def filter_tags(row, filt, operator):
    tags = row["tags"]
    tags[:] = [d for d in tags if isinstance(d, str)]
    if operator == "All":
        if all(elem in tags for elem in filt):
            return True

    s1 = set(tags)
    s2 = set(filt)
    if operator == "Any":
        if bool(s1 & s2):
            return True
    if operator == "None":
        if len(s1.intersection(s2)) == 0:
            return True
    return False


def filter_pipeline_data(data, modality, pipeline, library,framework, tags, operator):
    data = data[data['pipeline'].notna()]

    if modality != "All":
        data = data[data["modality"] == modality.lower()]

    if pipeline != "all":
        data = data[data["pipeline"] == pipeline]
    
    if library != "all" and library != "not transformers":
        data = data[data["library"] == library]
    if library == "not transformers":
        data = data[data["library"] != "transformers"]
    
    if framework != "all":
        print(framework)
        data = data[data[framework] == 1]

    if tags != []:
        data = data[data.apply(filter_tags, axis=1, filt=tags, operator=operator)]

    tags = data["tags"].explode()
    tags = tags[tags.notna()].value_counts().rename_axis("tag").to_frame('counts').reset_index()
    s = tags["tag"]
    s = s[s.apply(type) == str]

    return data, s.unique()