简例 AI学习

👨‍🔧 How to install

Install `fish-ai`

Make sure git and either uv, or a supported version of Python along with pip and venv is installed. Then grab the plugin using fisher:

fisher install realiserad/fish-ai

🙉 How to use

🎥 Demo

Create a configuration

Create a configuration file $XDG_CONFIG_HOME/fish-ai.ini (use ~/.config/fish-ai.ini if $XDG_CONFIG_HOME is not set) where you specify which LLM fish-ai should talk to. If you're not sure, use GitHub Models.

Anthropic

To use Anthropic:

[anthropic]
provider = anthropic
api_key = <your API key>
model = claude-sonnet-4-6

Azure OpenAI

To use Azure OpenAI:

[fish-ai]
configuration = azure

[azure]
provider = azure
server = https://<your instance>.openai.azure.com
model = <your deployment name>
api_key = <your API key>

Bedrock

AWS Bedrock provides LLMs hosted by AWS. They can be accessed either through the Mantle gateway or the Converse API.

If no api_key is configured, a short-term token is automatically generated from your AWS credentials. You can also specify an api_key directly if you prefer to use a Bedrock API key.

Use aws_profile to select a named profile from your AWS configuration. If omitted, the default credential chain is used.

Available model IDs are listed in the Bedrock documentation.

Converse API

To use the Converse API:

[fish-ai]
configuration = aws-converse

[aws-converse]
provider = bedrock
bedrock_api = converse
model = anthropic.claude-haiku-4-5-20251001-v1:0
aws_region = us-east-1
aws_profile = default

It requires the bedrock:InvokeModel permission.

Mantle gateway

To use the Mantle gateway:

[fish-ai]
configuration = aws-mantle

[aws-mantle]
provider = bedrock
model = anthropic.claude-haiku-4-5
aws_region = us-east-1
aws_profile = default

It requires the bedrock-mantle:CreateInference permission.

Cohere

To use Cohere:

[cohere]
provider = cohere
api_key = <your API key>
model = command-a-03-2025

DeepSeek

To use DeepSeek:

[deepseek]
provider = deepseek
api_key = <your API key>
model = deepseek-chat

GitHub Models

To use GitHub Models:

[fish-ai]
configuration = github

[github]
provider = self-hosted
server = https://models.github.ai/inference
api_key = <paste GitHub PAT here>
model = gpt-4o-mini

You can create a personal access token (PAT) here. The PAT does not require any permissions.

Google

To use Gemini from Google:

[google]
provider = google
api_key = <your API key>
model = gemini-3.1-pro-preview

Groq

To use Groq:

[groq]
provider = groq
api_key = <your API key>

OpenAI

To use OpenAI:

[fish-ai]
configuration = openai

[openai]
provider = openai
model = gpt-4o
api_key = <your API key>
organization = <your organization>

OpenRouter

To use OpenRouter:

[fish-ai]
configuration = openrouter

[openrouter]
provider = self-hosted
server = https://openrouter.ai/api/v1
model = google/gemini-3-flash-preview
api_key = <your API key>
extra_body = {"reasoning": {"effort": "minimal", "exclude": true}}

Self-hosted

To use a self-hosted LLM (behind an OpenAI-compatible API):

[fish-ai]
configuration = self-hosted

[self-hosted]
provider = self-hosted
server = https://<your server>:<port>/v1
model = <your model>
api_key = <your API key>

If you are self-hosting, my recommendation is to use Ollama with Llama 3.3 70B. An out of the box configuration running on localhost could then look something like this:

[fish-ai]
configuration = local-llama

[local-llama]
provider = self-hosted
model = llama3.3
server = http://localhost:11434/v1

Available models are listed here.

🤸 Additional options

You can tweak the behaviour of fish-ai by putting additional options in your fish-ai.ini configuration file.

Configure the progress indicator

You can change the progress indicator (the default is ⏳) shown when the plugin is waiting for a response from the LLM.

To change the default, set the progress_indicator option to zero or more characters.

[fish-ai]
progress_indicator = wait...

Put the API key on your keyring

Instead of putting the API key in the configuration file, you can let fish-ai load it from your keyring. To save a new API key or transfer an existing API key to your keyring, run fish_ai_put_api_key.