Config_Files/config.txt

[API]
anthropic_api_key = <anthropic_API_Key>
anthropic_model = claude-3-5-sonnet-20240620
cohere_api_key = <Cohere_API_Key>
cohere_model = command-r-plus
groq_api_key = <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-chat
mistral_model = mistral-large-latest
mistral_api_key = <mistral_api_key>
custom_openai_api = <key_here>
custom_openai_api_ip = <api_ip_here>

[Local-API]
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
vllm_model = <vllm model>
ollama_api_IP = http://127.0.0.1:11434/api/generate
ollama_api_key = <ollama api key>
ollama_model = <ollama model>
aphrodite_api_IP = http://127.0.0.1:8080/completion
aphrodite_api_key = <aphrodite_api_key>

[Paths]
output_path = Results
logging_file = Logs

[Processing]
processing_choice = cuda
# Can swap 'cuda' with 'cpu' if you want to use your CPU for processing

[Settings]
chunk_duration = 30
words_per_second = 3

[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
# 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]
embedding_provider = openai
embedding_model = text-embedding-3-small
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
# 'method' Can be 'words' / 'sentences' / 'paragraphs' / 'semantic' / 'tokens'
max_size = 400
overlap = 200
adaptive = false
# Use ntlk+punkt to split text into sentences and then ID average sentence length and set that as the chunk size
multi_level = false
language = english

#[Comments]
#OpenAI Models:
#    f
#Anthropic Models:
#    f
#Cohere Models:
#    f
#DeepSeek Models:
#    f
#Groq Models:
#    f
#Mistral Models:
#    mistral-large-latest
#    open-mistral-nemo
#    codestral-latest
#    mistral-embed
#    open-mistral-7b
#    open-mixtral-8x7b
#    open-mixtral-8x22b
#    open-codestral-mamba