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import os
import gradio as gr
from langgraph_sdk import get_client
from langchain_core.messages import HumanMessage, SystemMessage, AIMessage
from langsmith import Client
import asyncio
import logging
LANGGRAPH_DEPLOYMENT = "https://le-chat-bottes-08847786c41355da87302fa1e0f41f4a.us.langgraph.app/"
client = get_client(url=LANGGRAPH_DEPLOYMENT)
langsmith_client = Client()
async def log_feedback(run_id, score, comment=""):
"""Log feedback to LangSmith"""
try:
langsmith_client.create_feedback(
run_id=run_id,
key="user_feedback",
score=score,
comment=comment
)
logging.info(f"Successfully logged feedback for run_id: {run_id} with score: {score}")
return True
except Exception as e:
logging.error(f"Error logging feedback for run_id: {run_id}: {e}")
return False
async def respond(message, history, thread_state):
assistants = await client.assistants.search(
graph_id="retrieval_graph", metadata={"created_by": "system"}
)
if not thread_state:
thread = await client.threads.create()
thread_state = thread["thread_id"]
response = ""
run_id = None
async for chunk in client.runs.stream(
thread_id=thread_state,
assistant_id=assistants[0]["assistant_id"],
input={"messages": message},
stream_mode="events",
):
if chunk.event == "events":
if chunk.data["event"] == "on_chat_model_stream":
if run_id is None and "run_id" in chunk.data:
run_id = chunk.data["run_id"]
token = chunk.data["data"]["chunk"]["content"]
response += token
yield [
*history,
{"role": "user", "content": message},
{"role": "assistant", "content": response}
], thread_state, run_id
def clear_conversation():
return [], None, gr.update(visible=False)
with gr.Blocks(theme=gr.themes.Soft(), css="""
h1 {
text-align: center;
}
img {
margin: 0 !important;
}
.feedback-card {
border: 1px solid #e0e0e0;
border-radius: 8px;
padding: 16px;
margin-top: 12px;
}
.feedback-buttons {
gap: 8px;
}
.selected-thumb {
background: #e0e0e0 !important;
border-color: #4CAF50 !important;
}
.examples .example {
background: #f0f0f0;
padding: 10px;
margin: 5px;
border-radius: 5px;
cursor: pointer;
}
.examples .example:hover {
background: #e0e0e0;
}
""") as demo:
with gr.Column():
with gr.Row():
with gr.Column(scale=9):
gr.Markdown("# Le Chat Bottes 👢😺👢")
chatbot = gr.Chatbot(
height=640,
avatar_images=(
"https://em-content.zobj.net/source/microsoft-teams/337/farmer_1f9d1-200d-1f33e.png",
"https://em-content.zobj.net/source/microsoft-teams/363/robot_1f916.png"
),
show_label=False,
bubble_full_width=False,
container=False,
type="messages"
)
with gr.Column(visible=False) as feedback_card:
with gr.Row():
thumbs_up = gr.Button("👍", elem_classes="feedback-btn")
thumbs_down = gr.Button("👎", elem_classes="feedback-btn")
with gr.Row(visible=False) as feedback_input_row:
feedback_comment = gr.Textbox(
placeholder="Commentaire (optionnel)",
show_label=False,
scale=3
)
feedback_send_btn = gr.Button("Envoyer", scale=1)
thank_you_message = gr.HTML(
"<div style='color: #4CAF50; margin-top: 8px;'>Merci pour votre retour !</div>",
visible=False
)
with gr.Row():
txt = gr.Textbox(
placeholder="Posez votre question ici...",
show_label=False,
container=False,
scale=7,
autofocus=True,
max_lines=3,
)
submit_btn = gr.Button("Envoyer", scale=1)
with gr.Row():
gr.Examples(
examples=[
"Comment stocker l'eau de pluie sur une exploitation agricole ?",
"Quelles rotations culturales favorisent l'adaptation climatique ?",
"Comment réduire l'impact du gel printanier sur les vignes ?"
],
inputs=txt,
label=""
)
feedback_alert = gr.HTML(visible=False)
thread_state = gr.State()
current_run_id = gr.State()
selected_thumb = gr.State()
txt.submit(
respond,
[txt, chatbot, thread_state],
[chatbot, thread_state, current_run_id],
api_name=False
).then(
lambda: ("", gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True)),
None,
[txt, feedback_card, thank_you_message, thumbs_up, thumbs_down]
)
submit_btn.click(
respond,
[txt, chatbot, thread_state],
[chatbot, thread_state, current_run_id],
api_name=False
).then(
lambda: ("", gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True)),
None,
[txt, feedback_card, thank_you_message, thumbs_up, thumbs_down]
)
def show_feedback_input(thumb):
return (
gr.update(visible=True), # feedback_input_row
thumb, # selected_thumb
gr.update(visible=False), # thumbs_up
gr.update(visible=False) # thumbs_down
)
thumbs_up.click(
show_feedback_input,
inputs=[gr.Number(1, visible=False)],
outputs=[feedback_input_row, selected_thumb, thumbs_up, thumbs_down]
)
thumbs_down.click(
show_feedback_input,
inputs=[gr.Number(0, visible=False)],
outputs=[feedback_input_row, selected_thumb, thumbs_up, thumbs_down]
)
def submit_feedback(run_id, score, comment):
asyncio.run(log_feedback(run_id, score, comment))
return (
gr.update(visible=True), # thank_you_message
gr.update(value=""), # feedback_comment
gr.update(visible=False), # feedback_input_row
gr.update(visible=False), # thumbs_up
gr.update(visible=False) # thumbs_down
)
feedback_send_btn.click(
submit_feedback,
[current_run_id, selected_thumb, feedback_comment],
[thank_you_message, feedback_comment, feedback_input_row, thumbs_up, thumbs_down]
)
feedback_comment.submit(
submit_feedback,
[current_run_id, selected_thumb, feedback_comment],
[thank_you_message, feedback_comment, feedback_input_row, thumbs_up, thumbs_down]
)
if __name__ == "__main__":
demo.launch(share=True)
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