace engineering",
    "AERO": "aerospace engineering",
    "bio": "biotechnology",
    "BIO": "biotechnology"
}

# === PREPROCESSING FUNCTION ===
def preprocess_query(query: str) -> str:
    sorted_institutes = sorted(INSTITUTE_MAPPING.keys(), key=len, reverse=True)
    for key in sorted_institutes:
        pattern = rf'\b{re.escape(key)}\b'
        query = re.sub(pattern, INSTITUTE_MAPPING[key][0], query, flags=re.IGNORECASE)

    for key, full_name in BRANCH_MAPPING.items():
        pattern = rf'\b{re.escape(key)}\b'
        query = re.sub(pattern, full_name, query, flags=re.IGNORECASE)

    return query
# === AGENT SETUP ===
def create_agent_runner(user_id: str, session_id: str):
    instruction_text="""
You are a highly experienced college counselor specializing in helping high school students choose the right engineering colleges. You have access to several tools to help answer student queries.

AVAILABLE TOOLS:
1. db_tool - Search local college database  
2. tavily_tool - Search internet for college information  
3. predictor_tool - Predict colleges based on rank and preferences  
4. mentor_tool - Find mentors from specific colleges  

WORKFLOW:

Step 1: Classify the user's query into one of these categories:
a. "Know college based on my rank"  
b. "Know about a college"  
c. "Talk to a college student/mentor"  
d. "General query"  
e. "JOSAA or CSAB queries"  
f. "Unrelated query"

Step 2: Based on category, follow these steps:

For Category A (College predictions):
- Extract: userCrl (Common Rank List or category rank), userCategory, userGender, userHomeState  
- Optional: collegeName, branchName preferences  
- ALWAYS call the predictor_tool if userCrl is provided.  
- After Extracting the params from the query pass the params inside predictor_tool.
- Display the output in a clean table format showing predicted colleges, branches, cutoffs, etc.
- Add this at end of the response 'For detailed and better filters please visit https://www.precollege.in/college-predictor'

For Category B (College information):
- Extract college name  
- Call db_tool  
- If db_tool fails to return meaningful output(Answer according to query), fallback to tavily_tool to fetch data from the internet.  
- Present a brief, well-structured summary in natural language.

For Category C (Find mentors):
- Extract college name  
- Call mentor_tool  
- Provide the top 6 mentor details using mentor_tool(in name:link to mentor profile format) and include this at end of the respose 'For more mentor details: visit: https://precollege.in/mentors  

For Category D (General queries):
- Answer using db_tool  
- If db_tool doesn't provide enough, fallback to tavily_tool  
- Summarize the answer clearly and informatively.

For Category E (JOSAA or CSAB queries):
- Answer using tavily_tool using JOSAA and CSAB offical websites.(https://josaa.nic.in/, https://csab.nic.in/)
- Answer clearly and informatively in points.

For Category F (Unrelated query):
- If the query is unrelated to JoSAA counseling, colleges, branches, or mentoring:
- Respond: "Sorry, this is beyond my capabilities."

IMPORTANT RULES:
- ALWAYS use the tools specified above based on the workflow.  
- Never invent data. If something cannot be found, say so clearly.  
- Use clean formatting and polite tone.
- Do not skip steps or tools. Follow the workflow strictly.
"""

    agent = Agent(
        name="college_info_agent",
        model="gemini-1.5-flash",
        instruction=instruction_text,
        tools=[db_tool, tavily_tool, predictor_tool, mentor_tool],
        generate_content_config=types.GenerateContentConfig(
            max_output_tokens=1500,
            temperature=0.1,
        ),
    )
    session_svc = InMemorySessionService()
    session = session_svc.create_session(app_name="college_agent_app", user_id=user_id, session_id=session_id)
    runner = Runner(agent=agent, app_name="college_agent_app", session_service=session_svc)
    return runner, session
# === FASTAPI SETUP ===
app = FastAPI()

class ChatRequest(BaseModel):
    user_id: str
    session_id: str
    question: str

class ChatResponse(BaseModel):
    session_id: str
    answer: str
@app.post("/chat", response_model=ChatResponse)
async def chat_endpoint(req: ChatRequest):
    try:
        runner, session = create_agent_runner(req.user_id, req.session_id)
        processed_query = preprocess_query(req.question)
        # processed_query = req.question
        user_msg = types.Content(role="user", parts=[types.Part(text=processed_query)])
        reply_text = ""

        events = runner.run(user_id=req.user_id, session_id=session.id, new_message=user_msg)

        for ev in events:
            if ev.is_final_response():
                try:
                    for part in ev.content.parts:
                        if part.text:
                            reply_text = part.text
                            break
                except Exception:
                    try:
                        reply_text = ev.text
                    except Exception:
                        try:
                            reply_text = str(ev.message)
                        except Exception:
                            reply_text = "Sorry, I couldn't understand the response."
                break

        add_query_to_sheet(req.user_id, processed_query, reply_text)
        return ChatResponse(session_id=session.id, answer=reply_text)

    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
@app.get("/healthz")
def health_check():
    return {"status": "ok"}