generates previews

app.py

@@ -29,10 +29,11 @@ class TranscriptProcessor:
 
             # Define content generation requests
             requests = [
+                ContentRequest("previews", max_tokens=8192),
                 ContentRequest("clips", max_tokens=8192),
                 ContentRequest("description"),
-                ContentRequest("timestamps", temperature=0.4),
-                ContentRequest("titles_and_thumbnails", temperature=0.7),
+                ContentRequest("timestamps"),
+                ContentRequest("titles_and_thumbnails"),
             ]
 
             # Generate all content concurrently
@@ -42,12 +43,12 @@ class TranscriptProcessor:
             return tuple(results)
 
         except Exception as e:
-            return (f"Error processing input: {str(e)}",) * 4
+            return (f"Error processing input: {str(e)}",) * 5
 
     def update_prompts(self, *values) -> str:
         """Update the current session's prompts."""
         self.generator.current_prompts.update(zip(
-            ["clips", "description", "timestamps", "titles_and_thumbnails"],
+            ["previews", "clips", "description", "timestamps", "titles_and_thumbnails"],
             values
         ))
         return "Prompts updated for this session!"
@@ -63,7 +64,7 @@ def create_interface():
             submit_btn = gr.Button("Generate Content")
             outputs = [
                 gr.Textbox(label=label, lines=10, interactive=False)
-                for label in ["Twitter Clips", "Twitter Description", "Timestamps", "Title & Thumbnail Suggestions"]
+                for label in ["Preview Clips", "Twitter Clips", "Twitter Description", "Timestamps", "Title & Thumbnail Suggestions"]
             ]
             
             async def process_wrapper(text):
@@ -83,6 +84,9 @@ def create_interface():
             )
 
             prompt_inputs = [
+                gr.Textbox(
+                    label="Preview Clips Prompt", lines=10, value=processor.generator.current_prompts["previews"]
+                ),
                 gr.Textbox(
                     label="Clips Prompt", lines=10, value=processor.generator.current_prompts["clips"]
                 ),

prompts/previews.txt

@@ -6,7 +6,7 @@ You are a podcast producer tasked with selecting 5-10 short, engaging clips for
 - Represent interesting moments, revelations, or powerful statements
 - Work well together to give a taste of the episode's best content
 
-Please listen to the audio and suggest 5-10 clips that would make great preview material. For each suggestion:
+Please suggest 5-10 clips that would make great preview material. For each suggestion:
 1. Note the timestamp where the clip occurs
 2. Quote the relevant dialogue
 3. Briefly explain why this would make a good preview clip

utils/content_generator.py

@@ -13,7 +13,7 @@ client = anthropic.Anthropic()
 class ContentRequest:
     prompt_key: str
     max_tokens: int = 2000
-    temperature: float = 0.6
+    temperature: float = 1.0
 
 class ContentGenerator:
     def __init__(self):
@@ -23,7 +23,7 @@ class ContentGenerator:
         """Load default prompts from files."""
         return {
             key: Path(f"prompts/{key}.txt").read_text()
-            for key in ["clips", "description", "timestamps", "titles_and_thumbnails"]
+            for key in ["previews", "clips", "description", "timestamps", "titles_and_thumbnails"]
         }
 
     def _load_examples(self, filename: str, columns: List[str]) -> str: