first commit

.gitignore

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+.env
+__pycache__
+.DS*

README.md

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+# Temaplate Streamlit App for Haystack Search Pipelines
+
+In this repo you will find a template streamlit app set up for search applications.
+
+## Installation and Running
+To run the bare application which does _nothing_:
+1. Install requirements:
+`pip install -r requirements.txt`
+2. Run the streamlit app:
+`streamlit run app.py`
+3. Createa a `.env` and add your Twitter Bearer and OpenAI tokens:
+`TWITTER_BEARER_TOKEN` and `OPEN_AI_KEY`
+
+This will start up the app on `localhost:8501` where you will dind a simple search bar
+
+## What to edit:
+

app.py

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+
+from annotated_text import annotation
+from json import JSONDecodeError
+import logging
+from markdown import markdown
+
+import streamlit as st
+
+from utils.haystack import query
+from utils.ui import reset_results, set_initial_state
+
+set_initial_state()
+
+st.write("# What have they been tweeting about lately?")
+
+# Search bar
+username = st.text_input("", value=st.session_state.username, max_chars=100, on_change=reset_results)
+
+run_pressed = st.button("Run")
+
+run_query = (
+    run_pressed or username != st.session_state.username
+)
+
+# Get results for query
+if run_query and username:
+    reset_results()
+    st.session_state.username = username
+    with st.spinner("🔎"):
+        try:
+            st.session_state.result = query(username)
+        except JSONDecodeError as je:
+            st.error(
+                "👓    An error occurred reading the results. Is the document store working?"
+            )    
+        except Exception as e:
+            logging.exception(e)
+            st.error("🐞    An error occurred during the request.")
+        
+            
+
+if st.session_state.result:
+    voice = st.session_state.result
+    st.write(voice[0])
+        

requirements.txt

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+farm-haystack==1.13.0
+streamlit==1.10.0
+markdown
+st-annotated-text
+python-dotenv

utils/config.py

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+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+TWITTER_BEARER = os.getenv('TWITTER_BEARER_TOKEN')
+OEPN_AI_KEY = os.getenv('OPEN_AI_KEY')

utils/haystack.py

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+import streamlit as st
+import requests
+from utils.config import TWITTER_BEARER, OEPN_AI_KEY
+
+from haystack.nodes import PromptNode, PromptTemplate
+
+# cached to make index and models load only at start
+@st.cache(
+    hash_funcs={"builtins.SwigPyObject": lambda _: None}, allow_output_mutation=True
+)
+def start_haystack():
+    #Use this function to contruct a pipeline
+    prompt_node = PromptNode(model_name_or_path="text-davinci-003", api_key=OEPN_AI_KEY)
+
+    twitter_template = PromptTemplate(name="twitter-voice", prompt_text="""You will be given a twitter stream belonging to a specific profile. Tell us what they've lately been tweeting about and in what languages.
+                                                                    You may go into some detail about what topics they tend to like tweeting about. Please also mention their overall tone, for example: positive,
+                                                                    negative, political, sarcastic or something else.
+                                                                    
+                                                                    Example: 
+                                                                    
+                                                                    Twitter stream: Many people in our community asked how to utilize LLMs in their NLP pipelines and how to modify prompts for their tasks.…
+                                                                    RT @deepset_ai: We use parts of news articles from The Guardian as documents and create custom prompt templates to categorize these article
+                                                                    
+                                                                    Voice: This person has lately been tweeting about NLP and LLMs. Their tweets have been in Enlish
+                                                                    
+                                                                    Example: 
+                                                                    
+                                                                    Twitter stream: I've directed my team to set sharper rules on how we deal with unidentified objects.\n\nWe will inventory, improve ca… 
+                                                                    the incursion by China’s high-altitude balloon, we enhanced radar to pick up slower objects.\n \nBy doing so, w…
+                                                                    I gave an update on the United States’ response to recent aerial objects. 
+
+                                                                    Voice: This person has lately been tweeting about an unidentified object and an incursion by China with a high-altitude baloon.
+                                                                    They have been tweeting about the USA. They have had a political tone. They mostly post in English.
+
+                                                                    Twitter stream: $tweets.
+                                                                    
+                                                                    Voice:
+                                                                    """)
+    return prompt_node, twitter_template
+
+prompter, template = start_haystack()
+
+@st.cache(allow_output_mutation=True)
+def query(username):
+
+    bearer_token = TWITTER_BEARER
+
+    headers = {"Authorization": "Bearer {}".format(bearer_token)}
+
+    url = f"https://api.twitter.com/1.1/statuses/user_timeline.json?screen_name={username}&count={100}"
+    try:
+        response = requests.request("GET", url, headers = headers)
+        twitter_stream = ""
+        for tweet in response.json():
+            twitter_stream += (tweet["text"])
+        result = prompter.prompt(prompt_template=template, tweets=twitter_stream[0:4097])
+    except:
+        result = ["Please make sure you are providing a correct, public twitter accout"]
+    return result

utils/ui.py

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+import streamlit as st
+
+def set_state_if_absent(key, value):
+    if key not in st.session_state:
+        st.session_state[key] = value
+
+def set_initial_state():
+    set_state_if_absent("username", "Provide a Twitter username")
+    set_state_if_absent("result", None)
+
+def reset_results(*args):
+    st.session_state.results = None