mirror of
https://github.com/Aider-AI/aider.git
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Refactor: Update LLM docs to match gemini.md structure
This commit is contained in:
Paul Gauthier (aider)
parent
ec7ac60cfc
commit
21fa54d792
13 changed files with 173 additions and 65 deletions
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@ -10,21 +10,26 @@ To work with Anthropic's models, you need to provide your
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either in the `ANTHROPIC_API_KEY` environment variable or
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via the `--anthropic-api-key` command line switch.
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Aider has some built in shortcuts for the most popular Anthropic models and
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has been tested and benchmarked to work well with them:
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First, install aider:
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{% include install.md %}
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Then configure your API keys:
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```
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python -m pip install -U aider-chat
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export ANTHROPIC_API_KEY=<key> # Mac/Linux
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setx ANTHROPIC_API_KEY <key> # Windows, restart shell after setx
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```
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Start working with aider and Anthropic on your codebase:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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# Aider uses Claude 3.7 Sonnet by default
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aider
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# Claude 3 Opus
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aider --model claude-3-opus-20240229
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# List models available from Anthropic
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aider --list-models anthropic/
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```
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@ -7,9 +7,13 @@ nav_order: 500
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Aider can connect to the OpenAI models on Azure.
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```
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python -m pip install -U aider-chat
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First, install aider:
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{% include install.md %}
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Then configure your API keys and endpoint:
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```
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# Mac/Linux:
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export AZURE_API_KEY=<key>
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export AZURE_API_VERSION=2024-12-01-preview
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@ -20,6 +24,13 @@ setx AZURE_API_KEY <key>
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setx AZURE_API_VERSION 2024-12-01-preview
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setx AZURE_API_BASE https://myendpt.openai.azure.com
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# ... restart your shell after setx commands
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```
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Start working with aider and Azure on your codebase:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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aider --model azure/<your_model_deployment_name>
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@ -6,10 +6,7 @@ nav_order: 560
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# Amazon Bedrock
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Aider can connect to models provided by Amazon Bedrock.
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You will need to have an AWS account with access to the Bedrock service.
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To configure Aider to use the Amazon Bedrock API, you need to set up your AWS credentials.
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This can be done using the AWS CLI or by setting environment variables.
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You will need to have an AWS account with access to the Bedrock service and the specific models you wish to use.
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## Select a Model from Amazon Bedrock
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@ -37,6 +34,14 @@ feature, you will receive an error message like the following:
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anthropic.claude-3-7-sonnet-20250219-v1:0 with on-demand throughput isn\xe2\x80\x99t supported. Retry your
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request with the ID or ARN of an inference profile that contains this model."}'
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## Installation and Configuration
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First, install aider:
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{% include install.md %}
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Next, configure your AWS credentials. This can be done using the AWS CLI or by setting environment variables.
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## AWS CLI Configuration
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If you haven't already, install the [AWS CLI](https://aws.amazon.com/cli/) and configure it with your credentials:
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@ -49,7 +54,7 @@ This will prompt you to enter your AWS Access Key ID, Secret Access Key, and def
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## Environment Variables
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Alternatively, you can set the following environment variables:
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You can set the following environment variables:
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```bash
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export AWS_REGION=your_preferred_region
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@ -63,7 +68,7 @@ export AWS_PROFILE=your-profile
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```
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You can add these to your
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[.env file](/docs/config/dotenv.html).
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`.env` file.
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### Set Environment Variables with PowerShell
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@ -77,6 +82,8 @@ $env:AWS_REGION = 'us-west-2' # Put whichever AWS region that you'd like, that
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## Install boto3
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Aider needs the `boto3` library to connect to Bedrock.
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The AWS Bedrock provider requires the `boto3` package in order to function correctly:
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```bash
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@ -95,12 +102,14 @@ You must install `boto3` dependency to aider's virtual environment installed via
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uv tool run --from aider-chat pip install boto3
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```
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## Running Aider with Bedrock
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## Get Started
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Once your AWS credentials are set up, you can run Aider with the `--model` command line switch, specifying the Bedrock model you want to use:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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aider --model bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0
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```
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@ -10,13 +10,22 @@ Their Command-R+ model works well with aider
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as a *very basic* coding assistant.
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You'll need a [Cohere API key](https://dashboard.cohere.com/welcome/login).
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To use **Command-R+**:
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First, install aider:
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{% include install.md %}
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Then configure your API keys:
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```
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python -m pip install -U aider-chat
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export COHERE_API_KEY=<key> # Mac/Linux
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setx COHERE_API_KEY <key> # Windows, restart shell after setx
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```
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Start working with aider and Cohere on your codebase:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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aider --model command-r-plus-08-2024
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@ -9,11 +9,22 @@ Aider can connect to the DeepSeek.com API.
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To work with DeepSeek's models, you need to set the `DEEPSEEK_API_KEY` environment variable with your [DeepSeek API key](https://platform.deepseek.com/api_keys).
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The DeepSeek Chat V3 model has a top score on aider's code editing benchmark.
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```
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python -m pip install -U aider-chat
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First, install aider:
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{% include install.md %}
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Then configure your API keys:
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```
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export DEEPSEEK_API_KEY=<key> # Mac/Linux
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setx DEEPSEEK_API_KEY <key> # Windows, restart shell after setx
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```
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Start working with aider and DeepSeek on your codebase:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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# Use DeepSeek Chat v3
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aider --model deepseek/deepseek-chat
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@ -10,13 +10,22 @@ The Llama 3 70B model works
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well with aider and is comparable to GPT-3.5 in code editing performance.
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You'll need a [Groq API key](https://console.groq.com/keys).
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To use **Llama3 70B**:
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First, install aider:
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{% include install.md %}
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Then configure your API keys:
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```
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python -m pip install -U aider-chat
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export GROQ_API_KEY=<key> # Mac/Linux
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setx GROQ_API_KEY <key> # Windows, restart shell after setx
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```
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Start working with aider and Groq on your codebase:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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aider --model groq/llama3-70b-8192
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@ -5,11 +5,15 @@ nav_order: 400
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# LM Studio
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To use LM Studio:
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Aider can connect to models served by LM Studio.
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First, install aider:
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{% include install.md %}
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Then configure your API key and endpoint:
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```
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python -m pip install -U aider-chat
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# Must set a value here even if its a dummy value
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export LM_STUDIO_API_KEY=dummy-api-key # Mac/Linux
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setx LM_STUDIO_API_KEY dummy-api-key # Windows, restart shell after setx
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@ -17,12 +21,19 @@ setx LM_STUDIO_API_KEY dummy-api-key # Windows, restart shell after setx
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# LM Studio default server URL is http://localhost:1234/v1
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export LM_STUDIO_API_BASE=http://localhost:1234/v1 # Mac/Linux
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setx LM_STUDIO_API_BASE http://localhost:1234/v1 # Windows, restart shell after setx
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aider --model lm_studio/<your-model-name>
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```
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**Note:** Even though LM Studio doesn't require an API Key out of the box the `LM_STUDIO_API_KEY` must have a dummy value like `dummy-api-key` set or the client request will fail trying to send an empty `Bearer` token.
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Start working with aider and LM Studio on your codebase:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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aider --model lm_studio/<your-model-name>
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```
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See the [model warnings](warnings.html)
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section for information on warnings which will occur
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when working with models that aider is not familiar with.
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@ -7,6 +7,19 @@ nav_order: 500
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Aider can connect to local Ollama models.
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First, install aider:
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{% include install.md %}
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Then configure your Ollama API endpoint (usually the default):
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```bash
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export OLLAMA_API_BASE=http://127.0.0.1:11434 # Mac/Linux
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setx OLLAMA_API_BASE http://127.0.0.1:11434 # Windows, restart shell after setx
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```
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Start working with aider and Ollama on your codebase:
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```
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# Pull the model
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ollama pull <model>
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@ -14,11 +27,8 @@ ollama pull <model>
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# Start your ollama server, increasing the context window to 8k tokens
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OLLAMA_CONTEXT_LENGTH=8192 ollama serve
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# In another terminal window...
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python -m pip install -U aider-chat
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export OLLAMA_API_BASE=http://127.0.0.1:11434 # Mac/Linux
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setx OLLAMA_API_BASE http://127.0.0.1:11434 # Windows, restart shell after setx
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# In another terminal window, change directory into your codebase
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cd /to/your/project
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aider --model ollama_chat/<model>
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```
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@ -7,10 +7,13 @@ nav_order: 500
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Aider can connect to any LLM which is accessible via an OpenAI compatible API endpoint.
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```
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python -m pip install aider-install
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aider-install
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First, install aider:
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{% include install.md %}
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Then configure your API key and endpoint:
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```
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# Mac/Linux:
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export OPENAI_API_BASE=<endpoint>
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export OPENAI_API_KEY=<key>
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@ -19,6 +22,13 @@ export OPENAI_API_KEY=<key>
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setx OPENAI_API_BASE <endpoint>
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setx OPENAI_API_KEY <key>
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# ... restart shell after setx commands
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```
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Start working with aider and your OpenAI compatible API on your codebase:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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# Prefix the model name with openai/
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aider --model openai/<model-name>
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@ -10,27 +10,34 @@ To work with OpenAI's models, you need to provide your
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either in the `OPENAI_API_KEY` environment variable or
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via the `--api-key openai=<key>` command line switch.
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Aider has some built in shortcuts for the most popular OpenAI models and
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has been tested and benchmarked to work well with them:
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First, install aider:
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{% include install.md %}
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Then configure your API keys:
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```
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python -m pip install -U aider-chat
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export OPENAI_API_KEY=<key> # Mac/Linux
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setx OPENAI_API_KEY <key> # Windows, restart shell after setx
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```
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Start working with aider and OpenAI on your codebase:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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# o3-mini
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aider --model o3-mini --api-key openai=<key>
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aider --model o3-mini
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# o1-mini
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aider --model o1-mini --api-key openai=<key>
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aider --model o1-mini
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# GPT-4o
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aider --model gpt-4o --api-key openai=<key>
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aider --model gpt-4o
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# List models available from OpenAI
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aider --list-models openai/
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# You can also store you API key in environment variables (or .env)
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export OPENAI_API_KEY=<key> # Mac/Linux
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setx OPENAI_API_KEY <key> # Windows, restart shell after setx
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```
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You can use `aider --model <model-name>` to use any other OpenAI model.
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@ -8,11 +8,22 @@ nav_order: 500
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Aider can connect to [models provided by OpenRouter](https://openrouter.ai/models?o=top-weekly):
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You'll need an [OpenRouter API key](https://openrouter.ai/keys).
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```
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python -m pip install -U aider-chat
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First, install aider:
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{% include install.md %}
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Then configure your API keys:
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```
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export OPENROUTER_API_KEY=<key> # Mac/Linux
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setx OPENROUTER_API_KEY <key> # Windows, restart shell after setx
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```
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Start working with aider and OpenRouter on your codebase:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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# Or any other open router model
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aider --model openrouter/<provider>/<model>
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@ -23,16 +34,6 @@ aider --list-models openrouter/
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In particular, many aider users access Sonnet via OpenRouter:
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```
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python -m pip install -U aider-chat
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export OPENROUTER_API_KEY=<key> # Mac/Linux
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setx OPENROUTER_API_KEY <key> # Windows, restart shell after setx
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aider --model openrouter/anthropic/claude-3.7-sonnet
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```
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{: .tip }
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If you get errors, check your
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[OpenRouter privacy settings](https://openrouter.ai/settings/privacy).
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@ -13,6 +13,10 @@ or service account with permission to use the Vertex AI API.
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With your chosen login method, the gcloud CLI should automatically set the
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`GOOGLE_APPLICATION_CREDENTIALS` environment variable which points to the credentials file.
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First, install aider:
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{% include install.md %}
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To configure Aider to use the Vertex AI API, you need to set `VERTEXAI_PROJECT` (the GCP project ID)
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and `VERTEXAI_LOCATION` (the GCP region) [environment variables for Aider](/docs/config/dotenv.html).
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@ -27,9 +31,12 @@ VERTEXAI_PROJECT=my-project
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VERTEXAI_LOCATION=us-east5
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```
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Then you can run aider with the `--model` command line switch, like this:
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Start working with aider and Vertex AI on your codebase:
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```
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# Change directory into your codebase
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cd /to/your/project
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aider --model vertex_ai/claude-3-5-sonnet@20240620
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```
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@ -7,14 +7,22 @@ nav_order: 400
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You'll need a [xAI API key](https://console.x.ai.).
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To use xAI:
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First, install aider:
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{% include install.md %}
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Then configure your API keys:
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```bash
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python -m pip install aider-install
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aider-install
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export XAI_API_KEY=<key> # Mac/Linux
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setx XAI_API_KEY <key> # Windows, restart shell after setx
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```
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Start working with aider and xAI on your codebase:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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# Grok 3
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aider --model xai/grok-3-beta
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