Moved GPT4all to chat plugin more

searx/plugins/chat.py

@@ -1,4 +1,6 @@
 from searx.search import SearchWithPlugins
+from pathlib import Path
+from gpt4all import GPT4All
 
 
 name = "Chat Plugin"
@@ -11,5 +13,29 @@ def post_search(request, search: SearchWithPlugins) -> None:
     search_request = search.search_query
     container = search.result_container
     # container.infoboxes.append(container.infoboxes[0])
-    container.chat_box = [{'chat_box': 'hello world'}]
+    container.chat_box = {'chat_box': 'GPT4All'}
-    container.chat_box[0]['content'] = 'some string that relates to your search query here' + f'\n{search_request.query}'
+    container.chat_box['content'] = 'Generating response to query: ' + f'\n{search_request.query}'
+
+def generate_chat_content(query):
+    model = GPT4All(model_name='gpt4all-falcon-q4_0.gguf',
+            model_path=(Path.cwd() / 'searx' / 'plugins'),
+            allow_download=False)
+
+    system_template = """
+    ### System Instructions: 
+    1. Provide concise and directly relevant answers to the specific query in HTML format, emulating the style of an info box on a search engine.
+    2. Only use appropriate HTML tags (e.g., `<div>`, `<p>`, `<h1>`) to structure the response. Do not use markdown syntax or backticks(```) to format the response.
+    3. Directly address the query. For example, if the query is about a specific function or method in a programming language, focus on explaining and providing examples of that function or method.
+    4. Include practical examples or code snippets relevant to the query.
+    5. Keep definitions or explanations brief and specific, focusing only on aspects directly related to the query.
+    """
+
+    prompt_template = """
+    ### Query: 
+    {0}
+
+    ### Expected Information Box:
+    """
+    with model.chat_session(system_template, prompt_template):
+        response = model.generate(query, max_tokens=500, repeat_penalty=1.3)
+        return str(response)

searx/templates/kvanDark/elements/chat_box.html

@@ -3,21 +3,24 @@
     <p><bdi>{{ chat_box.content | safe }}</bdi></p>
 </aside>
 <script>
-    document.addEventListener("DOMContentLoaded", function () {
+    window.onload = function () {
-        function updateChatBox() {
+        // Extract the 'q' parameter from the search URL in the sidebar
-            fetch('/get-chat-content')
+        const searchUrl = document.querySelector('#search_url pre').textContent;
-                .then(response => response.json())
+        const url = new URL(searchUrl);
-                .then(data => {
+        const query = url.searchParams.get('q');
-                    const chatBox = document.querySelector('.chat_box');
-                    console.log('response from api', data);
-                    chatBox.querySelector('bdi').textContent = data.chat_box;
-                    chatBox.querySelector('p').textContent = data.content;
-                })
-                .catch(error => console.error('Error:', error));
-        }
 
-        // Call updateChatBox after search is completed
+        fetch('/generate-chat-content', {
-        // This might be tied to an event, depending on how your search functionality is implemented
+            method: 'POST',
-        updateChatBox();
+            headers: {
-    });
+                'Content-Type': 'application/json',
+            },
+            body: JSON.stringify({ query: query }),
+        })
+            .then(response => response.json())
+            .then(data => {
+                const chatBox = document.querySelector('.chat_box');
+                chatBox.querySelector('h2 bdi').style.display = 'none';
+                chatBox.querySelector('p bdi').innerHTML = data.content;
+            });
+    };
 </script>

searx/webapp.py

@@ -96,7 +96,7 @@ from searx.utils import (
 from searx.version import VERSION_STRING, GIT_URL, GIT_BRANCH
 from searx.query import RawTextQuery
 from searx.plugins import Plugin, plugins, initialize as plugin_initialize
-import searx.plugins.chat
+import searx.plugins.chat as chat
 from searx.plugins.oa_doi_rewrite import get_doi_resolver
 from searx.preferences import (
     Preferences,
@@ -664,7 +664,7 @@ def search():
         search_query, raw_text_query, _, _, selected_locale = get_search_query_from_webapp(
             request.preferences, request.form
         )
-        if searx.plugins.chat in request.user_plugins:
+        if chat in request.user_plugins:
             extremely_bad_global_variable_search_query = raw_text_query.getQuery()
         search = SearchWithPlugins(search_query, request.user_plugins, request)  # pylint: disable=redefined-outer-name
         result_container = search.search()
@@ -1309,43 +1309,13 @@ def config():
         }
     )
 
-@app.route('/get-chat-content')
+@app.route('/generate-chat-content', methods=['POST'])
-def get_chat_content():
+def generate_chat_content_endpoint():
-    global extremely_bad_global_variable_search_query
+    if request.json is None:
-    # Retrieve chat content from wherever it's stored
+        return jsonify({'content': ''})
-    # temp
+    query = request.json.get('query')
-    chat_content = None
+    chat_content = chat.generate_chat_content(query)
-    # retrieve from searx.plugins.chat
+    return jsonify({'chat_box': 'GPT4ALL', 'content': chat_content})
-    if extremely_bad_global_variable_search_query:
-        # do task
-        chat_content = {'chat_box': 'hello world', 'content': 'Not Generated Response Yet'}
-        model = GPT4All(model_name='gpt4all-falcon-q4_0.gguf',
-                model_path=(Path.cwd() / 'searx' / 'plugins'),
-                allow_download=False)
-
-        system_template = """
-### System Instructions: 
-1. Provide concise, accurate, and directly relevant answers to queries.
-2. Emulate the style of a Google Answer Box, which includes straightforward and authoritative responses.
-3. Where appropriate, use bullet points or structured formatting to clearly present information.
-4. Avoid unnecessary elaborations and focus on the key points of the query.
-5. Ensure the information is up-to-date and factually correct.
-"""
-
-        prompt_template = """
-### Query: 
-{0}
-
-### Expected Response:
-"""
-        with model.chat_session(system_template, prompt_template):
-            response = model.generate(extremely_bad_global_variable_search_query)
-            chat_content['content'] = str(response)
-
-        extremely_bad_global_variable_search_query = None
-
-
-    return jsonify(chat_content)
 
 
 @app.errorhandler(404)