Fixed intent in the dev server

.gitignore

@@ -3,6 +3,7 @@ __pycache__/
 *$py.class
 venv/
 .env
+dev/.env
 .idea/
 .vscode/
 .agent/

README.md

@@ -10,51 +10,87 @@
 
 A SearXNG plugin that generates local AI overviews powered by Ollama, using search results as RAG context.
 
-Features:
-- Token-by-token UI streaming
-- Clickable inline citations
-- Interactive mode: continue summary, ask follow-ups, copy, or regenerate
-- Simple response mode with no extras
-- Internally called low-latency RAG for follow-ups (bypasses HTTP loopback)
-- Native network integration via `searx.network` (respects proxy/SSL settings)
-- Stateless conversation persistence/shareability via URL hash
-- Model selector in the AI overview widget
-- Does not slow down result loading
-- One file install
+## Features:
 
-## Installation
+- Inline numbered citations
+- Interactive mode - Continue summary, ask follow-ups, copy, or regenerate
+- Overview of ranked results with prompts based on detected query intent:
+  - `How To` `Technical` `Factual` `Comparison` `Opinion` `Current` `Local` `Geneal`
+- Internally called RAG for follow-ups
+- Native network integration via `searx.network`
+- Stateless conversation presistence/shareability via URL hash
+- Ollama model selector
+- Feeds fetched results to Ollama without slowing down SearXNG  results
+- Real-time streaming via Valkey (No waiting for a completed response)
+- TF-IDF result ranking before being sent to Ollama
+- Smart chunking - Pages are split into 512-token segments and highest-scoring chunk per page used for context
+- Conversation memory - 30-minute cross-search conversation history via Valkey for follow-up questions
+- Markdown support
+- Intent emoji badge showing what intent prompt was used 
 
-Place `ollama_answers.py` into the `searx/plugins` directory of your SearXNG instance (or mount it in a container) and enable it in `settings.yml`:
+## Install
 
+1. Download the plugin:
+
+   ### Main repo (Gitea)
+   ```bash
+   curl -o ollama_answers.py https://git.tysstech.com/TySS-Dev/ollama-ai-answers-searxng/raw/branch/main/ollama_answers.py
+   ```
+
+   ### Mirror repo (Github):
+   ```bash
+   curl -o ollama_answers.py https://raw.githubusercontent.com/TySP-Dev/ollama-ai-answers-searxng/main/ollama_answers.py
+   ```
+
+3. Copy to your SearXNG plugins directory:
+   ```bash
+   cp ollama_answers.py path_to/searxng/plugins/ollama_answers.py
+   ```
+
+4. Add the volume mount to your `docker-compose.yml` under the searxng service:
+   ```yaml
+   volumes:
+     - ./plugins/ollama_answers.py:/usr/local/searxng/searx/plugins/ollama_answers.py:Z
+   ```
+
+5. Add environment variables to `docker-compose.yml`:
+   ```yaml
+   environment:
+     - LLM_URL=http://ollama:11434/v1/chat/completions
+     - LLM_MODEL=qwen3.5:9b
+     - VALKEY_HOST=searxng-valkey
+   ```
+
+6. Add to `settings.yml` plugins section:
    ```yaml
    plugins:
      searx.plugins.ollama_answers.SXNGPlugin:
        active: true
    ```
 
+7. Restart SearXNG:
+   ```bash
+   docker compose up -d --force-recreate core
+   ```
+
 ## Configuration
 
 Configure via environment variables.
 
-### Required
-
-| Variable | Description | Default |
+| Variable | Default | Description |
 |---|---|---|
-| `LLM_URL` | Ollama chat completions endpoint | `http://ollama:11434/v1/chat/completions` |
-| `LLM_MODEL` | Model name as listed in Ollama | `qwen3.5:9b` |
-
-### Optional
-
-| Variable | Description | Default |
-|---|---|---|
-| `LLM_SYSTEM_PROMPT` | Overrides the default system prompt | `You are a direct, citation-accurate search synthesis engine.` |
-| `LLM_MAX_TOKENS` | Max tokens in the AI response | `200` |
-| `LLM_TEMPERATURE` | Sampling temperature | `0.2` |
-| `LLM_CONTEXT_DEEP_COUNT` | Results used with full snippets | `5` |
-| `LLM_CONTEXT_SHALLOW_COUNT` | Results with headlines only (breadth) | `15` |
-| `LLM_TABS` | Comma-delimited tab whitelist | `general,science,it,news` |
-| `LLM_INTERACTIVE` | Interactive UI mode (copy, regenerate, follow-up) | `true` |
-| `LLM_QUESTION_MARK_REQUIRED` | Only trigger on queries containing `?` | `false` |
+| `LLM_URL` | `http://ollama:11434/v1/chat/completions` | Ollama endpoint |
+| `LLM_MODEL` | `qwen3.5:9b` | Default model |
+| `LLM_MAX_TOKENS` | `200` | Max response tokens |
+| `LLM_TEMPERATURE` | `0.2` | Response temperature |
+| `LLM_TABS` | `general,science,it,news` | Tabs to show AI overview on |
+| `LLM_QUESTION_MARK_REQUIRED` | `false` | Only trigger on queries with `?` |
+| `LLM_INTERACTIVE` | `true` | Show copy/regen/follow-up UI |
+| `LLM_SYSTEM_PROMPT` | *(built-in)* | Override the system prompt |
+| `LLM_CONTEXT_DEEP_COUNT` | `5` | Full-content results to fetch |
+| `LLM_CONTEXT_SHALLOW_COUNT` | `15` | Headline-only results |
+| `VALKEY_HOST` | `searxng-valkey` | Valkey container hostname |
+| `VALKEY_PORT` | `6379` | Valkey port |
 
 ## How It Works
 
@@ -66,6 +102,92 @@ Configure via environment variables.
 6. Client-side script calls a signed endpoint (`/ai-stream`)
 7. Ollama streams a response token-by-token in the UI
 
+## Known Issues
+
+- [ ] Update README with all updates
+
+- [x] When asking a follow up question the previous output disappears
+
+- [x] Parts of the UI are not theme aware resulting in a unpolished look when not using a dark theme
+
+- [x] When SearXNG provides a info blob for a search it appears on top of the overview i.e. `Wikipedia` or `Linux` 
+
+For any issues not stated here please create an issue ticket on [Gitea](https://git.tysstech.com/TySS-Dev/ollama-ai-answers-searxng/issues) or [GitHub](https://github.com/TySP-Dev/ollama-ai-answers-searxng/issues) and add the `bug` tag.
+
+## Roadmap
+
+### Dev Server
+
+- [x] Stream viewer — show tokens arriving in real time in the debug panel as they come out of Valkey, so you can see exactly what the LLM is generating chunk by chunk
+
+- [x] TF-IDF score visualizer — show a table of which URLs were fetched, their scores, and which chunks were selected for context
+
+- [ ] Intent detection display — show what intent was detected and which system prompt was used for each query
+
+- [ ] Saved queries — save/load test queries so you can quickly re-run the same set of searches after making changes to the plugin
+
+- [ ] A/B model comparison — run the same query against two different models simultaneously and show both responses side by side
+
+- [ ] Response time breakdown — show how long each phase took: SearXNG fetch, page fetching, TF-IDF scoring, LLM stream start, stream complete
+
+- [ ] Context inspector — show the full assembled context string that gets sent to the LLM, so you can see exactly what it's working with
+
+- [ ] Prompt viewer — show the full system prompt + user prompt that gets sent to Ollama
+
+- [ ] Export button — copy the full context + prompt + response as a JSON blob for bug reports
+
+- [ ] Per-intent system prompt editor — edit the system prompts for each intent type live without restarting
+
+- [ ] Token counter — show estimated token count of the context being sent
+
+### Plugin
+
+- [ ] Working on feature plans
+
+## Architecture
+
+```
+┌─────────────────────────────────────────────────────┐
+│                   Browser                           │
+│  POST /ai-stream → GET /ai-status/{id} (poll 150ms) │
+└────────────────┬────────────────────────────────────┘
+                 │
+┌────────────────▼────────────────────────────────────┐
+│              SearXNG + Plugin                       │
+│                                                     │
+│  post_search()                                      │
+│    → _enrich_results()  ← ThreadPoolExecutor        │
+│      → _fetch_page_text() × 5 parallel              │
+│      → _chunk_text() + _tfidf_score()               │
+│      → rerank by score                              │
+│    → _assemble_context()                            │
+│    → inject AI Overview HTML + JS                   │
+│                                                     │
+│  /ai-stream                                         │
+│    → validate token                                 │
+│    → _detect_intent() → select system prompt        │
+│    → _load_conversation() from Valkey               │
+│    → launch stream_to_valkey() thread               │
+│    → return {job_id} immediately                    │
+│                                                     │
+│  stream_to_valkey() [background thread]             │
+│    → Ollama stream=True                             │
+│    → RPUSH tokens to Valkey                         │
+│    → RPUSH __DONE__ when complete                   │
+│                                                     │
+│  /ai-status/{job_id}                                │
+│    → LRANGE chunks from offset                      │
+│    → return {chunks, done}                          │
+└────────────────┬────────────────────────────────────┘
+                 │
+┌────────────────▼────────────────────────────────────┐
+│                  Valkey                             │
+│  ai:job:{id}:chunks  (list, TTL 120s)               │
+│  ai:job:{id}:status  (string, TTL 120s)             │
+│  ai:conv:{session}   (JSON, TTL 1800s)              │
+└─────────────────────────────────────────────────────┘
+```
+
 ## Docker Compose Example
 
 ```yaml
@@ -74,6 +196,7 @@ services:
     environment:
       - LLM_URL=http://ollama:11434/v1/chat/completions
       - LLM_MODEL=qwen3.5:9b
+      - VALKEY_HOST=searxng-valkey
     volumes:
       - ./ollama_answers.py:/usr/local/searxng/searx/plugins/ollama_answers.py
 
@@ -96,6 +219,17 @@ environment:
   - LLM_API_KEY=your-bearer-token
 ```
 
+## Project Structure
+
+```
+ollama-ai-answers-searxng/
+├── ollama_answers.py      # single plugin file — all logic here
+├── README.md
+├── requirements.txt       # flask, flask-babel (for local dev only)
+└── tests/
+    └── dev.py             # local dev server
+```
+
 ## Development — Dev Server
 
 A standalone Flask dev server is included in `tests/dev.py`. It mocks the SearXNG plugin environment so you can test the full UI without a running SearXNG instance.
@@ -124,7 +258,7 @@ Then open [http://127.0.0.1:5000/](http://127.0.0.1:5000/) in your browser.
 
 ### Environment Variables (dev)
 
-The dev reads the same variables as the plugin:
+The dev server reads the same variables as the plugin:
 
 ```bash
 LLM_URL=http://localhost:11434/v1/chat/completions \

dev/.env.example

@@ -0,0 +1,39 @@
+# AI Answers Plugin — Dev Server Config
+# Copy this to .env and fill in your values
+# .env is gitignored and never committed
+
+# Ollama endpoint (required)
+LLM_URL=http://localhost:11434/v1/chat/completions
+
+# Default model
+LLM_MODEL=qwen3.5:9b
+
+# Max response tokens
+LLM_MAX_TOKENS=200
+
+# Response temperature (0.0 - 2.0)
+LLM_TEMPERATURE=0.2
+
+# Bearer token for authenticated LLM endpoints
+# Leave empty if no Bearer token is needed for your server
+LLM_API_KEY=
+
+# Live SearXNG instance for real search results
+# Leave empty to use mock results
+SEARXNG_URL=
+
+# Valkey for streaming (required)
+# Start with: docker run -d --name dev-valkey -p 6379:6379 valkey/valkey:9-alpine
+VALKEY_HOST=localhost
+VALKEY_PORT=6379
+
+# Dev server host and port
+DEV_HOST=127.0.0.1
+DEV_PORT=5000
+
+# Plugin settings
+LLM_INTERACTIVE=true
+LLM_QUESTION_MARK_REQUIRED=false
+LLM_TABS=general,science,it,news
+LLM_CONTEXT_DEEP_COUNT=5
+LLM_CONTEXT_SHALLOW_COUNT=15

requirements.txt

@@ -1,3 +1,5 @@
 flask
 flask-babel
 certifi
+python-dotenv
+valkey

tests/dev.py

@@ -1,346 +0,0 @@
-import sys
-import os
-sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-import logging
-from types import ModuleType
-from flask import Flask, request, redirect
-
-logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')
-os.environ.setdefault('LLM_URL', 'http://localhost:11434/v1/chat/completions')
-
-# SearXNG module mocks
-searx = ModuleType("searx")
-searx_plugins = ModuleType("searx.plugins")
-searx_results = ModuleType("searx.result_types")
-
-class MockPlugin:
-    def __init__(self, cfg):
-        self.active = getattr(cfg, 'active', True)
-
-class MockPluginInfo:
-    def __init__(self, **kwargs):
-        self.meta = kwargs
-
-class MockEngineResults:
-    def __init__(self):
-        self.types = ModuleType("types")
-        self.types.Answer = lambda *args, **kwargs: kwargs.get('answer', args[0] if args else "")
-        self._results = []
-    
-    def add(self, res):
-        self._results.append(res)
-
-searx_plugins.Plugin = MockPlugin
-searx_plugins.PluginInfo = MockPluginInfo
-searx_results.EngineResults = MockEngineResults
-
-searx.settings = {'server': {'secret_key': 'demo-secret'}}
-searx.network = ModuleType("searx.network")
-
-sys.modules["searx"] = searx
-sys.modules["searx.plugins"] = searx_plugins
-sys.modules["searx.result_types"] = searx_results
-
-# Network module mock
-searx_network = ModuleType("searx.network")
-def mock_network_call(method, url, **kwargs):
-    import http.client, ssl, json
-    from urllib.parse import urlparse
-    
-    parsed = urlparse(url)
-    port = parsed.port or (443 if parsed.scheme=='https' else 80)
-    target = f"{parsed.hostname}:{port}"
-    
-    if parsed.scheme == 'https':
-        conn = http.client.HTTPSConnection(target, timeout=30, context=ssl.create_default_context())
-    else:
-        conn = http.client.HTTPConnection(target, timeout=30)
-    
-    headers = kwargs.get('headers', {})
-    body = None
-    if kwargs.get('json'):
-        body = json.dumps(kwargs['json'])
-    elif kwargs.get('data'):
-        body = kwargs['data']
-
-    path = parsed.path
-    if parsed.query:
-        path += f"?{parsed.query}"
-    
-    if kwargs.get('params'):
-        from urllib.parse import urlencode
-        query_str = urlencode(kwargs['params'])
-        if '?' in path:
-            path += f"&{query_str}"
-        else:
-            path += f"?{query_str}"
-
-    conn.request(method, path, body=body, headers=headers)
-    return conn.getresponse()
-
-def mock_stream(method, url, **kwargs):
-    res = mock_network_call(method, url, **kwargs)
-    
-    class MockResponse:
-        def __init__(self, r):
-            self.status_code = r.status
-            self.text = "Mock Response" # Stub
-            self._r = r
-    
-    def generator():
-        while True:
-            chunk = res.read(128)
-            if not chunk: break
-            yield chunk
-
-    return MockResponse(res), generator()
-
-def mock_get(url, **kwargs):
-    import json
-    res = mock_network_call('GET', url, **kwargs)
-    
-    class MockResponse:
-        def __init__(self, r):
-            self.status_code = r.status
-            self._content = r.read()
-            self.text = self._content.decode('utf-8')
-        
-        def json(self):
-            return json.loads(self.text)
-            
-    return MockResponse(res)
-
-searx_network.stream = mock_stream
-searx_network.get = mock_get
-sys.modules["searx.network"] = searx_network
-
-from ollama_answers import SXNGPlugin
-from flask_babel import Babel
-
-app = Flask(__name__)
-babel = Babel(app)
-
-class MockConfig:
-    active = True
-
-plugin = SXNGPlugin(MockConfig())
-plugin.init(app)
-
-@app.route("/config", methods=["POST"])
-def update_config():
-    url = request.form.get("url", "").strip()
-    bearer = request.form.get("bearer", "").strip()
-    model = request.form.get("model", "").strip()
-    query = request.form.get("q", "")
-    if url:
-        plugin.endpoint_url = url
-    plugin.api_key = bearer if bearer else "ollama"
-    if model:
-        plugin.model = model
-    redirect_q = f"?q={query}" if query else ""
-    return redirect(f"/{redirect_q}")
-
-
-@app.route("/search")
-def mock_search():
-    query = request.args.get("q", "")
-    format_type = request.args.get("format", "html")
-    
-    if format_type != "json":
-        return "Demo only supports JSON format", 400
-    
-    results = [
-        {"title": f"Result 1 for: {query}", "content": f"This is simulated content about {query}. It contains relevant information.", "url": f"https://example.com/1/{query.replace(' ', '-')}", "publishedDate": "2026-01-18"},
-        {"title": f"Result 2 for: {query}", "content": f"Additional information regarding {query}. More context and details.", "url": f"https://example.com/2/{query.replace(' ', '-')}", "publishedDate": "2026-01-17"},
-        {"title": f"Result 3 for: {query}", "content": f"Further reading on {query}. Expert analysis.", "url": f"https://example.com/3/{query.replace(' ', '-')}", "publishedDate": "2026-01-16"},
-    ]
-    
-    return {
-        "results": results,
-        "infoboxes": [],
-        "answers": [],
-        "suggestions": [f"{query} explained", f"{query} tutorial"]
-    }
-
-@app.route("/")
-def index():
-    query = request.args.get("q", "why is the sky blue")
-    
-    class MockSearchQuery:
-        pageno = 1
-        lang = 'en'
-        categories = ['general']
-    MockSearchQuery.query = query
-    
-    class MockSearch:
-        search_query = MockSearchQuery()
-        class MockResultContainer:
-            def __init__(self):
-                self.answers = set()
-
-            def get_ordered_results(self):
-                base_results = [
-                    {"title": "Wikipedia", "content": "The sky appears blue due to Rayleigh scattering of sunlight. When sunlight enters the atmosphere, it collides with gas molecules and scatters in all directions. Blue light scatters more than other colors because it travels in shorter waves.", "url": "https://en.wikipedia.org/wiki/Rayleigh_scattering", "publishedDate": "2026-01-15"},
-                    {"title": "NASA Science", "content": "Shorter blue wavelengths scatter more than longer red wavelengths. This phenomenon, discovered by Lord Rayleigh in the 1870s, explains why we see a blue sky during the day.", "url": "https://science.nasa.gov/blue-sky", "publishedDate": "2026-01-10"},
-                    {"title": "Physics Today", "content": "The atmosphere acts as a filter, scattering blue light in all directions while letting other colors pass through more directly.", "url": "https://physicstoday.org/atmosphere", "publishedDate": "2026-01-01"},
-                    {"title": "Scientific American", "content": "At sunset, light travels through more atmosphere, scattering away the blue and leaving reds and oranges.", "url": "https://scientificamerican.com/sunset", "publishedDate": "2025-12-20"},
-                    {"title": "National Geographic", "content": "Ocean color also results from light scattering and absorption by water molecules.", "url": "https://nationalgeographic.com/ocean-blue", "publishedDate": "2025-12-15"},
-                ]
-                broad_results = [
-                    {"title": "MIT OpenCourseWare: Atmospheric Physics", "content": "Course materials.", "url": "https://ocw.mit.edu/physics"},
-                    {"title": "NOAA: Understanding the Atmosphere", "content": "Educational resource.", "url": "https://noaa.gov/atmosphere"},
-                    {"title": "BBC Science: Why is the sky blue?", "content": "Explainer article.", "url": "https://bbc.com/science/sky"},
-                    {"title": "Khan Academy: Light and Color", "content": "Video lesson.", "url": "https://khanacademy.org/light"},
-                    {"title": "HowStuffWorks: Rayleigh Scattering", "content": "Detailed explanation.", "url": "https://howstuffworks.com/rayleigh"},
-                    {"title": "Physics Stack Exchange: Sky color discussion", "content": "Q&A thread.", "url": "https://physics.stackexchange.com/sky"},
-                    {"title": "Quora: Atmospheric optics explained", "content": "Community answers.", "url": "https://quora.com/atmosphere"},
-                ]
-                if 'quantum' in query.lower():
-                    return [
-                        {"title": "IBM Quantum", "content": "Quantum computers rely on qubits, which can represent 0, 1, or both via superposition. They solve complex problems faster.", "url": "https://www.ibm.com/quantum", "publishedDate": "2026-01-15"},
-                        {"title": "Nature Physics", "content": "Entanglement allows qubits to be correlated instantly across distances. This is key for quantum cryptography and teleportation.", "url": "https://nature.com/articles/quantum", "publishedDate": "2026-01-10"},
-                        {"title": "Wikipedia", "content": "Quantum computing uses quantum mechanics. Major applications include drug discovery and materials science.", "url": "https://en.wikipedia.org/wiki/Quantum_computing", "publishedDate": "2025-12-01"}
-                    ] + broad_results
-                return base_results + broad_results
-        result_container = MockResultContainer()
-
-    search = MockSearch()
-    plugin.post_search(None, search)
-    
-    injection_html = ""
-    if search.result_container.answers:
-        injection_html = list(search.result_container.answers)[0]
-    
-    bearer_display = plugin.api_key if plugin.api_key != "ollama" else ""
-    return f"""
-    <!DOCTYPE html>
-    <html lang="en">
-    <head>
-        <meta charset="UTF-8">
-        <title>AI Answers Demo</title>
-        <style>
-            body {{
-                font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
-                padding: 2rem;
-                max-width: 800px;
-                margin: 0 auto;
-                background: #2e3440;
-                color: #eceff4;
-            }}
-            :root {{
-                --color-result-border: #3b4252;
-                --color-result-description: #d8dee9;
-                --color-base-font: #88c0d0;
-                --color-result-link: #81a1c1;
-            }}
-            .meta {{ color: #81a1c1; font-size: 0.9rem; }}
-            hr {{ border-color: #4c566a; }}
-            a {{ color: #88c0d0; }}
-            .config-panel {{
-                background: #3b4252;
-                border-radius: 6px;
-                padding: 1rem 1.25rem;
-                margin-bottom: 1.25rem;
-            }}
-            .config-panel summary {{
-                cursor: pointer;
-                font-size: 0.85rem;
-                color: #81a1c1;
-                user-select: none;
-            }}
-            .config-panel summary:hover {{ color: #88c0d0; }}
-            .config-row {{
-                display: flex;
-                flex-direction: column;
-                gap: 0.5rem;
-                margin-top: 0.75rem;
-            }}
-            .config-row label {{
-                font-size: 0.8rem;
-                color: #81a1c1;
-            }}
-            .config-row input {{
-                background: #2e3440;
-                border: 1px solid #4c566a;
-                border-radius: 4px;
-                color: #eceff4;
-                font-size: 0.85rem;
-                padding: 0.4rem 0.6rem;
-                width: 100%;
-                box-sizing: border-box;
-            }}
-            .config-row input:focus {{ outline: none; border-color: #81a1c1; }}
-            .config-btn {{
-                margin-top: 0.75rem;
-                background: #4c566a;
-                border: none;
-                border-radius: 4px;
-                color: #eceff4;
-                cursor: pointer;
-                font-size: 0.85rem;
-                padding: 0.4rem 1rem;
-            }}
-            .config-btn:hover {{ background: #5e81ac; }}
-            .search-row {{
-                display: flex;
-                gap: 0.5rem;
-                margin-bottom: 1.25rem;
-            }}
-            .search-row input {{
-                flex: 1;
-                background: #3b4252;
-                border: 1px solid #4c566a;
-                border-radius: 4px;
-                color: #eceff4;
-                font-size: 0.95rem;
-                padding: 0.45rem 0.75rem;
-            }}
-            .search-row input:focus {{ outline: none; border-color: #81a1c1; }}
-            .search-row button {{
-                background: #5e81ac;
-                border: none;
-                border-radius: 4px;
-                color: #eceff4;
-                cursor: pointer;
-                font-size: 0.9rem;
-                padding: 0.45rem 1rem;
-            }}
-            .search-row button:hover {{ background: #81a1c1; }}
-        </style>
-    </head>
-    <body>
-        <details class="config-panel" {'open' if not bearer_display and 'localhost' in plugin.endpoint_url else ''}>
-            <summary>&#9881; Ollama Configuration</summary>
-            <form method="POST" action="/config">
-                <input type="hidden" name="q" value="{query}">
-                <div class="config-row">
-                    <label>Endpoint URL</label>
-                    <input type="text" name="url" value="{plugin.endpoint_url}" placeholder="http://localhost:11434/v1/chat/completions">
-                </div>
-                <div class="config-row">
-                    <label>Bearer Token <span style="opacity:0.5;">(optional)</span></label>
-                    <input type="text" name="bearer" value="{bearer_display}" placeholder="Leave empty if not required">
-                </div>
-                <button type="submit" class="config-btn">Apply</button>
-            </form>
-        </details>
-
-        <form class="search-row" method="GET" action="/">
-            <input type="text" name="q" value="{query}" placeholder="Ask something...">
-            <button type="submit">Search</button>
-        </form>
-
-        <p class="meta">Model: <strong>{plugin.model}</strong></p>
-        <hr>
-        {injection_html if injection_html else '<p style="color:#f66;">No response — check your Ollama endpoint and token above.</p>'}
-    </body>
-    </html>
-    """
-
-if __name__ == "__main__":
-    print("AI Answers - Demo\n")
-    print(f"  Endpoint: {plugin.endpoint_url}")
-    print(f"  Model:    {plugin.model or 'N/A'}")
-    print(f"  Mode:     {'interactive' if plugin.interactive else 'simple'}")
-    print(f"\n  http://localhost:5000/?q=why+is+the+sky+blue\n")
-    app.run(debug=False, port=5000)