Create app.py

app.py

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+#=================
+# Import Libraries
+#=================
+
+import streamlit as st
+from crewai import Agent, Task, Crew
+import os
+
+from fpdf import FPDF
+import pandas as pd
+import plotly.express as px
+import time
+
+#=================
+# Add Streamlit Components
+#=================
+
+# Background
+page_bg_img = '''
+<style>
+.stApp  {
+background-image: url("https://images.all-free-download.com/images/graphiclarge/abstract_bright_corporate_background_310453.jpg");
+background-size: cover;
+}
+</style>
+'''
+st.markdown(page_bg_img, unsafe_allow_html=True)
+
+# Title and Sidebar
+st.title("AI Business Consultant")
+
+image_url = "https://cdn-icons-png.flaticon.com/512/1998/1998614.png"
+st.sidebar.image(image_url, caption="", use_column_width=True)
+st.sidebar.write(
+    "This AI Business Consultant is built using an AI Multi-Agent system. "
+    "It provides business insights, statistical analysis, and professional recommendations!"
+)
+
+# User Inputs
+business = st.text_input('Enter The Required Business Search Area', value="Artificial Intelligence")
+stakeholder = st.text_input('Enter The Stakeholder Team', value="Executives")
+
+# Optional Customization
+enable_customization = st.sidebar.checkbox("Enable Advanced Agent Customization")
+if enable_customization:
+    st.sidebar.markdown("### Customize Agent Goals")
+    planner_goal = st.sidebar.text_area(
+        "Planner Goal",
+        value="Plan engaging and factually accurate content about the topic."
+    )
+    writer_goal = st.sidebar.text_area(
+        "Writer Goal",
+        value="Write insightful and engaging content based on the topic."
+    )
+    analyst_goal = st.sidebar.text_area(
+        "Analyst Goal",
+        value="Perform statistical analysis to extract actionable insights."
+    )
+else:
+    planner_goal = "Plan engaging and factually accurate content about the topic."
+    writer_goal = "Write insightful and engaging content based on the topic."
+    analyst_goal = "Perform statistical analysis to extract actionable insights."
+
+#=================
+# LLM Object and API Key
+#=================
+llm = ChatGroq(groq_api_key=os.getenv("GROQ_API_KEY"), model_name="llama-3.2-90b-text-preview")
+
+#=================
+# Crew Agents
+#=================
+
+planner = Agent(
+    role="Business Consultant",
+    goal=planner_goal,
+    backstory=(
+        "You're tasked with providing insights about {topic} to the stakeholder: {stakeholder}. "
+        "Your work will form the foundation for the Business Writer and Data Analyst."
+    ),
+    allow_delegation=False,
+    verbose=True,
+    llm=llm
+)
+
+writer = Agent(
+    role="Business Writer",
+    goal=writer_goal,
+    backstory=(
+        "You will write a professional insights document about {topic}, "
+        "based on the Business Consultant's plan and the Data Analyst's results."
+    ),
+    allow_delegation=False,
+    verbose=True,
+    llm=llm
+)
+
+analyst = Agent(
+    role="Data Analyst",
+    goal=analyst_goal,
+    backstory=(
+        "You will perform statistical analysis on {topic}, based on the Business Consultant's plan. "
+        "Your analysis will support the Business Writer's final document for {stakeholder}."
+    ),
+    allow_delegation=False,
+    verbose=True,
+    llm=llm
+)
+
+#=================
+# Crew Tasks
+#=================
+
+plan = Task(
+    description=(
+        "1. Research trends, key players, and noteworthy news for {topic}.\n"
+        "2. Provide structured insights and actionable recommendations.\n"
+        "3. Suggest strategies for dealing with international operators.\n"
+        "4. Limit content to 500 words."
+    ),
+    expected_output="A comprehensive consultancy document with insights and recommendations.",
+    agent=planner
+)
+
+write = Task(
+    description=(
+        "1. Use the Business Consultant's plan to write a professional document for {topic}.\n"
+        "2. Structure the content with engaging sections and visuals.\n"
+        "3. Ensure alignment with the stakeholder's goals.\n"
+        "4. Limit the document to 200 words."
+    ),
+    expected_output="A professional document tailored for {stakeholder}.",
+    agent=writer
+)
+
+analyse = Task(
+    description=(
+        "1. Perform statistical analysis to provide actionable insights for {topic}.\n"
+        "2. Collaborate with the Business Consultant and Writer to align on key metrics.\n"
+        "3. Present findings in a format suitable for inclusion in the final document."
+    ),
+    expected_output="A data-driven analysis tailored for {stakeholder}.",
+    agent=analyst
+)
+
+#=================
+# Execution
+#=================
+
+crew = Crew(
+    agents=[planner, analyst, writer],
+    tasks=[plan, analyse, write],
+    verbose=2
+)
+
+def generate_pdf_report(result):
+    """Generate a professional PDF report from the Crew output."""
+    pdf = FPDF()
+    pdf.add_page()
+    pdf.set_font("Arial", size=12)
+    pdf.set_auto_page_break(auto=True, margin=15)
+
+    # Title
+    pdf.set_font("Arial", size=16, style="B")
+    pdf.cell(200, 10, txt="AI Business Consultant Report", ln=True, align="C")
+    pdf.ln(10)
+
+    # Content
+    pdf.set_font("Arial", size=12)
+    pdf.multi_cell(0, 10, txt=result)
+
+    # Save PDF
+    report_path = "Business_Insights_Report.pdf"
+    pdf.output(report_path)
+    return report_path
+
+if st.button("Run Analysis"):
+    with st.spinner('Executing analysis...'):
+        try:
+            start_time = time.time()
+            result = crew.kickoff(inputs={"topic": business, "stakeholder": stakeholder})
+            execution_time = time.time() - start_time
+
+            # Display Results
+            st.markdown("### Insights and Analysis")
+            st.write(result)
+
+            # Display Execution Time
+            st.success(f"Analysis completed in {execution_time:.2f} seconds!")
+
+            # Visualization Example
+            st.markdown("### Data Visualization Example")
+            data = pd.DataFrame({
+                "Metric": ["Trend 1", "Trend 2", "Trend 3"],
+                "Value": [45, 80, 65]
+            })
+            fig = px.bar(data, x="Metric", y="Value", title="Sample Metrics for Analysis")
+            st.plotly_chart(fig)
+
+            # Generate and Provide PDF Report
+            report_path = generate_pdf_report(result)
+            with open(report_path, "rb") as file:
+                st.download_button(
+                    label="Download Report as PDF",
+                    data=file,
+                    file_name="Business_Insights_Report.pdf",
+                    mime="application/pdf"
+                )
+
+        except Exception as e:
+            st.error(f"An error occurred during execution: {e}")