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appagents/research_agent.py

@@ -18,6 +18,7 @@ class MarketResearchAgent:
             TimeTools.current_datetime,
             GoogleTools.search,
             FinanceTools.get_summary,
+            FinanceTools.get_market_sentiment,
             FinanceTools.get_history,
             # NewsTools.top_headlines,
             # NewsTools.search_news,
@@ -33,8 +34,10 @@ class MarketResearchAgent:
             3. **Synthesis:** When multiple tools provide information, synthesize and summarize results into a coherent, easy-to-understand response.
             4. **Source Transparency:** Always cite your information sources clearly, preferably with links or named publications.
             5. **Clarity and Brevity:** Use plain, professional language. Avoid speculation, filler text, or unnecessary verbosity.
+            6. **Simplification:** Break down complex topics into simpler terms that a general audience can understand.
+            7. **Verification:**: Verify an answer, explicitly state that the data could not be confirmed or is unavailable
 
-            If you cannot verify an answer, explicitly state that the data could not be confirmed or is unavailable.
+            Strictly avoid fabricating information.
         """
 
 

prompts/trade_recommendation.txt

@@ -1,2 +1,4 @@
 Recommend 3 option spreades which has more than 80% likelihood of profiting me. 
-You must do a thorough analysis of the stock 3 months trend and study the market sentiment to conclude into the answer.
+You must do a **thorough analysis** of the stocks 3 months trend and study the market sentiment to conclude into the answer.
+Explain each spread legs with the strike price, exact expiry date and premium entry.
+Provide a rational of your recommendation and likelyhood of winning it in %.

tools/google_tools.py

@@ -1,6 +1,5 @@
 import os
 import requests
-import yfinance as yf
 from dotenv import load_dotenv
 from agents import function_tool
 from core.logger import log_call
@@ -13,21 +12,55 @@ load_dotenv()
 # 🔹 GOOGLE SEARCH TOOLSET (Serper.dev API)
 # ============================================================
 class GoogleTools:
-    """Provides tools for web search using Serper.dev (Google Search API)."""
+    """
+    GoogleTools provides function tools to perform web searches
+    using the Serper.dev API (Google Search). I am a fallback for
+    retrieving recent information from the web.
+
+    Features:
+    - Search for recent web pages.
+    - Limit number of results.
+    - Returns formatted title, link, date, and snippet for each result.
+    """
 
     @staticmethod
     @function_tool
     @log_call
     def search(query: str, num_results: int = 3) -> str:
         """
-        Perform a general Google search using the Serper.dev API.
+        Perform a general Google search using Serper.dev API.
 
-        Args:
-            query (str): The search query string.
-            num_results (int): Number of results to return.
+        Parameters:
+        -----------
+        query : str
+            The search query string, e.g., "latest Tesla stock news".
+        num_results : int, optional (default=3)
+            Maximum number of search results to return.
 
         Returns:
-            str: Formatted search results.
+        --------
+        str
+            Formatted string of top search results, each including:
+            - Title of the page
+            - URL link
+            - Published date
+            - Snippet / description
+            If no results are found or API key is missing, returns an error message.
+
+        Example:
+        --------
+        search("AI in finance", num_results=2)
+
+        Output:
+        Title: How AI is Transforming Finance
+        Link: https://example.com/ai-finance
+        Published: 2024-06-15
+        Snippet: AI is increasingly used for trading, risk management...
+        
+        Title: AI Applications in Banking
+        Link: https://example.com/ai-banking
+        Published: 2024-06-10
+        Snippet: Banks are leveraging AI for customer service, fraud detection...
         """
         try:
             api_key = os.getenv("SERPER_API_KEY")
@@ -36,13 +69,13 @@ class GoogleTools:
 
             url = "https://google.serper.dev/search"
             headers = {"X-API-KEY": api_key, "Content-Type": "application/json"}
-            payload = {"q": query, "num": num_results, "tbs": "qdr:d"}
+            payload = {"q": query, "num": num_results, "tbs": "qdr:d"}  # results from last 24h
 
             response = requests.post(url, headers=headers, json=payload)
             response.raise_for_status()
             data = response.json()
 
-            if "organic" not in data:
+            if "organic" not in data or not data["organic"]:
                 return "No results found."
 
             formatted_results = [
@@ -53,26 +86,60 @@ class GoogleTools:
             ]
             return "\n".join(formatted_results)
 
+        except requests.exceptions.RequestException as e:
+            return f"Network error during Google search: {e}"
         except Exception as e:
             return f"Error performing Google search: {e}"
 
 
-# # ============================================================
-# # 🔹 OPENAI & OTHER MODEL APIs (optional future grouping)
-# # ============================================================
-# class ModelTools:
-#     """Provides access to LLM APIs like OpenAI, Gemini, or Groq."""
-
-#     @staticmethod
-#     @function_tool
-#     def query_openai(prompt: str, model: str = "gpt-4o-mini") -> str:
-#         """Query OpenAI model."""
-#         try:
-#             client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
-#             response = client.chat.completions.create(
-#                 model=model,
-#                 messages=[{"role": "user", "content": prompt}],
-#             )
-#             return response.choices[0].message.content
-#         except Exception as e:
-#             return f"Error querying OpenAI API: {e}"
+# ============================================================
+# 🔹 OPENAI & OTHER MODEL TOOLS
+# ============================================================
+class ModelTools:
+    """
+    ModelTools provides function tools to interact with LLM APIs
+    such as OpenAI, Gemini, or Groq. 
+
+    Features:
+    - Send prompts to a language model.
+    - Receive structured text completions.
+    - Can be extended to support multiple LLM providers.
+    """
+
+    @staticmethod
+    @function_tool
+    def query_openai(prompt: str, model: str = "gpt-4o-mini") -> str:
+        """
+        Query an OpenAI language model with a prompt.
+
+        Parameters:
+        -----------
+        prompt : str
+            User-provided prompt for the model.
+        model : str, optional (default="gpt-4o-mini")
+            Model name to query (e.g., "gpt-4o-mini", "gpt-4").
+
+        Returns:
+        --------
+        str
+            Model's response content as text.
+            If an error occurs (network/API), returns an error message.
+
+        Example:
+        --------
+        query_openai("Explain AI in finance")
+
+        Output:
+        "AI in finance refers to the use of machine learning and natural language
+        processing techniques to automate trading, risk assessment, and customer service..."
+        """
+        try:
+            from openai import OpenAI  # delayed import
+            client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+            response = client.chat.completions.create(
+                model=model,
+                messages=[{"role": "user", "content": prompt}],
+            )
+            return response.choices[0].message.content
+        except Exception as e:
+            return f"Error querying OpenAI API: {e}"

tools/news_tools.py

@@ -13,31 +13,83 @@ load_dotenv()
 # 🔹 NEWS TOOLSET (NewsAPI.org)
 # ============================================================
 class NewsTools:
-    """Provides tools to fetch top headlines and topic-based news."""
+    """
+    NewsTools provides function tools to fetch recent news headlines or
+    topic-specific articles from NewsAPI.org. Always returns recent data.
+    """
 
     @staticmethod
     @function_tool
     @log_call
     def top_headlines(country: str = "us", num_results: int = 5) -> str:
-        """Fetch top headlines for a given country."""
+        """
+        Fetch the latest top headlines for a country.
+
+        Parameters:
+        -----------
+        country : str, optional (default="us")
+            Two-letter country code.
+        num_results : int, optional (default=5)
+            Number of articles to fetch.
+
+        Returns:
+        --------
+        str
+            Formatted headlines with title, source, and URL.
+        """
         return NewsTools._fetch_news(query="", country=country, num_results=num_results)
 
     @staticmethod
     @function_tool
     @log_call
     def search_news(query: str, num_results: int = 5) -> str:
-        """Search for recent news articles about a specific topic."""
+        """
+        Search for recent news articles about a specific topic.
+
+        Parameters:
+        -----------
+        query : str
+            Keyword or topic to search (e.g., "Tesla earnings").
+        num_results : int, optional (default=5)
+            Number of articles to fetch.
+
+        Returns:
+        --------
+        str
+            Formatted news articles with title, source, and URL.
+        """
         return NewsTools._fetch_news(query=query, country="", num_results=num_results)
 
     @staticmethod
     @log_call
     def _fetch_news(query: str, country: str, num_results: int) -> str:
-        """Internal helper for NewsAPI.org."""
+        """
+        Internal helper to fetch news from NewsAPI.org.
+
+        Ensures always recent news (last 7 days).
+
+        Parameters:
+        -----------
+        query : str
+            Search query (leave empty for top headlines).
+        country : str
+            Two-letter country code (ignored if query provided).
+        num_results : int
+            Max articles to return.
+
+        Returns:
+        --------
+        str
+            Formatted articles or error message.
+        """
         try:
             api_key = os.getenv("NEWS_API_KEY")
             if not api_key:
                 return "Missing NEWS_API_KEY in environment variables."
 
+            today = datetime.datetime.utcnow()
+            from_date = (today - datetime.timedelta(days=7)).strftime('%Y-%m-%dT%H:%M:%SZ')
+
             if query:
                 url = "https://newsapi.org/v2/everything"
                 params = {
@@ -45,7 +97,8 @@ class NewsTools:
                     "pageSize": num_results,
                     "apiKey": api_key,
                     "sortBy": "publishedAt",
-                    "language": "en"
+                    "language": "en",
+                    "from": from_date
                 }
             else:
                 url = "https://newsapi.org/v2/top-headlines"
@@ -73,4 +126,4 @@ class NewsTools:
         except requests.exceptions.RequestException as e:
             return f"Network error while calling News API: {e}"
         except Exception as e:
-            return f"Unexpected error fetching news: {e}"
+            return f"Unexpected error fetching news: {e}"

tools/yahoo_tools.py

@@ -4,8 +4,9 @@ import yfinance as yf
 from dotenv import load_dotenv
 from agents import function_tool
 from core.logger import log_call
+from datetime import datetime, timedelta
 
-# Load environment variables once
+# Load environment variables
 load_dotenv()
 
 
@@ -13,16 +14,60 @@ load_dotenv()
 # 🔹 YAHOO FINANCE TOOLSET
 # ============================================================
 class FinanceTools:
-    """Provides tools for fetching stock, crypto, or ETF data from Yahoo Finance."""
+    """
+    FinanceTools provides a set of function tools for interacting with Yahoo Finance for **Financial Data** only.
+    These tools can be used by an AI agent to fetch stock, ETF, or crypto data,
+    analyze recent market trends, market sentiments, and generate market insights.
+    """
 
     @staticmethod
     @function_tool
     @log_call
     def get_summary(symbol: str, period: str = "1d", interval: str = "1h") -> str:
-        """Fetch summary and price data for a ticker."""
+        """
+        Fetch the latest summary information and intraday price data for a given ticker.
+        Ensures recent data is retrieved by calculating start/end dates dynamically.
+
+        Parameters:
+        -----------
+        symbol : str
+            The ticker symbol (e.g., "AAPL", "GOOG", "BTC-USD").
+        period : str, optional (default="1d")
+            Time range for price data. Examples: "1d", "5d", "1mo", "3mo".
+        interval : str, optional (default="1h")
+            Granularity of the data. Examples: "1m", "5m", "1h", "1d".
+
+        Returns:
+        --------
+        str
+            A formatted string containing:
+            - Company/ticker name
+            - Current price and change
+            - Open, High, Low prices
+            - Volume
+            - Period and interval used
+        """
         try:
             ticker = yf.Ticker(symbol)
-            data = ticker.history(period=period, interval=interval)
+
+            # Calculate start and end dates based on period
+            end_date = datetime.today()
+            if period.endswith("d"):
+                days = int(period[:-1])
+            elif period.endswith("mo"):
+                days = int(period[:-2]) * 30
+            elif period.endswith("y"):
+                days = int(period[:-1]) * 365
+            else:
+                days = 30  # default 1 month
+            start_date = end_date - timedelta(days=days)
+
+            # Fetch recent data explicitly
+            data = ticker.history(
+                start=start_date.strftime("%Y-%m-%d"),
+                end=end_date.strftime("%Y-%m-%d"),
+                interval=interval
+            )
 
             if data.empty:
                 return f"No data found for symbol '{symbol}'."
@@ -50,16 +95,112 @@ class FinanceTools:
         except Exception as e:
             return f"Error fetching data for '{symbol}': {e}"
 
+    @staticmethod
+    @function_tool
+    @log_call
+    def get_market_sentiment(symbol: str, period: str = "1mo") -> str:
+        """
+        Analyze recent price changes and provide a simple market sentiment.
+        Uses dynamic start/end dates to ensure recent data.
+
+        This tool computes the percentage change over the specified period and
+        classifies the sentiment as:
+        - Bullish (if price increased >2%)
+        - Bearish (if price decreased >2%)
+        - Neutral (otherwise)
+
+        Parameters:
+        -----------
+        symbol : str
+            The ticker symbol (e.g., "AAPL", "GOOG", "BTC-USD").
+        period : str, optional (default="1mo")
+            Time range to analyze. Examples: "7d", "1mo", "3mo".
+
+        Returns:
+        --------
+        str
+            A human-readable sentiment string including percentage change.
+        """
+        try:
+            ticker = yf.Ticker(symbol)
+
+            # Calculate start/end dynamically
+            end_date = datetime.today()
+            if period.endswith("d"):
+                days = int(period[:-1])
+            elif period.endswith("mo"):
+                days = int(period[:-2]) * 30
+            elif period.endswith("y"):
+                days = int(period[:-1]) * 365
+            else:
+                days = 30
+            start_date = end_date - timedelta(days=days)
+
+            data = ticker.history(
+                start=start_date.strftime("%Y-%m-%d"),
+                end=end_date.strftime("%Y-%m-%d")
+            )
+
+            if data.empty:
+                return f"No data for {symbol}."
+
+            recent_change = data["Close"].iloc[-1] - data["Close"].iloc[0]
+            pct_change = (recent_change / data["Close"].iloc[0]) * 100
+
+            sentiment = "Neutral"
+            if pct_change > 2:
+                sentiment = "Bullish"
+            elif pct_change < -2:
+                sentiment = "Bearish"
+
+            return f"{symbol} market sentiment ({period}): {sentiment} ({pct_change:.2f}% change)"
+
+        except Exception as e:
+            return f"Error fetching market sentiment for '{symbol}': {e}"
+
     @staticmethod
     @function_tool
     @log_call
     def get_history(symbol: str, period: str = "1mo") -> str:
-        """Fetch historical data for a given ticker."""
+        """
+        Fetch historical price data for a given ticker.
+        Ensures recent data is retrieved dynamically using start/end dates.
+
+        Parameters:
+        -----------
+        symbol : str
+            The ticker symbol (e.g., "AAPL", "GOOG", "BTC-USD").
+        period : str, optional (default="1mo")
+            The length of historical data to retrieve. Examples: "1d", "5d", "1mo", "3mo", "1y", "5y".
+
+        Returns:
+        --------
+        str
+            A formatted string showing the last 5 rows of historical prices (Open, High, Low, Close, Volume).
+        """
         try:
             ticker = yf.Ticker(symbol)
-            data = ticker.history(period=period)
+
+            # Calculate start/end dynamically
+            end_date = datetime.today()
+            if period.endswith("d"):
+                days = int(period[:-1])
+            elif period.endswith("mo"):
+                days = int(period[:-2]) * 30
+            elif period.endswith("y"):
+                days = int(period[:-1]) * 365
+            else:
+                days = 30
+            start_date = end_date - timedelta(days=days)
+
+            data = ticker.history(
+                start=start_date.strftime("%Y-%m-%d"),
+                end=end_date.strftime("%Y-%m-%d")
+            )
+
             if data.empty:
                 return f"No historical data found for '{symbol}'."
             return f"Historical data for {symbol} ({period}):\n{data.tail(5).to_string()}"
+
         except Exception as e:
-            return f"Error fetching historical data: {e}"
+            return f"Error fetching historical data for '{symbol}': {e}"

ui/app.py

@@ -3,10 +3,8 @@ import os
 import glob
 import asyncio
 import sys
-import textwrap
 
-# Add project root to sys.path
-# Retaining original path logic for environment compatibility
+# Add project root
 sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
 
 from appagents.research_agent import MarketResearchAgent
@@ -17,22 +15,16 @@ from agents import Runner, trace
 # -----------------------------
 def load_prompts(folder="prompts"):
     prompts = []
-    prompt_lables = []
+    prompt_labels = []
     for file_path in glob.glob(os.path.join(folder, "*.txt")):
-        with open(file_path, "r") as f:
+        with open(file_path, "r", encoding="utf-8") as f:
             content = f.read().strip()
             if content:
                 prompts.append(content)
-                prompt_lables.append(os.path.basename(file_path).replace("_", " ").replace(".txt", "").title()) 
-    return prompts, prompt_lables
+                prompt_labels.append(os.path.basename(file_path).replace("_", " ").replace(".txt", "").title())
+    return prompts, prompt_labels
 
-# Assuming 'prompts' folder exists relative to where this script is run
-try:
-    prompts, prompt_labels = load_prompts()
-except:
-    # Fallback if prompts folder is not available
-    prompts = ["What are the top 3 market trends in AI?", "Analyze the competitive landscape for EV startups.", "Suggest a strategic pivot for a struggling e-commerce company."]
-    prompt_labels = ["AI Trends Analysis", "EV Competitive Map", "E-commerce Strategy"]
+prompts, prompt_labels = load_prompts()
 
 # -----------------------------
 # Streamlit page config
@@ -40,315 +32,230 @@ except:
 st.set_page_config(page_title="AI Chat", layout="wide")
 
 # -----------------------------
-# Custom CSS (Fancier, Premium UI & Mobile Fixes)
+# Custom CSS (chat, hero banner, input)
 # -----------------------------
 st.markdown("""
-    <style>
-    /* 1. Global & Layout Reset */
-    .stApp { background-color: #F7F9FC; /* Very light cool gray */ font-family: 'Inter', sans-serif; }
-    .block-container { 
-        padding-top: 2rem !important; 
-        padding-bottom: 5rem;
-        max-width: 1100px; /* Slightly wider content area */
-        margin: 0 auto;
-    }
-    header[data-testid="stHeader"] { display: none !important; }
+<style>
+header[data-testid="stHeader"] {display: none !important;}
+.block-container {padding-top: 0 !important; margin-top: -2rem !important;}
 
-    /* 2. Accent Color & Typography */
-    :root {
-        --accent-color: #5B48CC; /* Deep Violet/Purple */
-        --accent-light: #7E6DD3;
-        --text-color: #1A1A2E;
-        --secondary-text: #4C4C66;
-        --card-bg: #ffffff;
-        --border-color: #E0E4EB;
-        --shadow-strong: 0 10px 30px rgba(0, 0, 0, 0.15);
-    }
-    
-    /* 3. Sidebar (Quick Prompts Navigation) */
-    section[data-testid="stSidebar"] {
-        background-color: var(--card-bg);
-        border-right: 1px solid var(--border-color);
-        box-shadow: 0 0 10px rgba(0, 0, 0, 0.05); /* Subtle lift */
-        padding-top: 2.5rem !important; 
-    }
-    [data-testid="stSidebar"] h2 {
-        color: var(--accent-color);
-        font-weight: 700;
-        margin-bottom: 1.5rem;
-    }
-    [data-testid="stSidebar"] .stButton button {
-        /* Style the prompt button as a 'chip' */
-        text-align: left;
-        color: var(--secondary-text);
-        background-color: #f7f9fc;
-        border: 1px solid #DCE0E6;
-        border-radius: 8px;
-        box-shadow: 0 1px 3px rgba(0,0,0,0.05);
-        padding: 12px 15px;
-        margin-bottom: 8px;
-        transition: all 0.2s ease;
-    }
-    [data-testid="stSidebar"] .stButton button:hover {
-        background-color: #E8EBF0;
-        border-color: var(--accent-color);
-        color: var(--text-color);
-        box-shadow: 0 3px 8px rgba(0,0,0,0.1);
-    }
+/* Hero banner */
+.hero-banner {
+    width: 100%;
+    background: linear-gradient(90deg, #343541 0%, #444654 100%);
+    color: white;
+    padding: 1.5rem 2rem;
+    border-radius: 0 0 12px 12px;
+    margin-bottom: 1rem;
+    box-shadow: 0 4px 10px rgba(0,0,0,0.2);
+}
+.hero-text { font-size: 1.8rem; font-weight: 700; }
+.hero-subtext { font-size: 1rem; opacity: 0.8; }
 
-    /* 4. Main Header/Title */
-    .app-title-container {
-        text-align: center;
-        padding: 1rem 0 2rem 0;
-    }
-    .app-title {
-        font-size: 2.8rem; 
-        font-weight: 800; 
-        color: var(--text-color);
-        letter-spacing: -1px;
-    }
-    .app-subtitle {
-        font-size: 1.2rem; 
-        color: var(--secondary-text);
-        margin-top: 0.5rem;
-    }
-    
-    /* 5. Input Form (The Fancier Search Bar) */
-    [data-testid="stForm"] {
-        padding: 1.5rem 0;
-        position: sticky;
-        top: 0;
-        background-color: #f7f9fc;
-        z-index: 10;
-    }
-    [data-testid="stForm"] input {
-        border-radius: 16px; /* Fancier radius */
-        height: 65px;
-        font-size: 1.15rem;
-        border: 1px solid var(--border-color) !important;
-        box-shadow: 0 6px 20px rgba(0,0,0,0.08); /* Softer initial shadow */
-        transition: border-color 0.3s, box-shadow 0.3s;
-    }
-    [data-testid="stForm"] input:focus {
-        border-color: var(--accent-light) !important;
-        box-shadow: 0 0 0 3px rgba(91, 72, 204, 0.2), 0 6px 20px rgba(0,0,0,0.15); /* Accent glow on focus */
-    }
-    [data-testid="stForm"] button {
-        /* Gradient Button with strong shadow */
-        background: linear-gradient(45deg, var(--accent-light), var(--accent-color));
-        color: white;
-        border-radius: 16px;
-        font-weight: 700;
-        height: 65px;
-        margin-left: 15px;
-        box-shadow: 0 5px 20px rgba(91, 72, 204, 0.4);
-        transition: all 0.2s;
-    }
-    [data-testid="stForm"] button:hover {
-        background: linear-gradient(45deg, var(--accent-color), var(--accent-light));
-        box-shadow: 0 8px 25px rgba(91, 72, 204, 0.55);
-    }
+/* Sidebar */
+section[data-testid="stSidebar"] {padding-top: 0.5rem !important;}
 
-    /* 6. AI Response - Premium Card Styles */
-    .ai-response-card {
-        background-color: var(--card-bg);
-        border: none;
-        border-radius: 20px;
-        padding: 30px; 
-        margin-bottom: 40px;
-        box-shadow: var(--shadow-strong); /* Stronger shadow for depth */
-        line-height: 1.65;
-        color: var(--text-color);
-    }
-    .ai-response-card h4 {
-        color: var(--accent-color);
-        font-size: 1.4rem;
-        margin-top: 0;
-        margin-bottom: 20px;
-        padding-bottom: 10px;
-        border-bottom: 2px solid #F0F2F6; /* Clean separator */
-        font-weight: 700;
-    }
+/* Chat container */
+.chat-container {
+    display: flex;
+    flex-direction: column;
+    background-color: #ffffff;
+    padding: 1.5rem;
+    border-radius: 12px;
+    height: 70vh;
+    overflow-y: auto;
+    border: 1px solid #ddd;
+    box-shadow: 0 4px 8px rgba(0,0,0,0.05);
+    margin-top: 1rem;
+}
 
-    /* --- MOBILE FLOATING SIDEBAR FIX (Bidirectional Nav) --- */
-    @media (max-width: 768px) {
-        /* Force fixed position and high z-index on the sidebar content wrapper when open */
-        [data-testid="stSidebar"] {
-            z-index: 10000 !important; /* Extremely high z-index */
-        }
-        [data-testid="stSidebarContent"] {
-            position: fixed !important;
-            top: 0 !important;
-            left: 0 !important;
-            width: 85% !important; /* Good width for mobile access */
-            height: 100vh !important;
-            box-shadow: 4px 0 20px rgba(0,0,0,0.5); /* Strong shadow when open */
-            transition: transform 0.3s ease; 
-        }
-    }
-    </style>
+/* Chat bubbles */
+.user-bubble, .ai-bubble {
+    padding: 12px 16px;
+    border-radius: 12px;
+    max-width: 75%;
+    margin: 6px 0;
+    word-wrap: break-word;
+    font-size: 15px;
+    line-height: 1.4;
+    box-shadow: 0 1px 3px rgba(0,0,0,0.1);
+}
+.user-bubble {
+    background-color: #DCF8C6;
+    color: #111;
+    align-self: flex-end;
+}
+.ai-bubble {
+    background-color: #f0f0f0;
+    color: #111;
+    align-self: flex-start;
+}
+
+/* Icons */
+.icon {
+    font-size: 28px;
+    margin: 4px;
+    opacity: 0.8;
+}
+
+/* Input area */
+.stTextInput input {
+    border-radius: 10px;
+    border: 1px solid #ccc;
+    padding: 12px;
+    font-size: 15px;
+}
+.stForm button {
+    border-radius: 10px;
+    font-size: 15px;
+    background-color: #10a37f !important;
+    color: white !important;
+    border: none !important;
+}
+
+/* Mobile-specific Quick Prompts at top */
+@media (max-width: 768px) {
+    .mobile-prompts { display: block; margin-bottom: 1rem; }
+    .desktop-sidebar { display: none; }
+    .chat-container { height: 60vh; background-color: #f5f5f5; }
+    .user-bubble, .ai-bubble { font-size: 14px; }
+}
+@media (min-width: 769px) {
+    .mobile-prompts { display: none; }
+    .desktop-sidebar { display: block; }
+}
+</style>
 """, unsafe_allow_html=True)
 
 # -----------------------------
-# Session state
+# Session state defaults
 # -----------------------------
 if "chat_history" not in st.session_state:
-    st.session_state.chat_history = []
+    st.session_state.chat_history = []  # newest-first
 
 if "input_value" not in st.session_state:
     st.session_state.input_value = ""
 
-if "send_triggered" not in st.session_state:
-    st.session_state.send_triggered = False
+if "pending_response" not in st.session_state:
+    st.session_state.pending_response = False
 
-# -----------------------------
-# Function to fetch AI response (Mocked for runnable code)
-# -----------------------------
-async def get_ai_response(prompt):
-    # Mocking the agent response since the actual agent dependencies are unavailable
-    if "agent" not in locals():
-        class MockAgent:
-            def create(self): return self
-            async def run(self, prompt):
-                class MockResult:
-                    def __init__(self, output): self.final_output = output
-                
-                if "trends" in prompt.lower():
-                    return MockResult(textwrap.dedent("""
-                        #### Global AI Market Trends Summary
-                        The AI landscape is rapidly accelerating across three primary vectors:
-                        
-                        * **Hyper-Personalization at Scale:** New models leverage real-time behavioral data to offer truly individualized experiences in e-commerce, education, and healthcare.
-                        * **Synthetic Data Generation:** Due to privacy concerns and high costs of real-world data, the use of high-fidelity synthetic data for training complex models is skyrocketing.
-                        * **Governance and Regulation Focus:** Significant R&D and policy focus is shifting toward verifiable, explainable, and ethically compliant systems (e.g., EU AI Act compliance).
-                    """))
-                elif "competitive landscape" in prompt.lower():
-                    return MockResult(textwrap.dedent("""
-                        #### The Competitive Map for EV Startups
-                        The EV market competition is fierce, centered on two core strategic areas:
-                        
-                        1.  **Proprietary Software Ecosystems:** Winning long-term customers relies on creating unique in-vehicle software experiences and robust integration with personal digital devices.
-                        2.  **Next-Generation Charging Solutions:** Companies pioneering extreme fast-charging (over 350kW) or battery-swap models are gaining strategic advantages in logistics and consumer convenience.
-                    """))
-                else:
-                    return MockResult(textwrap.dedent(f"""
-                        #### Strategic Recommendation for '{prompt}'
-                        For a company seeking a strategic pivot, three actions are critical:
-                        
-                        * **De-Risking Supply Chains:** Shift sourcing and manufacturing to multi-regional supply hubs to mitigate geopolitical and logistics vulnerabilities.
-                        * **Subscription-Based Revenue Model:** Introduce a tier of subscription services for core offerings, creating recurring, high-margin revenue streams that stabilize cash flow.
-                        * **Talent Recalibration:** Invest heavily in upskilling existing teams in AI/ML and data science, moving away from legacy skill sets to future-proof the organization's technological capacity.
-                    """))
+if "pending_message" not in st.session_state:
+    st.session_state.pending_message = None
 
-        global MarketResearchAgent, Runner, trace
-        MarketResearchAgent = MockAgent()
-        Runner = type('Runner', (object,), {'run': MarketResearchAgent.run})
-        trace = lambda name: type('trace', (object,), {'__enter__': lambda s: None, '__exit__': lambda s,e,t: None})
+if "auto_send_prompt" not in st.session_state:
+    st.session_state.auto_send_prompt = None
 
-    try:
-        agent = MarketResearchAgent.create()
-        with trace("Chatting with AI"):
-            result = await Runner.run(agent, prompt)
-            return result.final_output
-    except Exception as e:
-        return f"Sorry, the analysis engine encountered an error: {e}"
+# -----------------------------
+# Async AI response
+# -----------------------------
+async def get_ai_response(prompt: str) -> str:
+    agent = MarketResearchAgent.create()
+    with trace("Chatting with AI"):
+        result = await Runner.run(agent, prompt)
+        return result.final_output
 
 # -----------------------------
-# Sidebar with prompts (Bidirectional Left Navigation)
+# Desktop Sidebar Quick Prompts
 # -----------------------------
-with st.sidebar:
-    st.title("💡 Quick Prompts")
-    st.markdown('<p style="font-size:0.9rem; color:var(--secondary-text); margin-bottom: 20px;">Jumpstart your research with these pre-defined queries.</p>', unsafe_allow_html=True)
+with st.sidebar.container() if st.config.get_option("server.headless") is False else st.container() as container:
+    st.markdown('<div class="desktop-sidebar">', unsafe_allow_html=True)
+    st.sidebar.title("💡 Quick Prompts")
     for idx, prompt_text in enumerate(prompts):
-        if st.button(prompt_labels[idx], key=f"prompt_{idx}", help=prompt_text):
-            st.session_state.input_value = prompt_text
-            st.session_state.send_triggered = True
+        label = prompt_labels[idx] if idx < len(prompt_labels) else f"Prompt {idx+1}"
+        if st.sidebar.button(label, key=f"prompt_{idx}"):
+            st.session_state.auto_send_prompt = prompt_text
+    st.markdown('</div>', unsafe_allow_html=True)
 
 # -----------------------------
-# Main Header/Title
+# Mobile Quick Prompts
+# -----------------------------
+with st.container():
+    st.markdown('<div class="mobile-prompts">', unsafe_allow_html=True)
+    with st.expander("💡 Quick Prompts"):
+        for idx, prompt_text in enumerate(prompts):
+            label = prompt_labels[idx] if idx < len(prompt_labels) else f"Prompt {idx+1}"
+            if st.button(label, key=f"mobile_prompt_{idx}"):
+                st.session_state.auto_send_prompt = prompt_text
+    st.markdown('</div>', unsafe_allow_html=True)
+
+# -----------------------------
+# Hero banner
 # -----------------------------
 st.markdown("""
-    <div class="app-title-container">
-        <div class="app-title">Hello, how can I help you today?</div>
-        <div class="app-subtitle">Your strategic partner for market analysis and next-level insights.</div>
+<div class="hero-banner">
+    <div>
+        <div class="hero-text">🤖 AI Chatbot</div>
+        <div class="hero-subtext">Your intelligent assistant for insights, trends, and strategy exploration.</div>
     </div>
+</div>
 """, unsafe_allow_html=True)
 
 # -----------------------------
-# Chat history display (FIXED to render correctly)
+# Chat input area
 # -----------------------------
-# Displaying directly in the main app flow for reliability
-if st.session_state.chat_history:
-    for chat in st.session_state.chat_history:
-        if chat["role"] == "user":
-            st.markdown(
-                f"""
-                <div style="margin-top: 30px;"></div>
-                <div class="user-message-block">
-                    <span style='font-size:2.2rem;'>💡</span>
-                    <div class="user-message-text">{chat['message']}</div>
-                </div>
-                """, 
-                unsafe_allow_html=True
-            )
-        else:
-            # The AI card is structured to allow the content (chat['message']) 
-            # which contains markdown, to be printed and styled inside the card.
-            st.markdown(
-                f"""
-                <div class="ai-response-card">
-                    <h4 style='display: flex; align-items: center;'>
-                        <span style='margin-right: 12px; font-size: 1.4em;'>🤖</span> Insight Report
-                    </h4>
-                    {chat['message']}
-                </div>
-                """,
-                unsafe_allow_html=True
-            )
-elif not st.session_state.send_triggered:
-    # Initial state message when no chat history exists
-    st.info("Start by asking a complex question about market trends, competitors, or strategy. Use the sidebar for quick ideas!")
-
+with st.form(key="chat_form", clear_on_submit=False):
+    user_input = st.text_input(
+        "Type your message here:",
+        value=st.session_state.input_value,
+        placeholder="Send a message...",
+        key="chat_input"
+    )
+    send_button = st.form_submit_button("Send")
 
 # -----------------------------
-# Chat input area (The central search bar)
+# Helper to insert user message immediately
 # -----------------------------
-with st.form(key="chat_form", clear_on_submit=True):
-    col1, col2 = st.columns([1, 0.12])
-    with col1:
-        user_input = st.text_input(
-            "Enter your prompt:",
-            value=st.session_state.input_value,
-            placeholder="E.g., What are the key regulatory hurdles for carbon capture technologies in Europe?",
-            label_visibility="collapsed",
-            key="chat_input"
-        )
-    with col2:
-        send_button = st.form_submit_button("Analyze")
+def send_user_message(msg):
+    st.session_state.chat_history.insert(0, {"role": "user", "message": msg})
+    st.session_state.pending_message = msg
+    st.session_state.pending_response = True
+    st.session_state.input_value = ""
 
 # -----------------------------
-# Handle sending message
+# Handle normal send
 # -----------------------------
-message_to_send = ""
-if send_button and user_input:
-    message_to_send = user_input.strip()
-elif st.session_state.send_triggered and st.session_state.input_value:
-    message_to_send = st.session_state.input_value.strip()
+if send_button and user_input.strip():
+    send_user_message(user_input.strip())
+
+# Handle sidebar/mobile prompt auto-send
+if st.session_state.auto_send_prompt:
+    send_user_message(st.session_state.auto_send_prompt)
+    st.session_state.auto_send_prompt = None
 
-if message_to_send:
-    # 1. Add user message to history
-    st.session_state.chat_history.insert(0, {"role": "user", "message": message_to_send})
-    
-    # 2. Get and add AI response
-    with st.spinner("⏳ Analyzing market data... Generating detailed insight report..."):
+# -----------------------------
+# Handle AI response asynchronously
+# -----------------------------
+if st.session_state.pending_response and st.session_state.pending_message:
+    with st.spinner("🤖 Thinking..."):
         try:
-            response = asyncio.run(get_ai_response(message_to_send))
-            st.session_state.chat_history.insert(0, {"role": "assistant", "message": response})
+            ai_response = asyncio.run(get_ai_response(st.session_state.pending_message))
         except Exception as e:
-            st.error(f"An unexpected error occurred during processing: {e}")
-            st.session_state.chat_history.insert(0, {"role": "assistant", "message": "Sorry, I encountered an internal error and couldn't complete the analysis."})
-    
-    # 3. Clear state and force a rerun (FIXED: using st.rerun())
-    st.session_state.input_value = ""
-    st.session_state.send_triggered = False
-    st.rerun()
+            ai_response = f"[Error generating response: {e}]"
+    st.session_state.chat_history.insert(0, {"role": "assistant", "message": ai_response})
+    st.session_state.pending_response = False
+    st.session_state.pending_message = None
+
+# -----------------------------
+# Display chat history with Markdown in AI bubbles
+# -----------------------------
+for chat in st.session_state.chat_history:
+    if chat["role"] == "user":
+        msg_html = chat["message"].replace("\n","<br>")
+        st.markdown(
+            f"<div style='display:flex; justify-content:flex-end; align-items:flex-start;'>"
+            f"<div class='user-bubble'>{msg_html}</div>"
+            f"<span class='icon'>👤</span>"
+            f"</div>", unsafe_allow_html=True
+        )
+    else:
+        st.markdown(
+            f"""
+<div style='display:flex; justify-content:flex-start; align-items:flex-start;'>
+  <span class='icon'>🤖</span>
+  <div class='ai-bubble'>
+    {chat['message']}
+  </div>
+</div>
+""",
+            unsafe_allow_html=True
+        )