Create app.py

app.py

@@ -0,0 +1,54 @@
+import streamlit as st
+from src.crew_initializer import initialize_crew
+from src.utils.pdf_generator import generate_pdf
+import json
+import logging
+
+# Configure logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+# Custom JSON Encoder
+class CustomJSONEncoder(json.JSONEncoder):
+    def default(self, obj):
+        try:
+            # Convert objects with __dict__ attributes to dictionaries
+            if hasattr(obj, "__dict__"):
+                return obj.__dict__
+            return super().default(obj)
+        except TypeError:
+            return str(obj)  # Fallback for unsupported types
+
+def main():
+    """
+    Main entry point for the Streamlit application.
+    Handles user input, executes tasks, and displays results.
+    """
+    st.title("Company Researcher Tool")
+
+    st.sidebar.header("Provide Company Details")
+    company_name = st.sidebar.text_input("Enter the Company Name:", "")
+
+    if st.sidebar.button("Run Analysis"):
+        st.write(f"### Running analysis for: {company_name}")
+
+        with st.spinner("Executing tasks, please wait..."):
+            try:
+                crew = initialize_crew()
+                result = crew.kickoff(inputs={"company": company_name})
+                result_serialized = json.loads(json.dumps(result,cls=CustomJSONEncoder))
+                st.success("Analysis Complete!")
+                st.json(result_serialized)
+
+                pdf_buffer = generate_pdf(result_serialized)
+                st.download_button(
+                    label="📄 Download Report (PDF)",
+                    data=pdf_buffer,
+                    file_name=f"{company_name}_report.pdf",
+                    mime="application/pdf"
+                )
+            except Exception as e:
+                logging.error(f"Error during analysis: {str(e)}")
+                st.error(f"An error occurred: {str(e)}")
+
+if __name__ == "__main__":
+    main()