Sulaiman8/Credit-Card-Recommender-Knowledge-graph-implementation

1import google.generativeai as genai2import pandas as pd3import os4import json5from data import df_all_cards6 7#handling intent classification for retrieval8def handle_query_classification(user_query):9    genai.configure(api_key=os.environ.get("api_key_1"))  10    model1 = genai.GenerativeModel('gemini-2.0-flash')11    prompt = f"""12        You are a smart financial assistant.13        14        ### User's Query:15        {user_query}16        17        ### Task:18        Classify the user's intent into one of the following categories:19        1. "retrieve" → If the user is asking for card suggestions, recommendations, or showing cards (e.g., "suggest a card", "need a travel card") OR if they mention their lifestyle, income, spending, or needs (e.g., travel, shopping, fuel, rewards, luxury).20        2. "specific" → If the user is asking about a particular credit card by name (even if the word "card" is not used). Examples: "Tell me about HDFC Regalia", "Is SBI Elite good?".21        3. "no_retrieval" → ONLY if the query is generic (e.g., “What is credit score?”), casual chit-chat (e.g., “Hi”), or doesn’t mention any lifestyle, financial needs, or specific card names.22 23        24        Respond ONLY in the following JSON format:25        If intent is "no_retrieval", you MUST include a helpful 'response' field.26        If intent is "retrieve" or "specific", do NOT include any response or explanation.27        28        Respond in this exact format:29        {{30          "intent": "retrieve" | "specific" | "no_retrieval",31          "response": "Only include this if intent is 'no_retrieval'"32        }}33        34        """35 36    raw_response = model1.generate_content(prompt).text.strip()37 38    # Clean any markdown formatting if present39    if raw_response.startswith("```"):40        raw_response = raw_response.strip("`").strip()41        if raw_response.startswith("json"):42            raw_response = raw_response[len("json"):].strip()43 44    try:45        parsed = json.loads(raw_response)46        return parsed47    except Exception as e:48        print("JSON parsing error:", e)49        print("Raw response from LLM:", raw_response)50        raise51# result = handle_query_classification("Want to optimize my spending – travel often, premium hotels, and online shopping.")52# if result["intent"] == "no_retrieval":53#     print(result['response'])54 55#passing the card mentioned in the user query56def find_matching_card(user_query):57    lowered_query = user_query.lower()58    for _, row in df_all_cards.iterrows():59        if row["name"].lower() in lowered_query:60            return row.to_dict()61    return None62 63 64#for queries enquiring about a card65def generate_card_response_with_context(user_query, card_info):66    genai.configure(api_key=os.environ.get("api_key_1"))  67    model1 = genai.GenerativeModel('gemini-2.0-flash')68    prompt = f"""69You are a helpful financial assistant. A user has asked about a specific credit card.70 71Card Name: {card_info.get('name')}72Description: {card_info.get('description')}73 74User's Question: {user_query}75 76Please provide a concise, relevant answer using the above card context.77"""78    response = model1.generate_content(prompt)79    return response.text.strip()80 81