mirror of
https://github.com/aljazceru/vibeline.git
synced 2026-01-17 21:44:36 +01:00
Move Python code into separate files for better organization
This commit is contained in:
Gigi
83
src/extract.py
Executable file
83
src/extract.py
Executable file
@@ -0,0 +1,83 @@
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#!/usr/bin/env python3
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import sys
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import ollama
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import re
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from pathlib import Path
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import time
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def determine_content_type(transcript_text: str) -> str:
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"""Determine the type of content in the transcript."""
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text = transcript_text.lower()
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if re.search(r'\bblog post\b', text) or re.search(r'\bdraft\b', text):
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return "blog_post"
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elif re.search(r'\bidea\b', text) and re.search(r'\bapp\b', text):
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return "idea_app"
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return "default"
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def generate_additional_content(content_type: str, transcript_text: str) -> str:
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"""Generate additional content based on the content type."""
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prompt_dir = Path("prompts")
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with open(prompt_dir / f"{content_type}.md", 'r', encoding='utf-8') as f:
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prompt_template = f.read()
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prompt = prompt_template.format(transcript=transcript_text)
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response = ollama.chat(model='llama2', messages=[
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{
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'role': 'user',
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'content': prompt
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}
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])
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return response['message']['content'].strip()
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def main():
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if len(sys.argv) != 2:
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print("Usage: python extract.py <transcript_file>")
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sys.exit(1)
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input_file = Path(sys.argv[1])
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if not input_file.exists():
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print(f"Error: File {input_file} does not exist")
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sys.exit(1)
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# Set up directory paths
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voice_memo_dir = Path("VoiceMemos")
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draft_dir = voice_memo_dir / "drafts"
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prompt_dir = voice_memo_dir / "prompts"
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# Create output directories if they don't exist
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draft_dir.mkdir(parents=True, exist_ok=True)
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prompt_dir.mkdir(parents=True, exist_ok=True)
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print(f"Processing transcript: {input_file}")
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print("Extracting content...")
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# Read transcript
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with open(input_file, 'r', encoding='utf-8') as f:
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transcript_text = f.read()
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# Determine content type and generate content if needed
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content_type = determine_content_type(transcript_text)
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if content_type != "default":
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print(f" Generating {content_type} content...")
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additional_content = generate_additional_content(content_type, transcript_text)
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# Save to appropriate directory with timestamp
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timestamp = time.strftime("%Y%m%d_%H%M%S")
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filename = input_file.stem
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if content_type == "blog_post":
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output_file = draft_dir / f"{filename}_{timestamp}.md"
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else: # idea_app
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output_file = prompt_dir / f"{filename}_{timestamp}.md"
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with open(output_file, 'w', encoding='utf-8') as f:
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f.write(additional_content)
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print(f" Content saved to: {output_file}")
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else:
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print(" No blog post or app idea content detected")
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print("----------------------------------------")
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if __name__ == "__main__":
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main()
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@@ -15,77 +15,11 @@ if [ ! -f "$input_file" ]; then
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exit 1
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fi
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# Set the directory paths
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VOICE_MEMO_DIR="VoiceMemos"
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DRAFT_DIR="$VOICE_MEMO_DIR/drafts"
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PROMPT_DIR="$VOICE_MEMO_DIR/prompts"
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# Create output directories if they don't exist
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mkdir -p "$DRAFT_DIR"
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mkdir -p "$PROMPT_DIR"
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echo "Processing transcript: $input_file"
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echo "Extracting content..."
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# Activate the virtual environment
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source vibenv/bin/activate
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# Run the Python script to extract content
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python -c "
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import ollama
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import re
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from pathlib import Path
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import time
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def determine_content_type(transcript_text: str) -> str:
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text = transcript_text.lower()
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if re.search(r'\bblog post\b', text) or re.search(r'\bdraft\b', text):
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return 'blog_post'
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elif re.search(r'\bidea\b', text) and re.search(r'\bapp\b', text):
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return 'idea_app'
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return 'default'
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def generate_additional_content(content_type: str, transcript_text: str) -> str:
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prompt_dir = Path('prompts')
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with open(prompt_dir / f'{content_type}.md', 'r', encoding='utf-8') as f:
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prompt_template = f.read()
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prompt = prompt_template.format(transcript=transcript_text)
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response = ollama.chat(model='llama2', messages=[
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{
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'role': 'user',
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'content': prompt
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}
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])
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return response['message']['content'].strip()
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# Read transcript
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with open('$input_file', 'r', encoding='utf-8') as f:
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transcript_text = f.read()
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# Determine content type and generate content if needed
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content_type = determine_content_type(transcript_text)
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if content_type != 'default':
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print(f' Generating {content_type} content...')
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additional_content = generate_additional_content(content_type, transcript_text)
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# Save to appropriate directory with timestamp
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timestamp = time.strftime('%Y%m%d_%H%M%S')
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filename = Path('$input_file').stem
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if content_type == 'blog_post':
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output_file = Path('$DRAFT_DIR') / f'{filename}_{timestamp}.md'
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else: # idea_app
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output_file = Path('$PROMPT_DIR') / f'{filename}_{timestamp}.md'
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with open(output_file, 'w', encoding='utf-8') as f:
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f.write(additional_content)
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print(f' Content saved to: {output_file}')
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else:
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print(' No blog post or app idea content detected')
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"
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# Run the Python script
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python extract.py "$input_file"
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# Deactivate the virtual environment
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deactivate
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echo "----------------------------------------"
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deactivate
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58
src/summarize.py
Executable file
58
src/summarize.py
Executable file
@@ -0,0 +1,58 @@
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#!/usr/bin/env python3
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import sys
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import ollama
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from pathlib import Path
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def generate_summary(transcript_text: str) -> str:
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"""Generate a summary of the transcript."""
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prompt_dir = Path("prompts")
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with open(prompt_dir / "summary.md", 'r', encoding='utf-8') as f:
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prompt_template = f.read()
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prompt = prompt_template.format(transcript=transcript_text)
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response = ollama.chat(model='llama2', messages=[
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{
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'role': 'user',
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'content': prompt
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}
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])
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return response['message']['content'].strip()
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def main():
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if len(sys.argv) != 2:
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print("Usage: python summarize.py <transcript_file>")
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sys.exit(1)
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input_file = Path(sys.argv[1])
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if not input_file.exists():
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print(f"Error: File {input_file} does not exist")
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sys.exit(1)
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# Set up directory paths
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voice_memo_dir = Path("VoiceMemos")
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summary_dir = voice_memo_dir / "summaries"
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summary_dir.mkdir(parents=True, exist_ok=True)
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# Get the filename without the path and extension
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filename = input_file.stem
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summary_file = summary_dir / f"{filename}_summary.txt"
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print(f"Processing transcript: {input_file}")
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print("Generating summary...")
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# Read transcript and generate summary
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with open(input_file, 'r', encoding='utf-8') as f:
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transcript_text = f.read()
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summary = generate_summary(transcript_text)
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# Save summary
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with open(summary_file, 'w', encoding='utf-8') as f:
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f.write(summary)
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print(f"Summary saved to: {summary_file}")
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print("----------------------------------------")
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if __name__ == "__main__":
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main()
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@@ -15,54 +15,11 @@ if [ ! -f "$input_file" ]; then
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exit 1
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fi
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# Set the directory paths
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VOICE_MEMO_DIR="VoiceMemos"
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SUMMARY_DIR="$VOICE_MEMO_DIR/summaries"
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# Create summaries directory if it doesn't exist
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mkdir -p "$SUMMARY_DIR"
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# Get the filename without the path and extension
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filename=$(basename "$input_file" .txt)
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summary_file="$SUMMARY_DIR/${filename}_summary.txt"
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echo "Processing transcript: $input_file"
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echo "Generating summary..."
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# Activate the virtual environment
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source vibenv/bin/activate
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# Run the Python script to generate the summary
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python -c "
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import ollama
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from pathlib import Path
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def generate_summary(transcript_text: str) -> str:
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prompt_dir = Path('prompts')
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with open(prompt_dir / 'summary.md', 'r', encoding='utf-8') as f:
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prompt_template = f.read()
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prompt = prompt_template.format(transcript=transcript_text)
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response = ollama.chat(model='llama2', messages=[
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{
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'role': 'user',
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'content': prompt
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}
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])
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return response['message']['content'].strip()
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# Read transcript
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with open('$input_file', 'r', encoding='utf-8') as f:
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transcript_text = f.read()
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# Generate and save summary
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summary = generate_summary(transcript_text)
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with open('$summary_file', 'w', encoding='utf-8') as f:
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f.write(summary)
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"
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# Run the Python script
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python summarize.py "$input_file"
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# Deactivate the virtual environment
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deactivate
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echo "Summary saved to: $summary_file"
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echo "----------------------------------------"
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deactivate
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