Add basic demo UI via streamlit (#671)

* Added starter code for frontend demo

* worked on comments

* Added Docker config for frontend

* update docker file. restructure folder structure. minimal renamings and defaults

* add screenshot to readme

Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>

docker-compose.yml

@@ -1,4 +1,4 @@
-version: '3'
+version: "3"
 services:
   haystack-api:
     build:
@@ -27,10 +27,16 @@ services:
     command: "/bin/bash -c 'sleep 15 && gunicorn rest_api.application:app -b 0.0.0.0 -k uvicorn.workers.UvicornWorker --workers 1 --timeout 180 --preload'"
   elasticsearch:
     # This will start an empty elasticsearch instance (so you have to add your documents yourself)
-    image: "elasticsearch:7.6.1"
+    #image: "elasticsearch:7.6.1"
     # If you want a demo image instead that is "ready-to-query" with some indexed Game of Thrones articles:
-    #image: "deepset/elasticsearch-game-of-thrones"
+    image: "deepset/elasticsearch-game-of-thrones"
     ports:
       - 9200:9200
     environment:
-      - discovery.type=single-node
+      - discovery.type=single-node
+  ui:
+    image: "deepset/haystack-streamlit-ui"
+    ports:
+      - 8501:8501
+    environment:
+      - API_ENDPOINT=http://haystack-api:8000

ui/Dockerfile

@@ -0,0 +1,18 @@
+FROM python:3.7.4-stretch
+
+WORKDIR /home/user
+
+RUN apt-get update && apt-get install -y curl git pkg-config cmake
+
+# copy code
+COPY utils.py /home/user/
+COPY webapp.py /home/user/
+
+# install as a package
+COPY requirements.txt /home/user/
+RUN pip install -r requirements.txt
+
+EXPOSE 8501
+
+# cmd for running the API
+CMD ["streamlit", "run", "webapp.py"]

ui/README.md

@@ -0,0 +1,24 @@
+## Demo UI
+
+This is a minimal UI that can spin up to test Haystack for your prototypes. It's based on streamlit and is very easy to extend for your purposes. 
+
+![Screenshot](https://raw.githubusercontent.com/deepset-ai/haystack/master/docs/_src/img/streamlit_ui_screenshot.png)
+
+## Usage
+
+### Option 1: Local
+Execute in this folder:
+```
+streamlit run webapp.py
+```
+
+Requirements: This expects a running Haystack REST API at `http://localhost:8000`
+
+### Option 2: Container
+
+Just run
+```
+docker-compose up -d
+``` 
+in the root folder of the Haystack repository. This will start three containers (Elasticsearch, Haystack API, Haystack UI).
+You can find the UI at `http://localhost:8501`

ui/requirements.txt

@@ -0,0 +1,2 @@
+streamlit==0.72.0
+st-annotated-text==1.0.1

ui/utils.py

@@ -0,0 +1,42 @@
+import requests
+import streamlit as st
+import os
+
+API_ENDPOINT = os.getenv("API_ENDPOINT", "http://localhost:8000")
+MODEL_ID = "1"
+DOC_REQUEST = "doc-qa"
+
+def format_request(question,filters=None,top_k_reader=5,top_k_retriever=5):
+    if filters == None:
+        return {
+       "questions": [question],
+       "top_k_retriever": top_k_retriever,
+       "top_k_reader": top_k_reader
+       }
+    return {
+        "questions": [question],
+        "filters": {
+            "option1":[filters]
+        },
+        "top_k_retriever": top_k_retriever,
+        "top_k_reader": top_k_reader
+    }    
+ 
+@st.cache(show_spinner=False)
+def retrieve_doc(question,filters=None,top_k_reader=5,top_k_retriever=5):
+   # Query Haystack API
+   url = API_ENDPOINT +'/models/' + MODEL_ID + "/" + DOC_REQUEST
+   req = format_request(question,filters,top_k_reader=top_k_reader,top_k_retriever=top_k_retriever)
+   response_raw = requests.post(url,json=req).json()
+
+   # Format response
+   result = []
+   answers = response_raw['results'][0]['answers']
+   for i in range(top_k_reader):
+       answer = answers[i]['answer']
+       if answer:
+           context = '...' + answers[i]['context'] + '...'
+           meta_name = answers[i]['meta']['name']
+           relevance = round(answers[i]['probability']*100,2)
+           result.append({'context':context,'answer':answer,'source':meta_name,'relevance':relevance})
+   return result, response_raw

ui/webapp.py

@@ -0,0 +1,28 @@
+import streamlit as st
+from utils import retrieve_doc
+from annotated_text import annotated_text
+
+def annotate_answer(answer,context):
+    start_idx = context.find(answer)
+    end_idx = start_idx+len(answer)
+    annotated_text(context[:start_idx],(answer,"ANSWER","#8ef"),context[end_idx:])
+      
+st.write("# Haystack Demo")
+st.sidebar.header("Options")
+top_k_reader = st.sidebar.slider("Number of answers",min_value=1,max_value=10,value=5,step=1)
+top_k_retriever = st.sidebar.slider("Number of documents from retriever",min_value=1,max_value=10,value=3,step=1)
+question = st.text_input("Please provide your query:",value="Who is the father of Arya Starck?")
+run_query = st.button("Run")
+debug = st.sidebar.checkbox("Show debug info")
+if run_query:
+    with st.spinner("Performing neural search on documents... 🧠 \n "
+                    "Do you want to optimize speed or accuracy? \n"
+                    "Check out the docs: https://haystack.deepset.ai/docs/latest/optimizationmd "):
+        results,raw_json = retrieve_doc(question,top_k_reader=top_k_reader,top_k_retriever=top_k_retriever)
+    st.write("## Retrieved answers:")
+    for result in results:
+        annotate_answer(result['answer'],result['context'])
+        '**Relevance:** ', result['relevance'] , '**source:** ' , result['source']
+    if debug:
+        st.subheader('REST API JSON response')
+        st.write(raw_json)