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@ -1,31 +1,46 @@
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# ---- llm ----
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model: openai:gpt-3.5-turbo # Specify the language model to use
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temperature: null # Set default temperature parameter
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top_p: null # Set default top-p parameter
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save: true # Indicates whether to persist the message
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save_session: null # Controls the persistence of the session, if null, asking the user
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# ---- apperence ----
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highlight: true # Controls syntax highlighting
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light_theme: false # Activates a light color theme when true. ENV: AICHAT_LIGHT_THEME
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# Custom REPL prompt, see https://github.com/sigoden/aichat/wiki/Custom-REPL-Prompt for more detils
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left_prompt:
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'{color.green}{?session {?agent {agent}#}{session}{?role /}}{!session {?agent {agent}}}{role}{?rag @{rag}}{color.cyan}{?session )}{!session >}{color.reset} '
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right_prompt:
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'{color.purple}{?session {?consume_tokens {consume_tokens}({consume_percent}%)}{!consume_tokens {consume_tokens}}}{color.reset}'
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# ---- behavior ----
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save: true # Indicates whether to persist the message
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wrap: no # Controls text wrapping (no, auto, <max-width>)
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wrap_code: false # Enables or disables wrapping of code blocks
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keybindings: emacs # Choose keybinding style (emacs, vi)
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buffer_editor: null # Command used to edit the current input with Ctrl+O
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# ---- prelude ----
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prelude: null # Set a default role or session to start with (e.g. role:<name>, session:<name>)
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repl_prelude: null # This overrides 'prelude' when using REPL
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repl_prelude: null # Overrides the `prelude` setting specifically for conversations started in REPL
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agent_prelude: null # Set a session to use when starting a agent. (e.g. temp, default)
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# Command that will be used to edit the current line buffer with ctrl+o
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# if unset fallback to $EDITOR and $VISUAL
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buffer_editor: null
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# ---- session ----
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# Controls the persistence of the session, if null, asking the user
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save_session: null
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# Compress session when token count reaches or exceeds this threshold (must be at least 1000)
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compress_threshold: 4000
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# Text prompt used for creating a concise summary of session message
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summarize_prompt: 'Summarize the discussion briefly in 200 words or less to use as a prompt for future context.'
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# Text prompt used for including the summary of the entire session
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summary_prompt: 'This is a summary of the chat history as a recap: '
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# ---- function-calling ----
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# Controls the function calling feature. For setup instructions, visit https://github.com/sigoden/llm-functions
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function_calling: false
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# Regex for seletecting dangerous functions.
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# User confirmation is required when executing these functions.
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# e.g. 'execute_command|execute_js_code' 'execute_.*'
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dangerously_functions_filter: null
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agent_prelude: null # Set a session to use when starting a agent. (e.g. temp, default)
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agents:
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- name: todo-sh
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model: null
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@ -33,23 +48,15 @@ agents:
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top_p: null
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dangerously_functions_filter: null
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# Specifies the embedding model to use
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rag_embedding_model: null
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# Specifies the rerank model to use
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rag_rerank_model: null
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# Specifies the chunk size
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rag_chunk_size: null
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# Specifies the chunk overlap
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rag_chunk_overlap: null
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# Specifies the number of documents to retrieve
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rag_top_k: 4
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# Specifies the minimum relevance score for vector-based searching
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rag_min_score_vector_search: 0
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# Specifies the minimum relevance score for keyword-based searching
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rag_min_score_keyword_search: 0
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# Specifies the minimum relevance score for reranking
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rag_min_score_rerank: 0
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# ---- rag ----
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rag_embedding_model: null # Specifies the embedding model to use
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rag_rerank_model: null # Specifies the rerank model to use
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rag_chunk_size: null # Specifies the chunk size
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rag_chunk_overlap: null # Specifies the chunk overlap
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rag_top_k: 4 # Specifies the number of documents to retrieve
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rag_min_score_vector_search: 0 # Specifies the minimum relevance score for vector-based searching
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rag_min_score_keyword_search: 0 # Specifies the minimum relevance score for keyword-based searching
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rag_min_score_rerank: 0 # Specifies the minimum relevance score for reranking
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# Defines the query structure using variables like __CONTEXT__ and __INPUT__ to tailor searches to specific needs
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rag_template: |
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Use the following context as your learned knowledge, inside <context></context> XML tags.
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@ -66,17 +73,7 @@ rag_template: |
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Given the context information, answer the query.
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Query: __INPUT__
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# Compress session when token count reaches or exceeds this threshold (must be at least 1000)
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compress_threshold: 4000
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# Text prompt used for creating a concise summary of session message
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summarize_prompt: 'Summarize the discussion briefly in 200 words or less to use as a prompt for future context.'
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# Text prompt used for including the summary of the entire session
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summary_prompt: 'This is a summary of the chat history as a recap: '
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# Custom REPL prompt, see https://github.com/sigoden/aichat/wiki/Custom-REPL-Prompt
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left_prompt: '{color.green}{?session {?agent {agent}#}{session}{?role /}}{!session {?agent {agent}}}{role}{?rag @{rag}}{color.cyan}{?session )}{!session >}{color.reset} '
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right_prompt: '{color.purple}{?session {?consume_tokens {consume_tokens}({consume_percent}%)}{!consume_tokens {consume_tokens}}}{color.reset}'
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# ---- clients ----
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clients:
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# All clients have the following configuration:
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# - type: xxxx
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