remove pagination, update readme

Author: asabya

README.md

@@ -1,8 +1,6 @@
-## w3kipedia
+## zwi-fave
 
-[w3kipedia](https://github.com/onepeerlabs/w3kipedia) was originally a try to participate for the [WAM](https://www.wearemillions.online/) hackathon for a better wikipedia on swarm.
-
-Now [w3kipedia-fave](https://github.com/onepeerlabs/w3kipedia-fave) is a modified version of w3kipedia that uses FaVe to store, index and search the content.
+This project uses FaVe and fairdatasociety/huggingface-vectorizer to index, store and search zwi files content.
 
 It has two components
 
@@ -14,8 +12,6 @@ It has two components
 
 Server will start a http-server that can fetch content from FaVe and display them in the web browser.  
 
-
-
 ### How to serve?
 
 ```
@@ -25,7 +21,7 @@ go build
 
 Docker:
 ```
-docker build -f  Dockerfile.server --tag w3ki-server .
+docker build -f  Dockerfile.server --tag zwi-fave-server .
 ```
 
 #### Help :
@@ -43,7 +39,7 @@ Usage of ./server:
 
 Docker:
 ```
-docker run w3ki-server -h
+docker run zwi-fave-server -h
 ```
 
 
@@ -58,20 +54,75 @@ Docker:
 ```
 docker run \
     -p 8080:8080 \
-    w3ki-server -fave=<FAVE_API_ENDPOINT> -collection=<COLLECTION_NAME>
+    zwi-fave-server -fave=<FAVE_API_ENDPOINT> -collection=<COLLECTION_NAME>
 ```
 
-This will start a local http-serve which will serve wikipedia content on port `:8080`. 
+This will start a local http-serve which will serve wikipedia content on port `:8080`.
 
-#### How Indexer works:
+this project [uses code](https://github.com/akhenakh/gozim/blob) that is [MIT licensed](https://github.com/akhenakh/gozim/blob/master/LICENSE)
 
-Indexer uses [FaVe](https://github.com/fairDataSociety/FaVe) to store content and index them for doing semantic search. It is sanitizing the Article content and vectorizing it to do FaVe Nearest Neighbour Search. 
+### Docker Compose
 
-#### How Server works:
+Best way to run the server is to use a single docker-compose file that will start vectorizer, FaVe and the server.
 
-Server lists all the items in the server with "text/html" mimetype. 
+Copy the following docker-compose file and save it as `docker-compose.yml` in a directory.
+```
+version: '3'
+services:
+  vectorizer:
+    command:
+      - --model-name
+      - sentence-transformers/all-mpnet-base-v2
+    image: fairdatasociety/huggingface-vectorizer:latest
+    ports:
+      - 9876:9876
+    restart: on-failure:0
+
+  fave:
+    command:
+      - --host
+      - 0.0.0.0
+      - --port
+      - '1234'
+      - --write-timeout
+      - 1500m
+      - --read-timeout
+      - 1500m
+    image: fairdatasociety/fave:latest
+    ports:
+      - 1234:1234
+    restart: on-failure:0
+    environment:
+      BEE_API: <BEE_URL>
+      RPC_API: <RPC_ENDPOINT_FOR_ENS>
+      STAMP_ID: 0
+      USER: <USER_NAME>
+      PASSWORD: <PASSWORD>
+      POD: <POD_NAME>
+      VECTORIZER_URL: http://vectorizer:9876
+      VERBOSE: true
+  zwi-fave:
+    command:
+      - -collection
+      - <COLLECTION_NAME>
+      - -port
+      - '8526'
+      - -fave
+      - http://fave:1234/v1
+    image: fairdatasociety/zwi-fave:latest
+    ports:
+      - 8526:8526
+    restart: on-failure:0
+```
 
-For showing the content it checks "GET" request on "/wiki/XXXX". it reads the "XXXX" relative url, then finds the entry for that item in the FaVe/FairOS-dfs document store,
-downloads the content and sends it back as response.
+Change the environment variables to match your setup.
+```
+BEE_API: <BEE_URL> # Bee api endpoint (Make sure to use local ip (e.g. 192.168.x.x), not "localhost" or "127.0.0.1")
+RPC_API: <RPC_ENDPOINT_FOR_ENS> # This is for fairOS-dfs to authenticate with ENS
+USER: <USER_NAME> # FairOS-dfs user name
+PASSWORD: <PASSWORD> # FairOS-dfs password
+POD: <POD_NAME> # FairOS-dfs pod name to store content
+COLLECTION_NAME: <COLLECTION_NAME> # Collection name to store content on FaVe
+```
 
-this project [uses code](https://github.com/akhenakh/gozim/blob) that is [MIT licensed](https://github.com/akhenakh/gozim/blob/master/LICENSE)
+Then run `docker-compose up` to start the server. The server should be available on port `:8526`.

cmd/server/templates/searchResult.html

@@ -70,19 +70,6 @@
      {{end}}
     </div> <!-- /container -->
 
-    <div id="footer">
-      <div class="container">
-        <ul class="pager">
-            <li class="previous">
-                <a href="/search/?search_data={{ .Query }}&page={{ .PreviousPage }}">← Previous</a>
-            </li>
-            <li class="next">
-                <a href="/search/?search_data={{ .Query }}&page={{ .NextPage }}">Next →</a>
-            </li>
-        </ul>
-      </div>
-    </div>
-
     <script src="/static/js/jquery.min.js"></script>
     <script src="/static/js/bootstrap.min.js"></script>
 

docker-compose.yaml

@@ -0,0 +1,46 @@
+version: '3'
+services:
+  vectorizer:
+    command:
+      - --model-name
+      - sentence-transformers/all-mpnet-base-v2
+    image: fairdatasociety/huggingface-vectorizer:latest
+    ports:
+      - 9876:9876
+    restart: on-failure:0
+
+  fave:
+    command:
+      - --host
+      - 0.0.0.0
+      - --port
+      - '1234'
+      - --write-timeout
+      - 1500m
+      - --read-timeout
+      - 1500m
+    image: fairdatasociety/fave:latest
+    ports:
+      - 1234:1234
+    restart: on-failure:0
+    environment:
+      BEE_API: <BEE_URL>
+      RPC_API: <RPC_ENDPOINT_FOR_ENS>
+      STAMP_ID: <STAMP_ID>
+      USER: <USER_NAME>
+      PASSWORD: <PASSWORD>
+      POD: <POD_NAME>
+      VECTORIZER_URL: http://vectorizer:9876
+      VERBOSE: true
+  zwi-fave:
+    command:
+      - -collection
+      - <COLLECTION_NAME>
+      - -port
+      - '8526'
+      - -fave
+      - http://fave:1234/v1
+    image: fairdatasociety/zwi-fave:latest
+    ports:
+      - 8526:8526
+    restart: on-failure:0