Indexing with large corpus

.github/FUNDING.yml

@@ -0,0 +1 @@
+patreon: wafl

README.md

@@ -1,6 +1,6 @@
 # ![Logo](images/logo.png) WAFL 0.1.0 [![Tests](https://github.com/fractalego/wafl/actions/workflows/development-tests1.yml/badge.svg)](https://github.com/fractalego/wafl/actions/workflows/development-tests1.yml)[![Docs](https://readthedocs.org/projects/wafl/badge/?version=latest)](https://wafl.readthedocs.io/en/latest/)
 
-Introduction
+Introductionhttps://www.youtube.com/watch?v=QKHSlBi5qok
 ============
 
 WAFL is a framework for personal agents. It integrates Large language models, speech recognition and text to speech.

todo.txt

@@ -1,3 +1,5 @@
+* knowledge cache does not cache the rules or facts
+
 * multiple knowledge bases, one for internal facts and one for each indexed paths
 * perhaps a way to structure the prompt using <> tags. The memory items need to be distinct.
 * use poetry

wafl/knowledge/indexing_implementation.py

@@ -45,6 +45,7 @@ async def load_knowledge(config, logger=None):
         if knowledge.hash == hash(rules_txt) and os.path.getmtime(
             cache_filename
         ) > os.path.getmtime(index_filename):
+            await knowledge.initialize_retrievers()
             return knowledge
 
     knowledge = SingleFileKnowledge(config, rules_txt, logger=logger)

wafl/runners/run_web_and_audio_interface.py

@@ -2,7 +2,7 @@
 import sys
 import threading
 
-from flask import render_template, redirect, url_for
+from flask import render_template, redirect
 
 from wafl.interface.list_interface import ListInterface
 from wafl.interface.voice_interface import VoiceInterface

wafl/variables.py

@@ -1,6 +1,6 @@
 def get_variables():
     return {
-        "version": "0.1.0",
+        "version": "0.1.1",
     }