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agent.py

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+# chatbot/agent.py
+
+import os
+import google.generativeai as genai
+from dotenv import load_dotenv
+
+# Load environment variables from .env
+load_dotenv()
+
+# Configure Gemini API
+genai.configure(api_key=os.getenv("AGENT_API_KEY"))
+
+# Initialize Gemini model
+model = genai.GenerativeModel("models/gemini-1.5-flash-latest")
+
+def generate_response(conversation):
+    """
+    Generate a response from Gemini.
+    conversation: list of (role, message) tuples.
+    Only 'user' role is supported.
+    """
+    # Convert conversation to Gemini-compatible format
+    messages = [{"role": "user", "parts": msg} for role, msg in conversation if role == "user"]
+
+    # Call Gemini directly (no system/model roles, no start_chat)
+    response = model.generate_content(messages)
+
+    return response.text.strip()

app.py

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+# app.py
+
+import streamlit as st
+from ui.chat_ui import render_chat_interface   # <── fixed import
+
+def main():
+    """
+    Entry point for TalentScout Hiring Assistant.
+    """
+    render_chat_interface()
+
+if __name__ == "__main__":
+    main()

chat_ui.py

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+# ui/chat_ui.py
+
+import os
+import json
+import streamlit as st
+from chatbot.agent import generate_response
+from prompts.base_prompts import (
+    greeting_prompt,
+    info_collection_prompt,
+    tech_stack_prompt,
+    dynamic_generation_prompt,
+    exit_keywords,
+    exit_message,
+)
+
+# Save candidate info to JSON
+def save_candidate_data(candidate):
+    os.makedirs("data", exist_ok=True)
+    file_path = os.path.join("data", "candidates.json")
+
+    try:
+        with open(file_path, "r") as f:
+            data = json.load(f)
+    except:
+        data = []
+
+    data.append(candidate)
+
+    with open(file_path, "w") as f:
+        json.dump(data, f, indent=2)
+
+
+def render_chat_interface():
+    st.set_page_config(page_title="TalentScout Hiring Assistant", layout="centered")
+
+    st.markdown(
+        "<h2 style='text-align: center;'>🤖 TalentScout Hiring Assistant</h2>",
+        unsafe_allow_html=True,
+    )
+
+    # Initialize states
+    if "conversation" not in st.session_state:
+        st.session_state.conversation = []
+    if "ended" not in st.session_state:
+        st.session_state.ended = False
+    if "started" not in st.session_state:
+        st.session_state.started = False
+    if "user_info" not in st.session_state:
+        st.session_state.user_info = {}
+    if "tech_stack_collected" not in st.session_state:
+        st.session_state.tech_stack_collected = False
+
+    # Greeting
+    if not st.session_state.started:
+        st.markdown(
+            f"<div class='chat-bubble bot'><strong>Assistant:</strong><br>{greeting_prompt}</div>",
+            unsafe_allow_html=True,
+        )
+        if st.button("Begin"):
+            st.session_state.started = True
+            st.rerun()
+        return
+
+    # Collect user info
+    if not st.session_state.user_info:
+        st.markdown(info_collection_prompt, unsafe_allow_html=True)
+
+        with st.form("candidate_info"):
+            full_name = st.text_input("Full Name")
+            email = st.text_input("Email Address")
+            phone = st.text_input("Phone Number")
+            years_exp = st.text_input("Years of Experience")
+            location = st.text_input("Current Location")
+            desired_pos = st.text_input("Desired Position")
+            submitted = st.form_submit_button("Save & Continue")
+
+            if submitted:
+                st.session_state.user_info = {
+                    "Full Name": full_name,
+                    "Email": email,
+                    "Phone": phone,
+                    "Experience": years_exp,
+                    "Location": location,
+                    "Desired Position": desired_pos,
+                }
+                save_candidate_data(st.session_state.user_info)
+                st.rerun()
+        return
+
+    # Collect tech stack
+    if not st.session_state.tech_stack_collected:
+        st.markdown(tech_stack_prompt, unsafe_allow_html=True)
+        tech_stack = st.text_input("Tech Stack (comma separated)")
+
+        if st.button("Submit Tech Stack"):
+            st.session_state.user_info["Tech Stack"] = tech_stack
+            st.session_state.tech_stack_collected = True
+
+            bot_msg = (
+                f"Thanks, {st.session_state.user_info['Full Name']}! "
+                f"Based on your tech stack, here are some questions:"
+            )
+            st.session_state.conversation.append(("bot", bot_msg))
+
+            # ✅ Fixed: no system role, just user prompt
+            prompt = dynamic_generation_prompt(tech_stack)
+            questions = generate_response([("user", prompt)])
+
+            st.session_state.conversation.append(("bot", questions))
+            st.rerun()
+        return
+
+    # Main conversation loop
+    if not st.session_state.ended:
+        for role, msg in st.session_state.conversation:
+            role_class = "bot" if role == "bot" else "user"
+            label = "Assistant" if role == "bot" else "You"
+            st.markdown(
+                f"<div class='chat-bubble {role_class}'><strong>{label}:</strong><br>{msg}</div>",
+                unsafe_allow_html=True,
+            )
+
+        with st.form("chat_form", clear_on_submit=True):
+            user_input = st.text_input("Your reply", placeholder="Type here...")
+            send = st.form_submit_button("Send")
+
+            if send and user_input.strip():
+                st.session_state.conversation.append(("user", user_input.strip()))
+
+                if any(exit_word in user_input.lower() for exit_word in exit_keywords):
+                    st.session_state.conversation.append(("bot", exit_message))
+                    st.session_state.ended = True
+                else:
+                    bot_reply = generate_response([("user", user_input.strip())])
+                    st.session_state.conversation.append(("bot", bot_reply))
+
+                st.rerun()
+    else:
+        st.success("✅ Session ended. Refresh the page to start again.")

gibberish.py

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+# utils/gibberish.py
+
+def is_gibberish(text: str) -> bool:
+    """
+    Detects whether a candidate's input text is likely to be gibberish.
+    A simple heuristic: if less than 50% of characters are alphabetic.
+    """
+    if not text:
+        return True
+    letters = sum(c.isalpha() for c in text)
+    ratio = letters / max(len(text), 1)
+    return ratio < 0.5

info_extract.py

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+# utils/info_extract.py
+
+def extract_user_info(text: str):
+    """
+    Extract candidate details if provided in a single text input string.
+    Example input: "Full Name: John Doe, Email Address: john@example.com"
+    Returns a dictionary with expected fields.
+    """
+    fields = [
+        "Full Name",
+        "Email Address",
+        "Phone Number",
+        "Years of Experience",
+        "Desired Position"
+    ]
+
+    info = {field: "" for field in fields}
+    parts = text.split(",")
+
+    for part in parts:
+        if ":" in part:
+            key, val = part.split(":", 1)
+            key = key.strip()
+            val = val.strip()
+            for field in fields:
+                if field.lower() == key.lower():
+                    info[field] = val
+                    break
+    return info