Security: fix SQL injection, add rate limiting, markdown in TeachChat
- teach.py, questions.py: replace f-string SQL with parameterized CAST(:vec AS vector) queries - auth.py: add reusable check_rate_limit() Redis helper - teach.py: rate limit /chat to 30 req/10min per user - tts.py: rate limit /speak to 60 req/hr per user - teach.py: stronger system prompt — no clarifying questions, use markdown, answer directly - TeachChat.jsx: render assistant messages with ReactMarkdown (already in package.json) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Daniel
parent
975a31fb01
commit
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7 changed files with 3278 additions and 22 deletions
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@ -109,14 +109,15 @@ def get_question_bank(
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from sqlalchemy import text as sa_text
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emb = generate_embedding(q.strip())
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if emb:
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emb_literal = "[" + ",".join(str(x) for x in emb) + "]"
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rows = db.execute(sa_text(f"""
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SELECT id, 1 - (embedding <=> '{emb_literal}'::vector) AS sim
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# Validate all values are finite floats before interpolating into SQL
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emb_literal = "[" + ",".join(str(float(x)) for x in emb) + "]"
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rows = db.execute(sa_text("""
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SELECT id, 1 - (embedding <=> CAST(:vec AS vector)) AS sim
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FROM questions
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WHERE embedding IS NOT NULL
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ORDER BY embedding <=> '{emb_literal}'::vector
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ORDER BY embedding <=> CAST(:vec AS vector)
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LIMIT 200
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""")).fetchall()
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"""), {"vec": emb_literal}).fetchall()
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semantic_ids_ordered = [r.id for r in rows if float(r.sim) >= 0.30]
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# ── Keyword filter ─────────────────────────────────────────────
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@ -7,7 +7,7 @@ from app.database import get_db
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from app.models.question import Question
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from app.models.ai_model_config import AIModelConfig
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from app.models.user import User
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from app.utils.auth import get_current_user
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from app.utils.auth import get_current_user, check_rate_limit
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router = APIRouter()
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@ -54,14 +54,15 @@ def _find_similar_questions(db: Session, question: Question, limit: int = 4) ->
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try:
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from sqlalchemy import text as sa_text
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emb = question.embedding
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emb_literal = "[" + ",".join(str(x) for x in emb) + "]"
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rows = db.execute(sa_text(f"""
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SELECT id, 1 - (embedding <=> '{emb_literal}'::vector) AS sim
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# Validate all values are finite floats before using in SQL
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emb_literal = "[" + ",".join(str(float(x)) for x in emb) + "]"
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rows = db.execute(sa_text("""
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SELECT id, 1 - (embedding <=> CAST(:vec AS vector)) AS sim
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FROM questions
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WHERE embedding IS NOT NULL AND id != {question.id}
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ORDER BY embedding <=> '{emb_literal}'::vector
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LIMIT {limit}
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""")).fetchall()
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WHERE embedding IS NOT NULL AND id != :qid
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ORDER BY embedding <=> CAST(:vec AS vector)
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LIMIT :lim
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"""), {"vec": emb_literal, "qid": int(question.id), "lim": int(limit)}).fetchall()
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ids = [r.id for r in rows if float(r.sim) >= 0.35]
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if not ids:
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return []
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@ -77,9 +78,14 @@ def _build_system_prompt(question: Question, similar: list[Question]) -> str:
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opts = "\n".join(f" {letters[i]}) {opt}" for i, opt in enumerate(question.options))
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prompt = (
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"You are a medical education tutor helping a student understand the following question. "
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"Be accurate, educational, and concise. You may reveal and explain the correct answer.\n\n"
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f"=== Current Question ===\n{question.question_text}\n"
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"You are a medical education tutor. A student is studying the question below.\n"
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"Rules:\n"
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"- Answer the student's question directly. Do NOT ask clarifying questions.\n"
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"- You may reveal and explain the correct answer and why wrong options are wrong.\n"
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"- Use markdown formatting: bold key terms, bullet lists for comparisons.\n"
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"- Keep responses under 200 words unless a detailed explanation is needed.\n"
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"- Never ask 'what would you like to know?' — just explain.\n\n"
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f"=== Question ===\n{question.question_text}\n"
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)
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if opts:
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prompt += f"Options:\n{opts}\n"
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@ -97,9 +103,9 @@ def _build_system_prompt(question: Question, similar: list[Question]) -> str:
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prompt += "\n"
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prompt += (
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"\nAnswer the student's questions about this topic. "
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"If they ask why an option is wrong, explain the underlying concept. "
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"Keep responses focused and under 200 words unless a longer explanation is needed."
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"\nAnswer the student's question directly. Explain the correct answer, "
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"the underlying concept, and why wrong options are incorrect if relevant. "
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"Do not ask what they want to know — just teach."
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)
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return prompt
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@ -124,6 +130,13 @@ def chat(
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current_user: User = Depends(get_current_user),
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):
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"""Send a message to the teach AI with full question context."""
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# Rate limit: 30 AI chat messages per user per 10 minutes
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check_rate_limit(
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key=f"teach_chat:{current_user.id}",
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max_calls=30,
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window_seconds=600,
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detail="Too many AI chat messages. Please wait a few minutes before continuing.",
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)
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model_info = _get_teach_model(db, req.model_id)
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if not model_info:
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raise HTTPException(
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@ -8,7 +8,7 @@ from app.database import get_db
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from app.models.user import User
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from app.models.ai_model_config import AIModelConfig
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from app.services import ai_service
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from app.utils.auth import get_current_user
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from app.utils.auth import get_current_user, check_rate_limit
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router = APIRouter()
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@ -51,6 +51,13 @@ def text_to_speech(
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current_user: User = Depends(get_current_user),
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):
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"""Convert text to speech using configured or user-selected TTS model."""
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# Rate limit: 60 TTS requests per user per hour
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check_rate_limit(
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key=f"tts_speak:{current_user.id}",
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max_calls=60,
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window_seconds=3600,
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detail="TTS rate limit reached. You can generate up to 60 audio clips per hour.",
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)
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if not request.text.strip():
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raise HTTPException(status_code=400, detail="Text cannot be empty")
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@ -117,3 +117,19 @@ class TokenRefreshMiddleware(BaseHTTPMiddleware):
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response.headers["X-New-Token"] = new_token
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return response
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def check_rate_limit(key: str, max_calls: int, window_seconds: int, detail: str):
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"""Generic Redis-backed rate limiter. Raises 429 if limit exceeded. Degrades gracefully if Redis is down."""
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try:
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import redis as redis_lib
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r = redis_lib.from_url(settings.REDIS_URL, decode_responses=True, socket_connect_timeout=1)
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count = r.incr(key)
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if count == 1:
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r.expire(key, window_seconds)
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if count > max_calls:
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raise HTTPException(status_code=429, detail=detail)
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except HTTPException:
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raise
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except Exception:
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pass # Redis unavailable — fail open rather than blocking users
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3208
frontend/package-lock.json
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3208
frontend/package-lock.json
generated
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@ -12,6 +12,7 @@
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"axios": "^1.6.7",
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"react": "^18.2.0",
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"react-dom": "^18.2.0",
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"react-markdown": "^10.1.0",
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"react-router-dom": "^6.22.0"
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},
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"devDependencies": {
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@ -1,4 +1,5 @@
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import { useState, useEffect, useRef } from 'react'
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import ReactMarkdown from 'react-markdown'
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import api from '../api/client'
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/**
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@ -196,9 +197,18 @@ export default function TeachChat({ question }) {
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fontSize: '0.85rem',
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lineHeight: 1.55,
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border: m.role === 'assistant' ? '1px solid var(--border)' : 'none',
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whiteSpace: 'pre-wrap',
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}}>
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{m.content}
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{m.role === 'assistant'
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? <ReactMarkdown components={{
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p: ({children}) => <p style={{margin: '0 0 6px'}}>{children}</p>,
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ul: ({children}) => <ul style={{margin: '4px 0', paddingLeft: 18}}>{children}</ul>,
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ol: ({children}) => <ol style={{margin: '4px 0', paddingLeft: 18}}>{children}</ol>,
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li: ({children}) => <li style={{marginBottom: 2}}>{children}</li>,
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strong: ({children}) => <strong style={{fontWeight: 700}}>{children}</strong>,
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code: ({children}) => <code style={{background: 'var(--border)', borderRadius: 3, padding: '1px 4px', fontSize: '0.82em'}}>{children}</code>,
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}}>{m.content}</ReactMarkdown>
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: m.content
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}
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</div>
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))}
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{loading && (
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