Making project Ollama focused

ai_answers.py

@@ -45,17 +45,6 @@ def _get_streaming_connection(url: str):
 PLUGIN_NAME = "AI Answers"
 DEFAULT_TABS = "general,science,it,news"
 
-PROVIDER_PRESETS = {
-    'openai':     {'url': 'https://api.openai.com/v1/chat/completions',       'model': 'gpt-4o-mini'},
-    'openrouter': {'url': 'https://openrouter.ai/api/v1/chat/completions',    'model': 'google/gemma-3-27b-it:free'},
-    'ollama':     {'url': 'http://localhost:11434/v1/chat/completions',       'model': 'llama3.2'},
-    'localai':    {'url': 'http://localhost:8080/v1/chat/completions',        'model': 'gpt-4'},
-    'lmstudio':   {'url': 'http://localhost:1234/v1/chat/completions',        'model': 'local-model'},
-    'gemini':     {'url': 'https://generativelanguage.googleapis.com/v1beta/models/{model}:streamGenerateContent', 'model': 'gemma-3-27b-it'},
-    'azure':      {'url': None,                                               'model': 'azure-deployment'},
-    'huggingface': {'url': 'https://api-inference.huggingface.co/models/{model}/v1/chat/completions', 'model': 'meta-llama/Meta-Llama-3-8B-Instruct'}
-}
-
 # UI assets
 
 INTERACTIVE_CSS = '''
@@ -745,89 +734,24 @@ class SXNGPlugin(Plugin):
         self.info = PluginInfo(
             id=self.id,
             name=gettext(f"{PLUGIN_NAME} Plugin"),
-            description=gettext("Live AI search answers using LLM providers."),
+            description=gettext("Local AI search overviews powered by Ollama."),
             preference_section="general",
         )
         self._load_config()
 
 
 
-    def _ollama_unload_model(self) -> None:
-        try:
-            if self.provider != 'ollama':
-                return
-            if not getattr(self, 'ollama_unload_after', False):
-                return
-            unload_url = (getattr(self, 'ollama_unload_url', '') or '').strip()
-            if not unload_url:
-                return
-
-            conn = None
-            try:
-                conn, path = _get_streaming_connection(unload_url)
-                conn.timeout = 2.0 
-                payload = json.dumps({
-                    "model": self.model,
-                    "messages": [],
-                    "keep_alive": 0
-                })
-                headers = {"Content-Type": "application/json"}
-                if self.api_key and self.api_key not in ('none', 'ollama'):
-                    headers["Authorization"] = f"Bearer {self.api_key}"
-                conn.request("POST", path, body=payload, headers=headers)
-                res = conn.getresponse()
-                res.read()
-                if res.status >= 400:
-                    logger.warning(f"{PLUGIN_NAME}: Ollama unload failed: {res.status} {res.reason}")
-            finally:
-                if conn:
-                    conn.close()
-        except Exception as e:
-            logger.warning(f"{PLUGIN_NAME}: Ollama unload error: {e}")
-
     def _load_config(self):
         self.interactive = os.getenv('LLM_INTERACTIVE', 'true').lower().strip() in ('true', '1', 'yes', 'on')
         self.question_mark_required = os.getenv('LLM_QUESTION_MARK_REQUIRED', 'false').lower().strip() in ('true', '1', 'yes', 'on')
-        raw_provider = os.getenv('LLM_PROVIDER', '').lower().strip()
 
-        raw_url = os.getenv('LLM_URL', '').strip()
+        raw_url = os.getenv('LLM_URL', 'http://ollama:11434/v1/chat/completions').strip()
-        if not raw_provider and raw_url:
+        if not raw_url.startswith(('http://', 'https://')):
-            url_lower = raw_url.lower()
+            raw_url = f"http://{raw_url}"
-            if 'openai.com' in url_lower:
+        self.endpoint_url = raw_url
-                raw_provider = 'openai'
-            elif 'openrouter.ai' in url_lower:
-                raw_provider = 'openrouter'
-            elif ':11434' in url_lower:
-                raw_provider = 'ollama'
-            elif 'generativelanguage.googleapis.com' in url_lower:
-                raw_provider = 'gemini'
-            elif 'openai.azure.com' in url_lower or '.azure.com' in url_lower:
-                raw_provider = 'azure'
-            elif 'huggingface.co' in url_lower:
-                raw_provider = 'huggingface'
-            else:
-                raw_provider = 'openai'
-                logger.info(f"{PLUGIN_NAME}: Using OpenAI-compatible mode for custom URL")
 
-        if not raw_provider:
+        self.api_key = 'ollama'
-            self.provider = ''
+        self.model = os.getenv('LLM_MODEL', 'llama3.2').strip()
-            self.model = ''
-            self.is_gemini = False
-            self.api_key = ''
-            return
-        
-        if raw_provider not in PROVIDER_PRESETS:
-            logger.warning(f"{PLUGIN_NAME}: Unknown provider '{raw_provider}', falling back to 'openai'")
-        self.provider = raw_provider if raw_provider in PROVIDER_PRESETS else 'openai'
-        self.is_gemini = (self.provider == 'gemini')
-        preset = PROVIDER_PRESETS[self.provider]
-
-        self.api_key = os.getenv('LLM_KEY', '')
-        if not self.api_key and self.provider in ('ollama', 'localai', 'lmstudio'):
-            self.api_key = 'none'
-        self.api_key = self.api_key.strip()
-
-        self.model = os.getenv('LLM_MODEL', preset['model']).strip()
 
         try:
             self.max_tokens = max(1, int(os.getenv('LLM_MAX_TOKENS', 200)))
@@ -852,27 +776,6 @@ class SXNGPlugin(Plugin):
 
         self.allowed_tabs = set(t.strip() for t in os.getenv('LLM_TABS', DEFAULT_TABS).split(','))
 
-        preset_url = preset['url']
-        if preset_url and '{model}' in preset_url:
-            preset_url = preset_url.format(model=self.model)
-        
-        raw_url = os.getenv('LLM_URL', '').strip() or preset_url
-        if not raw_url.startswith(('http://', 'https://')):
-            raw_url = f"https://{raw_url}"
-        self.endpoint_url = raw_url
-        
-        self.ollama_unload_after = os.getenv('LLM_OLLAMA_UNLOAD_AFTER', 'false').lower().strip() in ('true', '1', 'yes', 'on')
-        self.ollama_unload_url = ''
-        if self.provider == 'ollama' and self.ollama_unload_after:
-            try:
-                p = urlparse(self.endpoint_url)
-                scheme = p.scheme or 'http'
-                host = p.hostname or 'localhost'
-                port = p.port
-                netloc = f"{host}:{port}" if port else host
-                self.ollama_unload_url = f"{scheme}://{netloc}/api/chat"
-            except Exception:
-                self.ollama_unload_url = "http://localhost:11434/api/chat"
         server_secret = settings.get('server', {}).get('secret_key', '')
         self.secret = hashlib.sha256(f"ai_answers_{server_secret}".encode()).hexdigest()
 
@@ -923,9 +826,6 @@ class SXNGPlugin(Plugin):
 
 
     def init(self, app):
-        if not self.provider:
-            return
-
         @app.route('/ai-auxiliary-search', methods=['POST'])
         def ai_auxiliary_search():
             if not self.api_key:
@@ -1015,9 +915,6 @@ class SXNGPlugin(Plugin):
             except (ValueError, KeyError, AttributeError):
                 abort(403)
 
-            if self.provider != 'ollama':
-                return jsonify({'models': [self.model] if self.model else []})
-
             conn = None
             try:
                 p = urlparse(self.endpoint_url)
@@ -1122,111 +1019,6 @@ class SXNGPlugin(Plugin):
 {numbered_instructions}
 </CORE_DIRECTIVES>"""
 
-            def call_gemini():
-                base = self.endpoint_url.replace('streamGenerateContent', 'generateContent')
-                url = f"{base}&key={self.api_key}" if '?' in base else f"{base}?key={self.api_key}"
-                conn = None
-                try:
-                    conn, path = _get_streaming_connection(url)
-                    payload = json.dumps({
-                        "contents": [{"parts": [{"text": prompt}]}],
-                        "generationConfig": {"maxOutputTokens": min(self.max_tokens * 4, 8192), "temperature": self.temperature}
-                    })
-                    conn.request("POST", path, body=payload.encode('utf-8'), headers={"Content-Type": "application/json"})
-                    res = conn.getresponse()
-                    if res.status != 200:
-                        body = res.read(2048).decode('utf-8', errors='replace')[:500]
-                        logger.error(f"{PLUGIN_NAME}: Gemini API {res.status}: {body}")
-                        return '', f"API error {res.status}. Check server logs."
-                    obj = json.loads(res.read().decode('utf-8', errors='replace'))
-                    if obj.get('promptFeedback', {}).get('blockReason'):
-                        return '', f"Gemini blocked prompt: {obj['promptFeedback']['blockReason']}"
-                    candidates = obj.get('candidates', [])
-                    if not candidates:
-                        return '', "No candidates in Gemini response."
-                    first = candidates[0]
-                    if first.get('finishReason') == 'SAFETY':
-                        return '', "Gemini stopped generation due to safety filters."
-                    parts = first.get('content', {}).get('parts', [])
-                    text = ''.join(p.get('text', '') for p in parts if isinstance(p, dict))
-                    return text, None
-                except Exception as e:
-                    logger.error(f"{PLUGIN_NAME}: Gemini call error: {e}", exc_info=True)
-                    return '', f"Connection Error: {e}"
-                finally:
-                    if conn: conn.close()
-
-            def call_openai_compatible():
-                conn = None
-                try:
-                    conn, path = _get_streaming_connection(self.endpoint_url)
-                    payload_dict = {
-                        "model": effective_model,
-                        "messages": [
-                            {"role": "system",    "content": SYSTEM},
-                            {"role": "user",      "content": prompt},
-                            {"role": "assistant", "content": ""},
-                        ],
-                        "stream": False,
-                        "max_tokens": self.max_tokens,
-                        "temperature": self.temperature
-                    }
-                    payload = json.dumps(payload_dict)
-                    headers = {
-                        "Content-Type": "application/json",
-                        "HTTP-Referer": "https://github.com/searxng/searxng",
-                        "X-Title": "SearXNG"
-                    }
-                    if self.provider == 'azure':
-                        headers['api-key'] = self.api_key
-                    else:
-                        headers['Authorization'] = f"Bearer {self.api_key}"
-                    conn.request("POST", path, body=payload.encode('utf-8'), headers=headers)
-                    res = conn.getresponse()
-                    if res.status != 200:
-                        body = res.read(2048).decode('utf-8', errors='replace')[:500]
-                        logger.error(f"{PLUGIN_NAME}: {self.provider} API {res.status}: {body}")
-                        return '', f"API error {res.status}. Check server logs."
-                    obj = json.loads(res.read().decode('utf-8', errors='replace'))
-                    if "error" in obj:
-                        err = obj["error"]
-                        msg = err.get("message", str(err)) if isinstance(err, dict) else str(err)
-                        return '', f"API Error: {msg}"
-                    choices = obj.get("choices", [])
-                    if not choices:
-                        return '', "No choices in API response."
-                    message = choices[0].get("message", {})
-                    content = re.sub(r'<think>.*?</think>', '', message.get("content") or "", flags=re.DOTALL).strip()
-                    reasoning = message.get("reasoning") or message.get("reasoning_content") or ""
-                    if not content and reasoning:
-                        logger.warning(f"{PLUGIN_NAME}: {self.provider} returned empty content; extracting answer from reasoning field")
-                        header_pat = re.compile(r'^\s*\*?\*?[A-Z][^:]{0,40}:\*?\*?\s*$', re.MULTILINE)
-                        matches = list(header_pat.finditer(reasoning))
-                        if matches:
-                            answer = reasoning[matches[-1].end():].strip()
-                        else:
-                            paras = [p.strip() for p in re.split(r'\n{2,}', reasoning) if p.strip()]
-                            answer = paras[-1] if paras else reasoning.strip()
-                        full = answer
-                    else:
-                        full = (f"<think>\n{reasoning}\n</think>\n\n" if reasoning else "") + content
-                    full = re.sub(r'<think>.*?</think>', '', full, flags=re.DOTALL).strip()
-                    return full, None
-                except Exception as e:
-                    logger.error(f"{PLUGIN_NAME}: {self.provider} call error: {e}", exc_info=True)
-                    return '', f"Connection Error: {e}"
-                finally:
-                    if conn: conn.close()
-
-            call_fn = call_gemini if self.is_gemini else call_openai_compatible
-            text, error = call_fn()
-
-            if self.provider == 'ollama' and getattr(self, 'ollama_unload_after', False):
-                self._ollama_unload_model()
-
-            return jsonify({"text": text, "error": error})
-        return True
-
     def _assemble_context(self, clean_results, infoboxes, answers, offset=0) -> tuple[str, list]:
         """Builds context string from normalized search data. Returns (context_str, urls)."""
         context_parts = []