Add everyrow research app

Gradio app that lets users upload a CSV, provide a research query,
and runs everyrow's agent_map on every row to produce enriched results.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

README.md

@@ -1,13 +1,11 @@
 ---
-title: Everyrow Research
-emoji: 📉
-colorFrom: pink
-colorTo: pink
+title: everyrow research
+emoji: 🔍
+colorFrom: blue
+colorTo: purple
 sdk: gradio
-sdk_version: 6.5.1
+sdk_version: "5.0"
 app_file: app.py
 pinned: false
 short_description: everyrow to research and enrich your dataset
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,110 @@
+import asyncio
+import os
+import tempfile
+
+import gradio as gr
+import pandas as pd
+
+from everyrow.ops import agent_map
+from everyrow.task import EffortLevel
+
+EFFORT_LEVELS = {
+    "Low": EffortLevel.LOW,
+    "Minimal": EffortLevel.MINIMAL,
+    "High": EffortLevel.HIGH,
+}
+
+
+def preview_csv(file):
+    if file is None:
+        return gr.update(visible=False), None
+    df = pd.read_csv(file.name)
+    return gr.update(visible=True), df
+
+
+async def run_agent_map(api_key, file, query, effort_label):
+    if not api_key:
+        raise gr.Error("Please enter your everyrow API key.")
+    if file is None:
+        raise gr.Error("Please upload a CSV file.")
+    if not query.strip():
+        raise gr.Error("Please enter a research query.")
+
+    os.environ["EVERYROW_API_KEY"] = api_key
+
+    df = pd.read_csv(file.name)
+    if df.empty:
+        raise gr.Error("The uploaded CSV is empty.")
+
+    effort_level = EFFORT_LEVELS[effort_label]
+
+    result = await agent_map(task=query, input=df, effort_level=effort_level)
+
+    output_df = result.data
+
+    tmp = tempfile.NamedTemporaryFile(
+        delete=False, suffix=".csv", prefix="everyrow_results_"
+    )
+    output_df.to_csv(tmp.name, index=False)
+
+    return output_df, gr.update(value=tmp.name, visible=True)
+
+
+with gr.Blocks(title="everyrow research") as demo:
+    gr.Markdown(
+        """
+        # everyrow research
+        Upload a CSV, describe what you want to research for each row, and get
+        enriched results powered by [everyrow](https://everyrow.com).
+        """
+    )
+
+    api_key = gr.Textbox(
+        label="everyrow API key",
+        type="password",
+        placeholder="sk-cho-...",
+    )
+
+    file = gr.File(label="Upload CSV", file_types=[".csv"])
+
+    preview_heading = gr.Markdown("### Preview", visible=False)
+    preview_table = gr.Dataframe(label="Input preview", visible=False)
+
+    query = gr.Textbox(
+        label="Research query",
+        placeholder="e.g. Find this company's latest funding round and amount",
+        lines=3,
+    )
+
+    effort = gr.Dropdown(
+        choices=list(EFFORT_LEVELS.keys()),
+        value="Low",
+        label="Effort level",
+    )
+
+    submit_btn = gr.Button("Run", variant="primary")
+
+    gr.Markdown("### Results")
+    output_table = gr.Dataframe(label="Results")
+    download_btn = gr.File(label="Download CSV", visible=False)
+
+    def on_upload(file):
+        if file is None:
+            return gr.update(visible=False), gr.update(visible=False)
+        df = pd.read_csv(file.name)
+        return gr.update(visible=True), gr.update(value=df, visible=True)
+
+    file.change(
+        fn=on_upload,
+        inputs=[file],
+        outputs=[preview_heading, preview_table],
+    )
+
+    submit_btn.click(
+        fn=run_agent_map,
+        inputs=[api_key, file, query, effort],
+        outputs=[output_table, download_btn],
+    )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1 @@
+everyrow>=0.2.0