Upload folder using huggingface_hub

Dockerfile

@@ -1,31 +1,33 @@
-FROM python:3.12-slim
+# Use official Python slim image
+FROM python:3.11-slim
 
+# Set environment variables
 ENV PYTHONUNBUFFERED=1 \
-    DEBIAN_FRONTEND=noninteractive \
-    PYTHONPATH=/app:$PYTHONPATH
+    PIP_NO_CACHE_DIR=1 \
+    DEBIAN_FRONTEND=noninteractive
 
+# Set working directory
 WORKDIR /app
 
-# System deps
+# Install system dependencies
 RUN apt-get update && apt-get install -y \
-    git build-essential curl \
+    git \
+    build-essential \
+    curl \
     && rm -rf /var/lib/apt/lists/*
 
-# Install uv
-RUN curl -LsSf https://astral.sh/uv/install.sh | sh
-ENV PATH="/root/.local/bin:$PATH"
+# Copy requirements file
+COPY requirements.txt .
 
-# Copy project metadata
-COPY pyproject.toml .
-COPY uv.lock .
+# Install Python dependencies
+RUN pip install --upgrade pip
+RUN pip install -r requirements.txt
 
-# Install dependencies using uv, then export and install with pip to system
-RUN uv sync --frozen --no-dev && \
-    uv pip install -e . --system
-
-# Copy your source code
+# Copy the rest of the app
 COPY . .
 
+# Expose port for Streamlit
 EXPOSE 7860
 
+# Command to run the Streamlit app
 CMD ["streamlit", "run", "ui/app.py", "--server.port=7860", "--server.address=0.0.0.0", "--server.headless=true"]

README.md

@@ -1,9 +1,9 @@
 ---
-title: AI Deep Researcher        # Give your app a title
+title: Deep Research App        # Give your app a title
 emoji: 🤖                       # Pick an emoji
 colorFrom: indigo               # Theme start color
 colorTo: blue                   # Theme end color
-sdk: docker                     # SDK type
+sdk: gradio                     # SDK type
 sdk_version: "4.39.0"           # Example Gradio version
 app_file: ui/app.py             # <-- points to your app.py inside ui/
 pinned: false
@@ -22,6 +22,7 @@ To achieve this, the project integrates the following technologies and AI featur
 - **SendGrid** (for emailing report)
 - **LLMs** - (OpenAI, Geminia, Groq)
 
+
 ## How it works?
 The system is a multi-agent solution, where each agent has a specific responsibility:
 
@@ -40,152 +41,10 @@ The system is a multi-agent solution, where each agent has a specific responsibi
     - Reads results from all search agents.
     - Generates a well-formatted, consolidated report.
 
-5. **Email Agent (not functional at present)**
+5. **Email Agent**
     - Responsible for sending the report via email using SendGrid.
 
 6. **Orchestrator**
     - The entry point of the system.
     - Facilitates communication and workflow between all agents.
 
-## Project Folder Structure
-
-```
-deep-research/
-├── ui/
-│   ├── app.py                    # Main Streamlit application entry point
-│   └── __pycache__/              # Python bytecode cache
-├── appagents/
-│   ├── __init__.py               # Package initialization
-│   ├── orchestrator.py           # Orchestrator agent - coordinates all agents
-│   ├── planner_agent.py          # Planner agent - builds structured query plans
-│   ├── guardrail_agent.py        # Guardrail agent - validates user input
-│   ├── search_agent.py           # Search agent - performs web searches
-│   ├── writer_agent.py           # Writer agent - generates consolidated reports
-│   ├── email_agent.py            # Email agent - sends reports via email (not functional)
-│   └── __pycache__/              # Python bytecode cache
-├── core/
-│   ├── __init__.py               # Package initialization
-│   ├── logger.py                 # Centralized logging configuration
-│   └── __pycache__/              # Python bytecode cache
-├── tools/
-│   ├── __init__.py               # Package initialization
-│   ├── google_tools.py           # Google search utilities
-│   ├── time_tools.py             # Time-related utility functions
-│   └── __pycache__/              # Python bytecode cache
-├── prompts/
-│   ├── __init__.py               # Package initialization (if present)
-│   ├── planner_prompt.txt        # Prompt for planner agent (if present)
-│   ├── guardrail_prompt.txt      # Prompt for guardrail agent (if present)
-│   ├── search_prompt.txt         # Prompt for search agent (if present)
-│   └── writer_prompt.txt         # Prompt for writer agent (if present)
-├── Dockerfile                     # Docker configuration for container deployment
-├── pyproject.toml                 # Project metadata and dependencies (copied from root)
-├── uv.lock                        # Locked dependency versions (copied from root)
-├── README.md                      # Project documentation
-└── run.py                         # Script to run the application locally (if present)
-```
-
-## File Descriptions
-
-### UI Layer (`ui/`)
-- **app.py** - Main Streamlit web application that provides the user interface. Handles:
-  - Text input for research queries
-  - Run/Download buttons (PDF, Markdown)
-  - Real-time streaming of results
-  - Display of final research reports
-  - Session state management
-  - Button enable/disable during streaming
-
-### Agents (`appagents/`)
-- **orchestrator.py** - Central coordinator that:
-  - Manages the multi-agent workflow
-  - Handles communication between all agents
-  - Streams results back to the UI
-  - Implements the research pipeline
-
-- **planner_agent.py** - Creates a structured plan for the query:
-  - Breaks down user query into actionable research steps
-  - Defines search queries and research angles
-
-- **guardrail_agent.py** - Validates user input:
-  - Checks for inappropriate content
-  - Ensures compliance with policies
-  - Stops workflow if violations detected
-
-- **search_agent.py** - Executes web searches:
-  - Performs parallel web searches
-  - Integrates with Google Search / Serper API
-  - Gathers raw research data
-
-- **writer_agent.py** - Generates final report:
-  - Consolidates search results
-  - Formats findings into structured markdown
-  - Creates well-organized research summaries
-
-- **email_agent.py** - Email delivery (not functional):
-  - Intended to send reports via SendGrid
-  - Currently not integrated in the workflow
-
-### Core Utilities (`core/`)
-- **logger.py** - Centralized logging configuration:
-  - Provides consistent logging across agents
-  - Handles log levels and formatting
-
-### Tools (`tools/`)
-- **google_tools.py** - Google/Serper API wrapper:
-  - Executes web searches
-  - Handles API authentication and response parsing
-
-- **time_tools.py** - Utility functions:
-  - Time-related operations
-  - Timestamp management
-
-### Configuration Files
-- **Dockerfile** - Container deployment:
-  - Builds Docker image with Python 3.12
-  - Installs dependencies using `uv`
-  - Sets up Streamlit server on port 7860
-  - Configures PYTHONPATH for module imports
-
-- **pyproject.toml** - Project metadata:
-  - Package name: "agents"
-  - Python version requirement: 3.12
-  - Lists all dependencies (OpenAI, LangChain, Streamlit, etc.)
-
-- **uv.lock** - Dependency lock file:
-  - Ensures reproducible builds
-  - Pins exact versions of all dependencies
-
-## Key Technologies
-
-| Component | Technology | Purpose |
-|-----------|-----------|---------|
-| LLM Framework | OpenAI Agents | Multi-agent orchestration |
-| Web Search | Serper API / Google Search | Research data gathering |
-| Web UI | Streamlit | User interface and interaction |
-| Document Export | ReportLab | PDF generation from markdown |
-| Async Operations | AsyncIO | Parallel agent execution |
-| Dependencies | UV | Fast Python package management |
-| Containerization | Docker | Cloud deployment |
-
-## Running Locally
-
-```bash
-# Install dependencies
-uv sync
-
-# Set environment variables defined in .env.name file
-export OPENAI_API_KEY="your-key"
-export SERPER_API_KEY="your-key"
-
-# Run the Streamlit app
-python run.py
-```
-
-## Deployment
-
-The project is deployed on Hugging Face Spaces as a Docker container:
-- **Space**: https://huggingface.co/spaces/mishrabp/deep-research
-- **URL**: https://huggingface.co/spaces/mishrabp/deep-research
-- **Trigger**: Automatic deployment on push to `main` branch
-- **Configuration**: `.github/workflows/deep-research-app-hf.yml`

SETUP.md

@@ -0,0 +1,18 @@
+### Setting up .venv
+```bash
+conda create --prefix /home/azureuser/ws/agenticai/projects/deep-research/.venv python=3.11 -y
+
+conda activate /home/azureuser/ws/agenticai/projects/deep-research/.venv
+
+conda deactivate 
+
+uv pip install --upgrade -r requirements.txt
+```
+
+### Run Unit Tests
+```bash
+pytest -v tests/test_data_agent.py
+
+python -m pytest -v
+
+```

appagents/planner_agent.py

@@ -31,14 +31,12 @@ groq_api_key = os.getenv('GROQ_API_KEY')
 groq_client = AsyncOpenAI(base_url=GROQ_BASE_URL, api_key=groq_api_key)
 groq_model = OpenAIChatCompletionsModel(model="groq/compound", openai_client=groq_client)
 
-openai_model = "gpt-4.1-mini"
-
 # Note: Many models do not like tool call and json output_schema used together.
 
 planner_agent = Agent(
     name="PlannerAgent",
     instructions=INSTRUCTIONS,
-    model=openai_model,
+    model=gemini_model,
     tools=[TimeTools.current_datetime],
     output_type=WebSearchPlan,
     input_guardrails=[guardrail_against_unparliamentary],

core/logger.py

@@ -14,7 +14,7 @@ def log_call(func):
         print(f"[{timestamp}] 🚀 Calling: {func.__name__}({arg_list})")
         try:
             result = func(*args, **kwargs)
-            # print(f"[{timestamp}] ✅ Finished: {func.__name__}")
+            print(f"[{timestamp}] ✅ Finished: {func.__name__}")
             return result
         except Exception as e:
             print(f"[{timestamp}] ❌ Error in {func.__name__}: {e}")

requirements.txt

@@ -0,0 +1,31 @@
+openai>=1.85.0
+    # via
+    #   agents (pyproject.toml)
+    #   autogen-ext
+    #   langchain-openai
+    #   openai-agents
+    #   semantic-kernel
+openai-agents>=0.0.17
+    # via agents (pyproject.toml)
+python-dotenv>=1.0.1
+requests>=2.31.0
+    # via
+    #   agents (pyproject.toml)
+    #   autogen-ext
+    #   langchain-openai
+    #   openai-agents
+    #   semantic-kernel
+yfinance>=0.2.27
+    # via tools/news_tools.py, tools/yahoo_tools.py
+gradio>=3.34.0
+    # via autogen-ext
+sendgrid>=6.9.7
+    # via tools/email_tools.py
+mcp==1.9.3
+    # via
+    #   agents (pyproject.toml)
+    #   autogen-ext
+    #   mcp-server-fetch
+    #   openai-agents
+mcp-server-fetch==2025.1.17
+    # via agents (pyproject.toml)

run.py

@@ -1,11 +1,26 @@
 import os
-import subprocess
 import sys
+import importlib
 
-# Use module execution to guarantee Streamlit runs inside the current interpreter
-subprocess.run([
-    sys.executable, "-m", "streamlit",
-    "run",
-    os.path.join("ui", "app.py"),
-    "--server.runOnSave", "true"
-])
+def main():
+    # Root directory of the project
+    root_dir = os.path.dirname(os.path.abspath(__file__))
+
+    # Ensure the root and ui folder are on the Python path
+    ui_path = os.path.join(root_dir, "ui")
+    for p in [root_dir, ui_path]:
+        if p not in sys.path:
+            sys.path.insert(0, p)
+
+    print("🚀 Starting Gradio app (ui/app.py)...\n")
+
+    # Import and launch the UI
+    app_module = importlib.import_module("ui.app")
+
+    if hasattr(app_module, "ui"):
+        app_module.ui.launch(inbrowser=True)
+    else:
+        print("❌ Could not find `ui` object in ui/app.py")
+
+if __name__ == "__main__":
+    main()

ui/app.py

@@ -1,432 +1,182 @@
 import streamlit as st
 import asyncio
-import time
-import html
-from datetime import datetime, UTC
-from io import BytesIO
-
 from dotenv import load_dotenv
-from reportlab.platypus import SimpleDocTemplate, Paragraph
-from reportlab.lib.styles import getSampleStyleSheet
 
 from appagents.orchestrator import Orchestrator
 from agents import SQLiteSession
 
 load_dotenv(override=True)
 
-# --------------------
 # Page config
-# --------------------
 st.set_page_config(page_title="Deep Research AI", layout="wide")
 
-# --------------------
-# Session-state init
-# --------------------
-if "session_store" not in st.session_state:
-    st.session_state.session_store = {}
-
-if "session_id" not in st.session_state:
-    st.session_state.session_id = str(id(st))
-
-if "final_report" not in st.session_state:
-    st.session_state.final_report = ""
-
-if "button_disabled" not in st.session_state:
-    st.session_state.button_disabled = False
-
-
-# (dark mode removed - UI uses single light theme)
-
-# --------------------
-# CSS for theme-agnostic layout
-# --------------------
-THEME_AGNOSTIC_CSS = """
+# ---------- CSS: center & 80% width, nicer typography ----------
+CUSTOM_CSS = """
 <style>
-:root {
-  color-scheme: light dark;
-}
-
-.block-container { 
-  max-width: 90% !important; 
-  margin-left: 5% !important; 
-  margin-right: 5% !important; 
-  padding-top: 1.5rem !important; 
-  padding-bottom: 2rem !important; 
-}
-
-/* Use system foreground/background colors */
-body {
-  color: var(--text-color);
-  background-color: var(--bg-color);
-}
-
-h1, h2, h3, h4, h5, h6 { 
-  font-size: 2.2rem !important; 
-  text-align: left !important; 
-  color: inherit !important;
-  font-weight: 600 !important;
-}
-
-/* Text areas - inherit system colors */
-textarea, .stTextArea > div > div > textarea { 
-  background-color: inherit !important; 
-  color: inherit !important; 
-  font-size: 1.05rem !important;
-  border: 1px solid var(--border-color) !important;
-}
-
-/* Buttons - proper button styling */
-.stButton > button, .stDownloadButton > button {
-  border: 2px solid currentColor !important;
-  border-radius: 6px !important;
-  padding: 10px 20px !important;
-  font-weight: 600 !important;
-  cursor: pointer !important;
-  transition: all 0.2s ease !important;
-  background-color: transparent !important;
-  color: inherit !important;
-  min-width: 150px !important;
-  min-height: 44px !important;
-}
-
-.stButton > button:hover, .stDownloadButton > button:hover {
-  background-color: rgba(0, 0, 0, 0.1) !important;
-  transform: translateY(-2px) !important;
-  box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15) !important;
-}
-
-.stButton > button:active, .stDownloadButton > button:active {
-  transform: translateY(0) !important;
-}
-
-/* Download buttons */
-.stDownloadButton > button {
-  width: 180px !important;
-  height: 48px !important;
-}
-
-/* Text and paragraphs */
-p, span, div {
-  color: inherit !important;
-}
-
-/* Code blocks */
-code {
-  padding: 2px 4px;
-  border-radius: 3px;
-}
-
-/* Info, success, error, warning boxes */
-.stAlert {
-  border-radius: 6px !important;
-}
-
-/* Markdown content */
-.stMarkdown {
-  color: inherit !important;
-}
-
-/* List items */
-ul, ol, li {
-  color: inherit !important;
-}
-
-/* Links */
-a {
-  text-decoration: none;
-}
-
-a:hover {
-  text-decoration: underline;
+/* Make main container 80% width and centered */
+.block-container {
+    max-width: 80% !important;
+    margin-left: auto !important;
+    margin-right: auto !important;
+    padding-top: 1.5rem;
+    padding-bottom: 2rem;
 }
 
-/* Ensure sufficient contrast for readability */
-.stApp {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;
-  line-height: 1.6;
-}
-
-/* Progress bar visibility */
-.stProgress > div > div > div {
-  background-color: currentColor !important;
-  opacity: 0.5 !important;
+/* Larger title */
+h1 {
+    font-size: 2.2rem !important;
+    text-align: center;
+    margin-bottom: 0.25rem;
 }
 
-/* Remove text truncation */
-.stMarkdown {
-  max-height: none !important;
-  overflow: visible !important;
+/* report box: preserve whitespace, allow overflow scrolling */
+.report-box {
+    background: #ffffff;
+    padding: 24px;
+    border-radius: 12px;
+    border: 1px solid #e9ecef;
+    box-shadow: 0 6px 18px rgba(23,43,77,0.04);
+    font-size: 1.05rem;
+    line-height: 1.65;
+    white-space: pre-wrap;           /* preserve newlines */
+    word-wrap: break-word;
+    overflow-wrap: break-word;
+    max-height: 70vh;                /* allow vertical scrolling if very long */
+    overflow: auto;
 }
 
-/* Responsive buttons layout */
-@media (max-width: 768px) {
-  h1, h2, h3 {
-    font-size: 1.6rem !important;
-  }
-  
-  .stButton > button {
-    width: 100% !important;
-    height: auto !important;
-    padding: 10px !important;
-  }
-  
-  .stDownloadButton > button {
-    width: 100% !important;
-    height: auto !important;
-    padding: 10px !important;
-  }
+/* Input area style */
+textarea, .stTextArea>div>div>textarea {
+    font-size: 1.05rem !important;
 }
 
-/* Tablet devices */
-@media (min-width: 769px) and (max-width: 1024px) {
-  .block-container {
-    max-width: 85% !important;
-  }
-  
-  h1, h2, h3 {
-    font-size: 1.8rem !important;
-  }
+/* center the Run button under the textarea */
+.run-btn {
+    display:flex;
+    justify-content:center;
+    align-items:center;
+    margin-top: 12px;
 }
 
-/* Desktop devices */
-@media (min-width: 1025px) {
-  .block-container {
-    max-width: 90% !important;
-  }
-  
-  h1, h2, h3 {
-    font-size: 2.2rem !important;
-  }
+/* progress / status spacing */
+.progress-area {
+    margin-top: 12px;
+    margin-bottom: 10px;
 }
 </style>
 """
+st.markdown(CUSTOM_CSS, unsafe_allow_html=True)
 
-st.markdown(THEME_AGNOSTIC_CSS, unsafe_allow_html=True)
+# ---------- session-store for persistent SQLiteSession ----------
+if "session_store" not in st.session_state:
+    st.session_state.session_store = {}
+
+if "session_id" not in st.session_state:
+    # stable per-tab session id
+    st.session_state.session_id = str(id(st))
 
-st.markdown(THEME_AGNOSTIC_CSS, unsafe_allow_html=True)
 
-# --------------------
-# Helpers: orchestrator streaming
-# --------------------
 async def run_async_chunks(query: str, session_id: str):
+    """
+    Async generator: yields chunks from orchestrator.run(query)
+    """
+    # create or reuse persistent SQLiteSession
     if session_id not in st.session_state.session_store:
-        st.session_state.session_store[session_id] = SQLiteSession(f"session_{session_id}.db")
+        st.session_state.session_store[session_id] = SQLiteSession(
+            f"session_{session_id}.db"
+        )
+
     session = st.session_state.session_store[session_id]
     orchestrator = Orchestrator(session=session)
+
     async for chunk in orchestrator.run(query):
         yield chunk
 
-def safe_title_from_query(q: str):
-    q = q.strip()
-    if not q:
-        return "Untitled Report"
-    first_line = q.splitlines()[0]
-    # limit length for title
-    return (first_line[:80] + "...") if len(first_line) > 80 else first_line
-
-# --------------------
-# Export helpers
-# --------------------
-def make_pdf_bytes(text: str) -> bytes:
-    """Convert markdown text to PDF with proper formatting."""
-    buf = BytesIO()
-    doc = SimpleDocTemplate(buf, topMargin=0.5*72, bottomMargin=0.5*72, leftMargin=0.75*72, rightMargin=0.75*72)
-    styles = getSampleStyleSheet()
-    story = []
-    
-    # parse markdown: headings, lists, bold, italic
-    lines = text.split("\n")
-    for line in lines:
-        stripped = line.strip()
-        
-        if not stripped:
-            story.append(Paragraph(" ", styles["Normal"]))  # empty line
-            continue
-        
-        # heading levels
-        if stripped.startswith("# "):
-            story.append(Paragraph(html.escape(stripped[2:]), styles["Heading1"]))
-        elif stripped.startswith("## "):
-            story.append(Paragraph(html.escape(stripped[3:]), styles["Heading2"]))
-        elif stripped.startswith("### "):
-            story.append(Paragraph(html.escape(stripped[4:]), styles["Heading3"]))
-        elif stripped.startswith("- ") or stripped.startswith("* "):
-            # bullet list
-            story.append(Paragraph("• " + html.escape(stripped[2:]), styles["Normal"]))
-        elif stripped[0].isdigit() and ". " in stripped[:4]:
-            # numbered list
-            story.append(Paragraph(html.escape(stripped), styles["Normal"]))
-        else:
-            # regular paragraph with basic markdown formatting
-            # escape first, then replace with safe formatting tags
-            p_text = html.escape(stripped)
-            
-            # handle **bold** (convert escaped ** back and wrap in <b> tags)
-            p_text = p_text.replace("&lt;b&gt;", "<b>").replace("&lt;/b&gt;", "</b>")
-            # Simple approach: replace **text** with <b>text</b>
-            import re
-            p_text = re.sub(r'\*\*(.+?)\*\*', r'<b>\1</b>', p_text)
-            p_text = re.sub(r'__(.+?)__', r'<b>\1</b>', p_text)
-            # handle *italic* → <i>italic</i> carefully (avoid double replacement)
-            p_text = re.sub(r'\*([^*]+?)\*', r'<i>\1</i>', p_text)
-            p_text = re.sub(r'_([^_]+?)_', r'<i>\1</i>', p_text)
-            
-            story.append(Paragraph(p_text, styles["Normal"]))
-    
-    doc.build(story)
-    buf.seek(0)
-    return buf.read()
-
-def make_md_bytes(text: str) -> bytes:
-    return text.encode("utf-8")
-
-def make_html_bytes(text: str, title="Deep Research Report") -> bytes:
-    # simple HTML wrapper, escape content and preserve newlines
-    body = "<br/>".join(html.escape(text).split("\n"))
-    html_doc = f"""<!doctype html>
-<html>
-<head>
-<meta charset="utf-8">
-<title>{html.escape(title)}</title>
-<style>body{{font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial; padding:24px; max-width:900px; margin:auto; line-height:1.6; color: #0b1220; background: #ffffff }}</style>
-</head>
-<body>
-<h1>{html.escape(title)}</h1>
-<div>{body}</div>
-</body>
-</html>"""
-    return html_doc.encode("utf-8")
-
-# --------------------
-# Streaming runner (final output replaces trace)
-# --------------------
-def run_streaming(query: str, final_ph, status_ph):
+
+def run_streaming(query: str):
+    """
+    Streamlit-friendly runner: updates spinner, progress bar and the output placeholder.
+    Stores full output in st.session_state to avoid truncation between reruns.
+    """
+
     session_id = st.session_state.session_id
 
     # placeholders
-    # status_ph = st.empty()
+    status_ph = st.empty()
     progress_ph = st.empty()
+    output_ph = st.empty()
 
-    # reset final_report
-    st.session_state.final_report = ""
-    # track only the last received chunk
-    last_chunk = ""
-    progress_val = 0
-    progress_bar = progress_ph.progress(progress_val)
+    # keep full output in session_state so it survives reruns while streaming
+    if "full_output" not in st.session_state:
+        st.session_state.full_output = ""
 
-    # ensure any prior final output is cleared while streaming
-    try:
-        final_ph.empty()
-    except Exception:
-        pass
-    # status_ph.info("🔎 Researching — streaming (final result only)...")
+    # reset before new run
+    st.session_state.full_output = ""
+    progress_value = 0
+    progress_bar = progress_ph.progress(progress_value)
+
+    # spinner + async loop
+    status_ph.info("🔎 Processing — streaming results now...")
 
     async def _stream():
-        nonlocal progress_val, last_chunk
-        status_ph.info("Streaming... receiving data")
-        bStartChunkCollected = False
+        nonlocal progress_value, progress_bar
+        # naive increment step; will cap at 98 until finished
         async for chunk in run_async_chunks(query, session_id):
-            # start collecting chunks once we see one beginning with #
-            if not bStartChunkCollected and chunk.strip().startswith("#"):
-                bStartChunkCollected = True
-
-            if bStartChunkCollected:
-                last_chunk += chunk
-                # render accumulated markdown in real-time so user sees content streaming
-                status_ph.markdown(last_chunk)
-            
-            progress_val = min(progress_val + 2, 98)
-            progress_bar.progress(progress_val)
-
-    # run async generator (compatibility fallback)
+            # append chunk
+            st.session_state.full_output += chunk
+
+            # update progress (move forward slowly, final step sets 100)
+            progress_value = min(progress_value + 2, 98)
+            progress_bar.progress(progress_value)
+
+            # render full output inside a styled div that preserves whitespace
+            output_html = f"<div class='report-box'>{st.session_state.full_output}</div>"
+            output_ph.markdown(output_html, unsafe_allow_html=True)
+
+    # run the async generator
     try:
         asyncio.run(_stream())
     except RuntimeError:
+        # If the event loop is already running (e.g., in some environments),
+        # fallback to creating a new loop and running until complete.
         loop = asyncio.new_event_loop()
         asyncio.set_event_loop(loop)
         loop.run_until_complete(_stream())
         loop.close()
-    except Exception as e:
-        # on exception, re-enable button and show error
-        st.session_state.button_disabled = False
-        status_ph.error(f"❌ Error during research: {str(e)}")
-        progress_ph.empty()
-        return
-
-    # finalize
-    progress_bar.progress(100)
-    status_ph.success("✅ Research complete!")
-
-    # set final_report to only the last yield (trim surrounding whitespace)
-    md_text = last_chunk.strip()
-    st.session_state.final_report = md_text
-    progress_ph.empty()
-
-    # re-enable button after completion
-    st.session_state.button_disabled = False
-
-    # history saving disabled (kept minimal in-memory state only)
 
-    # render final output as Markdown into the dedicated placeholder
-    # Use Streamlit's markdown renderer so headings, lists, links render correctly.
-    if st.session_state.final_report:
-        final_ph.markdown(st.session_state.final_report)
-    else:
-        final_ph.empty()
-    
-    # rerun to reflect button re-enable and final output
-    st.rerun()
-
-# Sidebar removed per UI request. Dark-mode and history removed.
+    # final rendering and progress completion
+    progress_bar.progress(100)
+    status_ph.success("✅ Completed research — full report below.")
+    # ensure final full output rendered (in case last chunk didn't render)
+    output_html = f"<div class='report-box'>{st.session_state.full_output}</div>"
+    output_ph.markdown(output_html, unsafe_allow_html=True)
 
 
-# --------------------
-# Main UI
-# --------------------
+# ---------- UI ----------
 st.title("🧠 Deep Research (Powered by Agentic AI)")
-st.write("What topic would you like to research?")
-
-query = st.text_area("Enter your research topic", value="Most popular free MLOps & LLMOps tools in 2025.", height=50, label_visibility="collapsed")
 
-# Action row with buttons
-col1, col2, col3, col4 = st.columns([2.0, 2.0, 2.0, 2.0])
-
-with col1:
-    run_clicked = st.button("🚀 Run Deep Research", key="run", disabled=st.session_state.button_disabled)
-
-# PDF and MD download buttons appear inline after a final_report exists
-if st.session_state.final_report:
-    with col2:
-        # PDF generator stream - create bytes on demand
-        pdf_bytes = make_pdf_bytes(st.session_state.final_report)
-        st.download_button("📄 Download PDF", data=pdf_bytes, file_name="report.pdf", mime="application/pdf")
-    
-    with col3:
-        # Markdown
-        md_bytes = make_md_bytes(st.session_state.final_report)
-        st.download_button("📝 Download MD", data=md_bytes, file_name="report.md", mime="text/markdown")
-
-# placeholder for final report (used so streaming traces can be cleared)
-final_ph = st.empty()
+st.write("What topic would you like to research?")
+query = st.text_area(
+    "",  # no label to keep compact
+    value="The impact of AI on USA stock market performance in 2025.",
+    height=140,
+)
 
-# placeholder for streaming status and progress updates
-status_ph = st.empty()
+# centered run button
+col1, col2, col3 = st.columns([1, 2, 1])
+with col2:
+    run_clicked = st.button("🚀 Run Deep Research", key="run_button", help="Click to start research")
 
-# Run research if requested; disable button on click and re-run
 if run_clicked and query.strip():
-    st.session_state.button_disabled = True
-    st.rerun()
-
-# Execute streaming if button was disabled (i.e., on the rerun after click)
-if st.session_state.button_disabled and query.strip():
-    run_streaming(query.strip(), final_ph, status_ph)
-elif not st.session_state.button_disabled:
-    # if final_report exists (e.g., from previous run), show it in the final placeholder
-    if st.session_state.final_report:
-        # final_ph.markdown(f"<div class='report-box'>{st.session_state.final_report}</div>", unsafe_allow_html=True)
-        final_ph.markdown(st.session_state.final_report, unsafe_allow_html=True)
+    run_streaming(query.strip())
+else:
+    # If we already have previous output, show it (keeps output visible after page reruns)
+    if "full_output" in st.session_state and st.session_state.full_output:
+        output_html = f"<div class='report-box'>{st.session_state.full_output}</div>"
+        st.markdown(output_html, unsafe_allow_html=True)
     else:
-        st.info("Enter a topic and press Run. Final report will replace streaming traces.")
+        st.info("Enter a topic above and press Run to start the research agent.")
 
-# small debug caption
+# Optional: small footer that shows session id for debugging
+st.write("")
 st.caption(f"Session: {st.session_state.session_id}")