Update app.py

app.py

@@ -1,4 +1,4 @@
-
+import gspread
 import os
 import json
 from dotenv import load_dotenv
@@ -14,25 +14,16 @@ from google.adk.runners import Runner
 from google.adk.tools import FunctionTool
 from google.genai import types
 from langchain_tavily import TavilySearch
-import gspread
 import uuid
 import datetime
 
 # === CONFIGURE ENV AND AUTH ===
 load_dotenv()
-hf_token = os.getenv("HUGGINGFACE_TOKEN")
-assert hf_token, "Please set HUGGINGFACE_TOKEN in your .env"
-login(token=hf_token)
-assert os.getenv("GOOGLE_API_KEY"), "Set GOOGLE_API_KEY in .env"
-assert os.getenv("TAVILY_API_KEY"), "Set TAVILY_API_KEY in .env"
-genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
-
-
 service_account_path = {
   "type": os.getenv("type"),
   "project_id": os.getenv("project_id"),
   "private_key_id": str(os.getenv("private_key_id")).replace('\\n', '\n'),
-  "private_key":  str(os.getenv("private_key")).replace('\\n', '\n'),
+  "private_key": str(os.getenv("private_key")).replace('\\n', '\n'),
   "client_email": os.getenv("client_email"),
   "client_id": os.getenv("client_id"),
   "auth_uri": os.getenv("auth_uri"),
@@ -41,17 +32,12 @@ service_account_path = {
   "client_x509_cert_url": os.getenv("client_x509_cert_url"),
   "universe_domain":os.getenv("universe_domain")
 }
-
-def add_query_to_sheet(user_id, query, response):
-    gc = gspread.service_account_from_dict(service_account_path)
-    sh = gc.open_by_key(SHEET_KEY)
-    worksheet = sh.worksheet("Sheet1")
-    
-     
-    timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-    worksheet.append_row([user_id, timestamp, query, response])
-
-
+hf_token = os.getenv("HUGGINGFACE_TOKEN")
+assert hf_token, "Please set HUGGINGFACE_TOKEN in your .env"
+login(token=hf_token)
+assert os.getenv("GOOGLE_API_KEY"), "Set GOOGLE_API_KEY in .env"
+assert os.getenv("TAVILY_API_KEY"), "Set TAVILY_API_KEY in .env"
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
 
 def flatten_json(obj: dict) -> str:
     pieces = []
@@ -63,6 +49,8 @@ def flatten_json(obj: dict) -> str:
     recurse("", obj)
     return "\n".join(pieces)
 
+
+
 # === LOAD AND INDEX LOCAL COLLEGE JSONS ===
 @st.cache_resource
 def load_vector_store(data_dir: str):
@@ -71,10 +59,12 @@ def load_vector_store(data_dir: str):
         if fname.lower().endswith('.json'):
             path = os.path.join(data_dir, fname)
             try:
-                with open(path, 'r', encoding='utf-8') as f: data = json.load(f)
+                with open(path, 'r', encoding='utf-8') as f:
+                    data = f.read()
             except UnicodeDecodeError:
-                with open(path, 'r', encoding='latin-1') as f: data = json.load(f)
-            texts.append(flatten_json(data))
+                with open(path, 'r', encoding='latin-1') as f:
+                    data = f.read()
+            texts.append(data)
     # st.info(f"Loaded {len(texts)} documents.")
 
     st_model = SentenceTransformer('all-MiniLM-L6-v2')
@@ -84,8 +74,22 @@ def load_vector_store(data_dir: str):
 
     return FAISS.from_texts(texts, LocalEmbeddings())
 
-vector_store = load_vector_store('Jsons-Colleges/Jsons')
+vector_store = load_vector_store("Jsons-Colleges/Jsons")
+ 
+
+SHEET_KEY = os.getenv("SHEET_KEY")
 
+def add_query_to_sheet(user_id, query, response):
+    gc = gspread.service_account_from_dict(service_account_path)
+    sh = gc.open_by_key(SHEET_KEY)
+    worksheet = sh.worksheet("Sheet1")
+    
+     
+    timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    worksheet.append_row([user_id, timestamp, query, response])
+
+
+    
 # === TOOLS ===
 def db_search(query: str) -> dict:
     docs = vector_store.similarity_search(query, k=6)
@@ -107,7 +111,7 @@ tavily_tool = FunctionTool(tavily_search)
 
 # === AGENT SETUP ===
 @st.cache_resource
-def create_agent():
+def create_agent(user_id, session_id):
     agent = Agent(
         name="college_info_agent",
         model="gemini-2.0-flash",
@@ -118,7 +122,8 @@ You are a highly experienced college counselor, specializing in helping high sch
     2. If `db_search` returns an empty `results` list, immediately call `tavily_search`.\n
     3. Do not produce any output until one of those calls returns data.\n
     4. As soon as you have non‑empty results, stop further searches and craft your answer using only that source.\n
-    5. When suggesting a list of colleges based on student's rank, always consider the following:
+    5. If a user asks about a college, use the available source to provide the most detailed response possible, preferably structured in bullet points for clarity.
+    6. If a user enters a rank and asks a list of colleges based on their's rank, always consider the following:
         a. Rank of the student (mandatory)
         b. Category (if not provided, assume General)
         c. State (optional)
@@ -126,16 +131,17 @@ You are a highly experienced college counselor, specializing in helping high sch
     
         Note: In your final response, only include colleges where the student is eligible based on their rank. Do not list colleges where the cutoff rank is lower than the student's rank. Ask them to check out Precollege Predictor for more personalized answers, the link of college predictor https://www.precollege.in/college-predictor
         
-    6. Rank Eligibility Rule: A student is eligible for a college if their rank is less than or equal to the college’s closing cutoff. (e.g., Rank 2000 is eligible if the cutoff is 2500.)
+    7. Rank Eligibility Rule: A student is eligible for a college if their rank is less than or equal to the college’s closing cutoff. (e.g., Rank 2000 is eligible if the cutoff is 2500.)
     
-    7. If the user wants to compare colleges, present the comparison in a table format for clarity (Mention the opening and closing ranks for the General category.).
+    8. If the user wants to compare colleges, present the comparison in a table format for clarity (Mention the opening and closing ranks for the General category.).
+
+    9. Ensure that your response is always complete and fully addresses the user's question, without leaving any sentence or thought unfinished.
     
-    8. If you cannot find sufficient or specific information, politely direct the student to connect with a verified mentor at: https://precollege.in
+    10. If you cannot find sufficient or specific information, politely direct the student to connect with a verified mentor at: https://precollege.in
     
-    9. If the user asks a question unrelated to college counseling, respond with:
+    11. If the user asks a question unrelated to college counseling, respond with:
     "Sorry, this is beyond the scope of this application"
 """
-
         ),
         tools=[db_tool, tavily_tool],
         generate_content_config=types.GenerateContentConfig(
@@ -144,11 +150,11 @@ You are a highly experienced college counselor, specializing in helping high sch
         )
     )
     session_svc = InMemorySessionService()
-    session = session_svc.create_session(app_name="college_agent_app", user_id="user1", session_id="session1")
+    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
 
-runner, session = create_agent()
+
 
 # === STREAMLIT UI ===
 st.title("🎓 Jossa-ChatBot")
@@ -185,5 +191,4 @@ if query:
         reply="Please provide complete context."
     st.session_state.history.append(("assistant", reply))
     add_query_to_sheet(user_id=user_id, query=query, response=reply)
-    st.rerun()  
-
+    st.rerun()