Spaces:
Running
Running
| [API] | |
| anthropic_api_key = <anthropic_api_key | |
| anthropic_model = claude-3-sonnet-20240229 | |
| cohere_api_key = <cohere_api_key> | |
| cohere_model = command-r-plus | |
| groq_api_key = <your_groq_api_key> | |
| groq_model = llama3-70b-8192 | |
| openai_api_key = <openai_api_key> | |
| openai_model = gpt-4o | |
| huggingface_api_key = <huggingface_api_token> | |
| huggingface_model = CohereForAI/c4ai-command-r-plus | |
| openrouter_api_key = <openrouter_api_key> | |
| openrouter_model = mistralai/mistral-7b-instruct:free | |
| deepseek_api_key = <deepseek_api_key> | |
| deepseek_model = deepseek-coder | |
| mistral_model = mistral-large-latest | |
| mistral_api_key = <mistral_api_key> | |
| [Local-API] | |
| kobold_api_IP = http://127.0.0.1:5001/api/v1/generate | |
| kobold_api_key = | |
| llama_api_IP = http://127.0.0.1:8080/completion | |
| llama_api_key = | |
| ooba_api_key = | |
| ooba_api_IP = http://127.0.0.1:5000/v1/chat/completions | |
| tabby_api_IP = http://127.0.0.1:5000/v1/chat/completions | |
| tabby_api_key = | |
| vllm_api_IP = http://127.0.0.1:8000/v1/chat/completions | |
| vllm_model = | |
| ollama_api_IP = http://127.0.0.1:11434/v1/chat/completions | |
| ollama_api_key = | |
| ollama_model = llama3 | |
| aphrodite_api_IP = http://127.0.0.1:8080/completion | |
| aphrodite_api_key = | |
| [Processing] | |
| processing_choice = cuda | |
| [Settings] | |
| chunk_duration = 30 | |
| words_per_second = 3 | |
| [Auto-Save] | |
| save_character_chats = False | |
| save_rag_chats = False | |
| [Prompts] | |
| prompt_sample = "What is the meaning of life?" | |
| video_summarize_prompt = "Above is the transcript of a video. Please read through the transcript carefully. Identify the main topics that are discussed over the course of the transcript. Then, summarize the key points about each main topic in bullet points. The bullet points should cover the key information conveyed about each topic in the video, but should be much shorter than the full transcript. Please output your bullet point summary inside <bulletpoints> tags. Do not repeat yourself while writing the summary." | |
| [Database] | |
| type = sqlite | |
| sqlite_path = /Databases/media_summary.db | |
| elasticsearch_host = localhost | |
| elasticsearch_port = 9200 | |
| chroma_db_path = chroma_db | |
| backup_path = ./tldw_DB_Backups/ | |
| prompts_db_path = Databases/prompts.db | |
| rag_qa_db_path = Databases/RAG_QA_Chat.db | |
| character_db_path = Databases/chatDB.db | |
| [Embeddings] | |
| embedding_provider = openai | |
| embedding_model = text-embedding-3-small | |
| onnx_model_path = ./App_Function_Libraries/models/onnx_models/ | |
| model_dir = ./App_Function_Libraries/models/embedding_models | |
| embedding_api_url = http://localhost:8080/v1/embeddings | |
| embedding_api_key = your_api_key_here | |
| chunk_size = 400 | |
| overlap = 200 | |
| # 'embedding_provider' Can be 'openai', 'local', or 'huggingface' | |
| # `embedding_model` Set to the model name you want to use for embeddings. For OpenAI, this can be 'text-embedding-3-small', or 'text-embedding-3-large'. | |
| # huggingface: model = dunzhang/stella_en_400M_v5 | |
| [Chunking] | |
| method = words | |
| max_size = 400 | |
| overlap = 200 | |
| adaptive = false | |
| multi_level = false | |
| language = english | |
| # 'method' Can be 'words' / 'sentences' / 'paragraphs' / 'semantic' / 'tokens' | |
| # Use ntlk+punkt to split text into sentences and then ID average sentence length and set that as the chunk size | |
| [Metrics] | |
| log_file_path = | |
| #os.getenv("tldw_LOG_FILE_PATH", "tldw_app_logs.json") | |
| max_bytes = | |
| #int(os.getenv("tldw_LOG_MAX_BYTES", 10 * 1024 * 1024)) # 10 MB | |
| backup_count = 5 | |
| #int(os.getenv("tldw_LOG_BACKUP_COUNT", 5)) | |