comparison chat_analysis.xml @ 4:dd4874a77f62 draft

planemo upload for repository https://github.com/goeckslab/ChatAnalysis commit 81dd1e732f7264affc7b8acdf5ba174dbc0c32a9

3:eaa8cead8adb

<tool id="interactive_tool_chat_analysis" tool_type="interactive" name="Chat with your data" version="0.1">
    <requirements>
        <container type="docker">
            quay.io/goeckslab/chatanalysis:main
        </container>
    </requirements>
    <entry_points>
        <entry_point name="Chat with $input_dataset.element_identifier" requires_domain="True">
            <port>

    </entry_points>
    <command>
        <![CDATA[
        echo "Starting Streamlit" &&
        echo "working dir now: `pwd`" &&
        mkdir -p plots &&
        streamlit run /ChatAnalysis/chat_analysis.py
            "$openai_api_key_file"
            "$groq_api_key_file"
            "$chat_history"
            "$export_csv"
            "./plots"
            "$input_dataset"
        ]]>
    </command>
    <configfiles>
        <configfile name="openai_api_key_file"><![CDATA[
            $__user__.extra_preferences.get('chatgpt|api_key')

    </configfiles>
    <stdio>
        <exit_code range="0:0" level="log"/>
    </stdio>
    <inputs>
        <param name="input_dataset"  type="data" format="csv,tabular" label="Data(csv or tsv) you want to chat with" optional="false"/>
    </inputs>
    <outputs>
        <data name="chat_history" format="pdf" label="${tool.name} -- chat history pdf on ${on_string}"/>
        <data name="export_csv" format="csv" label="${tool.name} -- the exported csv you selected on ${on_string}"/>
    </outputs>
    <tests>
        <test expect_num_outputs="2">
            <param name="input_dataset" value="test.csv"/>
            <output name="chat_history" file="chat_history.pdf" compare="sim_size" />
            <output name="export_csv" file="exported.csv" compare="sim_size" />
        </test>
    </tests>
    <help>
        Analyze and visualize a dataset with a Chat Agent.

4:dd4874a77f62

<tool id="interactive_tool_chat_analysis" tool_type="interactive" name="Chat with your data" version="0.2">
    <requirements>
        <container type="docker">
            quay.io/goeckslab/chatanalysis:smolagents
        </container>
    </requirements>
    <entry_points>
        <entry_point name="Chat with $input_dataset.element_identifier" requires_domain="True">
            <port>

    </entry_points>
    <command>
        <![CDATA[
        echo "Starting Streamlit" &&
        echo "working dir now: `pwd`" &&
        mkdir -p generate_files &&
        echo "input dataset: $input_dataset" &&
        echo "input dataset datatype: $dataset_type" &&
        ln -sf $__tool_directory__/.env /ChatAnalysis/.env &&
        streamlit run /ChatAnalysis/smolagents_da.py
            "$__user_email__"
            "$openai_api_key_file"
            "$groq_api_key_file"
            "$chat_history"
            "./generate_files"
            "$input_dataset"
            "$dataset_type"
        ]]>
    </command>
    <configfiles>
        <configfile name="openai_api_key_file"><![CDATA[
            $__user__.extra_preferences.get('chatgpt|api_key')

    </configfiles>
    <stdio>
        <exit_code range="0:0" level="log"/>
    </stdio>
    <inputs>
        <param name="input_dataset"  type="data" format="csv,tsv,h5ad,xlsx,xls,json,parquet,h5,fa,fasta,vcf,gtf,gff,bed" label="Data you want to chat with" optional="false"/>
        <param name="dataset_type" type="select" label="The type of your dataset" >
            <option value="csv">csv</option>
            <option value="tsv">tsv</option>
            <option value="h5ad">h5ad</option>
            <option value="xlsx">xlsx</option>
            <option value="xls">xls</option>
            <option value="json">json</option>
            <option value="parquet">parquet</option>
            <option value="h5">h5</option>
            <option value="fa">fa</option>
            <option value="fasta">fasta</option>
            <option value="vcf">vcf</option>
            <option value="gtf">gtf</option>
            <option value="gff">gff</option>
            <option value="bed">bed</option>
        </param>  
    </inputs>
    <outputs>
        <data name="chat_history" format="json" label="${tool.name} -- chat history json on ${on_string} -- use to restore chat history next time"/>
        <collection name="generate_files" type="list" label="${tool.name} -- generated files">
            <discover_datasets pattern="__name_and_ext__" directory="generate_files" />
        </collection>
    </outputs>
    <tests>
        <test>
        </test>
    </tests>
    <help>
        Analyze and visualize a dataset with a Chat Agent.