feat(transcription): [2f388f42] integrate prompt database and AI insights

Implements the core functionality for the AI-powered analysis of meeting transcripts in the Transcription Tool.

This commit introduces a new 'AI Insights' feature that allows users to generate various summaries and analyses from a transcript on demand.

- Creates a  to manage and version different AI prompts for tasks like generating meeting minutes, extracting action items, and creating sales summaries.
- Adds a new  responsible for orchestrating the analysis process: fetching the transcript, calling the Gemini API with the appropriate prompt, and caching the results in the database.
- Extends the FastAPI backend with a new endpoint  to trigger the insight generation.
- Updates the React frontend () with a new 'AI Insights' panel, including buttons to trigger the analyses and a modal to display the results.
- Updates the documentation () to reflect the new features, API endpoints, and version.
This commit is contained in:
2026-01-26 07:43:24 +00:00
parent 01c4968ddf
commit 771b06c1bc
5 changed files with 348 additions and 10 deletions

View File

@@ -11,6 +11,7 @@ from datetime import datetime
from .config import settings
from .database import init_db, get_db, Meeting, TranscriptChunk, AnalysisResult, SessionLocal
from .services.orchestrator import process_meeting_task
from .services.insights_service import generate_insight
# Initialize FastAPI App
app = FastAPI(
@@ -42,7 +43,8 @@ def list_meetings(db: Session = Depends(get_db)):
@app.get("/api/meetings/{meeting_id}")
def get_meeting(meeting_id: int, db: Session = Depends(get_db)):
meeting = db.query(Meeting).options(
joinedload(Meeting.chunks)
joinedload(Meeting.chunks),
joinedload(Meeting.analysis_results) # Eager load analysis results
).filter(Meeting.id == meeting_id).first()
if not meeting:
@@ -99,6 +101,26 @@ async def upload_audio(
from pydantic import BaseModel
class InsightRequest(BaseModel):
insight_type: str
@app.post("/api/meetings/{meeting_id}/insights")
def create_insight(meeting_id: int, payload: InsightRequest, db: Session = Depends(get_db)):
"""
Triggers the generation of a specific insight (e.g., meeting minutes, action items).
If the insight already exists, it returns the stored result.
Otherwise, it generates, stores, and returns the new insight.
"""
try:
insight = generate_insight(db, meeting_id, payload.insight_type)
return insight
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
# For unexpected errors, return a generic 500 error
print(f"ERROR: Unexpected error in create_insight: {e}")
raise HTTPException(status_code=500, detail="An internal error occurred while generating the insight.")
class RenameRequest(BaseModel):
old_name: str
new_name: str

View File

@@ -0,0 +1,113 @@
MEETING_MINUTES_PROMPT = """
You are a professional assistant specialized in summarizing meeting transcripts.
Your task is to create a formal and structured protocol (Meeting Minutes) from the provided transcript.
Please analyze the following transcript and generate the Meeting Minutes in German.
**Transcript:**
---
{transcript_text}
---
**Instructions for the Meeting Minutes:**
1. **Header:**
* Start with a clear title: "Meeting-Protokoll".
* Add a placeholder for the meeting date: "Datum: [Datum des Meetings]".
2. **Agenda Items:**
* Identify the main topics discussed.
* Structure the protocol using these topics as headlines (e.g., "Tagesordnungspunkt 1: [Thema]").
3. **Key Discussions & Decisions:**
* For each agenda item, summarize the key points of the discussion.
* Clearly list all decisions that were made. Use a format like "**Entscheidung:** ...".
4. **Action Items (Next Steps):**
* Extract all clear tasks or action items.
* For each action item, identify the responsible person (Owner) and the deadline, if mentioned.
* Present the action items in a clear list under a headline "Nächste Schritte / Action Items". Use the format: "- [Aufgabe] (Verantwortlich: [Person], Fällig bis: [Datum/unbestimmt])".
5. **General Tone & Language:**
* The protocol must be written in formal, professional German.
* Be concise and focus on the essential information (discussions, decisions, tasks).
* Do not invent information that is not present in the transcript.
Please provide the output in Markdown format.
"""
ACTION_ITEMS_PROMPT = """
You are a highly efficient assistant focused on productivity and task management.
Your goal is to extract all actionable tasks (Action Items) from a meeting transcript.
Please analyze the following transcript and list all tasks.
**Transcript:**
---
{transcript_text}
---
**Instructions for the Action Item List:**
1. **Extraction:**
* Carefully read the entire transcript and identify every statement that constitutes a task, a to-do, or a commitment to do something.
* Ignore general discussions, opinions, and status updates. Focus only on future actions.
2. **Format:**
* Present the extracted tasks as a bulleted list.
* For each task, clearly state:
* **What** needs to be done.
* **Who** is responsible for it (Owner).
* **When** it should be completed by (Due Date), if mentioned.
3. **Output Structure:**
* Use the following format for each item: `- [Task Description] (Owner: [Person's Name], Due: [Date/unspecified])`
* If the owner or due date is not explicitly mentioned, use "[unbestimmt]".
* The list should be titled "Action Item Liste".
4. **Language:**
* The output should be in German.
Please provide the output in Markdown format.
"""
SALES_SUMMARY_PROMPT = """
You are a Senior Sales Manager analyzing a meeting transcript from a client conversation.
Your objective is to create a concise, rollenbasierte Zusammenfassung for the sales team. The summary should highlight key information relevant to closing a deal.
Please analyze the following transcript and generate a Sales Summary.
**Transcript:**
---
{transcript_text}
---
**Instructions for the Sales Summary:**
1. **Customer Needs & Pain Points:**
* Identify and list the core problems, challenges, and needs expressed by the client.
* What are their primary business goals?
2. **Buying Signals:**
* Extract any phrases or questions that indicate a strong interest in the product/service (e.g., questions about price, implementation, specific features).
3. **Key Decision-Makers:**
* Identify the people in the meeting who seem to have the most influence on the purchasing decision. Note their role or title if mentioned.
4. **Budget & Timeline:**
* Note any mentions of budget, pricing expectations, or the timeline for their decision-making process.
5. **Next Steps (from a Sales Perspective):**
* What are the immediate next actions the sales team needs to take to move this deal forward? (e.g., "Send proposal," "Schedule demo for the technical team").
**Output Format:**
* Use clear headings for each section (e.g., "Kundenbedürfnisse & Pain Points", "Kaufsignale").
* Use bullet points for lists.
* The language should be direct, actionable, and in German.
Please provide the output in Markdown format.
"""
# You can add more prompts here for other analysis types.
# For example, a prompt for a technical summary, a marketing summary, etc.

View File

@@ -0,0 +1,110 @@
import sys
import os
from sqlalchemy.orm import Session
from .. import database
from .. import prompt_library
# Add project root to path to allow importing from 'helpers'
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..', '..')))
from helpers import call_gemini_flash
def _format_transcript(chunks: list[database.TranscriptChunk]) -> str:
"""
Formats the transcript chunks into a single, human-readable string.
Example: "[00:00:01] Speaker A: Hello world."
"""
full_transcript = []
# Sort chunks by their index to ensure correct order
sorted_chunks = sorted(chunks, key=lambda c: c.chunk_index)
for chunk in sorted_chunks:
if not chunk.json_content:
continue
for item in chunk.json_content:
# json_content can be a list of dicts
if isinstance(item, dict):
speaker = item.get('speaker', 'Unknown')
start_time = item.get('start', 0)
text = item.get('line', '')
# Format timestamp from seconds to HH:MM:SS
hours, remainder = divmod(int(start_time), 3600)
minutes, seconds = divmod(remainder, 60)
timestamp = f"{hours:02}:{minutes:02}:{seconds:02}"
full_transcript.append(f"[{timestamp}] {speaker}: {text}")
return "\n".join(full_transcript)
def get_prompt_by_type(insight_type: str) -> str:
"""
Returns the corresponding prompt from the prompt_library based on the type.
"""
if insight_type == "meeting_minutes":
return prompt_library.MEETING_MINUTES_PROMPT
elif insight_type == "action_items":
return prompt_library.ACTION_ITEMS_PROMPT
elif insight_type == "sales_summary":
return prompt_library.SALES_SUMMARY_PROMPT
else:
raise ValueError(f"Unknown insight type: {insight_type}")
def generate_insight(db: Session, meeting_id: int, insight_type: str) -> database.AnalysisResult:
"""
Generates a specific insight for a meeting, stores it, and returns it.
Checks for existing analysis to avoid re-generating.
"""
# 1. Check if the insight already exists
existing_insight = db.query(database.AnalysisResult).filter(
database.AnalysisResult.meeting_id == meeting_id,
database.AnalysisResult.prompt_key == insight_type
).first()
if existing_insight:
return existing_insight
# 2. Get the meeting and its transcript
meeting = db.query(database.Meeting).filter(database.Meeting.id == meeting_id).first()
if not meeting:
raise ValueError(f"Meeting with id {meeting_id} not found.")
if not meeting.chunks:
raise ValueError(f"Meeting with id {meeting_id} has no transcript chunks.")
# 3. Format the transcript and select the prompt
transcript_text = _format_transcript(meeting.chunks)
if not transcript_text.strip():
raise ValueError(f"Transcript for meeting {meeting_id} is empty.")
prompt_template = get_prompt_by_type(insight_type)
final_prompt = prompt_template.format(transcript_text=transcript_text)
# 4. Call the AI model
# Update meeting status
meeting.status = "ANALYZING"
db.commit()
try:
generated_text = call_gemini_flash(prompt=final_prompt, temperature=0.5)
# 5. Store the new insight
new_insight = database.AnalysisResult(
meeting_id=meeting_id,
prompt_key=insight_type,
result_text=generated_text
)
db.add(new_insight)
meeting.status = "COMPLETED"
db.commit()
db.refresh(new_insight)
return new_insight
except Exception as e:
meeting.status = "ERROR"
db.commit()
# Log the error properly in a real application
print(f"Error generating insight for meeting {meeting_id}: {e}")
raise

View File

@@ -1,10 +1,19 @@
import React, { useState, useEffect } from 'react'
import axios from 'axios'
import { Upload, FileText, Clock, CheckCircle2, Loader2, AlertCircle, Trash2, ArrowLeft, Copy, Edit3, X, Scissors, Users } from 'lucide-react'
import { Upload, FileText, Clock, CheckCircle2, Loader2, AlertCircle, Trash2, ArrowLeft, Copy, Edit3, X, Scissors, Users, Wand2 } from 'lucide-react'
import clsx from 'clsx'
const API_BASE = '/tr/api'
// --- INTERFACES ---
interface AnalysisResult {
id: number;
prompt_key: string;
result_text: string;
created_at: string;
}
interface TranscriptMessage {
time: string
display_time: string
@@ -30,8 +39,29 @@ interface Meeting {
duration_seconds?: number
created_at: string
chunks?: Chunk[]
analysis_results?: AnalysisResult[]
}
// --- MODAL COMPONENT ---
const InsightModal = ({ title, content, onClose, onCopy }: { title: string, content: string, onClose: () => void, onCopy: (text: string) => void }) => (
<div className="fixed inset-0 bg-black/60 z-50 flex items-center justify-center p-4 backdrop-blur-sm animate-fade-in">
<div className="bg-white dark:bg-slate-900 rounded-2xl shadow-2xl w-full max-w-3xl max-h-[90vh] flex flex-col border border-slate-200 dark:border-slate-800">
<header className="p-4 border-b border-slate-200 dark:border-slate-800 flex justify-between items-center flex-shrink-0">
<h2 className="text-lg font-bold flex items-center gap-2"><Wand2 className="h-5 w-5 text-blue-500" /> {title}</h2>
<div className='flex items-center gap-2'>
<button onClick={() => onCopy(content)} className="flex items-center gap-2 text-sm px-3 py-1.5 bg-slate-100 dark:bg-slate-800 hover:bg-slate-200 dark:hover:bg-slate-700 rounded-md font-medium transition-colors"><Copy className='h-4 w-4'/> Copy</button>
<button onClick={onClose} className="p-1.5 text-slate-500 hover:bg-slate-100 dark:hover:bg-slate-800 rounded-full"><X className="h-5 w-5" /></button>
</div>
</header>
<main className="p-6 overflow-auto">
<pre className="whitespace-pre-wrap font-sans text-sm leading-relaxed">{content}</pre>
</main>
</div>
</div>
)
export default function App() {
const [view, setView] = useState<'list' | 'detail'>('list')
const [selectedId, setSelectedId] = useState<number | null>(null)
@@ -48,6 +78,12 @@ export default function App() {
const [editValue, setEditValue] = useState("")
const [isProcessing, setIsProcessing] = useState(false)
// Insight State
const [showInsightModal, setShowInsightModal] = useState(false)
const [insightLoading, setInsightLoading] = useState(false)
const [insightResult, setInsightResult] = useState('')
const [insightTitle, setInsightTitle] = useState('')
const fetchMeetings = async () => {
try {
const res = await axios.get(`${API_BASE}/meetings`)
@@ -102,6 +138,39 @@ export default function App() {
} catch (e) { alert("Delete failed") }
}
// --- AI INSIGHTS ---
const handleGenerateInsight = async (insightType: string, title: string) => {
if (!detailMeeting) return;
setInsightLoading(true);
setInsightTitle(title);
try {
// First, check if result already exists
const existing = detailMeeting.analysis_results?.find(r => r.prompt_key === insightType);
if (existing) {
setInsightResult(existing.result_text);
setShowInsightModal(true);
return;
}
// If not, generate it
const res = await axios.post(`${API_BASE}/meetings/${detailMeeting.id}/insights`, {
insight_type: insightType
});
setInsightResult(res.data.result_text);
setShowInsightModal(true);
// Refresh detail view to get the new analysis result in the meeting object
fetchDetail(detailMeeting.id);
} catch(e) {
console.error("Failed to generate insight", e);
alert(`Error: Could not generate ${title}.`);
} finally {
setInsightLoading(false);
}
}
// --- GLOBAL SPEAKER MANAGEMENT ---
const getUniqueSpeakers = () => {
@@ -235,6 +304,7 @@ export default function App() {
return (
<div className="min-h-screen bg-slate-50 dark:bg-slate-950 text-slate-900 dark:text-slate-200 font-sans">
{showInsightModal && <InsightModal title={insightTitle} content={insightResult} onClose={() => setShowInsightModal(false)} onCopy={text => navigator.clipboard.writeText(text)} />}
<div className="max-w-4xl mx-auto px-4 py-8">
<button
onClick={() => { setView('list'); setSelectedId(null); setDetailMeeting(null); }}
@@ -287,6 +357,20 @@ export default function App() {
</div>
)}
{/* AI INSIGHTS PANEL */}
<div className="mb-6 bg-purple-50 dark:bg-purple-900/20 p-4 rounded-xl border border-purple-100 dark:border-purple-800">
<div className="flex items-center gap-3 mb-3">
<Wand2 className="h-5 w-5 text-purple-600 dark:text-purple-300" />
<h3 className="font-bold text-purple-800 dark:text-purple-200">AI Insights</h3>
{insightLoading && <Loader2 className="h-4 w-4 animate-spin text-purple-500" />}
</div>
<div className="grid grid-cols-1 md:grid-cols-3 gap-3">
<button disabled={insightLoading} onClick={() => handleGenerateInsight('meeting_minutes', 'Meeting Protocol')} className="text-sm font-medium px-4 py-2 bg-white dark:bg-slate-800 border dark:border-slate-700 rounded-lg shadow-sm hover:bg-slate-50 dark:hover:bg-slate-700/50 disabled:opacity-50 transition-colors">Generate Protocol</button>
<button disabled={insightLoading} onClick={() => handleGenerateInsight('action_items', 'Action Items')} className="text-sm font-medium px-4 py-2 bg-white dark:bg-slate-800 border dark:border-slate-700 rounded-lg shadow-sm hover:bg-slate-50 dark:hover:bg-slate-700/50 disabled:opacity-50 transition-colors">Extract Action Items</button>
<button disabled={insightLoading} onClick={() => handleGenerateInsight('sales_summary', 'Sales Summary')} className="text-sm font-medium px-4 py-2 bg-white dark:bg-slate-800 border dark:border-slate-700 rounded-lg shadow-sm hover:bg-slate-50 dark:hover:bg-slate-700/50 disabled:opacity-50 transition-colors">Sales Summary</button>
</div>
</div>
{isProcessing && (
<div className="fixed inset-0 bg-white/50 dark:bg-black/50 z-50 flex items-center justify-center backdrop-blur-sm">
<div className="bg-white dark:bg-slate-800 p-6 rounded-xl shadow-2xl flex items-center gap-4">