Add dedicated information panel to the UI (#137)

* Allow streaming to the chatbot and the information panel without threading
* Highlight evidence in a simple manner

libs/ktem/ktem/pages/chat/__init__.py

@@ -23,6 +23,9 @@ class ChatPage(BasePage):
                 self.report_issue = ReportIssue(self._app)
             with gr.Column(scale=6):
                 self.chat_panel = ChatPanel(self._app)
+            with gr.Column(scale=3):
+                with gr.Accordion(label="Information panel", open=True):
+                    self.info_panel = gr.Markdown(elem_id="chat-info-panel")
 
     def on_register_events(self):
         self.chat_panel.submit_btn.click(
@@ -33,7 +36,11 @@ class ChatPage(BasePage):
                 self.data_source.files,
                 self._app.settings_state,
             ],
-            outputs=[self.chat_panel.text_input, self.chat_panel.chatbot],
+            outputs=[
+                self.chat_panel.text_input,
+                self.chat_panel.chatbot,
+                self.info_panel,
+            ],
         ).then(
             fn=update_data_source,
             inputs=[
@@ -52,7 +59,11 @@ class ChatPage(BasePage):
                 self.data_source.files,
                 self._app.settings_state,
             ],
-            outputs=[self.chat_panel.text_input, self.chat_panel.chatbot],
+            outputs=[
+                self.chat_panel.text_input,
+                self.chat_panel.chatbot,
+                self.info_panel,
+            ],
         ).then(
             fn=update_data_source,
             inputs=[

libs/ktem/ktem/pages/chat/events.py

@@ -1,3 +1,4 @@
+import asyncio
 import os
 import tempfile
 from copy import deepcopy
@@ -116,24 +117,33 @@ def create_pipeline(settings: dict, files: Optional[list] = None):
     return pipeline
 
 
-def chat_fn(chat_input, chat_history, files, settings):
+async def chat_fn(chat_input, chat_history, files, settings):
+    """Chat function"""
+    queue: asyncio.Queue[Optional[dict]] = asyncio.Queue()
+
+    # construct the pipeline
     pipeline = create_pipeline(settings, files)
+    pipeline.set_output_queue(queue)
 
-    text = ""
-    refs = []
-    for response in pipeline(chat_input):
-        if response.metadata.get("citation", None):
-            citation = response.metadata["citation"]
-            for idx, fact_with_evidence in enumerate(citation.answer):
-                quotes = fact_with_evidence.substring_quote
-                if quotes:
-                    refs.append(
-                        (None, f"***Reference {idx+1}***: {' ... '.join(quotes)}")
-                    )
-        else:
-            text += response.text
+    asyncio.create_task(pipeline(chat_input))
+    text, refs = "", ""
 
-        yield "", chat_history + [(chat_input, text)] + refs
+    while True:
+        try:
+            response = queue.get_nowait()
+        except Exception:
+            await asyncio.sleep(0)
+            continue
+
+        if response is None:
+            break
+
+        if "output" in response:
+            text += response["output"]
+        if "evidence" in response:
+            refs += response["evidence"]
+
+        yield "", chat_history + [(chat_input, text)], refs
 
 
 def is_liked(convo_id, liked: gr.LikeData):