diff --git a/scripts/clip_interrogator_ext.py b/scripts/clip_interrogator_ext.py
index 38dd1df..b9edf15 100644
--- a/scripts/clip_interrogator_ext.py
+++ b/scripts/clip_interrogator_ext.py
@@ -1,3 +1,4 @@
+import csv
 import gradio as gr
 import open_clip
 import os
@@ -10,10 +11,44 @@ from clip_interrogator import Config, Interrogator
 
 from modules import devices, lowvram, script_callbacks, shared
 
-__version__ = '0.0.6'
+__version__ = '0.0.7'
 
 ci = None
 
+BATCH_OUTPUT_MODES = [
+    'Text file for each image',
+    'Single text file with all prompts',
+    'csv file with columns for filenames and prompts',
+]
+
+class BatchWriter:
+    def __init__(self, folder, mode):
+        self.folder = folder
+        self.mode = mode
+        self.csv, self.file = None, None
+        if mode == BATCH_OUTPUT_MODES[1]:
+            self.file = open(os.path.join(folder, 'batch.txt'), 'w', encoding='utf-8')
+        elif mode == BATCH_OUTPUT_MODES[2]:
+            self.file = open(os.path.join(folder, 'batch.csv'), 'w', encoding='utf-8', newline='')
+            self.csv = csv.writer(self.file, quoting=csv.QUOTE_MINIMAL)
+            self.csv.writerow(['filename', 'prompt'])
+
+    def add(self, file, prompt):
+        if self.mode == BATCH_OUTPUT_MODES[0]:
+            txt_file = os.path.splitext(file)[0] + ".txt"
+            with open(os.path.join(self.folder, txt_file), 'w', encoding='utf-8') as f:
+                f.write(prompt)
+        elif self.mode == BATCH_OUTPUT_MODES[1]:
+            self.file.write(f"{prompt}\n")
+        elif self.mode == BATCH_OUTPUT_MODES[2]:
+            self.file.write(f"{file},{prompt}\n")
+            self.csv.writerow([file, prompt])
+
+    def close(self):
+        if self.file is not None:
+            self.file.close()
+
+
 def load(clip_model_name):
     global ci
     if ci is None:
@@ -69,15 +104,15 @@ def image_analysis(image, clip_model_name):
     
     return medium_ranks, artist_ranks, movement_ranks, trending_ranks, flavor_ranks
 
-def interrogate(image, mode):
+def interrogate(image, mode, caption=None):
     if mode == 'best':
-        prompt = ci.interrogate(image)
+        prompt = ci.interrogate(image, caption=caption)
     elif mode == 'caption':
-        prompt = ci.generate_caption(image)
+        prompt = ci.generate_caption(image) if caption is None else caption
     elif mode == 'classic':
-        prompt = ci.interrogate_classic(image)
+        prompt = ci.interrogate_classic(image, caption=caption)
     elif mode == 'fast':
-        prompt = ci.interrogate_fast(image)
+        prompt = ci.interrogate_fast(image, caption=caption)
     elif mode == 'negative':
         prompt = ci.interrogate_negative(image)
     else:
@@ -140,7 +175,7 @@ def analyze_tab():
     button.click(image_analysis, inputs=[image, model], outputs=[medium, artist, movement, trending, flavor])
 
 def batch_tab():
-    def batch_process(folder, model, mode):
+    def batch_process(folder, model, mode, output_mode):
         if not os.path.exists(folder):
             return f"Folder {folder} does not exist"
         if not os.path.isdir(folder):
@@ -163,17 +198,28 @@ def batch_tab():
             shared.total_tqdm.updateTotal(len(files))
             ci.config.quiet = True
 
+            # generate captions in first pass
+            captions = []
             for file in files:
-                image = Image.open(os.path.join(folder, file))
-                prompt = interrogate(image, mode)
-                txt_file = os.path.splitext(file)[0] + ".txt"
-                with open(os.path.join(folder, txt_file), 'w', encoding='utf-8') as f:
-                    f.write(prompt)
-
-                shared.total_tqdm.update()
                 if shared.state.interrupted:
                     break
+                image = Image.open(os.path.join(folder, file))
+                captions.append(ci.generate_caption(image))
+                shared.total_tqdm.update()
 
+            # interrogate in second pass
+            writer = BatchWriter(folder, output_mode)
+            shared.total_tqdm.clear()
+            shared.total_tqdm.updateTotal(len(files))
+            for idx, file in enumerate(files):
+                if shared.state.interrupted:
+                    break
+                image = Image.open(os.path.join(folder, file))
+                prompt = interrogate(image, mode, caption=captions[idx])
+                writer.add(file, prompt)
+                shared.total_tqdm.update()
+
+            writer.close()
             ci.config.quiet = False
             unload()
         except torch.cuda.OutOfMemoryError as e:
@@ -189,13 +235,14 @@ def batch_tab():
             folder = gr.Text(label="Images folder", value="", interactive=True)
         with gr.Row():
             model = gr.Dropdown(get_models(), value='ViT-L-14/openai', label='CLIP Model')
-            mode = gr.Radio(['caption', 'best', 'fast', 'classic', 'negative'], label='Mode', value='fast')
+            mode = gr.Radio(['caption', 'best', 'fast', 'classic', 'negative'], label='Prompt Mode', value='fast')
+            output_mode = gr.Dropdown(BATCH_OUTPUT_MODES, value=BATCH_OUTPUT_MODES[0], label='Output Mode')
         with gr.Row():        
             button = gr.Button("Go!", variant='primary')
             interrupt = gr.Button('Interrupt', visible=True)
             interrupt.click(fn=lambda: shared.state.interrupt(), inputs=[], outputs=[])
 
-    button.click(batch_process, inputs=[folder, model, mode], outputs=[])
+    button.click(batch_process, inputs=[folder, model, mode, output_mode], outputs=[])
 
 def prompt_tab():
     with gr.Column():