Commit
·
121ffd6
1
Parent(s):
39f298a
Update app.py
Browse files
app.py
CHANGED
@@ -15,7 +15,7 @@ import streamlit as st
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from txtai.embeddings import Documents, Embeddings
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from txtai.pipeline import Segmentation, Summary, Tabular, Translation
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from txtai.workflow import ServiceTask, Task,
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class Application:
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@@ -23,11 +23,14 @@ class Application:
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Main application.
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"""
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def __init__(self):
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"""
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Creates a new application.
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"""
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# Component options
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self.components = {}
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@@ -42,20 +45,177 @@ class Application:
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self.documents = None
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self.data = None
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def
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"""
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-
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Args:
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label: label
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Returns:
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numeric
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"""
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value =
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return int(value) if value else None
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def split(self, text):
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"""
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Splits text on commas and returns a list.
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return [x.strip() for x in text.split(",")]
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def options(self, component):
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"""
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Extracts component settings into a component configuration dict.
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Args:
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component: component type
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Returns:
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dict with component settings
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options = {"type": component}
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st.
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st.
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options["path"] =
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options["
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options["
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options["
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options["
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options["join"] = st.sidebar.checkbox("Join tokenized")
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options["minlength"] = self.number("Min section length")
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elif component == "service":
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options["
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options["
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options["
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options["
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if options["params"]:
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options["params"] = {key: None for key in self.split(options["params"])}
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if options["extract"]:
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options["extract"] = self.split(options["extract"])
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elif component == "tabular":
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options["
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if options["textcolumns"]:
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options["textcolumns"] = self.split(options["textcolumns"])
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elif component == "
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st.
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options["target"] =
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return options
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@@ -137,7 +311,7 @@ class Application:
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"""
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# Clear application
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self.__init__()
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# pylint: disable=W0108
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tasks = []
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@@ -151,12 +325,12 @@ class Application:
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self.documents = Documents()
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tasks.append(Task(self.documents.add, unpack=False))
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elif wtype == "
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self.pipelines[wtype] = Segmentation(**self.components[
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tasks.append(Task(self.pipelines[
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elif wtype == "service":
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tasks.append(ServiceTask(**self.components[
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elif wtype == "summary":
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self.pipelines[wtype] = Summary(component.pop("path"))
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elif wtype == "tabular":
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self.pipelines[wtype] = Tabular(**self.components["tabular"])
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tasks.append(Task(self.pipelines[
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elif wtype == "
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self.pipelines[wtype] = Translation()
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tasks.append(Task(lambda x: self.pipelines["
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self.workflow = Workflow(tasks)
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@@ -180,11 +354,11 @@ class Application:
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components: list of components to export to YAML
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Returns:
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YAML string
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"""
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# pylint: disable=W0108
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data = {}
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tasks = []
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name = None
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component = dict(component)
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name = wtype = component.pop("type")
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if wtype == "
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tasks.append({"action": "summary"})
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data["
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elif wtype == "service":
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config = dict(**component)
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config["task"] =
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tasks.append(config)
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elif wtype == "
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data[
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tasks.append({"action":
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elif wtype == "textract":
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data["textractor"] = component
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tasks.append({"action": "textractor", "task": "url"})
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elif wtype == "transcribe":
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data["transcription"] = {"path": component.pop("path")}
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tasks.append({"action": "transcription", "task": "url"})
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elif wtype == "translate":
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data["translation"] = {}
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tasks.append({"action": "translation", "args": list(component.values())})
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elif wtype == "embeddings":
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upsert = component.pop("upsert")
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data[
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# Add in workflow
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data["workflow"] = {name: {"tasks": tasks}}
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return [text for uid, text, _ in self.data if uid == key][0]
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def process(self, data):
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"""
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Processes the current application action.
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Args:
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data: input data
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"""
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if data and self.workflow:
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self.documents, self.pipelines, self.workflow = None, None, None
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if self.embeddings and self.data:
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# Set query and limit
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query = st.text_input("Query")
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limit = min(5, len(self.data))
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st.markdown(
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"""
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<style>
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Runs Streamlit application.
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"""
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st.sidebar
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st.sidebar.markdown("---")
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col1, col2 = st.columns(2)
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# Build or re-build workflow when build button clicked
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build = col1.button("Build", help="Build the workflow and run within this application")
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if build:
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with st.spinner("Building workflow...."):
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self.build(components)
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col2.download_button("Export", config, file_name="workflow.yml", help="Export the API workflow as YAML")
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with st.expander("Data", expanded=not self.data):
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# Parse text items
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data = self.parse(data) if data else data
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# Process current action
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self.process(data)
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@st.cache(allow_output_mutation=True)
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Application
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"""
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return Application()
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if __name__ == "__main__":
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from txtai.embeddings import Documents, Embeddings
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from txtai.pipeline import Segmentation, Summary, Tabular, Translation
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from txtai.workflow import ServiceTask, Task, Workflow
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class Application:
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Main application.
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"""
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def __init__(self, directory):
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"""
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Creates a new application.
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"""
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# Workflow configuration directory
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self.directory = directory
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# Component options
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self.components = {}
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self.documents = None
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self.data = None
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def load(self, components):
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"""
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Load an existing workflow file.
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Args:
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components: list of components to load
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Returns:
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(names of components loaded, workflow config)
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"""
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with open(os.path.join(self.directory, "config.yml")) as f:
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config = yaml.safe_load(f)
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names = [row["name"] for row in config]
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files = [row["file"] for row in config]
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selected = st.selectbox("Load workflow", ["--"] + names)
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if selected != "--":
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index = [x for x, name in enumerate(names) if name == selected][0]
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with open(os.path.join(self.directory, files[index])) as f:
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workflow = yaml.safe_load(f)
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st.markdown("---")
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# Get tasks for first workflow
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tasks = list(workflow["workflow"].values())[0]["tasks"]
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selected = []
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for task in tasks:
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name = task.get("action", task.get("task"))
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if name in components:
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selected.append(name)
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elif name in ["index", "upsert"]:
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selected.append("embeddings")
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return (selected, workflow)
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return (None, None)
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def state(self, key):
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"""
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Lookup a session state variable.
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Args:
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key: variable key
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Returns:
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variable value
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"""
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if key in st.session_state:
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return st.session_state[key]
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return None
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def appsetting(self, workflow, name):
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"""
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Looks up an application configuration setting.
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Args:
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workflow: workflow configuration
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name: setting name
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Returns:
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app setting value
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"""
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if workflow:
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config = workflow.get("app")
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if config:
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return config.get(name)
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return None
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def setting(self, config, name, default=None):
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"""
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Looks up a component configuration setting.
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Args:
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config: component configuration
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name: setting name
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default: default setting value
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Returns:
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setting value
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"""
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return config.get(name, default) if config else default
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def text(self, label, config, name, default=None):
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"""
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Create a new text input field.
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Args:
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label: field label
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config: component configuration
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name: setting name
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default: default setting value
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Returns:
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text input field value
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"""
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default = self.setting(config, name, default)
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if not default:
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default = ""
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elif isinstance(default, list):
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default = ",".join(default)
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elif isinstance(default, dict):
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default = ",".join(default.keys())
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return st.text_input(label, value=default)
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def number(self, label, config, name, default=None):
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"""
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Creates a new numeric input field.
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Args:
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label: field label
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config: component configuration
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name: setting name
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default: default setting value
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Returns:
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numeric value
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"""
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value = self.text(label, config, name, default)
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return int(value) if value else None
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def boolean(self, label, config, name, default=False):
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"""
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Creates a new checkbox field.
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Args:
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label: field label
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config: component configuration
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name: setting name
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default: default setting value
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Returns:
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boolean value
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"""
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default = self.setting(config, name, default)
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return st.checkbox(label, value=default)
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def select(self, label, config, name, options, default=0):
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"""
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Creates a new select box field.
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Args:
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label: field label
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config: component configuration
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name: setting name
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options: list of dropdown options
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default: default setting value
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Returns:
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boolean value
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"""
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index = self.setting(config, name)
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index = [x for x, option in enumerate(options) if option == default]
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# Derive default index
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default = index[0] if index else default
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return st.selectbox(label, options, index=default)
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def split(self, text):
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"""
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Splits text on commas and returns a list.
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return [x.strip() for x in text.split(",")]
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def options(self, component, workflow):
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"""
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Extracts component settings into a component configuration dict.
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Args:
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component: component type
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238 |
+
workflow: existing workflow, can be None
|
239 |
|
240 |
Returns:
|
241 |
dict with component settings
|
|
|
243 |
|
244 |
options = {"type": component}
|
245 |
|
246 |
+
st.markdown("---")
|
247 |
|
248 |
+
# Lookup component configuration
|
249 |
+
# - Runtime components have config defined within tasks
|
250 |
+
# - Pipeline components have config defined at workflow root
|
251 |
+
config = None
|
252 |
+
if workflow:
|
253 |
+
if component in ["service", "translation"]:
|
254 |
+
# Service config is found in tasks section
|
255 |
+
tasks = list(workflow["workflow"].values())[0]["tasks"]
|
256 |
+
config = [task for task in tasks if task.get("task") == component or task.get("action") == component][0]
|
257 |
+
else:
|
258 |
+
config = workflow.get(component)
|
259 |
|
260 |
+
if component == "embeddings":
|
261 |
+
st.markdown("**Embeddings Index** \n*Index workflow output*")
|
262 |
+
options["path"] = self.text("Embeddings model path", config, "path", "sentence-transformers/nli-mpnet-base-v2")
|
263 |
+
options["upsert"] = self.boolean("Upsert", config, "upsert")
|
264 |
+
|
265 |
+
elif component == "segmentation":
|
266 |
+
st.markdown("**Segment** \n*Split text into semantic units*")
|
267 |
+
options["sentences"] = self.boolean("Split sentences", config, "sentences")
|
268 |
+
options["lines"] = self.boolean("Split lines", config, "lines")
|
269 |
+
options["paragraphs"] = self.boolean("Split paragraphs", config, "paragraphs")
|
270 |
+
options["join"] = self.boolean("Join tokenized", config, "join")
|
271 |
+
options["minlength"] = self.number("Min section length", config, "minlength")
|
|
|
|
|
272 |
|
273 |
elif component == "service":
|
274 |
+
st.markdown("**Service** \n*Extract data from an API*")
|
275 |
+
options["url"] = self.text("URL", config, "url")
|
276 |
+
options["method"] = self.select("Method", config, "method", ["get", "post"], 0)
|
277 |
+
options["params"] = self.text("URL parameters", config, "params")
|
278 |
+
options["batch"] = self.boolean("Run as batch", config, "batch", True)
|
279 |
+
options["extract"] = self.text("Subsection(s) to extract", config, "extract")
|
280 |
|
281 |
if options["params"]:
|
282 |
options["params"] = {key: None for key in self.split(options["params"])}
|
283 |
if options["extract"]:
|
284 |
options["extract"] = self.split(options["extract"])
|
285 |
|
286 |
+
elif component == "summary":
|
287 |
+
st.markdown("**Summary** \n*Abstractive text summarization*")
|
288 |
+
options["path"] = self.text("Model", config, "path", "sshleifer/distilbart-cnn-12-6")
|
289 |
+
options["minlength"] = self.number("Min length", config, "minlength")
|
290 |
+
options["maxlength"] = self.number("Max length", config, "maxlength")
|
291 |
+
|
292 |
elif component == "tabular":
|
293 |
+
st.markdown("**Tabular** \n*Split tabular data into rows and columns*")
|
294 |
+
options["idcolumn"] = self.text("Id columns", config, "idcolumn")
|
295 |
+
options["textcolumns"] = self.text("Text columns", config, "textcolumns")
|
296 |
if options["textcolumns"]:
|
297 |
options["textcolumns"] = self.split(options["textcolumns"])
|
298 |
|
299 |
+
elif component == "translation":
|
300 |
+
st.markdown("**Translate** \n*Machine translation*")
|
301 |
+
options["target"] = self.text("Target language code", config, "args", "en")
|
302 |
|
303 |
return options
|
304 |
|
|
|
311 |
"""
|
312 |
|
313 |
# Clear application
|
314 |
+
self.__init__(self.directory)
|
315 |
|
316 |
# pylint: disable=W0108
|
317 |
tasks = []
|
|
|
325 |
self.documents = Documents()
|
326 |
tasks.append(Task(self.documents.add, unpack=False))
|
327 |
|
328 |
+
elif wtype == "segmentation":
|
329 |
+
self.pipelines[wtype] = Segmentation(**self.components[wtype])
|
330 |
+
tasks.append(Task(self.pipelines[wtype]))
|
331 |
|
332 |
elif wtype == "service":
|
333 |
+
tasks.append(ServiceTask(**self.components[wtype]))
|
334 |
|
335 |
elif wtype == "summary":
|
336 |
self.pipelines[wtype] = Summary(component.pop("path"))
|
|
|
338 |
|
339 |
elif wtype == "tabular":
|
340 |
self.pipelines[wtype] = Tabular(**self.components["tabular"])
|
341 |
+
tasks.append(Task(self.pipelines[wtype]))
|
342 |
|
343 |
+
elif wtype == "translation":
|
344 |
self.pipelines[wtype] = Translation()
|
345 |
+
tasks.append(Task(lambda x: self.pipelines["translation"](x, **self.components["translation"])))
|
346 |
|
347 |
self.workflow = Workflow(tasks)
|
348 |
|
|
|
354 |
components: list of components to export to YAML
|
355 |
|
356 |
Returns:
|
357 |
+
(workflow name, YAML string)
|
358 |
"""
|
359 |
|
360 |
# pylint: disable=W0108
|
361 |
+
data = {"app": {"data": self.state("data"), "query": self.state("query")}}
|
362 |
tasks = []
|
363 |
name = None
|
364 |
|
|
|
366 |
component = dict(component)
|
367 |
name = wtype = component.pop("type")
|
368 |
|
369 |
+
if wtype == "embeddings":
|
370 |
+
upsert = component.pop("upsert")
|
|
|
371 |
|
372 |
+
data[wtype] = component
|
373 |
+
data["writable"] = True
|
374 |
+
|
375 |
+
name = "index"
|
376 |
+
tasks.append({"action": "upsert" if upsert else "index"})
|
377 |
+
|
378 |
+
elif wtype == "segmentation":
|
379 |
+
data[wtype] = component
|
380 |
+
tasks.append({"action": wtype})
|
381 |
|
382 |
elif wtype == "service":
|
383 |
config = dict(**component)
|
384 |
+
config["task"] = wtype
|
385 |
tasks.append(config)
|
386 |
|
387 |
+
elif wtype == "summary":
|
388 |
+
data[wtype] = {"path": component.pop("path")}
|
389 |
+
tasks.append({"action": wtype})
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
390 |
|
391 |
+
elif wtype == "tabular":
|
392 |
+
data[wtype] = component
|
393 |
+
tasks.append({"action": wtype})
|
394 |
|
395 |
+
elif wtype == "translation":
|
396 |
+
data[wtype] = {}
|
397 |
+
tasks.append({"action": wtype, "args": list(component.values())})
|
398 |
|
399 |
# Add in workflow
|
400 |
data["workflow"] = {name: {"tasks": tasks}}
|
|
|
414 |
|
415 |
return [text for uid, text, _ in self.data if uid == key][0]
|
416 |
|
417 |
+
def process(self, data, workflow):
|
418 |
"""
|
419 |
Processes the current application action.
|
420 |
|
421 |
Args:
|
422 |
data: input data
|
423 |
+
workflow: workflow configuration
|
424 |
"""
|
425 |
|
426 |
if data and self.workflow:
|
|
|
446 |
self.documents, self.pipelines, self.workflow = None, None, None
|
447 |
|
448 |
if self.embeddings and self.data:
|
449 |
+
default = self.appsetting(workflow, "query")
|
450 |
+
default = default if default else ""
|
451 |
+
|
452 |
# Set query and limit
|
453 |
+
query = st.text_input("Query", value=default)
|
454 |
limit = min(5, len(self.data))
|
455 |
|
456 |
+
# Save query state
|
457 |
+
st.session_state["query"] = query
|
458 |
+
|
459 |
st.markdown(
|
460 |
"""
|
461 |
<style>
|
|
|
496 |
Runs Streamlit application.
|
497 |
"""
|
498 |
|
499 |
+
with st.sidebar:
|
500 |
+
st.image("https://github.com/neuml/txtai/raw/master/logo.png", width=256)
|
501 |
+
st.markdown("# Workflow builder \n*Build and apply workflows to data* \n\nRead more on [GitHub](https://github.com/neuml/txtai) ")
|
502 |
+
st.markdown("---")
|
503 |
|
504 |
+
# Component configuration
|
505 |
+
labels = {"segmentation": "segment", "translation": "translate"}
|
506 |
+
components = ["embeddings", "segmentation", "service", "summary", "tabular", "translation"]
|
507 |
|
508 |
+
selected, workflow = self.load(components)
|
509 |
+
selected = st.multiselect("Select components", components, default=selected, format_func=lambda text: labels.get(text, text))
|
|
|
510 |
|
511 |
+
# Get selected options
|
512 |
+
components = [self.options(component, workflow) for component in selected]
|
513 |
+
st.markdown("---")
|
514 |
+
|
515 |
+
# Export buttons
|
516 |
col1, col2 = st.columns(2)
|
517 |
+
|
518 |
+
# Build or re-build workflow when build button clicked or new workflow loaded
|
519 |
build = col1.button("Build", help="Build the workflow and run within this application")
|
520 |
+
if build or (workflow and workflow != self.state("workflow")):
|
521 |
with st.spinner("Building workflow...."):
|
522 |
self.build(components)
|
523 |
|
|
|
527 |
col2.download_button("Export", config, file_name="workflow.yml", help="Export the API workflow as YAML")
|
528 |
|
529 |
with st.expander("Data", expanded=not self.data):
|
530 |
+
default = self.appsetting(workflow, "data")
|
531 |
+
default = default if default else ""
|
532 |
+
|
533 |
+
data = st.text_area("Input", height=10, value=default)
|
534 |
+
|
535 |
+
# Save data and workflow state
|
536 |
+
st.session_state["data"] = data
|
537 |
+
st.session_state["workflow"] = workflow
|
538 |
|
539 |
# Parse text items
|
540 |
data = self.parse(data) if data else data
|
541 |
|
542 |
# Process current action
|
543 |
+
self.process(data, workflow)
|
544 |
|
545 |
|
546 |
@st.cache(allow_output_mutation=True)
|
|
|
552 |
Application
|
553 |
"""
|
554 |
|
555 |
+
return Application(".")
|
556 |
|
557 |
|
558 |
if __name__ == "__main__":
|