Update app.py

app.py

@@ -46,10 +46,19 @@ def run_single_test(endpoint, method, bearer_token,
 
         data, json_payload = None, None
         if payload and isinstance(payload, str) and payload.strip():
-            try:
-                json_payload = json.loads(payload)
-            except Exception:
-                data = payload
+            if payload.lower().startswith("header:"):
+                try:
+                    kv = payload.split(":",1)[1]
+                    key, value = kv.split("=",1)
+                    headers[key.strip()] = value.strip().strip('"')
+                except Exception:
+                    result['Notes'] = f'Invalid header format: {payload}'
+                    return result
+            else:
+                try:
+                    json_payload = json.loads(payload)
+                except Exception:
+                    data = payload
 
         if method.upper() == 'GET':
             response = requests.get(endpoint, headers=headers, timeout=10)
@@ -102,8 +111,6 @@ def run_single_test(endpoint, method, bearer_token,
             else:
                 result['Outcome'] = 'UNCERTAIN'
                 result['Notes'] = f'Low similarity: {similarity:.1%}'
-                result['Outcome'] = 'UNCERTAIN'
-                result['Notes'] = f'Low similarity: {similarity:.1%}'
         except Exception as sim_error:
             result['Outcome'] = 'UNCERTAIN'
             result['Notes'] = f'Cannot compute similarity: {str(sim_error)}'
@@ -121,20 +128,23 @@ def run_single_test(endpoint, method, bearer_token,
         return result
 
 def normalize_to_csv(file):
-    filename = file.name if hasattr(file, "name") else str(file)
+    filename = file if isinstance(file, str) else getattr(file, "name", None)
     ext = os.path.splitext(filename)[1].lower()
     try:
         if ext in [".xlsx", ".xlsm", ".xls"]:
-            df = pd.read_excel(filename, engine="openpyxl")
-        else:
+            df = pd.read_excel(file, engine="openpyxl")
+        elif ext == ".csv":
+            df = pd.read_csv(file, encoding="utf-8")
+        elif ext in [".tsv", ".txt"]:
             try:
-                df = pd.read_csv(filename, sep="\t", encoding="utf-8")
+                df = pd.read_csv(file, sep="\t", encoding="utf-8")
             except UnicodeDecodeError:
-                df = pd.read_csv(filename, sep="\t", encoding="latin1")
-    except Exception:
-        df = pd.read_csv(filename, sep="\t", encoding="latin1")
+                df = pd.read_csv(file, sep="\t", encoding="latin1")
+        else:
+            raise ValueError(f"Unsupported file type: {ext}")
+    except Exception as e:
+        raise RuntimeError(f"Error reading file: {e}")
 
-    # Normalize headers
     df.columns = [c.strip() for c in df.columns]
     return df
 
@@ -144,7 +154,7 @@ def process_file(file, bearer_token: str):
         required_columns = ['Endpoint', 'Method', 'ExpectedStatus', 'ExpectedBody']
         missing = [c for c in required_columns if c not in df.columns]
         if missing:
-            return None, f"❌ Missing columns: {', '.join(missing)}"
+            return pd.DataFrame([{"Outcome":"ERROR","Notes":f"Missing columns: {', '.join(missing)}"}]), f"❌ Missing columns: {', '.join(missing)}"
 
         results = []
         for _, row in df.iterrows():
@@ -168,7 +178,7 @@ def process_file(file, bearer_token: str):
         """
         return results_df, summary
     except Exception as e:
-        return None, f"❌ Error processing file: {str(e)}"
+        return pd.DataFrame([{"Outcome":"ERROR","Notes":str(e)}]), f"❌ Error processing file: {str(e)}"
 
 def download_results(df):
     if df is None or df.empty:
@@ -202,11 +212,11 @@ with gr.Blocks(css="* { font-family: 'Times New Roman', serif; }") as app:
 
     def run_with_feedback(file, token):
         df, summary = process_file(file, token)
-        return df, summary, "✅ Tests started..."
+        return df, summary
 
     token_input.change(fn=lambda t: t, inputs=token_input, outputs=token_state)
     run_button.click(fn=run_with_feedback, inputs=[file_input, token_state],
-                     outputs=[results_output, summary_output, run_button])
+                     outputs=[results_output, summary_output])
     download_button.click(fn=download_results, inputs=[results_output], outputs=[download_output])
 
 if __name__ == "__main__":