Create test_chat.py

test_chat.py

@@ -0,0 +1,70 @@
+import os
+
+# import random
+import time
+
+import gradio as gr
+
+# from langchain.schema import AIMessage, HumanMessage
+# from langchain_community.chat_models import ChatOpenAI
+
+
+# import openai
+
+
+os.environ["no_proxy"] = "localhost,127.0.0.1,::1"
+
+
+def print_like_dislike(x: gr.LikeData):
+    print(x.index, x.value, x.liked)
+
+
+def add_text(history, text):
+    history = history + [(text, None)]
+    return history, gr.Textbox(value="", interactive=False)
+
+
+def add_file(history, file):
+    history = history + [((file.name,), None)]
+    return history
+
+
+def bot(history):
+    response = "**That's cool!**"
+    history[-1][1] = ""
+    for character in response:
+        history[-1][1] += character
+        time.sleep(0.05)
+        yield history
+
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot(
+        [],
+        elem_id="chatbot",
+        bubble_full_width=False,
+        # avatar_images=(None, (os.path.join(os.path.dirname(__file__), "avatar.png"))),
+    )
+
+    with gr.Row():
+        txt = gr.Textbox(
+            scale=4,
+            show_label=False,
+            placeholder="Enter text and press enter, or upload an image",
+            container=False,
+        )
+        btn = gr.UploadButton("📁", file_types=["image", "video", "audio"])
+
+    txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
+        bot, chatbot, chatbot, api_name="bot_response"
+    )
+    txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
+    file_msg = btn.upload(add_file, [chatbot, btn], [chatbot], queue=False).then(
+        bot, chatbot, chatbot
+    )
+
+    chatbot.like(print_like_dislike, None, None)
+
+
+demo.queue()
+demo.launch()