YouTube Automation: Build a Text to Speech AI Agent (2026)
Learn how to build a 24/7 YouTube Automation workflow using a Text to Speech AI Agent. Scale your faceless channel with automated scripts and voices.top manual editing. Build a self-reasoning TTS AI Agent for YouTube Automation. Master the 2026 'Agentic' workflow to produce high-quality, faceless content.
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import ollama
import re
import edge_tts
import asyncio
class YoutScriptAgent:
def __init__(self,model="qwen3:1.7b"):
self.model = model
self.voice = "en-US-AndrewNeural"
def generate_script(self,topic,traget_audience,duration_mins):
prompt = f"""
You are an expert YouTube Scriptwriter. Your goal is to write a high-retention script.
TOPIC: {topic}
TARGET AUDIENCE: {traget_audience}
ESTIMATED DURATION: {duration_mins} minutes
Structure the script as follows:
1. **The Hook (0:00-0:45)**: Grab attention immediately.
2. **The Intro**: Briefly explain what they will learn.
3. **Main Content**: Break down into 3-5 clear points. Include visual cues in [brackets].
4. **The CTA**: Naturally lead into a call to action.
5. **Outro**: Wrap up and suggest another video.
Write in a conversational, high-energy tone.
"""
response = ollama.chat(
model = self.model,
messages = [{"role":"user","content":prompt}]
)
script_text = response['message']['content']
script_text = re.sub(r'\*|\[.*?\]', '',script_text)
return script_text.strip()
async def generate_voice(self,text,output_file="output.mp3"):
print("step 2 - generating voice")
communicate = edge_tts.Communicate(text,self.voice)
await communicate.save(output_file)
if __name__ == "__main__":
agent = YoutScriptAgent()
topic = "The Future of AI: 5 Mind Blowing predications"
raw_script = agent.generate_script(topic,"Tech Enthusaists",2)
print("step 1 - generated script")
print(raw_script[:200])
asyncio.run(agent.generate_voice(raw_script))
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