mirror of
https://github.com/microsoft/autogen.git
synced 2025-08-01 05:12:22 +00:00
5387a0a607
* add agent notebook and documentation * fix bug * set flush to True when printing msg in agent * add a math problem in agent notebook * remove * header * improve notebook doc * notebook update * improve notebook example * improve doc * agent notebook example with user feedback * log * log * improve notebook doc * improve print * doc * human_input_mode * human_input_mode str * indent * indent * Update flaml/autogen/agent/user_proxy_agent.py Co-authored-by: Chi Wang <wang.chi@microsoft.com> * shell command and multiple code blocks * Update notebook/autogen_agent.ipynb Co-authored-by: Chi Wang <wang.chi@microsoft.com> * Update notebook/autogen_agent.ipynb Co-authored-by: Chi Wang <wang.chi@microsoft.com> * Update notebook/autogen_agent.ipynb Co-authored-by: Chi Wang <wang.chi@microsoft.com> * coding agent * math notebook * renaming and doc format * typo * infer lang * sh * docker * docker * reset consecutive autoreply counter * fix explanation * paper talk * human feedback * web info * rename test * config list explanation * link to blogpost * installation * homepage features * features * features * rename agent * remove notebook * notebook test * docker command * notebook update * lang -> cmd * notebook * make it work for gpt-3.5 * return full log * quote * docker * docker * docker * docker * docker * docker image list * notebook * notebook * use_docker * use_docker * use_docker * doc * agent * doc * abs path * pandas * docker * reuse docker image * context window * news * print format * pyspark version in py3.8 * pyspark in py3.8 * pyspark and ray * quote * pyspark * pyspark * pyspark --------- Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
132 lines
4.1 KiB
Markdown
132 lines
4.1 KiB
Markdown
# Installation
|
|
|
|
## Python
|
|
|
|
FLAML requires **Python version >= 3.7**. It can be installed from pip:
|
|
|
|
```bash
|
|
pip install flaml
|
|
```
|
|
|
|
or conda:
|
|
```
|
|
conda install flaml -c conda-forge
|
|
```
|
|
|
|
### Optional Dependencies
|
|
|
|
#### [Auto Generation](Use-Cases/Auto-Generation)
|
|
|
|
```bash
|
|
pip install "flaml[autogen]"
|
|
```
|
|
|
|
#### [Task-oriented AutoML](Use-Cases/Task-Oriented-AutoML)
|
|
|
|
```bash
|
|
pip install "flaml[automl]"
|
|
```
|
|
|
|
#### Extra learners/models
|
|
|
|
* openai models
|
|
```bash
|
|
pip install "flaml[openai]"
|
|
```
|
|
* catboost
|
|
```bash
|
|
pip install "flaml[catboost]"
|
|
```
|
|
* vowpal wabbit
|
|
```bash
|
|
pip install "flaml[vw]"
|
|
```
|
|
* time series forecaster: prophet, statsmodels
|
|
```bash
|
|
pip install "flaml[forecast]"
|
|
```
|
|
* huggingface transformers
|
|
```bash
|
|
pip install "flaml[hf]"
|
|
```
|
|
|
|
#### Notebook
|
|
|
|
To run the [notebook examples](https://github.com/microsoft/FLAML/tree/main/notebook),
|
|
install flaml with the [notebook] option:
|
|
|
|
```bash
|
|
pip install "flaml[notebook]"
|
|
```
|
|
|
|
#### Distributed tuning
|
|
|
|
* ray
|
|
```bash
|
|
pip install "flaml[ray]"
|
|
```
|
|
* spark
|
|
> *Spark support is added in v1.1.0*
|
|
```bash
|
|
pip install "flaml[spark]>=1.1.0"
|
|
```
|
|
|
|
For cloud platforms such as [Azure Synapse](https://azure.microsoft.com/en-us/products/synapse-analytics/), Spark clusters are provided.
|
|
But you may also need to install `Spark` manually when setting up your own environment.
|
|
For latest Ubuntu system, you can install Spark 3.3.0 standalone version with below script.
|
|
For more details of installing Spark, please refer to [Spark Doc](https://spark.apache.org/docs/latest/api/python/getting_started/install.html).
|
|
```bash
|
|
sudo apt-get update && sudo apt-get install -y --allow-downgrades --allow-change-held-packages --no-install-recommends \
|
|
ca-certificates-java ca-certificates openjdk-17-jdk-headless \
|
|
&& sudo apt-get clean && sudo rm -rf /var/lib/apt/lists/*
|
|
wget --progress=dot:giga "https://www.apache.org/dyn/closer.lua/spark/spark-3.3.0/spark-3.3.0-bin-hadoop2.tgz?action=download" \
|
|
-O - | tar -xzC /tmp; archive=$(basename "spark-3.3.0/spark-3.3.0-bin-hadoop2.tgz") \
|
|
bash -c "sudo mv -v /tmp/\${archive/%.tgz/} /spark"
|
|
export SPARK_HOME=/spark
|
|
export PYTHONPATH=/spark/python/lib/py4j-0.10.9.5-src.zip:/spark/python
|
|
export PATH=$PATH:$SPARK_HOME/bin
|
|
```
|
|
|
|
* nni
|
|
```bash
|
|
pip install "flaml[nni]"
|
|
```
|
|
* blendsearch
|
|
```bash
|
|
pip install "flaml[blendsearch]"
|
|
```
|
|
|
|
* synapse
|
|
> *To install flaml in Azure Synapse and similar cloud platform*
|
|
```bash
|
|
pip install flaml[synapse]
|
|
```
|
|
|
|
#### Test and Benchmark
|
|
|
|
* test
|
|
```bash
|
|
pip install flaml[test]
|
|
```
|
|
* benchmark
|
|
```bash
|
|
pip install flaml[benchmark]
|
|
```
|
|
|
|
## .NET
|
|
|
|
FLAML has a .NET implementation in [ML.NET](http://dot.net/ml), an open-source, cross-platform machine learning framework for .NET.
|
|
|
|
You can use FLAML in .NET in the following ways:
|
|
|
|
**Low-code**
|
|
|
|
- [*Model Builder*](https://dotnet.microsoft.com/apps/machinelearning-ai/ml-dotnet/model-builder) - A Visual Studio extension for training ML models using FLAML. For more information on how to install the, see the [install Model Builder](https://docs.microsoft.com/dotnet/machine-learning/how-to-guides/install-model-builder?tabs=visual-studio-2022) guide.
|
|
- [*ML.NET CLI*](https://docs.microsoft.com/dotnet/machine-learning/automate-training-with-cli) - A dotnet CLI tool for training machine learning models using FLAML on Windows, MacOS, and Linux. For more information on how to install the ML.NET CLI, see the [install the ML.NET CLI](https://docs.microsoft.com/dotnet/machine-learning/how-to-guides/install-ml-net-cli?tabs=windows) guide.
|
|
|
|
**Code-first**
|
|
|
|
- [*Microsoft.ML.AutoML*](https://www.nuget.org/packages/Microsoft.ML.AutoML/0.20.0-preview.22313.1) - NuGet package that provides direct access to the FLAML AutoML APIs that power low-code solutions like Model Builder and the ML.NET CLI. For more information on installing NuGet packages, see the install and use a NuGet package in [Visual Studio](https://docs.microsoft.com/nuget/quickstart/install-and-use-a-package-in-visual-studio) or [dotnet CLI](https://docs.microsoft.com/nuget/quickstart/install-and-use-a-package-using-the-dotnet-cli) guides.
|
|
|
|
To get started with the ML.NET API and AutoML, see the [csharp-notebooks](https://github.com/dotnet/csharp-notebooks#machine-learning).
|