allows experimentation with prompts

producer.py

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+import gradio as gr
+import anthropic
+import pandas as pd
+from typing import Tuple, Dict
+from youtube_transcript_api import YouTubeTranscriptApi
+import re
+
+# Initialize Anthropic client
+client = anthropic.Anthropic()
+
+# Default prompts that we can experiment with
+DEFAULT_PROMPTS = {
+    "clips": """You are a social media expert for the Dwarkesh Podcast. Generate 10 viral-worthy clips from the transcript.
+Format as:
+Tweet 1
+Tweet Text: [text]
+Clip Transcript: [45-120 seconds of transcript]
+
+Previous examples:
+{clips_examples}""",
+    "description": """Create an engaging episode description tweet (280 chars max) that:
+1. Highlights compelling aspects
+2. Includes topic areas and handles
+3. Ends with "Links below" or "Enjoy!"
+
+Previous examples:
+{description_examples}""",
+    "timestamps": """Generate timestamps (HH:MM:SS) every 3-8 minutes covering key transitions and moments.
+Use 2-6 word descriptions.
+Start at 00:00:00.
+
+Previous examples:
+{timestamps_examples}""",
+    "titles_and_thumbnails": """Create 3-5 compelling title-thumbnail combinations that tell a story.
+
+Title Format: "Guest Name – Key Story or Core Insight"
+Thumbnail: 2-4 ALL CAPS words that create intrigue with the title
+
+Example: "David Reich – How One Small Tribe Conquered the World 70,000 Years Ago"
+Thumbnail: "LAST HUMANS STANDING"
+
+The combination should create intellectual curiosity without clickbait.
+
+Previous examples:
+{titles_and_thumbnails_examples}""",
+}
+
+# Current prompts used in the session
+current_prompts = DEFAULT_PROMPTS.copy()
+
+
+def load_examples(filename: str, columns: list) -> str:
+    """Load examples from CSV file."""
+    try:
+        df = pd.read_csv(filename)
+        if len(columns) == 1:
+            examples = df[columns[0]].dropna().tolist()
+            return "\n\n".join(examples)
+
+        examples = []
+        for _, row in df.iterrows():
+            if all(pd.notna(row[col]) for col in columns):
+                example = "\n".join(f"{col}: {row[col]}" for col in columns)
+                examples.append(example)
+        return "\n\n".join(examples)
+    except Exception as e:
+        print(f"Error loading {filename}: {str(e)}")
+        return ""
+
+
+def generate_content(
+    prompt_key: str, transcript: str, max_tokens: int = 1000, temp: float = 0.6
+) -> str:
+    """Generate content using Claude."""
+    examples = {
+        "clips": load_examples(
+            "Viral Twitter Clips.csv", ["Tweet Text", "Clip Transcript"]
+        ),
+        "description": load_examples("Viral Episode Descriptions.csv", ["Tweet Text"]),
+        "timestamps": load_examples("Timestamps.csv", ["Timestamps"]),
+        "titles_and_thumbnails": load_examples(
+            "Titles & Thumbnails.csv", ["Titles", "Thumbnail"]
+        ),
+    }
+
+    message = client.messages.create(
+        model="claude-3-5-sonnet-20241022",
+        max_tokens=max_tokens,
+        temperature=temp,
+        system=current_prompts[prompt_key].format(
+            **{f"{prompt_key}_examples": examples[prompt_key]}
+        ),
+        messages=[
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": f"Process this transcript:\n\n{transcript}",
+                    }
+                ],
+            }
+        ],
+    )
+    return message.content[0].text
+
+
+def get_youtube_transcript(url: str) -> str:
+    """Get transcript from YouTube URL."""
+    try:
+        video_id = re.search(
+            r"(?:youtube\.com\/watch\?v=|youtu\.be\/|youtube\.com\/embed\/|youtube\.com\/v\/)([A-Za-z0-9_-]+)",
+            url,
+        ).group(1)
+        transcript = YouTubeTranscriptApi.list_transcripts(video_id).find_transcript(
+            ["en"]
+        )
+        return " ".join(entry["text"] for entry in transcript.fetch())
+    except Exception as e:
+        raise Exception(f"Error fetching YouTube transcript: {str(e)}")
+
+
+def process_transcript(input_text: str) -> Tuple[str, str, str, str]:
+    """Process input and generate all content."""
+    try:
+        # Get transcript from URL or use direct input
+        transcript = (
+            get_youtube_transcript(input_text)
+            if any(x in input_text for x in ["youtube.com", "youtu.be"])
+            else input_text
+        )
+
+        # Generate all content types
+        return (
+            generate_content("clips", transcript, max_tokens=8192),
+            generate_content("description", transcript),
+            generate_content("timestamps", transcript, temp=0.4),
+            generate_content("titles_and_thumbnails", transcript, temp=0.7),
+        )
+    except Exception as e:
+        error_msg = f"Error processing input: {str(e)}"
+        return (error_msg,) * 4
+
+
+def update_prompts(*values) -> str:
+    """Update the current session's prompts."""
+    global current_prompts
+    current_prompts = {
+        "clips": values[0],
+        "description": values[1],
+        "timestamps": values[2],
+        "titles_and_thumbnails": values[3],
+    }
+    return (
+        "Prompts updated for this session! Changes will reset when you reload the page."
+    )
+
+
+def create_interface():
+    """Create the Gradio interface."""
+    with gr.Blocks(title="Podcast Transcript Analyzer") as app:
+        with gr.Tab("Generate Content"):
+            gr.Markdown("# Podcast Content Generator")
+            input_text = gr.Textbox(
+                label="Input", placeholder="YouTube URL or transcript...", lines=10
+            )
+            submit_btn = gr.Button("Generate Content")
+            outputs = [
+                gr.Textbox(label="Twitter Clips", lines=10, interactive=False),
+                gr.Textbox(label="Twitter Description", lines=3, interactive=False),
+                gr.Textbox(label="Timestamps", lines=10, interactive=False),
+                gr.Textbox(
+                    label="Title & Thumbnail Suggestions", lines=10, interactive=False
+                ),
+            ]
+            submit_btn.click(
+                fn=process_transcript, inputs=[input_text], outputs=outputs
+            )
+
+        with gr.Tab("Experiment with Prompts"):
+            gr.Markdown("# Experiment with Prompts")
+            gr.Markdown(
+                """
+            Here you can experiment with different prompts during your session. 
+            Changes will remain active until you reload the page.
+            
+            Tip: Copy your preferred prompts somewhere safe if you want to reuse them later!
+            """
+            )
+
+            prompt_inputs = [
+                gr.Textbox(
+                    label="Clips Prompt", lines=10, value=DEFAULT_PROMPTS["clips"]
+                ),
+                gr.Textbox(
+                    label="Description Prompt",
+                    lines=10,
+                    value=DEFAULT_PROMPTS["description"],
+                ),
+                gr.Textbox(
+                    label="Timestamps Prompt",
+                    lines=10,
+                    value=DEFAULT_PROMPTS["timestamps"],
+                ),
+                gr.Textbox(
+                    label="Titles & Thumbnails Prompt",
+                    lines=10,
+                    value=DEFAULT_PROMPTS["titles_and_thumbnails"],
+                ),
+            ]
+            status = gr.Textbox(label="Status", interactive=False)
+
+            # Update prompts when they change
+            for prompt in prompt_inputs:
+                prompt.change(fn=update_prompts, inputs=prompt_inputs, outputs=[status])
+
+            # Reset button
+            reset_btn = gr.Button("Reset to Default Prompts")
+            reset_btn.click(
+                fn=lambda: (
+                    update_prompts(*DEFAULT_PROMPTS.values()),
+                    *DEFAULT_PROMPTS.values(),
+                ),
+                outputs=[status] + prompt_inputs,
+            )
+
+    return app
+
+
+if __name__ == "__main__":
+    create_interface().launch()