Update app.py

app.py

@@ -206,3 +206,109 @@ def retrieval(query: str):
             return {"results": "No relevant match found in ChromaDB."}
     except Exception as e:
         return {"error": str(e)}
+
+import pandas as pd
+from io import StringIO 
+import os
+import base64
+@app.get("/save_file_dify")
+def save_file_dify(csv_data: str):    
+    
+    # Split into lines
+    lines = csv_data.split("\n")
+
+    # Find the max number of columns
+    max_cols = max(line.count(",") + 1 for line in lines if line.strip())
+
+    # Normalize all rows to have the same number of columns
+    fixed_lines = [line + "," * (max_cols - line.count(",") - 1) for line in lines]
+
+    # Reconstruct CSV string
+    fixed_csv_data = "\n".join(fixed_lines)
+    
+    # Convert CSV string to DataFrame
+    df = pd.read_csv(StringIO(fixed_csv_data))
+
+    
+    #save in dify dataset and return download link
+    download_link = get_download_link_dify(df)
+        
+    return download_link
+    
+
+def get_download_link_dify(df):
+    # code to save file in dify framework
+    import requests
+
+    # API Configuration
+    BASE_URL = "http://redmindgpt.redmindtechnologies.com:81/v1"
+    DATASET_ID = "084ae979-d101-414b-8854-9bbf5d3a442e" 
+    API_KEY = "dataset-feqz5KrqHkFRdWbh2DInt58L"  
+
+    dataset_name = 'output_dataset'
+    # Endpoint URL
+    url = f"{BASE_URL}/datasets/{DATASET_ID}/document/create-by-file"
+    print(url)
+    # Headers
+    headers = {
+        "Authorization": f"Bearer {API_KEY}"
+    }
+
+    # Data payload (form data as a plain text string)
+    data_payload = {
+        "data": """
+        {
+            "indexing_technique": "high_quality",
+            "process_rule": {
+                "rules": {
+                    "pre_processing_rules": [
+                        {"id": "remove_extra_spaces", "enabled": true},
+                        {"id": "remove_urls_emails", "enabled": true}
+                    ],
+                    "segmentation": {
+                        "separator": "###",
+                        "max_tokens": 500
+                    }
+                },
+                "mode": "custom"
+            }
+        }
+        """
+    }
+
+    # Convert DataFrame to binary (in-memory)
+    file_buffer = dataframe_to_binary(df)
+    
+    files = {
+        "file": ("output.xlsx", file_buffer, "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet")
+    }
+
+    # Send the POST request
+    response = requests.post(url, headers=headers, data=data_payload, files=files)
+    print(response)
+    data = response.json()
+    document_id = data['document']['id']
+
+    # code to get download_url
+    url = f"http://redmindgpt.redmindtechnologies.com:81/v1/datasets/{DATASET_ID}/documents/{document_id}/upload-file"
+   
+    response = requests.get(url, headers=headers)
+    print(response)
+    
+    download_url = response.json().get("download_url")
+    download_url = download_url.replace("download/","")
+    return download_url
+
+def dataframe_to_binary(df):
+    import io
+    # Create a BytesIO stream
+    output = io.BytesIO()
+    
+    # Write the DataFrame to this in-memory buffer as an Excel file
+    df.to_excel(output, index=False, engine="openpyxl")
+    
+    # Move the cursor to the beginning of the stream
+    output.seek(0)
+    
+    return output
+