Create app.py

app.py

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+import fitz  # PyMuPDF
+import os
+import json
+import gradio as gr
+from groq import Groq
+
+# 🔐 Initialize Groq Client
+client = Groq(api_key=os.getenv("GROQ_API_KEY"))
+
+def extract_form_fields(pdf_bytes):
+    doc = fitz.open(stream=pdf_bytes, filetype="pdf")
+    form_fields = {}
+    for page in doc:
+        widgets = page.widgets()
+        if widgets:
+            for widget in widgets:
+                key = widget.field_name
+                value = widget.field_value if widget.field_value else ""
+                form_fields[key] = value
+    return form_fields
+
+def get_pdf_text(pdf_bytes):
+    doc = fitz.open(stream=pdf_bytes, filetype="pdf")
+    return "\n".join([page.get_text() for page in doc])
+
+def get_field_details(form_fields, pdf_text):
+    prompt = f"""
+You are an expert at analyzing and auto-filling PDF form fields. 
+Here is the extracted PDF text:
+{pdf_text}
+
+Based on this, explain the meaning or expected value of each of the following fields in JSON format:
+
+{json.dumps(list(form_fields.keys()), indent=2)}
+
+Return your output in the following JSON format:
+{{ "field_name_1": "description", "field_name_2": "description", ... }}
+    """
+    response = client.chat.completions.create(
+        model="llama3-8b-8192",
+        messages=[{"role": "user", "content": prompt}]
+    )
+
+    return response.choices[0].message.content
+
+def analyze_form(pdf_file):
+    if not pdf_file:
+        return "❌ No file provided.", "", ""
+
+    try:
+        pdf_bytes = pdf_file.read()
+        fields = extract_form_fields(pdf_bytes)
+        pdf_text = get_pdf_text(pdf_bytes)
+        explanation = get_field_details(fields, pdf_text)
+
+        return "✅ Analysis complete.", json.dumps(fields, indent=2), explanation
+    except Exception as e:
+        return f"❌ Error: {str(e)}", "", ""
+
+# 🎨 Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("## 📄 Form Field Analyzer")
+    gr.Markdown("Upload a **tax or registration PDF form**. This tool extracts fillable fields and describes what each might represent.")
+
+    with gr.Row():
+        file_input = gr.File(label="Upload PDF", file_types=[".pdf"])
+        analyze_btn = gr.Button("Analyze Form")
+
+    status_output = gr.Textbox(label="Status")
+    fields_output = gr.Code(label="📋 Extracted Fields (JSON)", language="json")
+    desc_output = gr.Code(label="💡 Field Descriptions (LLM Response)", language="json")
+
+    analyze_btn.click(fn=analyze_form, inputs=[file_input], outputs=[status_output, fields_output, desc_output])
+
+demo.launch()