Added length and raw text

app.py

@@ -23,7 +23,7 @@ def validate_dataset(dataset, openapi):
         return "⚠️Waiting for documents and key..."
 
 
-def do_ask(question, button, openapi, dataset, progress=gr.Progress()):
+def do_ask(question, button, openapi, dataset, slider, progress=gr.Progress()):
     global docs
     docs_ready = dataset.iloc[-1, 0] != ""
     if button == "✨Ready✨" and type(openapi) is str and len(openapi) > 0 and docs_ready:
@@ -39,13 +39,17 @@ def do_ask(question, button, openapi, dataset, progress=gr.Progress()):
                     key = row['citation string']
                 docs.add(row['filepath'], row['citation string'], key=key)
     else:
-        return ""
+        return "", "", ""
     progress(0, "Building Index...")
     docs._build_faiss_index()
     progress(0.25, "Querying...")
-    result = docs.query(question)
+    result = docs.query(question, length_prompt=f'use {slider:d} words')
     progress(1.0, "Done!")
-    return result.formatted_answer, result.context
+    # format the passages
+    passages = ""
+    for i, (key, passage) in enumerate(result.passages.items()):
+        passages += f'{i+1}. {key}\n\n```{passage}```\n\n'
+    return result.formatted_answer, result.context, passages
 
 
 with gr.Blocks() as demo:
@@ -86,6 +90,7 @@ with gr.Blocks() as demo:
                           uploaded_files], outputs=[dataset])
     query = gr.Textbox(
         placeholder="Enter your question here...", label="Question")
+    slider = gr.Slider(25, 200, value=100, step=5, label='answer length')
     ask = gr.Button("Ask Question")
     gr.Markdown("## Answer")
     answer = gr.Markdown(label="Answer")
@@ -93,8 +98,13 @@ with gr.Blocks() as demo:
         gr.Markdown(
             "### Context\n\nThe following context was used to generate the answer:")
         context = gr.Markdown(label="Context")
+
+    with gr.Accordion("Raw Text", open=False):
+        gr.Markdown(
+            "### Raw Text\n\nThe following raw text was used to generate the answer:")
+        passages = gr.Markdown(label="Passages")
     ask.click(fn=do_ask, inputs=[query, buildb,
-                                 openai_api_key, dataset], outputs=[answer, context])
+                                 openai_api_key, dataset, slider], outputs=[answer, context, passages])
 
 demo.queue(concurrency_count=20)
 demo.launch(show_error=True)