智能专家3号

src/flask_prompt_master/routes/expert_generate_2.py

@@ -5,15 +5,18 @@
 """
 from flask import Blueprint, render_template, request, jsonify
 from openai import OpenAI
+import hashlib
 import json
 import logging
 import os
+import time
 from src.flask_prompt_master import db
 from src.flask_prompt_master.models.models import User, Prompt
 from src.flask_prompt_master.models.history_models import PromptHistory, UserStatistics
 
 logger = logging.getLogger(__name__)
 expert_generate_2_bp = Blueprint('expert_generate_2', __name__)
+_dedup_cache = {}
 
 client = OpenAI(
     api_key=os.environ.get('LLM_API_KEY') or 'sk-fdf7cc1c73504e628ec0119b7e11b8cc',
@@ -154,6 +157,15 @@ def expert_generate_2_api():
         if not user_input:
             return jsonify({'code': 400, 'message': '请输入您的需求', 'data': None})
 
+        uid = _get_user_id()
+        req_key = (uid, hashlib.md5(user_input.encode()).hexdigest())
+        now_ts = time.time()
+        if req_key in _dedup_cache and (now_ts - _dedup_cache[req_key]) < 8:
+            return jsonify({'code': 429, 'message': '请勿重复提交，请稍后再试', 'data': None})
+        _dedup_cache[req_key] = now_ts
+        if len(_dedup_cache) > 500:
+            _dedup_cache.clear()
+
         # 第一阶段：意图分析
         intent_response = client.chat.completions.create(
             model="deepseek-chat",
@@ -206,7 +218,7 @@ def expert_generate_2_api():
         if not generated_prompt:
             return jsonify({'code': 500, 'message': '生成失败，请重试', 'data': None})
 
-        user_id = _get_user_id()
+        user_id = uid
         try:
             p = Prompt(input_text=user_input, generated_text=generated_prompt, user_id=user_id)
             db.session.add(p)

src/flask_prompt_master/routes/expert_generate_3.py

@@ -6,15 +6,18 @@
 """
 from flask import Blueprint, render_template, request, jsonify
 from openai import OpenAI
+import hashlib
 import json
 import logging
 import os
+import time
 from src.flask_prompt_master import db
 from src.flask_prompt_master.models.models import User, Prompt
 from src.flask_prompt_master.models.history_models import PromptHistory, UserStatistics
 
 logger = logging.getLogger(__name__)
 expert_generate_3_bp = Blueprint('expert_generate_3', __name__)
+_dedup_cache = {}
 
 _llm_client = OpenAI(
     api_key=os.environ.get('LLM_API_KEY') or 'sk-fdf7cc1c73504e628ec0119b7e11b8cc',
@@ -153,6 +156,26 @@ def expert_generate_3_api():
         raw_input = (payload.get('input_text') or '').strip()
         if not raw_input:
             return jsonify({'code': 400, 'message': '请输入您的需求', 'data': None})
+
+        temperature = payload.get('temperature')
+        temperature = float(temperature) if temperature is not None else 0.7
+        temperature = max(0.0, min(2.0, temperature))
+        max_tokens = payload.get('max_tokens')
+        max_tokens = int(max_tokens) if max_tokens is not None else 1000
+        max_tokens = max(100, min(4000, max_tokens))
+        timeout = payload.get('timeout')
+        timeout = int(timeout) if timeout is not None else 60
+        timeout = max(10, min(300, timeout))
+
+        uid = _resolve_user_id()
+        req_key = (uid, hashlib.md5(raw_input.encode()).hexdigest())
+        now_ts = time.time()
+        if req_key in _dedup_cache and (now_ts - _dedup_cache[req_key]) < 8:
+            return jsonify({'code': 429, 'message': '请勿重复提交，请稍后再试', 'data': None})
+        _dedup_cache[req_key] = now_ts
+        if len(_dedup_cache) > 500:
+            _dedup_cache.clear()
+
         resp1 = _llm_client.chat.completions.create(
             model="deepseek-chat",
             messages=[
@@ -160,7 +183,7 @@ def expert_generate_3_api():
                 {"role": "user", "content": raw_input}
             ],
             temperature=0.1,
-            timeout=60
+            timeout=timeout
         )
         intent_raw = (resp1.choices[0].message.content or "").strip()
         intent_raw = intent_raw.replace('```json', '').replace('```', '').strip()
@@ -189,14 +212,13 @@ def expert_generate_3_api():
                 {"role": "system", "content": tpl.format(analysis=analysis_str)},
                 {"role": "user", "content": raw_input}
             ],
-            temperature=0.7,
-            max_tokens=1000,
-            timeout=60
+            temperature=temperature,
+            max_tokens=max_tokens,
+            timeout=timeout
         )
         result_prompt = (resp2.choices[0].message.content or "").strip()
         if not result_prompt:
             return jsonify({'code': 500, 'message': '生成失败，请重试', 'data': None})
-        uid = _resolve_user_id()
         try:
             db.session.add(Prompt(input_text=raw_input, generated_text=result_prompt, user_id=uid))
             db.session.commit()

src/flask_prompt_master/templates/expert_generate_2.html

@@ -80,13 +80,16 @@
 <script>
 document.getElementById('expertPromptForm').addEventListener('submit', async function(e) {
     e.preventDefault();
+    var form = e.target;
+    if (form.dataset.submitting === '1') return;
+    form.dataset.submitting = '1';
+    var generateBtn = document.getElementById('generateBtn');
+    generateBtn.disabled = true;
     var input_text = document.getElementById('input_text').value.trim();
     var loadingIndicator = document.getElementById('loadingIndicator');
     var resultCard = document.getElementById('resultCard');
-    var generateBtn = document.getElementById('generateBtn');
-    if (!input_text) { alert('请输入您的需求'); return; }
+    if (!input_text) { form.dataset.submitting = ''; generateBtn.disabled = false; alert('请输入您的需求'); return; }
     loadingIndicator.classList.remove('d-none');
-    generateBtn.disabled = true;
     resultCard.classList.add('d-none');
     try {
         var response = await fetch('/api/expert-generate-2/generate', {
@@ -114,6 +117,7 @@ document.getElementById('expertPromptForm').addEventListener('submit', async fun
     } finally {
         loadingIndicator.classList.add('d-none');
         generateBtn.disabled = false;
+        form.dataset.submitting = '';
     }
 });
 function copyToClipboard(text) {

src/flask_prompt_master/templates/expert_generate_3.html

@@ -22,6 +22,32 @@
                             <textarea class="form-control" id="input_text" name="input_text" rows="4" required></textarea>
                             <div class="form-text">详细描述您的需求，系统将进行专业分析并生成高质量提示词</div>
                         </div>
+                        <div class="mb-3">
+                            <button class="btn btn-link btn-sm p-0 text-secondary" type="button" data-bs-toggle="collapse" data-bs-target="#advancedSettings" aria-expanded="false">
+                                <i class="fas fa-sliders-h me-1"></i>高级参数
+                            </button>
+                            <div class="collapse mt-2" id="advancedSettings">
+                                <div class="card card-body bg-light">
+                                    <div class="row g-2">
+                                        <div class="col-md-4">
+                                            <label for="paramTemperature" class="form-label small">temperature</label>
+                                            <input type="number" class="form-control form-control-sm" id="paramTemperature" value="0.7" min="0" max="2" step="0.1" title="生成随机性，0更确定，2更随机">
+                                            <div class="form-text small">0–2，默认0.7</div>
+                                        </div>
+                                        <div class="col-md-4">
+                                            <label for="paramMaxTokens" class="form-label small">max_tokens</label>
+                                            <input type="number" class="form-control form-control-sm" id="paramMaxTokens" value="1000" min="100" max="4000" step="100" title="最大生成 token 数">
+                                            <div class="form-text small">100–4000，默认1000</div>
+                                        </div>
+                                        <div class="col-md-4">
+                                            <label for="paramTimeout" class="form-label small">timeout（秒）</label>
+                                            <input type="number" class="form-control form-control-sm" id="paramTimeout" value="60" min="10" max="300" step="10" title="请求超时时间">
+                                            <div class="form-text small">10–300秒，默认60</div>
+                                        </div>
+                                    </div>
+                                </div>
+                            </div>
+                        </div>
                         <button type="submit" class="btn btn-primary" id="generateBtn">
                             <i class="fas fa-magic"></i> 生成专家提示词
                         </button>
@@ -80,19 +106,30 @@
 <script>
 document.getElementById('expertForm3').addEventListener('submit', async function(e) {
     e.preventDefault();
+    var form = e.target;
+    if (form.dataset.submitting === '1') return;
+    form.dataset.submitting = '1';
+    var generateBtn = document.getElementById('generateBtn');
+    generateBtn.disabled = true;
     var input_text = document.getElementById('input_text').value.trim();
     var loadingIndicator = document.getElementById('loadingIndicator');
     var resultCard = document.getElementById('resultCard');
-    var generateBtn = document.getElementById('generateBtn');
-    if (!input_text) { alert('请输入您的需求'); return; }
+    var temperature = parseFloat(document.getElementById('paramTemperature').value) || 0.7;
+    var maxTokens = parseInt(document.getElementById('paramMaxTokens').value, 10) || 1000;
+    var timeout = parseInt(document.getElementById('paramTimeout').value, 10) || 60;
+    if (!input_text) { form.dataset.submitting = ''; generateBtn.disabled = false; alert('请输入您的需求'); return; }
     loadingIndicator.classList.remove('d-none');
-    generateBtn.disabled = true;
     resultCard.classList.add('d-none');
     try {
         var response = await fetch('/api/expert-generate-3/generate', {
             method: 'POST',
             headers: { 'Content-Type': 'application/json' },
-            body: JSON.stringify({ input_text: input_text })
+            body: JSON.stringify({
+                input_text: input_text,
+                temperature: temperature,
+                max_tokens: maxTokens,
+                timeout: timeout
+            })
         });
         var data = await response.json();
         if (data.code === 200) {
@@ -114,6 +151,7 @@ document.getElementById('expertForm3').addEventListener('submit', async function
     } finally {
         loadingIndicator.classList.add('d-none');
         generateBtn.disabled = false;
+        form.dataset.submitting = '';
     }
 });
 function copyToClipboard(text) {