Update app.py

app.py

@@ -8,14 +8,14 @@ import json
 # Load your custom NER model
 nlp_ner = spacy.load("ner_model_v1")
 
-def send_results_to_api(data, result_url):
+# def send_results_to_api(data, result_url):
 
-    headers = {"Content-Type": "application/json"}
-    response = requests.post(result_url, json=data, headers=headers)
-    if response.status_code == 200:
-        return response.json()  # Return any response from the API if needed
-    else:
-        return {"error": f"Failed to send results to API: {response.status_code}"}
+#     headers = {"Content-Type": "application/json"}
+#     response = requests.post(result_url, json=data, headers=headers)
+#     if response.status_code == 200:
+#         return response.json()  # Return any response from the API if needed
+#     else:
+#         return {"error": f"Failed to send results to API: {response.status_code}"}
 
 def process_xlsx(params):
     # xlsx_file = 'https://fragilestatesindex.org/wp-content/uploads/2023/06/FSI-2023-DOWNLOAD.xlsx'
@@ -24,9 +24,9 @@ def process_xlsx(params):
     except json.JSONDecodeError as e:
         return {"error": f"Invalid JSON input: {e.msg} at line {e.lineno} column {e.colno}"}
 
-    addresses = params.get("text_list", [])
-    api = params.get("api", "")
-    job_id = params.get("job_id", "")
+    addresses = params.get("texts", [])
+    # api = params.get("api", "")
+    # job_id = params.get("job_id", "")
 
     solutions=[]
     text_id = 0
@@ -43,23 +43,21 @@ def process_xlsx(params):
             entities_dict[ent.label_].append({'word': ent.text, 'index': idx})
 
         # Create the final output dictionary
-        output = {
-            'text': adress,
-            'text_id': text_id,
-            'answer': entities_dict
-        }
-        solutions.append(output)
+        # 
+        output = {'text_id': text_id, 'answer': entities_dict}
+        obj = {"text": adress, "answer":output}
+        solutions.append(obj)
         text_id = text_id+1
         
-    result_url = f"{api}/{job_id}"
-    send_results_to_api(solutions, result_url)
+    # result_url = f"{api}/{job_id}"
+    # send_results_to_api(solutions, result_url)
 
-    return json.dumps({"solutions": solutions}, indent=4)
+    return json.dumps({"solutions": solutions})
 
 
 import gradio as gr
-inputt = gr.Textbox(label="Parameters (JSON format) Eg. {'audio_files':['file1.mp3','file2.wav'], 'api':'https://api.example.com', 'job_id':'1001'}")
+inputt = gr.Textbox(label="Parameters (JSON format) Eg. {'texts':['file1.mp3','file2.wav']}")
 outputs = gr.JSON()
 
 application = gr.Interface(fn=process_xlsx, inputs=inputt, outputs=outputs, title="Named Entity Recognition with API Integration")
-application.launch(share=True)
+application.launch()