Update app_chatgpt.py

app_chatgpt.py

@@ -7,8 +7,35 @@ import pytesseract
 import io
 import os
 import gradio as gr
+import boto3
+import uuid
 
 openai.api_key = os.environ.get("Open_ai_key")
+bucket_name = os.environ.get("Bucket_name")
+
+session = boto3.Session(
+    aws_access_key_id=os.getenv("AWS_ACCESS_KEY_ID"),
+    aws_secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY")
+)
+
+
+def upload_files_to_s3(erp_file_path, external_file_path, bucket_name):
+    s3 = session.client("s3")
+    session_id = str(uuid.uuid4())
+
+    # Append UUID to filenames
+    erp_filename = f"{os.path.splitext(os.path.basename(erp_file_path))[0]}_{session_id}{os.path.splitext(erp_file_path)[1]}"
+    external_filename = f"{os.path.splitext(os.path.basename(external_file_path))[0]}_{session_id}{os.path.splitext(external_file_path)[1]}"
+
+    # Upload files
+    s3.upload_file(erp_file_path, bucket_name, erp_filename)
+    s3.upload_file(external_file_path, bucket_name, external_filename)
+
+    return {
+        "erp_s3_key": erp_filename,
+        "external_s3_key": external_filename
+    }
+
 
 def extract_transactions(file):
     """Extract raw text content from various supported file formats."""
@@ -46,51 +73,41 @@ def reconcile_statements_openai(erp_file, external_file):
     yield "⏳ Processing your request...", ""
 
     try:
+        s3_info = upload_files_to_s3(
+            erp_file_path=erp_file,
+            external_file_path=external_file,
+            bucket_name=bucket_name
+        )
         erp_data = extract_transactions(erp_file)
         external_data = extract_transactions(external_file)
 
-
         prompt = f"""
 You are a financial analyst specializing in account reconciliations. Your task is to compare two data sets: one from an ERP system and the other from a 
-
 Bank or Vendor statement.
-
 The goal is to identify which transactions match across both data sets, and which transactions are unmatched or potentially erroneous.
-
 Each dataset contains transaction entries with **Date**, **Amount**, and **Description**.
-
 ERP descriptions may include prefixes like "Vendor Payment - ", while external descriptions are simpler.
 Please attempt to normalize and fuzzy-match transactions by:
 - Ignoring common prefixes/suffixes
 - Allowing for small amount rounding differences (±$0.01–$1)
 - Matching based on partial vendor or keyword overlaps
 .
-
 ---
-
 Please follow this format in your response:
-
 1. 📘 **Introduction**  
    Briefly explain what reconciliation means and how you'll approach it.
-
 2. ✅ **Matched Transactions**  
    Make a table to show side by side comparison of matched transactions
-
 3. 🏦 **Unmatched Bank Transactions**  
    List any transactions found in 
    a. External file but not in the ERP file OR 
    b. ERP file but Not in External file
-
 4. 🧾 **Summary & Suggested Next Steps**  
    Explain what the discrepancies might mean and what the user should do next.
-
 ---
-
 Here is the ERP data:
 {erp_data}
-
 ---
-
 Here is the External (Bank or Vendor) data::
 {external_data}
 """
@@ -98,7 +115,8 @@ Here is the External (Bank or Vendor) data::
         response = openai.ChatCompletion.create(
             model="gpt-4",
             messages=[
-                {"role": "system", "content": "You are a financial analyst who specializes in reconciling financial data."},
+                {"role": "system",
+                 "content": "You are a financial analyst who specializes in reconciling financial data."},
                 {"role": "user", "content": prompt}
             ],
             temperature=0.2,
@@ -117,6 +135,7 @@ Here is the External (Bank or Vendor) data::
     except Exception as e:
         yield "❌ Error occurred", f"<h3>Error</h3><pre>{e}</pre>"
 
+
 # Gradio UI
 with gr.Blocks(css="""
 #company-logo {
@@ -138,9 +157,8 @@ with gr.Blocks(css="""
         )
         support_email_display = gr.Markdown("📬 Or email us at: `[email protected]` (copy & paste)")
 
-    #support_btn = gr.Button("📧 Contact Support: [email protected]", link="mailto:[email protected]?subject=Support%20Request&body=Hi%20Beiing%20Human%20Team%2C%0A%0AI%20have%20a%20question%20about%20the%20reconciliation%20tool.%20Here%20are%20the%20details...")
+    # support_btn = gr.Button("📧 Contact Support: [email protected]", link="mailto:[email protected]?subject=Support%20Request&body=Hi%20Beiing%20Human%20Team%2C%0A%0AI%20have%20a%20question%20about%20the%20reconciliation%20tool.%20Here%20are%20the%20details...")
 
-    
     status = gr.Markdown()
     result = gr.HTML()
 
@@ -150,4 +168,4 @@ with gr.Blocks(css="""
         outputs=[status, result]
     )
 
-iface.launch()
+iface.launch()