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[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_key = <kobold api key> kobold_api_IP = http://127.0.0.1:5001/api/v1/generate llama_api_key = <llama.cpp api key> llama_api_IP = http://127.0.0.1:8080/completion ooba_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 = <tabbyapi key> vllm_api_IP = http://127.0.0.1:8000/v1/chat/completions [Paths] output_path = Results logging_file = Logs [Processing] processing_choice = cuda [Settings] max_tokens = 1000 [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 = media_summary.db elasticsearch_host = localhost elasticsearch_port = 9200 # Additionally you can use elasticsearch as the database type, just replace `sqlite` with `elasticsearch` for `type` and provide the `elasticsearch_host` and `elasticsearch_port` of your configured ES instance. chroma_db_path = chroma_db [Embeddings] provider = openai # Can be 'openai', 'local', or 'huggingface' model = text-embedding-3-small # Model name or path api_key = your_api_key_here api_url = http://localhost:8080/v1/embeddings # Only needed for 'local' provider [Chunking] method = words max_size = 400 overlap = 200 adaptive = false multi_level = false language = english |