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add reaction handling; improve interaction;correct question extractio…
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…n; relates #30
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@mageirakos
mageirakos committed Mar 10, 2021
1 parent b0f4687 commit f88e5ef
Showing 1 changed file with 142 additions and 28 deletions.
170 changes: 142 additions & 28 deletions api/slackbot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,21 +19,21 @@
signing_secret=os.environ.get("SLACK_SIGNING_SECRET"),
)


@app.event("app_mention")
def mention_handler(body, say):
event = body["event"]
user_id = event["user"]
# TODO: regex to serach for <@id> and keep the rest
question = event["text"][2 + len(user_id) + 1 :] # <@donkeybot_id> <question>
slack_user_id = event["user"]
text = event["text"]
# find the mention pattern start, skip the `<@id>` and keep the rest as the question
question = text[text.find(f"<@")+2+len(slack_user_id)+1:].lstrip()
say(
{
"blocks": [
{
"type": "section",
"text": {
"type": "mrkdwn",
"text": f":wave:Hey there <@{user_id}>!\n\n*Where do you want me to look for the answer:*",
"text": f":wave:Hey there <@{slack_user_id}>!\n\n*Where do you want me to look for the answer:*",
},
},
{
Expand All @@ -42,7 +42,7 @@ def mention_handler(body, say):
{
"type": "button",
"text": {"type": "plain_text", "text": "FAQs"},
"value": f"{question}", # The value to send to handler along with the interaction payload. Maximum length for this field is 2000 characters.
"value": f"{question}",
"action_id": "faq_button",
},
{
Expand All @@ -66,38 +66,152 @@ def mention_handler(body, say):
def search_faqs(body, ack, say):
ack()
question = body["actions"][0]["value"].lstrip()
user_id = body["user"]["id"]
pprint(body)
answers = donkeybot.get_faq_answers(question, num_faqs=1, store_answers=False)
for answer in answers:
print()
pprint(answer.__dict__)
say(
f':scroll: <@{user_id}> regarding "{question}"\
\n Most similar FAQ: "{answer.metadata["most_similar_faq_question"]}"\
\n{answer.extended_answer}\
\n\n *How was the answer?* React once with :white_check_mark: or :x:'
)
slack_user_id = body["user"]["id"]
answers = donkeybot.get_faq_answers(question, num_faqs=1, store_answers=True)
assert len(answers) == 1
answer = answers[0]
most_similar_faq_question = answer.metadata["most_similar_faq_question"]
extended_answer = answer.extended_answer
answer_id = answer.id
say(
{
"blocks": [
{
"type": "section",
"text": {
"type": "mrkdwn",
"text": f":scroll: <@{slack_user_id}> regarding: _{question}_\nMost similar faq: _{most_similar_faq_question}_\n-{extended_answer}\n\n*How was the answer?*",
},
},
{
"type": "actions",
"elements": [
{
"type": "button",
"text": {
"type": "plain_text",
"text": ":white_check_mark:",
},
"value": f"{answer_id}",
"action_id": "correct_answer",
},
{
"type": "button",
"text": {"type": "plain_text", "text": ":x:"},
"value": f"{answer_id}",
"action_id": "wrong_answer",
},
],
},
]
}
)
return


@app.action("docs_button")
def search_docs(body, ack, say):
ack()
question = body["actions"][0]["value"].lstrip()
user_id = body["user"]["id"]
# pprint(body)
say(f'Okay :ok_hand: <@{user_id}>, please wait...')
answers = donkeybot.get_answers(question, top_k=1, store_answers=False)
slack_user_id = body["user"]["id"]
say(
f"Okay :ok_hand:<@{slack_user_id}>, searching Docs & GitHub issues. Please wait..."
)
answers = donkeybot.get_answers(question, top_k=1, store_answers=True)
# TODO: we probably don't need the loop if we just return 1 answer (unless we do some re-ranking)
# for now the bot is asked to generate a single answer
# re-ranking could be done insite the .get_answers method and here only get the "top 1" answer
for answer in answers:
print()
pprint(answer.__dict__)
extended_answer = answer.extended_answer
confidence = answer.confidence
origin = answer.origin
answer_id = answer.id
say(
f':scroll: <@{user_id}> regarding "{question}"\
\n{answer.extended_answer}\n Confidence: {answer.confidence}\
\n Source: {answer.origin}\
\n\n *How was the answer?* React once with :white_check_mark: or :x:'
{
"blocks": [
{
"type": "section",
"text": {
"type": "mrkdwn",
"text": f":scroll: <@{slack_user_id}> regarding _{question}_\n-{extended_answer}\nConfidence: {confidence}\nSource: {origin}\n\n*How was the answer?*",
},
},
{
"type": "actions",
"elements": [
{
"type": "button",
"text": {
"type": "plain_text",
"text": ":white_check_mark:",
},
"value": f"{answer_id}",
"action_id": "correct_answer",
},
{
"type": "button",
"text": {"type": "plain_text", "text": ":x:"},
"value": f"{answer_id}",
"action_id": "wrong_answer",
},
],
},
]
}
)

return

@app.action("correct_answer")
def label_correct(body, client, ack, say):
ack()
# remove negative if exist => substitute with positive
response = client.reactions_get(
channel=body["channel"]["id"], timestamp=body["message"]["ts"]
)
if "reactions" in response.data["message"]:
for reaction in response.data["message"]["reactions"]:
if reaction["name"] == "x":
client.reactions_remove(
channel=body["channel"]["id"],
timestamp=body["message"]["ts"],
name="x",
)

answer_id = body["actions"][0]["value"]
# 1 is the positive label
donkeybot.update_label(answer_id, label=1)

client.reactions_add(
channel=body["channel"]["id"],
timestamp=body["message"]["ts"],
name="white_check_mark",
)
return

@app.action("wrong_answer")
def label_wrong(body, client, ack, say):
ack()
# remove positive if exist => substitute with negative
response = client.reactions_get(
channel=body["channel"]["id"], timestamp=body["message"]["ts"]
)
if "reactions" in response.data["message"]:
for reaction in response.data["message"]["reactions"]:
if reaction["name"] == "white_check_mark":
client.reactions_remove(
channel=body["channel"]["id"],
timestamp=body["message"]["ts"],
name="white_check_mark",
)

answer_id = body["actions"][0]["value"]
# 0 is the negative label
donkeybot.update_label(answer_id, label=0)

client.reactions_add(
channel=body["channel"]["id"], timestamp=body["message"]["ts"], name="x"
)
return


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