gptel is a simple Large Language Model chat client for Emacs, with support for multiple models and backends. It works in the spirit of Emacs, available at any time and uniformly in any buffer.
| LLM Backend | Supports | Requires |
|---|---|---|
| ChatGPT | ✓ | API key |
| Anthropic (Claude) | ✓ | API key |
| Gemini | ✓ | API key |
| Ollama | ✓ | Ollama running locally |
| Llama.cpp | ✓ | Llama.cpp running locally |
| Llamafile | ✓ | Local Llamafile server |
| GPT4All | ✓ | GPT4All running locally |
| Kagi FastGPT | ✓ | API key |
| Kagi Summarizer | ✓ | API key |
| Azure | ✓ | Deployment and API key |
| Groq | ✓ | API key |
| Mistral Le Chat | ✓ | API key |
| Perplexity | ✓ | API key |
| OpenRouter | ✓ | API key |
| together.ai | ✓ | API key |
| Anyscale | ✓ | API key |
| PrivateGPT | ✓ | PrivateGPT running locally |
| DeepSeek | ✓ | API key |
| Sambanova (Deepseek) | ✓ | API key |
| Cerebras | ✓ | API key |
| Github Models | ✓ | Token |
| Novita AI | ✓ | Token |
| xAI | ✓ | API key |
| Github CopilotChat | ✓ | Github account |
| Bedrock | ✓ | AWS credentials |
General usage: (YouTube Demo)
intro-demo.mp4
intro-demo-2.mp4
In-place usage
gptel-rewrite-demo-1.mp4
Tool use
gptel-tool-use-filesystem-confirm-demo-2.mp4
gptel-tool-use-feed-search-demo.mp4
See also this youtube demo (2 minutes) by Armin Darvish.
- gptel is async and fast, streams responses.
- Interact with LLMs from anywhere in Emacs (any buffer, shell, minibuffer, wherever).
- LLM responses are in Markdown or Org markup.
- Supports multiple independent conversations and one-off ad hoc interactions.
- Supports tool-use to equip LLMs with agentic capabilities.
- Supports Model Context Protocol (MCP) integration using mcp.el.
- Supports multi-modal input (include images, documents).
- Supports “reasoning” content in LLM responses.
- Save chats as regular Markdown/Org/Text files and resume them later.
- Edit your previous prompts or LLM responses when continuing a conversation. These will be fed back to the model.
- Supports introspection, so you can see exactly what will be sent. Inspect and modify queries before sending them.
- Pause multi-stage requests at an intermediate stage and resume them later.
- Don’t like gptel’s workflow? Use it to create your own for any supported model/backend with a simple API.
gptel uses Curl if available, but falls back to the built-in url-retrieve to work without external dependencies.
- Installation
- Setup
- Usage
- FAQ
- Chat buffer UI
- Transient menu behavior
- I want to set gptel options, but only for this buffer
- I want the transient menu options to be saved so I only need to set them once
- Using the transient menu leaves behind extra windows
- Can I change the transient menu key bindings?
- (Doom Emacs) Sending a query from the gptel menu fails because of a key conflict with Org mode
- Miscellaneous
- Additional Configuration
- Alternatives
- Acknowledgments
- Release version:
M-x package-install⏎gptelin Emacs. - Development snapshot: Add MELPA or NonGNU-devel ELPA to your list of package sources, then install with
M-x package-install⏎gptel. - Optional: Install
markdown-mode.
Clone or download this repository and run M-x package-install-file⏎ on the repository directory.
In packages.el
(package! gptel :recipe (:nonrecursive t))In config.el
(use-package! gptel
:config
(setq! gptel-api-key "your key"))“your key” can be the API key itself, or (safer) a function that returns the key. Setting gptel-api-key is optional, you will be asked for a key if it’s not found.
In your .spacemacs file, add llm-client to dotspacemacs-configuration-layers.
(llm-client :variables
llm-client-enable-gptel t)Procure an OpenAI API key.
Optional: Set gptel-api-key to the key. Alternatively, you may choose a more secure method such as:
- Setting it to a custom function that returns the key.
- Leaving it set to the default
gptel-api-key-from-auth-sourcefunction which reads keys from~/.authinfo. (See authinfo details)
ChatGPT is configured out of the box. If you want to use other LLM backends (like Ollama, Claude/Anthropic or Gemini) you need to register and configure them first.
As an example, registering a backend typically looks like the following:
(gptel-make-anthropic "Claude" :stream t :key gptel-api-key)Once this backend is registered, you’ll see model names prefixed by “Claude:” appear in gptel’s menu.
See below for details on your preferred LLM provider, including local LLMs.
You can use Emacs’ built-in support for authinfo to store API keys required by gptel. Add your API keys to ~/.authinfo, and leave gptel-api-key set to its default. By default, the API endpoint DNS name (e.g. “api.openai.com”) is used as HOST and “apikey” as USER.
machine api.openai.com login apikey password sk-secret-openai-api-key-goes-here
machine api.anthropic.com login apikey password sk-secret-anthropic-api-key-goes-here
Register a backend with
(gptel-make-azure "Azure-1" ;Name, whatever you'd like
:protocol "https" ;Optional -- https is the default
:host "YOUR_RESOURCE_NAME.openai.azure.com"
:endpoint "/openai/deployments/YOUR_DEPLOYMENT_NAME/chat/completions?api-version=2023-05-15" ;or equivalent
:stream t ;Enable streaming responses
:key #'gptel-api-key
:models '(gpt-3.5-turbo gpt-4))Refer to the documentation of gptel-make-azure to set more parameters.
You can pick this backend from the menu when using gptel. (see Usage).
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq
gptel-model 'gpt-3.5-turbo
gptel-backend (gptel-make-azure "Azure-1"
:protocol "https"
:host "YOUR_RESOURCE_NAME.openai.azure.com"
:endpoint "/openai/deployments/YOUR_DEPLOYMENT_NAME/chat/completions?api-version=2023-05-15"
:stream t
:key #'gptel-api-key
:models '(gpt-3.5-turbo gpt-4)))Register a backend with
(gptel-make-gpt4all "GPT4All" ;Name of your choosing
:protocol "http"
:host "localhost:4891" ;Where it's running
:models '(mistral-7b-openorca.Q4_0.gguf)) ;Available modelsThese are the required parameters, refer to the documentation of gptel-make-gpt4all for more.
You can pick this backend from the menu when using gptel (see Usage).
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above. Additionally you may want to increase the response token size since GPT4All uses very short (often truncated) responses by default.
;; OPTIONAL configuration
(setq
gptel-max-tokens 500
gptel-model 'mistral-7b-openorca.Q4_0.gguf
gptel-backend (gptel-make-gpt4all "GPT4All"
:protocol "http"
:host "localhost:4891"
:models '(mistral-7b-openorca.Q4_0.gguf)))Register a backend with
(gptel-make-ollama "Ollama" ;Any name of your choosing
:host
3D11
"localhost:11434" ;Where it's running
:stream t ;Stream responses
:models '(mistral:latest)) ;List of modelsThese are the required parameters, refer to the documentation of gptel-make-ollama for more.
You can pick this backend from the menu when using gptel (see Usage)
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq
gptel-model 'mistral:latest
gptel-backend (gptel-make-ollama "Ollama"
:host "localhost:11434"
:stream t
:models '(mistral:latest)))Register a backend with
;; :key can be a function that returns the API key.
(gptel-make-gemini "Gemini" :key "YOUR_GEMINI_API_KEY" :stream t)These are the required parameters, refer to the documentation of gptel-make-gemini for more.
You can pick this backend from the menu when using gptel (see Usage)
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq
gptel-model 'gemini-2.5-pro-exp-03-25
gptel-backend (gptel-make-gemini "Gemini"
:key "YOUR_GEMINI_API_KEY"
:stream t))(If using a llamafile, run a server llamafile instead of a “command-line llamafile”, and a model that supports text generation.)
Register a backend with
;; Llama.cpp offers an OpenAI compatible API
(gptel-make-openai "llama-cpp" ;Any name
:stream t ;Stream responses
:protocol "http"
:host "localhost:8000" ;Llama.cpp server location
:models '(test)) ;Any names, doesn't matter for LlamaThese are the required parameters, refer to the documentation of gptel-make-openai for more.
You can pick this backend from the menu when using gptel (see Usage)
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq
gptel-model 'test
gptel-backend (gptel-make-openai "llama-cpp"
:stream t
:protocol "http"
:host "localhost:8000"
:models '(test)))Kagi’s FastGPT model and the Universal Summarizer are both supported. A couple of notes:
- Universal Summarizer: If there is a URL at point, the summarizer will summarize the contents of the URL. Otherwise the context sent to the model is the same as always: the buffer text upto point, or the contents of the region if the region is active.
- Kagi models do not support multi-turn conversations, interactions are “one-shot”. They also do not support streaming responses.
Register a backend with
(gptel-make-kagi "Kagi" ;any name
:key "YOUR_KAGI_API_KEY") ;can be a function that returns the keyThese are the required parameters, refer to the documentation of gptel-make-kagi for more.
You can pick this backend and the model (fastgpt/summarizer) from the transient menu when using gptel.
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq
gptel-model 'fastgpt
gptel-backend (gptel-make-kagi "Kagi"
:key "YOUR_KAGI_API_KEY"))The alternatives to fastgpt include summarize:cecil, summarize:agnes, summarize:daphne and summarize:muriel. The difference between the summarizer engines is documented here.
Register a backend with
;; Together.ai offers an OpenAI compatible API
(gptel-make-openai "TogetherAI" ;Any name you want
:host "api.together.xyz"
:key "your-api-key" ;can be a function that returns the key
:stream t
:models '(;; has many more, check together.ai
mistralai/Mixtral-8x7B-Instruct-v0.1
codellama/CodeLlama-13b-Instruct-hf
codellama/CodeLlama-34b-Instruct-hf))You can pick this backend from the menu when using gptel (see Usage)
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq
gptel-model 'mistralai/Mixtral-8x7B-Instruct-v0.1
gptel-backend
(gptel-make-openai "TogetherAI"
:host "api.together.xyz"
:key "your-api-key"
:stream t
:models '(;; has many more, check together.ai
mistralai/Mixtral-8x7B-Instruct-v0.1
codellama/CodeLlama-13b-Instruct-hf
codellama/CodeLlama-34b-Instruct-hf)))Register a backend with
;; Anyscale offers an OpenAI compatible API
(gptel-make-openai "Anyscale" ;Any name you want
:host "api.endpoints.anyscale.com"
:key "your-api-key" ;can be a function that returns the key
:models '(;; has many more, check anyscale
mistralai/Mixtral-8x7B-Instruct-v0.1))You can pick this backend from the menu when using gptel (see Usage)
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq
gptel-model 'mistralai/Mixtral-8x7B-Instruct-v0.1
gptel-backend
(gptel-make-openai "Anyscale"
:host "api.endpoints.anyscale.com"
:key "your-api-key"
:models '(;; has many more, check anyscale
mistralai/Mixtral-8x7B-Instruct-v0.1)))Register a backend with
(gptel-make-perplexity "Perplexity" ;Any name you want
:key "your-api-key" ;can be a function that returns the key
:stream t) ;If you want responses to be streamedYou can pick this backend from the menu when using gptel (see Usage)
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq
gptel-model 'sonar
gptel-backend (gptel-make-perplexity "Perplexity"
:key "your-api-key" :stream t))Register a backend with
(gptel-make-anthropic "Claude" ;Any name you want
:stream t ;Streaming responses
:key "your-api-key")The :key can be a function that returns the key (more secure).
You can pick this backend from the menu when using gptel (see Usage).
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq
gptel-model 'claude-3-sonnet-20240229 ; "claude-3-opus-20240229" also available
gptel-backend (gptel-make-anthropic "Claude"
:stream t :key "your-api-key"))To use Claude 3.7 Sonnet model in its “thinking” mode, you can define a second Claude backend and select it via the UI or elisp:
(gptel-make-anthropic "Claude-thinking" ;Any name you want
:key "your-API-key"
:stream t
:models '(claude-3-7-sonnet-20250219)
:header (lambda () (when-let* ((key (gptel--get-api-key)))
`(("x-api-key" . ,key)
("anthropic-version" . "2023-06-01")
("anthropic-beta" . "pdfs-2024-09-25")
("anthropic-beta" . "output-128k-2025-02-19")
("anthropic-beta" . "prompt-caching-2024-07-31"))))
:request-params '(:thinking (:type "enabled" :budget_tokens 2048)
:max_tokens 4096))You can set the reasoning budget tokens and max tokens for this usage via the :budget_tokens and :max_tokens keys here, respectively.
You can control whether/how the reasoning output is shown via gptel’s menu or gptel-include-reasoning, see handling reasoning content.
Register a backend with
;; Groq offers an OpenAI compatible API
(gptel-make-openai "Groq" ;Any name you want
:host "api.groq.com"
:endpoint "/openai/v1/chat/completions"
:stream t
:key "your-api-key" ;can be a function that returns the key
:models '(llama-3.1-70b-versatile
llama-3.1-8b-instant
llama3-70b-8192
llama3-8b-8192
mixtral-8x7b-32768
gemma-7b-it))You can pick this backend from the menu when using gptel (see Usage). Note that Groq is fast enough that you could easily set :stream nil and still get near-instant responses.
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq gptel-model 'mixtral-8x7b-32768
gptel-backend
(gptel-make-openai "Groq"
:host "api.groq.com"
:endpoint "/openai/v1/chat/completions"
:stream t
:key "your-api-key"
:models '(llama-3.1-70b-versatile
llama-3.1-8b-instant
llama3-70b-8192
llama3-8b-8192
mixtral-8x7b-32768
gemma-7b-it)))Register a backend with
;; Mistral offers an OpenAI compatible API
(gptel-make-openai "MistralLeChat" ;Any name you want
:host "api.mistral.ai"
:endpoint "/v1/chat/completions"
:protocol "https"
:key "your-api-key" ;can be a function that returns the key
:models '("mistral-small"))You can pick this backend from the menu when using gptel (see Usage).
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq gptel-model 'mistral-small
gptel-backend
(gptel-make-openai "MistralLeChat" ;Any name you want
:host "api.mistral.ai"
:endpoint "/v1/chat/completions"
:protocol "https"
:key "your-api-key" ;can be a function that returns the key
:models '("mistral-small")))Register a backend with
;; OpenRouter offers an OpenAI compatible API
(gptel-make-openai "OpenRouter" ;Any name you want
:host "openrouter.ai"
:endpoint "/api/v1/chat/completions"
:stream t
:key "your-api-key" ;can be a function that returns the key
:models '(openai/gpt-3.5-turbo
mistralai/mixtral-8x7b-instruct
meta-llama/codellama-34b-instruct
codellama/codellama-70b-instruct
google/palm-2-codechat-bison-32k
google/gemini-pro))
You can pick this backend from the menu when using gptel (see Usage).
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq gptel-model 'mixtral-8x7b-32768
gptel-backend
(gptel-make-openai "OpenRouter" ;Any name you want
:host "openrouter.ai"
:endpoint "/api/v1/chat/completions"
:stream t
:key "your-api-key" ;can be a function that returns the key
:models '(openai/gpt-3.5-turbo
mistralai/mixtral-8x7b-instruct
meta-llama/codellama-34b-instruct
codellama/codellama-70b-instruct
google/palm-2-codechat-bison-32k
google/gemini-pro)))
Register a backend with
(gptel-make-privategpt "privateGPT" ;Any name you want
:protocol "http"
:host "localhost:8001"
:stream t
:context t ;Use context provided by embeddings
:sources t ;Return information about source documents
:models '(private-gpt))
You can pick this backend from the menu when using gptel (see Usage).
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq gptel-model 'private-gpt
gptel-backend
(gptel-make-privategpt "privateGPT" ;Any name you want
:protocol "http"
:host "localhost:8001"
:stream t
:context t ;Use context provided by embeddings
:sources t ;Return information about source documents
:models '(private-gpt)))
Register a backend with
(gptel-make-deepseek "DeepSeek" ;Any name you want
:stream t ;for streaming responses
:key "your-api-key") ;can be a function that returns the keyYou can pick this backend from the menu when using gptel (see Usage).
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq gptel-model 'deepseek-reasoner
gptel-backend (gptel-make-deepseek "DeepSeek"
:stream t
:key "your-api-key"))Sambanova offers various LLMs through their Samba Nova Cloud offering, with Deepseek-R1 being one of them. The token speed for Deepseek R1 via Sambanova is about 6 times faster than when accessed through deepseek.com
Register a backend with
(gptel-make-openai "Sambanova" ;Any name you want
:host "api.sambanova.ai"
:endpoint "/v1/chat/completions"
:stream t ;for streaming responses
:key "your-api-key" ;can be a function that returns the key
:models '(DeepSeek-R1))You can pick this backend from the menu when using gptel (see Usage).
The code aboves makes the backend available for selection. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Add these two lines to your configuration:
;; OPTIONAL configuration
(setq gptel-model 'DeepSeek-R1)
(setq gptel-backend (gptel-get-backend "Sambanova"))Register a backend with
;; Cerebras offers an instant OpenAI compatible API
(gptel-make-openai "Cerebras"
:host "api.cerebras.ai"
:endpoint "/v1/chat/completions"
:stream t ;optionally nil as Cerebras is instant AI
:key "your-api-key" ;can be a function that returns the key
:models '(llama3.1-70b
llama3.1-8b))You can pick this backend from the menu when using gptel (see Usage).
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq gptel-model 'llama3.1-8b
gptel-backend
(gptel-make-openai "Cerebras"
:host "api.cerebras.ai"
:endpoint "/v1/chat/completions"
:stream nil
:key "your-api-key"
:models '(llama3.1-70b
llama3.1-8b)))NOTE: GitHub Models is not GitHub Copilot! If you want to use GitHub Copilot chat via gptel, look at the instructions for GitHub CopilotChat below instead.
Register a backend with
;; Github Models offers an OpenAI compatible API
(gptel-make-openai "Github Models" ;Any name you want
:host "models.inference.ai.azure.com"
:endpoint "/chat/completions?api-version=2024-05-01-preview"
:stream t
:key "your-github-token"
:models '(gpt-4o))You will need to create a github token.
For all the available models, check the marketplace.
You can pick this backend from the menu when using (see Usage).
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq gptel-model 'gpt-4o
gptel-backend
(gptel-make-openai "Github Models" ;Any name you want
:host "models.inference.ai.azure.com"
:endpoint "/chat/completions?api-version=2024-05-01-preview"
:stream t
:key "your-github-token"
:models '(gpt-4o))Register a backend with
;; Novita AI offers an OpenAI compatible API
(gptel-make-openai "NovitaAI" ;Any name you want
:host "api.novita.ai"
:endpoint "/v3/openai"
:key "your-api-key" ;can be a function that returns the key
:stream t
:models '(;; has many more, check https://novita.ai/llm-api
gryphe/mythomax-l2-13b
meta-llama/llama-3-70b-instruct
meta-llama/llama-3.1-70b-instruct))You can pick this backend from the menu when using gptel (see Usage)
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq
gptel-model 'gryphe/mythomax-l2-13b
gptel-backend
(gptel-make-openai "NovitaAI"
:host "api.novita.ai"
:endpoint "/v3/openai"
:key "your-api-key"
:stream t
:models '(;; has many more, check https://novita.ai/llm-api
mistralai/Mixtral-8x7B-Instruct-v0.1
meta-llama/llama-3-70b-instruct
meta-llama/llama-3.1-70b-instruct)))Register a backend with
(gptel-make-xai "xAI" ; Any name you want
:stream t
:key "your-api-key") ; can be a function that returns the keyYou can pick this backend from the menu when using gptel (see Usage)
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
(setq gptel-model 'grok-3-latest
gptel-backend
(gptel-make-xai "xAI" ; Any name you want
:key "your-api-key" ; can be a function that returns the key
:stream t))Register a backend with
(gptel-make-gh-copilot "Copilot")You will be informed to login into Github as required.
You can pick this backend from the menu when using gptel (see Usage).
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq gptel-model 'claude-3.7-sonnet
gptel-backend (gptel-make-gh-copilot "Copilot"))Register a backend with
(gptel-make-bedrock "AWS"
:region "ap-northeast-1"
;; subset of gptel--bedrock-models
:models '(claude-3-5-sonnet-20241022)
;; optional for provisioned access
:model-region 'apac)The Bedrock backend gets your AWS credentials from the environment variables. It expects to find either
AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_SESSION_TOKEN (optional), or if present, can use AWS_PROFILE to get these directly from the aws cli.
NOTE: The Bedrock backend needs curl >= 8.5 in order for the sigv4 signing to work properly, curl/curl#11794
An error will be signalled if gptel-curl is NIL.
You can pick this backend from the menu when using gptel (see Usage).
The above code makes the backend available to select. If you want it to be the default backend for gptel, you can set this as the value of gptel-backend. Use this instead of the above.
;; OPTIONAL configuration
(setq gptel-model 'claude-3-5-sonnet-20241022
gptel-backend
(gptel-make-bedrock "AWS"
:region "ap-northeast-1"
;; subset of gptel--bedrock-models
:models '(claude-3-5-sonnet-20241022)
;; optional
:model-region 'apac))gptel provides a few powerful, general purpose and flexible commands. You can dynamically tweak their behavior to the needs of your task with directives, redirection options and more. There is a video demo showing various uses of gptel – but gptel-send might be all you need.
| To send queries | Description |
|---|---|
gptel-send | Send all text up to (point), or the selection if region is active. Works anywhere in Emacs. |
gptel | Create a new dedicated chat buffer. Not required to use gptel. |
gptel-rewrite | Rewrite, refactor or change the selected region. Can diff/ediff changes before merging/applying. |
| To tweak behavior | |
C-u gptel-send | Transient menu for preferences, input/output redirection etc. |
gptel-menu | (Same) |
| To add context | |
gptel-add | Add/remove a region or buffer to gptel’s context. In Dired, add/remove marked files. |
gptel-add-file | Add a file (text or supported media type) to gptel’s context. Also available from the transient menu. |
| Org mode bonuses | |
gptel-org-set-topic | Limit conversation context to an Org heading. (For branching conversations see below.) |
gptel-org-set-properties | Write gptel configuration as Org properties, for per-heading chat configuration. |
- Call
M-x gptel-sendto send the text up to the cursor. The response will be inserted below. Continue the conversation by typing below the response. - If a region is selected, the conversation will be limited to its contents.
- Call
M-x gptel-sendwith a prefix argument (C-u)- to set chat parameters (model, backend, system message etc) for this buffer,
- include quick instructions for the next request only,
- to add additional context – regions, buffers or files – to gptel,
- to read the prompt from or redirect the response elsewhere,
- or to replace the prompt with the response.
You can also define a “preset” bundle of options that are applied together, see Option presets below.
Note: gptel works anywhere in Emacs. The dedicated chat buffer only adds some conveniences.
- Run
M-x gptelto start or switch to the chat buffer. It will ask you for the key if you skipped the previous step. Run it with a prefix-arg (C-u M-x gptel) to start a new session. - In the gptel buffer, send your prompt with
M-x gptel-send, bound toC-c RET. - Set chat parameters (LLM provider, model, directives etc) for the session by calling
gptel-sendwith a prefix argument (C-u C-c RET):
That’s it. You can go back and edit previous prompts and responses if you want.
The default mode is markdown-mode if available, else text-mode. You can set gptel-default-mode to org-mode if desired.
You can also define a “preset” bundle of options that are applied together, see Option presets below.
gptel supports sending media in Markdown and Org chat buffers, but this feature is disabled by default.
- You can enable it globally, for all models that support it, by setting
gptel-track-media. - Or you can set it locally, just for the chat buffer, via the header line:
There are two ways to include media or plain-text files with requests:
- Adding media files to the context with
gptel-add-file, described further below. - Including links to media in chat buffers, described here:
To include plain-text files, images or other supported document types with requests in chat buffers, you can include links to them in the chat buffer. Such a link must be “standalone”, i.e. on a line by itself surrounded by whitespace.
In Org mode, for example, the following are all valid ways of including an image with the request:
- “Standalone” file links:
In this yaml file, I have some key-remapping configuration: [[file:/path/to/remap.yaml]] Could you explain what it does, and which program might be using it?
Describe this picture [[file:/path/to/screenshot.png]] Focus specifically on the text content.
- “Standalone” file link with description:
Describe this picture [[file:/path/to/screenshot.png][some picture]] Focus specifically on the text content.
- “Standalone”, angle file link:
Describe this picture <file:/path/to/screenshot.png> Focus specifically on the text content.
The following links are not valid, and the text of the link will be sent instead of the file contents:
- Inline link:
Describe this [[file:/path/to/screenshot.png][picture]]. Focus specifically on the text content.
- Link not “standalone”:
Describe this picture: [[file:/path/to/screenshot.png]] Focus specifically on the text content.
- Not a valid Org link:
Describe the picture file:/path/to/screenshot.png
Similar criteria apply to Markdown chat buffers.
Saving the file will save the state of the conversation as well. To resume the chat, open the file and turn on gptel-mode before editing the buffer.
Most gptel options can be set from gptel’s transient menu, available by calling gptel-send with a prefix-argument, or via gptel-menu. To change their default values in your configuration, see Additional Configuration. Chat buffer-specific options are also available via the header-line in chat buffers.
Selecting a model and backend can be done interactively via the -m command of gptel-menu. Available registered models are prefixed by the name of their backend with a string like ChatGPT:gpt-4o-mini, where ChatGPT is the backend name you used to register it and gpt-4o-mini is the name of the model.
By default, gptel will query the LLM with the active region or the buffer contents up to the cursor. Often it can be helpful to provide the LLM with additional context from outside the current buffer. For example, when you’re in a chat buffer but want to ask questions about a (possibly changing) code buffer and auxiliary project files.
You can include additional text regions, buffers or files with gptel’s queries in two ways. The first is via links in chat buffers, as described above (see “Including media with requests”).
The second is globally via dedicated context commands: you can add a selected region, buffer or file to gptel’s context from the menu, or call gptel-add. To add a file use gptel-add in Dired, or use the dedicated gptel-add-file command. Directories will have their files added recursively after prompting for confirmation.
This additional context is “live” and not a snapshot. Once added, the regions, buffers or files are scanned and included at the time of each query. When using multi-modal models, added files can be of any supported type – typically images.
You can examine the active context from the menu:
And then browse through or remove context from the context buffer:
Some LLMs include in their response a “thinking” or “reasoning” block. This text improves the quality of the LLM’s final output, but may not be interesting to you by itself. You can decide how you would like this “reasoning” content to be handled by gptel by setting the user option gptel-include-reasoning. You can include it in the LLM response (the default), omit it entirely, include it in the buffer but ignore it on subsequent conversation turns, or redirect it to another buffer. As with most options, you can specify this behvaior from gptel’s transient menu globally, buffer-locally or for the next request only.
When included with the response, reasoning content will be delimited by Org blocks or markdown backticks.
gptel can provide the LLM with client-side elisp “tools”, or function specifications, along with the request. If the LLM decides to run the tool, it supplies the tool call arguments, which gptel uses to run the tool in your Emacs session. The result is optionally returned to the LLM to complete the task.
This exchange can be used to equip the LLM with capabilities or knowledge beyond what is available out of the box – for instance, you can get the LLM to control your Emacs frame, create or modify files and directories, or look up information relevant to your request via web search or in a local database. Here is a very simple example:
screencast_20241222T075329.mp4
To use tools in gptel, you need
- a model that supports this usage. All the flagship models support tool use, as do many of the smaller open models.
- Tool specifications that gptel understands. gptel does not currently include any tools out of the box.
Defining a gptel tool requires an elisp function and associated metadata. Here are two simple tool definitions:
To read the contents of an Emacs buffer:
(gptel-make-tool
:name "read_buffer" ; javascript-style snake_case name
:function (lambda (buffer) ; the function that will run
(unless (buffer-live-p (get-buffer buffer))
(error "error: buffer %s is not live." buffer))
(with-current-buffer buffer
(buffer-substring-no-properties (point-min) (point-max))))
:description "return the contents of an emacs buffer"
:args (list '(:name "buffer"
:type string ; :type value must be a symbol
:description "the name of the buffer whose contents are to be retrieved"))
:category "emacs") ; An arbitrary label for groupingBesides the function itself, which can be named or anonymous (as above), the tool specification requires a :name, :description and a list of argument specifications in :args. Each argument specification is a plist with atleast the keys :name, :type and :description.
To create a text file:
(gptel-make-tool
:name "create_file" ; javascript-style snake_case name
:function (lambda (path filename content) ; the function that runs
(let ((full-path (expand-file-name filename path)))
(with-temp-buffer
(insert content)
(write-file full-path))
(format "Created file %s in %s" filename path)))
:description "Create a new file with the specified content"
:args (list '(:name "path" ; a list of argument specifications
:type string
:description "The directory where to create the file")
'(:name "filename"
:type string
:description "The name of the file to create")
'(:name "content"
:type string
:description "The content to write to the file"))
:category "filesystem") ; An arbitrary label for groupingWith some prompting, you can get an LLM to write these tools for you.
Tools can also be asynchronous, use optional arguments and arguments with more structure (enums, arrays, objects etc). See gptel-make-tool for details.
Once defined, tools can be selected (globally, buffer-locally or for the next request only) from gptel’s transient menu:
From here you can also require confirmation for all tool calls, and decide if tool call results should be included in the LLM response. See Additional Configuration for doing these things via elisp.
The Model Context Protocol (MCP) is a protocol for providing resources and tools to LLMs, and many MCP servers exist that provide LLM tools for file access, database connections, API integrations etc. The mcp.el package for Emacs can act as an MCP client and manage these tool calls for gptel.
To use MCP servers with gptel, you thus need three pieces:
- The mcp.el package for Emacs, available on MELPA.
- MCP servers configured for and running via mcp.el.
- gptel and access to an LLM
gptel includes gptel-integrations, a small library to make this more convenient. This library is not automatically loaded by gptel, so if you would like to use it you have to require it:
(require 'gptel-integrations)Once loaded, you can run the gptel-mcp-connect and gptel-mcp-disconnect commands to register and unregister MCP-provided tools in gptel. These will also show up in the tools menu in gptel, accessed via M-x gptel-menu or M-x gptel-tools:
MCP-provided tools can be used as normal with gptel. Here is a screencast of the process. (In this example the “github” MCP server is installed separately using npm.)
gptel-mcp-01.mp4
Here’s an example of using these tools:
gptel-mcp-github.mp4
In any buffer: with a region selected, you can modify text, rewrite prose or refactor code with gptel-rewrite. Example with prose:
gptel-rewrite-prose-demo-1.mp4
The result is previewed over the original text. By default, the buffer is not modified.
Pressing RET or clicking in the rewritten region should give you a list of options: you can iterate on, diff, ediff, merge or accept the replacement. Example with code:
gptel-rewrite-code-demo-1.mp4
Acting on the LLM response:
If you would like one of these things to happen automatically, you can customize gptel-rewrite-default-action.
These options are also available from gptel-rewrite:
And you can call them directly when the cursor is in the rewritten region:
gptel offers a few extra conveniences in Org mode.
You can limit the conversation context to an Org heading with the command gptel-org-set-topic.
(This sets an Org property (GPTEL_TOPIC) under the heading. You can also add this property manually instead.)
You can have branching conversations in Org mode, where each hierarchical outline path through the document is a separate conversation branch. This is also useful for limiting the context size of each query. See the variable gptel-org-branching-context.
If this variable is non-nil, you should probably edit gptel-prompt-prefix-alist and gptel-response-prefix-alist so that the prefix strings for org-mode are not Org headings, e.g.
(setf (alist-get 'org-mode gptel-prompt-prefix-alist) "@user\n")
(setf (alist-get 'org-mode gptel-response-prefix-alist) "@assistant\n")Otherwise, the default prompt prefix will make successive prompts sibling headings, and therefore on different conversation branches, which probably isn’t what you want.
Note: using this option requires Org 9.7 or higher to be available. The ai-org-chat package uses gptel to provide this branching conversation behavior for older versions of Org.
You can declare the gptel model, backend, temperature, system message and other parameters as Org properties with the command gptel-org-set-properties. gptel queries under the corresponding heading will always use these settings, allowing you to create mostly reproducible LLM chat notebooks, and to have simultaneous chats with different models, model settings and directives under different Org headings.
To be minimally annoying, gptel does not move the cursor by default. Add the following to your configuration to enable auto-scrolling.
(add-hook 'gptel-post-stream-hook 'gptel-auto-scroll)To be minimally annoying, gptel does not move the cursor by default. Add the following to your configuration to move the cursor:
(add-hook 'gptel-post-response-functions 'gptel-end-of-response)You can also call gptel-end-of-response as a command at any time.
For dedicated chat buffers: customize gptel-prompt-prefix-alist and gptel-response-prefix-alist. You can set a different pair for each major-mode.
Anywhere in Emacs: Use gptel-pre-response-hook and gptel-post-response-functions, which see.
gptel uses text-properties to watermark LLM responses. Thus this text is interpreted as a response even if you copy it into another buffer. In regular buffers (buffers without gptel-mode enabled), you can turn off this tracking by unsetting gptel-track-response.
When restoring a chat state from a file on disk, gptel will apply these properties from saved metadata in the file when you turn on gptel-mode.
gptel does not use any prefix or semantic/syntax element in the buffer (such as headings) to separate prompts and responses. The reason for this is that gptel aims to integrate as seamlessly as possible into your regular Emacs usage: LLM interaction is not the objective, it’s just another tool at your disposal. So requiring a bunch of “user” and “assistant” tags in the buffer is noisy and restrictive. If you want these demarcations, you can customize gptel-prompt-prefix-alist and gptel-response-prefix-alist. Note that these prefixes are for your readability only and purely cosmetic.
In every menu used to set options, gptel provides a “scope” option, bound to the = key:
You can flip this switch before setting the option to buffer or oneshot. You only need to flip this switch once, it’s a persistent setting. buffer sets the option buffer-locally, oneshot will set it for the next gptel request only. The default scope is global.
Any model options you set are saved according to the scope (see previous question). But the redirection options in the menu are set for the next query only:
You can make them persistent across this Emacs session by pressing C-x C-s:
(You can also cycle through presets you’ve saved with C-x p and C-x n.)
Now these will be enabled whenever you send a query from the transient menu. If you want to use these saved options without invoking the transient menu, you can use a keyboard macro:
;; Replace with your key to invoke the transient menu:
(keymap-global-set "<f6>" "C-u C-c <return> <return>")Or see this wiki entry.
If using gptel’s transient menus causes new/extra window splits to be created, check your value of transient-display-buffer-action. See this discussion for more context.
If you are using Helm, see Transient#361.
In general, do not customize this Transient option unless you know what you’re doing!
Yes, see transient-suffix-put. This changes the key to select a backend/model from “-m” to “M” in gptel’s menu:
(transient-suffix-put 'gptel-menu (kbd "-m") :key "M")Doom binds RET in Org mode to +org/dwim-at-point, which appears to conflict with gptel’s transient menu bindings for some reason.
Two solutions:
- Press
C-minstead of the return key. - Change the send key from return to a key of your choice:
(transient-suffix-put 'gptel-menu (kbd "RET") :key "<f8>")
gptel’s default usage pattern is simple, and will stay this way: Read input in any buffer and insert the response below it. Some custom behavior is possible with the transient menu (C-u M-x gptel-send).
For more programmable usage, gptel provides a general gptel-request function that accepts a custom prompt and a callback to act on the response. You can use this to build custom workflows not supported by gptel-send. See the documentation of gptel-request, and the wiki for examples.
(HTTP/2 429) You exceeded your current quota, please check your plan and billing details.
Using the ChatGPT (or any OpenAI) API requires adding credit to your account.
Other Emacs clients for LLMs prescribe the format of the interaction (a comint shell, org-babel blocks, etc). I wanted:
- Something that is as free-form as possible: query the model using any text in any buffer, and redirect the response as required. Using a dedicated
gptelbuffer just adds some visual flair to the interaction. - Integration with org-mode, not using a walled-off org-babel block, but as regular text. This way the model can generate code blocks that I can run.
| Connection options | |
|---|---|
gptel-use-curl | Use Curl (default), fallback to Emacs’ built-in url. |
gptel-proxy | Proxy server for requests, passed to curl via --proxy. |
gptel-api-key | Variable/function that returns the API key for the active backend. |
| LLM request options | (Note: not supported uniformly across LLMs) |
gptel-backend | Default LLM Backend. |
gptel-model | Default model to use, depends on the backend. |
gptel-stream | Enable streaming responses, if the backend supports it. |
gptel-directives | Alist of system directives, can switch on the fly. |
gptel-max-tokens | Maximum token count (in query + response). |
gptel-temperature | Randomness in response text, 0 to 2. |
gptel-cache | Cache prompts, system message or tools (Anthropic only) |
gptel-use-context | How/whether to include additional context |
gptel-use-tools | Disable, allow or force LLM tool-use |
gptel-tools | List of tools to include with requests |
| Chat UI options | |
gptel-default-mode | Major mode for dedicated chat buffers. |
gptel-prompt-prefix-alist | Text inserted before queries. |
gptel-response-prefix-alist | Text inserted before responses. |
gptel-track-response | Distinguish between user messages and LLM responses? |
gptel-track-media | Send text, images or other media from links? |
gptel-confirm-tool-calls | Confirm all tool calls? |
gptel-include-tool-results | Include tool results in the LLM response? |
gptel-use-header-line | Display status messages in header-line (default) or minibuffer |
gptel-display-buffer-action | Placement of the gptel chat buffer. |
| Org mode UI options | |
gptel-org-branching-context | Make each outline path a separate conversation branch |
gptel-org-ignore-elements | Ignore parts of the buffer when sending a query |
| Hooks for customization | |
gptel-save-state-hook | Runs before saving the chat state to a file on disk |
gpt
A00C
el-prompt-transform-functions | Runs in a temp buffer to transform text before sending |
gptel-post-request-hook | Runs immediately after dispatching a gptel-request. |
gptel-pre-response-hook | Runs before inserting the LLM response into the buffer |
gptel-post-response-functions | Runs after inserting the full LLM response into the buffer |
gptel-post-stream-hook | Runs after each streaming insertion |
gptel-context-wrap-function | To include additional context formatted your way |
gptel-rewrite-default-action | Automatically diff, ediff, merge or replace refactored text |
gptel-post-rewrite-functions | Runs after a gptel-rewrite request succeeds |
If you use several LLMs for different tasks with accompanying system prompts (instructions) and tool configurations, manually adjusting gptel settings each time can become tedious. Presets are a bundle of gptel settings – such as the model, backend, system message, and enabled tools – that you can switch to at once.
Once defined, presets can be applied from gptel’s transient menu:
To define a preset, use the gptel-make-preset function, which takes a name and keyword-value pairs of settings.
Presets can be used to set individual options. Here is an example of a preset to set the system message (and do nothing else):
(gptel-make-preset 'explain
:system "Explain what this code does to a novice programmer.")More generally, you can specify a bundle of options:
(gptel-make-preset 'gpt4coding ;preset name, a symbol
:description "A preset optimized for coding tasks" ;for your reference
:backend "Claude" ;gptel backend or backend name
:model 'claude-3-7-sonnet-20250219.1
:system "You are an expert coding assistant. Your role is to provide high-quality code solutions, refactorings, and explanations."
:tools '("read_buffer" "modify_buffer")) ;gptel tools or tool namesBesides a couple of special keys (:description, :parents to inherit other presets), there is no predefined list of keys. Instead, the key :foo corresponds to setting gptel-foo (preferred) or gptel--foo. So the preset can include the value of any gptel option. For example, the following preset sets gptel-temperature and gptel-use-context:
(gptel-make-preset 'proofreader
:description "Preset for proofreading tasks"
:backend "ChatGPT"
:model 'gpt-4.1-mini
:tools '("read_buffer" "spell_check" "grammar_check")
:temperature 0.7 ;sets gptel-temperature
:use-context 'system) ;sets gptel-use-contextSwitching to a preset applies the specified settings without affecting other settings. Depending on the scope option (= in gptel’s transient menu), presets can be applied globally, buffer-locally or for the next request only.
You can apply a preset to a single query by including @preset-name in the prompt, where preset-name is the name of the preset. (The oneshot scope option in gptel’s transient menus is another way to do this, see the FAQ.)
For example, if you have a preset named websearch defined which includes tools for web access and search:
(gptel-make-preset 'websearch
:description "Haiku with basic web search capability."
:backend "Claude"
:model 'claude-3-5-haiku-20241022
:tools '("search_web" "read_url" "get_youtube_meta"))The following query is sent with this preset applied:
@websearch Are there any 13” e-ink monitors on the market? Create a table comparing them, sourcing specs and reviews from online sources. Also do the same for “transreflective-LCD” displays – I’m not sure what exactly they’re called but they’re comparable to e-ink.
This @preset-name cookie only applies to the final user turn of the coversation that is sent. So the presence of the cookie in past messages/turns is not significant.
The @preset-name cookie can be anywhere in the prompt. For example:
<long piece of text>
What do you make of the above description, @proofreader?
In chat buffers this prefix will be offered as a completion and fontified, making it easy to use and spot.
Other Emacs clients for LLMs include
- llm: llm provides a uniform API across language model providers for building LLM clients in Emacs, and is intended as a library for use by package authors. For similar scripting purposes, gptel provides the command
gptel-request, which see. - Ellama: A full-fledged LLM client built on llm, that supports many LLM providers (Ollama, Open AI, Vertex, GPT4All and more). Its usage differs from gptel in that it provides separate commands for dozens of common tasks, like general chat, summarizing code/text, refactoring code, improving grammar, translation and so on.
- chatgpt-shell: comint-shell based interaction with ChatGPT. Also supports DALL-E, executable code blocks in the responses, and more.
- org-ai: Interaction through special
#+begin_ai ... #+end_aiOrg-mode blocks. Also supports DALL-E, querying ChatGPT with the contents of project files, and more. - Minuet: Code-completion using LLM. Supports fill-in-the-middle (FIM) completion for compatible models such as DeepSeek and Codestral.
There are several more: chat.el, gpt.el, le-gpt, robby.
gptel is a general-purpose package for chat and ad-hoc LLM interaction. The following packages use gptel to provide additional or specialized functionality:
- gptel-quick: Quickly look up the region or text at point.
- Evedel: Instructed LLM Programmer/Assistant.
- Elysium: Automatically apply AI-generated changes as you code.
- ai-blog.el: Streamline generation of blog posts in Hugo.
- magit-gptcommit: Generate Commit Messages within magit-status Buffer using gptel.
- consult-omni: Versatile multi-source search package. It includes gptel as one of its many sources.
- ai-org-chat: Provides branching conversations in Org buffers using gptel. (Note that gptel includes this feature as well (see
gptel-org-branching-context), but requires a recent version of Org mode 9.7 or later to be installed.) - Corsair: Helps gather text to populate LLM prompts for gptel.
- Felipe Ochoa and akssri for adding AWS Bedrock support to gptel.
- John Wiegley for the design of gptel’s presets and gptel-request’s async pipeline, but also for loads of general feedback and advice.
- Henrik Ahlgren for a keen eye to detail and polish applied to gptel’s UI.
- psionic-k for extensive testing of the tool use feature and the design of gptel’s in-buffer tool use records.
- JD Smith for feedback and code assistance with gptel-menu’s redesign
- Abin Simon for extensive feedback on improving gptel’s directives and UI.
- Alexis Gallagher and Diego Alvarez for fixing a nasty multi-byte bug with
url-retrieve. - Jonas Bernoulli for the Transient library.
- daedsidog for adding context support to gptel.
- Aquan1412 for adding PrivateGPT support to gptel.
- r0man for improving gptel’s Curl integration.