264 lines
11 KiB
Markdown
264 lines
11 KiB
Markdown
# AutoGPT Agent setup
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[🐋 **Set up & Run with Docker**](./docker.md)
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[👷🏼 **For Developers**](./for-developers.md)
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## 📋 Requirements
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### Linux / macOS
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- Python 3.10 or later
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- Poetry ([instructions](https://python-poetry.org/docs/#installation))
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### Windows (WSL)
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- WSL 2
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- See also the [requirements for Linux](#linux-macos)
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- [Docker Desktop](https://docs.docker.com/desktop/install/windows-install/)
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### Windows
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!!! attention
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We recommend setting up AutoGPT with WSL. Some things don't work exactly the same on
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Windows and we currently can't provide specialized instructions for all those cases.
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- Python 3.10 or later ([instructions](https://www.tutorialspoint.com/how-to-install-python-in-windows))
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- Poetry ([instructions](https://python-poetry.org/docs/#installation))
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- [Docker Desktop](https://docs.docker.com/desktop/install/windows-install/)
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## Setting up AutoGPT
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### Getting AutoGPT
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Since we don't ship AutoGPT as a desktop application, you'll need to download the
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[project] from GitHub and give it a place on your computer.
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- To get the latest bleeding edge version, use `master`.
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- If you're looking for more stability, check out the latest AutoGPT [release][releases].
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[project]: https://github.com/Significant-Gravitas/AutoGPT
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[releases]: https://github.com/Significant-Gravitas/AutoGPT/releases
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!!! note
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These instructions don't apply if you're looking to run AutoGPT as a docker image.
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Instead, check out the [Docker setup](./docker.md) guide.
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### Completing the Setup
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Once you have cloned or downloaded the project, you can find the AutoGPT Agent in the
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`original_autogpt/` folder.
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Inside this folder you can configure the AutoGPT application with an `.env` file and (optionally) a JSON configuration file:
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- `.env` for environment variables, which are mostly used for sensitive data like API keys
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- a JSON configuration file to customize certain features of AutoGPT's [Components](../../forge/components/introduction.md)
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See the [Configuration](../configuration/options.md) reference for a list of available environment variables.
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1. Find the file named `.env.template`. This file may
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be hidden by default in some operating systems due to the dot prefix. To reveal
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hidden files, follow the instructions for your specific operating system:
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[Windows][show hidden files/Windows] and [macOS][show hidden files/macOS].
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2. Create a copy of `.env.template` and call it `.env`;
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if you're already in a command prompt/terminal window:
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```shell
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cp .env.template .env
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```
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3. Open the `.env` file in a text editor.
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4. Set API keys for the LLM providers that you want to use: see [below](#setting-up-llm-providers).
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5. Enter any other API keys or tokens for services you would like to use.
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!!! note
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To activate and adjust a setting, remove the `# ` prefix.
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6. Save and close the `.env` file.
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7. _Optional: run `poetry install` to install all required dependencies._ The
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application also checks for and installs any required dependencies when it starts.
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8. _Optional: configure the JSON file (e.g. `config.json`) with your desired settings._
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The application will use default settings if you don't provide a JSON configuration file.
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Learn how to [set up the JSON configuration file](../../forge/components/components.md#json-configuration)
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You should now be able to explore the CLI (`./autogpt.sh --help`) and run the application.
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See the [user guide](../usage.md) for further instructions.
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[show hidden files/Windows]: https://support.microsoft.com/en-us/windows/view-hidden-files-and-folders-in-windows-97fbc472-c603-9d90-91d0-1166d1d9f4b5
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[show hidden files/macOS]: https://www.pcmag.com/how-to/how-to-access-your-macs-hidden-files
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## Setting up LLM providers
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You can use AutoGPT with any of the following LLM providers.
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Each of them comes with its own setup instructions.
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AutoGPT was originally built on top of OpenAI's GPT-4, but now you can get
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similar and interesting results using other models/providers too.
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If you don't know which to choose, you can safely go with OpenAI*.
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<small>* subject to change</small>
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### OpenAI
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!!! attention
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To use AutoGPT with GPT-4 (recommended), you need to set up a paid OpenAI account
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with some money in it. Please refer to OpenAI for further instructions ([link][openai/help-gpt-4-access]).
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Free accounts are [limited][openai/api-limits] to GPT-3.5 with only 3 requests per minute.
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1. Make sure you have a paid account with some credits set up: [Settings > Organization > Billing][openai/billing]
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1. Get your OpenAI API key from: [API keys][openai/api-keys]
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2. Open `.env`
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3. Find the line that says `OPENAI_API_KEY=`
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4. Insert your OpenAI API Key directly after = without quotes or spaces:
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```ini
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OPENAI_API_KEY=sk-proj-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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```
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!!! info "Using a GPT Azure-instance"
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If you want to use GPT on an Azure instance, set `USE_AZURE` to `True` and
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make an Azure configuration file.
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Rename `azure.yaml.template` to `azure.yaml` and provide the relevant
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`azure_api_base`, `azure_api_version` and deployment IDs for the models that you
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want to use.
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E.g. if you want to use `gpt-3.5-turbo` and `gpt-4-turbo`:
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```yaml
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# Please specify all of these values as double-quoted strings
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# Replace string in angled brackets (<>) to your own deployment Name
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azure_model_map:
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gpt-3.5-turbo: "<gpt-35-turbo-deployment-id>"
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gpt-4-turbo: "<gpt-4-turbo-deployment-id>"
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...
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```
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Details can be found in the [openai/python-sdk/azure], and in the [Azure OpenAI docs] for the embedding model.
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If you're on Windows you may need to install an [MSVC library](https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170).
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!!! important
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Keep an eye on your API costs on [the Usage page][openai/usage].
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[openai/api-keys]: https://platform.openai.com/account/api-keys
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[openai/billing]: https://platform.openai.com/account/billing/overview
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[openai/usage]: https://platform.openai.com/account/usage
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[openai/api-limits]: https://platform.openai.com/docs/guides/rate-limits/free-tier-rate-limits
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[openai/help-gpt-4-access]: https://help.openai.com/en/articles/7102672-how-can-i-access-gpt-4-gpt-4-turbo-and-gpt-4o#h_9bddcd317c
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[openai/python-sdk/azure]: https://github.com/openai/openai-python?tab=readme-ov-file#microsoft-azure-openai
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### Anthropic
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1. Make sure you have credits in your account: [Settings > Plans & billing][anthropic/billing]
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2. Get your Anthropic API key from [Settings > API keys][anthropic/api-keys]
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3. Open `.env`
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4. Find the line that says `ANTHROPIC_API_KEY=`
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5. Insert your Anthropic API Key directly after = without quotes or spaces:
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```ini
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ANTHROPIC_API_KEY=sk-ant-api03-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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```
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6. Set `SMART_LLM` and/or `FAST_LLM` to the Claude 3 model you want to use.
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See Anthropic's [models overview][anthropic/models] for info on the available models.
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Example:
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```ini
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SMART_LLM=claude-3-opus-20240229
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```
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!!! important
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Keep an eye on your API costs on [the Usage page][anthropic/usage].
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[anthropic/api-keys]: https://console.anthropic.com/settings/keys
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[anthropic/billing]: https://console.anthropic.com/settings/plans
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[anthropic/usage]: https://console.anthropic.com/settings/usage
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[anthropic/models]: https://docs.anthropic.com/en/docs/models-overview
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### Groq
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!!! note
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Although Groq is supported, its built-in function calling API isn't mature.
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Any features using this API may experience degraded performance.
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Let us know your experience!
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1. Get your Groq API key from [Settings > API keys][groq/api-keys]
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2. Open `.env`
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3. Find the line that says `GROQ_API_KEY=`
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4. Insert your Groq API Key directly after = without quotes or spaces:
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```ini
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GROQ_API_KEY=gsk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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```
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5. Set `SMART_LLM` and/or `FAST_LLM` to the Groq model you want to use.
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See Groq's [models overview][groq/models] for info on the available models.
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Example:
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```ini
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SMART_LLM=llama3-70b-8192
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```
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[groq/api-keys]: https://console.groq.com/keys
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[groq/models]: https://console.groq.com/docs/models
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### Llamafile
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With llamafile you can run models locally, which means no need to set up billing,
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and guaranteed data privacy.
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For more information and in-depth documentation, check out the [llamafile documentation].
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!!! warning
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At the moment, llamafile only serves one model at a time. This means you can not
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set `SMART_LLM` and `FAST_LLM` to two different llamafile models.
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!!! warning
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Due to the issues linked below, llamafiles don't work on WSL. To use a llamafile
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with AutoGPT in WSL, you will have to run the llamafile in Windows (outside WSL).
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<details>
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<summary>Instructions</summary>
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1. Get the `llamafile/serve.py` script through one of these two ways:
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1. Clone the AutoGPT repo somewhere in your Windows environment,
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with the script located at `classic/original_autogpt/scripts/llamafile/serve.py`
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2. Download just the [serve.py] script somewhere in your Windows environment
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2. Make sure you have `click` installed: `pip install click`
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3. Run `ip route | grep default | awk '{print $3}'` *inside WSL* to get the address
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of the WSL host machine
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4. Run `python3 serve.py --host {WSL_HOST_ADDR}`, where `{WSL_HOST_ADDR}`
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is the address you found at step 3.
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If port 8080 is taken, also specify a different port using `--port {PORT}`.
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5. In WSL, set `LLAMAFILE_API_BASE=http://{WSL_HOST_ADDR}:8080/v1` in your `.env`.
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6. Follow the rest of the regular instructions below.
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[serve.py]: https://github.com/Significant-Gravitas/AutoGPT/blob/master/classic/original_autogpt/scripts/llamafile/serve.py
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</details>
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* [Mozilla-Ocho/llamafile#356](https://github.com/Mozilla-Ocho/llamafile/issues/356)
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* [Mozilla-Ocho/llamafile#100](https://github.com/Mozilla-Ocho/llamafile/issues/100)
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!!! note
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These instructions will download and use `mistral-7b-instruct-v0.2.Q5_K_M.llamafile`.
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`mistral-7b-instruct-v0.2` is currently the only tested and supported model.
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If you want to try other models, you'll have to add them to `LlamafileModelName` in
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[`llamafile.py`][classic/forge/llamafile.py].
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For optimal results, you may also have to add some logic to adapt the message format,
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like `LlamafileProvider._adapt_chat_messages_for_mistral_instruct(..)` does.
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1. Run the llamafile serve script:
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```shell
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python3 ./scripts/llamafile/serve.py
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```
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The first time this is run, it will download a file containing the model + runtime,
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which may take a while and a few gigabytes of disk space.
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To force GPU acceleration, add `--use-gpu` to the command.
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3. In `.env`, set `SMART_LLM`/`FAST_LLM` or both to `mistral-7b-instruct-v0.2`
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4. If the server is running on different address than `http://localhost:8080/v1`,
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set `LLAMAFILE_API_BASE` in `.env` to the right base URL
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[llamafile documentation]: https://github.com/Mozilla-Ocho/llamafile#readme
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[classic/forge/llamafile.py]: https://github.com/Significant-Gravitas/AutoGPT/blob/master/classic/forge/llm/providers/llamafile/llamafile.py
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