f

App_Function_Libraries/TTS/TTS_Providers.py

@@ -92,6 +92,20 @@ def generate_audio(api_key, text, provider, voice=None, model=None, voice2=None,
             model=model
         )
 
+    elif provider == "google":
+        pass
+
+    elif provider == "gpt-soviTTS":
+        pass
+
+    elif provider == "piper":
+        logging.info("Using Piper TTS provider")
+        return generate_audio_piper(
+            input_text=text,
+            model=model,
+            output_file=output_file,
+        )
+
     else:
         error_msg = f"Invalid TTS provider: {provider}"
         logging.error(error_msg)
@@ -664,6 +678,53 @@ def test_generate_audio_alltalk():
 #######################################################
 
 
+#######################################################
+#
+# Piper TTS Provider Functions
+# https://github.com/rhasspy/piper
+# https://github.com/erew123/alltalk_tts/wiki/API-%E2%80%90-OpenAI-V1-Speech-Compatible-Endpoint
+
+def generate_audio_piper(input_text, voice=None, model=None, response_format=None, speed=None):
+    """Generate audio using Piper TTS.
+
+    Args:
+
+    Returns:
+        str: Path to the generated audio file
+    """
+
+    # Input validation
+    pass
+
+#
+# End of Piper TTS Provider Functions
+#######################################################
+
+
+#######################################################
+#
+# Vevo TTS Provider Functions
+#
+# https://github.com/open-mmlab/Amphion
+# https://huggingface.co/amphion/Vevo
+
+def generate_audio_piper(input_text, voice=None, model=None, response_format=None, speed=None):
+    """Generate audio using Piper TTS.
+
+    Args:
+
+    Returns:
+        str: Path to the generated audio file
+    """
+
+    # Input validation
+    pass
+
+#
+# End of Piper TTS Provider Functions
+#######################################################
+
+
 #######################################################
 #
 # gpt-soviTTS TTS Provider Functions

App_Function_Libraries/Utils/Utils.py

@@ -460,6 +460,10 @@ def load_and_log_configs():
         yandex_search_api_key = config.get('Search-Engines', 'search_engine_api_key_yandex', fallback='')
         yandex_search_engine_id = config.get('Search-Engines', 'search_engine_id_yandex', fallback='')
 
+        # Prompts
+        sub_question_generation_prompt = config.get('Prompts', 'sub_question_generation_prompt', fallback='')
+        search_result_relevance_eval_prompt = config.get('Prompts', 'search_result_relevance_eval_prompt', fallback='')
+        analyze_search_results_prompt = config.get('Prompts', 'analyze_search_results_prompt', fallback='')
 
         return {
             'anthropic_api': {
@@ -695,7 +699,12 @@ def load_and_log_configs():
                 'tavily_search_api_key': tavily_search_api_key,
                 'yandex_search_api_key': yandex_search_api_key,
                 'yandex_search_engine_id': yandex_search_engine_id
-            }
+            },
+            'prompts': {
+                'sub_question_generation_prompt': sub_question_generation_prompt,
+                'search_result_relevance_eval_prompt': search_result_relevance_eval_prompt,
+                'analyze_search_results_prompt': analyze_search_results_prompt,
+            },
         }
 
     except Exception as e:

App_Function_Libraries/Web_Scraping/WebSearch_APIs.py

@@ -478,6 +478,7 @@ def aggregate_results(
         - evidence (List[Dict]): List of relevant content items included in the summary.
         - confidence (float): A rough confidence score (placeholder).
     """
+    logging.info("Aggregating and summarizing relevant results")
     if not relevant_results:
         return {
             "Report": "No relevant results found. Unable to provide an answer.",
@@ -493,7 +494,6 @@ def aggregate_results(
     )
 
     # Example analysis prompt
-    # FIXME - Add to config.txt/utils.py
     analyze_search_results_prompt = f"""
         Generate a comprehensive, well-structured, and informative answer for a given question, 
         using ONLY the information found in the provided web Search Results (URL, Page Title, Summary).
@@ -535,13 +535,17 @@ def aggregate_results(
     input_data = "Follow the above instructions."
 
     try:
+        logging.info("Generating the report")
         returned_response = chat_api_call(
             api_endpoint=api_endpoint,
             api_key=None,
             input_data=input_data,
             prompt=analyze_search_results_prompt,
-            temp=0.7
+            temp=0.7,
+            system_message=None,
+            streaming=False
         )
+        logging.debug(f"Returned response from LLM: {returned_response}")
         if returned_response:
             # You could do further parsing or confidence estimation here
             return {
@@ -552,6 +556,7 @@ def aggregate_results(
     except Exception as e:
         logging.error(f"Error aggregating results: {e}")
 
+    logging.error("Could not create the report due to an error.")
     return {
         "summary": "Could not create the report due to an error.",
         "evidence": list(relevant_results.values()),

Docs/Design/Diagram_Generation.md

@@ -4,6 +4,8 @@
 ### Link Dump:
 https://excalidraw.com/
 https://www.napkin.ai/
+https://github.com/southbridgeai/diagen
+
 
 
 

Docs/Design/Researcher.md

@@ -115,6 +115,8 @@ Gemini Deepresearcher
 https://github.com/assafelovic/gpt-researcher
 https://arxiv.org/abs/2411.15114
 
+https://github.com/binary-husky/gpt_academic/blob/master/docs/README.English.md
+https://arxiv.org/abs/2409.13741
 https://github.com/assafelovic/gpt-researcher/tree/master/gpt_researcher
 
 https://github.com/neuml/annotateai

Docs/Design/Structured_Outputs.md

@@ -1,5 +1,9 @@
 # Structured Outputs
 
+
+https://towardsdatascience.com/diving-deeper-with-structured-outputs-b4a5d280c208
+
+
 ## Introduction
 This page serves as documentation regarding the structured outputs within tldw and provides context/justification for the decisions made within the module.
 

Docs/Design/Summarization.md

@@ -18,4 +18,5 @@ https://neptune.ai/blog/llm-evaluation-text-summarization
 https://phoenix.arize.com/llm-summarization-getting-to-production/
 https://blog.metrostar.com/iteratively-summarize-long-documents-llm
 https://arxiv.org/html/2412.15487v1
+https://arxiv.org/pdf/2204.01849
 

Docs/Design/TTS_STT.md

@@ -34,9 +34,6 @@ https://github.com/albirrkarim/react-speech-highlight-demo
 https://funaudiollm.github.io/cosyvoice2/
 https://funaudiollm.github.io/cosyvoice2/
 https://github.com/InternLM/InternLM-XComposer/tree/main/InternLM-XComposer-2.5-OmniLive
-https://github.com/huggingface/transformers.js-examples/tree/main/moonshine-web
-https://huggingface.co/onnx-community/moonshine-base-ONNX
-https://github.com/usefulsensors/moonshine
 https://github.com/Azure-Samples/aisearch-openai-rag-audio
 https://www.reddit.com/r/LocalLLaMA/comments/1f0awd6/best_local_open_source_texttospeech_and/
 https://github.com/FanaHOVA/smol-podcaster
@@ -47,18 +44,25 @@ https://huggingface.co/spaces/mozilla-ai/document-to-podcast/blob/main/app.py
 https://huggingface.co/spaces/Nymbo/Voice-Clone-Multilingual/tree/main
 https://github.com/aedocw/epub2tts
 https://github.com/microsoft/SpeechT5
+https://www.lightnote.co/?utm_source=www.hivefive.community&utm_medium=newsletter&utm_campaign=hive-five-202-a-bias-to-action
 https://github.com/smellslikeml/dolla_llama
-
+https://github.com/dnhkng/GlaDOS
 
 STT
     https://github.com/KoljaB/RealtimeSTT
+    https://github.com/southbridgeai/offmute
+    MoonShine
+        https://github.com/usefulsensors/moonshine
+        https://github.com/huggingface/transformers.js-examples/tree/main/moonshine-web
+        https://huggingface.co/onnx-community/moonshine-base-ONNX
 
 TTS
     https://github.com/KoljaB/RealtimeTTS
 
 101
     https://www.inferless.com/learn/comparing-different-text-to-speech---tts--models-for-different-use-cases
     https://clideo.com/resources/what-is-tts
+    https://pub.towardsai.net/the-ultimate-guide-to-audio-processing-principles-techniques-and-applications-7724efea00e8
     RVC 101
         https://gudgud96.github.io/2024/09/26/annotated-rvc/
 
@@ -130,6 +134,8 @@ MaskGCT
 Parler
     https://github.com/huggingface/parler-tts
 
+Sherpa ONNX
+    https://github.com/k2-fsa/sherpa-onnx
 
 YourTTS
     https://github.com/Edresson/YourTTS

Docs/Design/UX.md

@@ -84,6 +84,9 @@ https://markwhen.com/
 https://kando.menu/
 https://deepseek-artifacts.vercel.app/
 
+Not waifus, but clippy:
+  https://github.com/fghrsh/live2d_demo
+
 
 Prompt Engineering page:
 - 3 Sections

Docs/Issues/Citations_and_Confabulations.md

@@ -6,20 +6,21 @@
 3. [References](#references)
 
 
-
-https://arxiv.org/abs/2412.04235
-https://arxiv.org/abs/2412.11536
-https://github.com/sunnynexus/RetroLLM
-https://huggingface.co/PleIAs/Pleias-Nano
-https://deepmind.google/discover/blog/facts-grounding-a-new-benchmark-for-evaluating-the-factuality-of-large-language-models/
-https://arxiv.org/abs/2412.14860
-https://arxiv.org/abs/2412.14686
-https://arxiv.org/abs/2412.18069
-
-
-
 RAG
   https://www.lycee.ai/blog/rag-ragallucinations-and-how-to-fight-them
+  https://huggingface.co/PleIAs/Pleias-Nano
+  https://arxiv.org/abs/2412.11536
+  https://cloud.google.com/generative-ai-app-builder/docs/check-grounding
+  https://cloud.google.com/generative-ai-app-builder/docs/grounded-gen
+  https://arxiv.org/html/2412.15189v1#S6
+  https://aclanthology.org/2024.fever-1.10/
+  https://arxiv.org/pdf/2412.15189
+  https://huggingface.co/papers/2408.12060
+  https://primer.ai/research/rag-v-divide-and-conquer-with-factual-claims/
+  https://arxiv.org/abs/2411.06037
+  https://www.sciencedirect.com/science/article/abs/pii/S0306457320309675
+  https://github.com/Huffon/factsumm
+  https://arxiv.org/abs/2410.07176
 
 Finetuning: 
 - https://eugeneyan.com/writing/finetuning/
@@ -30,8 +31,12 @@ Finetuning:
 - **101**
 - Unsorted
     - https://mattyyeung.github.io/deterministic-quoting#7-conclusion-is-this-really-ready-for-healthcare
+  https://github.com/sunnynexus/RetroLLM
+    - https://github.com/MadryLab/context-cite
 
-
+Abstractive Proposition Segmentation
+  https://arxiv.org/abs/2406.19803
+  https://huggingface.co/google/gemma-2b-aps-it
 
 Anthropic:
 ```
@@ -71,6 +76,12 @@ Benchmarks
   https://huggingface.co/spaces/vectara/Hallucination-evaluation-leaderboard
   https://huggingface.co/spaces/hallucinations-leaderboard/leaderboard
   https://osu-nlp-group.github.io/AttributionBench/
+  Fake News
+    https://arxiv.org/abs/2412.14686
+  FACTS
+    https://www.kaggle.com/facts-leaderboard
+    https://storage.googleapis.com/deepmind-media/FACTS/FACTS_grounding_paper.pdf
+    https://deepmind.google/discover/blog/facts-grounding-a-new-benchmark-for-evaluating-the-factuality-of-large-language-models/
 
 
 Detecting Hallucinations using Semantic Entropy:
@@ -93,38 +104,52 @@ Explainability
 
 Research
   https://github.com/EdinburghNLP/awesome-hallucination-detection
-  https://arxiv.org/abs/2407.13481
-  https://arxiv.org/abs/2408.06195
-  https://arxiv.org/abs/2407.19813
   https://www.lycee.ai/blog/rag-ragallucinations-and-how-to-fight-them
-  https://arxiv.org/abs/2407.16557
-  https://arxiv.org/abs/2407.16604
-  https://arxiv.org/pdf/2309.11495
-  https://deepmind.google/research/publications/85420/
   https://thetechoasis.beehiiv.com/p/eliminating-hallucinations-robots-imitate-us
-  https://arxiv.org/abs/2407.19825
-  https://arxiv.org/abs/2411.14257
-  https://arxiv.org/pdf/2406.02543
-  https://arxiv.org/pdf/2410.19385
-  https://arxiv.org/abs/2406.10279
-  https://arxiv.org/abs/2402.17811
-  https://arxiv.org/pdf/2409.18475
   https://llm-editing.github.io/
-  https://arxiv.org/abs/2411.14257
-  https://arxiv.org/pdf/2407.03651
   https://cleanlab.ai/blog/trustworthy-language-model/
-  https://arxiv.org/abs/2408.07852
+  General
+    https://arxiv.org/pdf/2410.19385
+    https://arxiv.org/pdf/2409.18475
+    https://arxiv.org/pdf/2406.02543
+    https://arxiv.org/abs/2407.19825
+    https://arxiv.org/abs/2407.16604
+    https://arxiv.org/abs/2407.16557
+    https://arxiv.org/abs/2412.04235
+  Attention/Long Context
+    https://arxiv.org/abs/2407.13481
+    https://arxiv.org/pdf/2407.03651
+  CoV
+    https://arxiv.org/pdf/2309.11495
+  KnowledgeGraph
+    https://arxiv.org/abs/2408.07852
+  Mutual Reasoning
+    https://arxiv.org/abs/2408.06195
+  Self-Reasoning
+    https://arxiv.org/abs/2407.19813
+    https://arxiv.org/abs/2412.14860
   Detecting Hallucinations
     https://arxiv.org/abs/2410.22071
     https://arxiv.org/abs/2410.02707
+    https://arxiv.org/abs/2411.14257
   Reflective thinking
     https://arxiv.org/html/2404.09129v1
     https://github.com/yanhong-lbh/LLM-SelfReflection-Eval
   Semantic Entropy
     https://www.nature.com/articles/s41586-024-07421-0
     https://arxiv.org/abs/2406.15927
+  Software Packages
+    https://arxiv.org/abs/2406.10279
+  TruthX
+    https://arxiv.org/abs/2402.17811
+  Working memory
+    https://arxiv.org/abs/2412.18069
   HALVA
     https://research.google/blog/halva-hallucination-attenuated-language-and-vision-assistant/
+Long Form Factuality - Google
+  https://github.com/google-deepmind/long-form-factuality
+  https://deepmind.google/research/publications/85420/
+
 
 
 LLM As Judge:

requirements.txt

@@ -31,6 +31,7 @@ openai
 #outlines
 pandas
 Pillow
+#piper-tts
 playwright
 # I'm not using postgres yet...
 #psycopg2