Files
chatwoot/enterprise/app/jobs/response_builder_job.rb
Sojan Jose 480f34803b feat: Response Bot using GPT and Webpage Sources (#7518)
This commit introduces the ability to associate response sources to an inbox, allowing external webpages to be parsed by Chatwoot. The parsed data is converted into embeddings for use with GPT models when managing customer queries.

The implementation relies on the `pgvector` extension for PostgreSQL. Database migrations related to this feature are handled separately by `Features::ResponseBotService`. A future update will integrate these migrations into the default rails migrations, once compatibility with Postgres extensions across all self-hosted installation options is confirmed.

Additionally, a new GitHub action has been added to the CI pipeline to ensure the execution of specs related to this feature.
2023-07-21 18:11:51 +03:00

77 lines
2.0 KiB
Ruby

class ResponseBuilderJob < ApplicationJob
queue_as :default
def perform(response_document)
reset_previous_responses(response_document)
data = prepare_data(response_document)
response = post_request(data)
create_responses(response, response_document)
end
private
def reset_previous_responses(response_document)
response_document.responses.destroy_all
end
def prepare_data(response_document)
{
model: 'gpt-3.5-turbo',
messages: [
{
role: 'system',
content: system_message_content
},
{
role: 'user',
content: response_document.content
}
]
}
end
def system_message_content
<<~SYSTEM_MESSAGE_CONTENT
You are a content writer looking to convert user content into short FAQs which can be added to your website's helper centre.
Format the webpage content provided in the message to FAQ format like the following example.#{' '}
Ensure that you only generate faqs from the information provider in the message.#{' '}
Ensure that output is always valid json.#{' '}
If no match is available, return an empty JSON.
```
[ { "question": "What is the pricing?",
"answer" : " There are different pricing tiers available."
}]
```
SYSTEM_MESSAGE_CONTENT
end
def post_request(data)
headers = prepare_headers
HTTParty.post(
'https://api.openai.com/v1/chat/completions',
headers: headers,
body: data.to_json
)
end
def prepare_headers
{
'Content-Type' => 'application/json',
'Authorization' => "Bearer #{ENV.fetch('OPENAI_API_KEY')}"
}
end
def create_responses(response, response_document)
response_body = JSON.parse(response.body)
faqs = JSON.parse(response_body['choices'][0]['message']['content'].strip)
faqs.each do |faq|
response_document.responses.create!(
question: faq['question'],
answer: faq['answer'],
account_id: response_document.account_id
)
end
end
end