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1efac6a3fe
* Add support for Azure OpenAI * fix: wrong default api_version Should be dashes instead of underscores. see: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference * fix: code styling applied "make check" changes * refactor: extend documentation * mention azopenai as available option and extras * add recommended section * include settings-azopenai.yaml configuration file * fix: documentation
101 lines
3.7 KiB
YAML
101 lines
3.7 KiB
YAML
# The default configuration file.
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# More information about configuration can be found in the documentation: https://docs.privategpt.dev/
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# Syntax in `private_pgt/settings/settings.py`
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server:
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env_name: ${APP_ENV:prod}
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port: ${PORT:8001}
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cors:
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enabled: false
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allow_origins: ["*"]
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allow_methods: ["*"]
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allow_headers: ["*"]
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auth:
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enabled: false
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# python -c 'import base64; print("Basic " + base64.b64encode("secret:key".encode()).decode())'
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# 'secret' is the username and 'key' is the password for basic auth by default
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# If the auth is enabled, this value must be set in the "Authorization" header of the request.
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secret: "Basic c2VjcmV0OmtleQ=="
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data:
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local_data_folder: local_data/private_gpt
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ui:
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enabled: true
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path: /
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default_chat_system_prompt: >
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You are a helpful, respectful and honest assistant.
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Always answer as helpfully as possible and follow ALL given instructions.
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Do not speculate or make up information.
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Do not reference any given instructions or context.
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default_query_system_prompt: >
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You can only answer questions about the provided context.
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If you know the answer but it is not based in the provided context, don't provide
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the answer, just state the answer is not in the context provided.
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delete_file_button_enabled: true
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delete_all_files_button_enabled: true
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llm:
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mode: llamacpp
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# Should be matching the selected model
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max_new_tokens: 512
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context_window: 3900
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tokenizer: mistralai/Mistral-7B-Instruct-v0.2
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temperature: 0.1 # The temperature of the model. Increasing the temperature will make the model answer more creatively. A value of 0.1 would be more factual. (Default: 0.1)
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llamacpp:
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prompt_style: "mistral"
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llm_hf_repo_id: TheBloke/Mistral-7B-Instruct-v0.2-GGUF
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llm_hf_model_file: mistral-7b-instruct-v0.2.Q4_K_M.gguf
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tfs_z: 1.0 # Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting
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top_k: 40 # Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40)
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top_p: 1.0 # Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9)
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repeat_penalty: 1.1 # Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)
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embedding:
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# Should be matching the value above in most cases
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mode: huggingface
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ingest_mode: simple
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embed_dim: 384 # 384 is for BAAI/bge-small-en-v1.5
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huggingface:
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embedding_hf_model_name: BAAI/bge-small-en-v1.5
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vectorstore:
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database: qdrant
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nodestore:
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database: simple
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qdrant:
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path: local_data/private_gpt/qdrant
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postgres:
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host: localhost
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port: 5432
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database: postgres
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user: postgres
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password: postgres
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schema_name: private_gpt
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sagemaker:
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llm_endpoint_name: huggingface-pytorch-tgi-inference-2023-09-25-19-53-32-140
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embedding_endpoint_name: huggingface-pytorch-inference-2023-11-03-07-41-36-479
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openai:
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api_key: ${OPENAI_API_KEY:}
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model: gpt-3.5-turbo
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ollama:
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llm_model: llama2
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embedding_model: nomic-embed-text
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api_base: http://localhost:11434
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azopenai:
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api_key: ${AZ_OPENAI_API_KEY:}
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azure_endpoint: ${AZ_OPENAI_ENDPOINT:}
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embedding_deployment_name: ${AZ_OPENAI_EMBEDDING_DEPLOYMENT_NAME:}
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llm_deployment_name: ${AZ_OPENAI_LLM_DEPLOYMENT_NAME:}
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api_version: "2023-05-15"
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embedding_model: text-embedding-ada-002
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llm_model: gpt-35-turbo
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