Description
A web search server for ParlAI, including Blenderbot2.
The server reacting correctly:
- Uses
html2text
to strip the markup out of the page. - Uses
beautifulsoup4
to parse the title. - Currently only uses the
googlesearch
module to query Google for urls, but is coded in a modular / search engine agnostic way to allow very easily add new search engine support.
Using the googlesearch
module is very slow because it parses webpages instead of querying webservices. This is fine for playing with the model, but makes that searcher unusable for training or large scale inference purposes.
To be able to train, one would just have to for example pay for Google Cloud or Microsoft Azure's search services, and derive the Search class to query them.
Quick Start:
First install the requirements:
pip install -r requirements.txt
Run this command in one terminal tab:
python search_server.py serve --host 0.0.0.0:8080
[Optional] You can then test the server with
curl -X POST "http://0.0.0.0:8080" -d "q=baseball&n=1"
Then for example start Blenderbot2 in a different terminal tab:
python -m parlai interactive --model-file zoo:blenderbot2/blenderbot2_3B/model --search_server 0.0.0.0:8080
Colab
There is a jupyter notebook. Just run it. Some instances run out of memory, some don't.
Testing the server:
You need to already be running a server by calling serve on the same hostname and ip. This will create a parlai.agents.rag.retrieve_api.SearchEngineRetriever and try to connect and send a query, and parse the answer.
python search_server.py test_server --host 0.0.0.0:8080
Testing the parser:
python search_server.py test_parser www.some_url_of_your_choice.com/