Extract prompts to markdown files and add dynamic prompt selection based on transcript content

prompts/default.md

@@ -0,0 +1,14 @@
+Please provide a concise summary of the following transcript. 
+Focus on the main topics, key points, and any action items or decisions mentioned.
+Keep the summary short, clear, and well-structured.
+
+Transcript:
+{transcript}
+
+Summary: 
+{summary}
+
+Action items:
+- [ ] Item one
+- [ ] Item two
+- [ ] ...

prompts/idea_app.md

@@ -0,0 +1,12 @@
+Please analyze this transcript about an app idea and provide a structured summary focusing on:
+1. The core app concept and its main purpose
+2. Key features and functionality discussed
+3. Target audience or user base
+4. Any technical considerations or implementation details
+5. Potential challenges or concerns raised
+6. Next steps or action items mentioned
+
+Transcript:
+{transcript}
+
+Summary: 

summarize_transcripts.py

@@ -10,16 +10,26 @@ def read_transcript(transcript_file: Path) -> str:
     with open(transcript_file, 'r', encoding='utf-8') as f:
         return f.read()
 
+def load_prompt_template(transcript_text: str) -> str:
+    """Load the appropriate prompt template based on transcript content."""
+    prompt_dir = Path("prompts")
+    
+    # Check if transcript contains app-related content
+    if "idea" in transcript_text.lower() and "app" in transcript_text.lower():
+        prompt_file = prompt_dir / "idea_app.md"
+    else:
+        prompt_file = prompt_dir / "default.md"
+    
+    with open(prompt_file, 'r', encoding='utf-8') as f:
+        return f.read()
+
 def process_transcript(transcript_text: str) -> str:
     """Process a transcript using LLaMA to generate a summary."""
-    prompt = f"""Please provide a concise summary of the following transcript. 
-Focus on the main topics, key points, and any action items or decisions mentioned.
-Keep the summary clear and well-structured.
-
-Transcript:
-{transcript_text}
-
-Summary:"""
+    # Load the appropriate prompt template
+    prompt_template = load_prompt_template(transcript_text)
+    
+    # Format the prompt with the transcript
+    prompt = prompt_template.format(transcript=transcript_text)
     
     # Use Ollama to generate the summary
     response = ollama.chat(model='llama2', messages=[