port to 2.0

README.md

@@ -17,22 +17,22 @@ pinned: false
 ##### A simple app to get an overview of what the Mastodon user has been posting about and their tone
 
 This is a demo just for fun 🥳
-This repo contains a streamlit application that given a Mastodon username, tells you what type of things they've been posting about lately, their tone, and the languages they use. It uses the LLM by OpenAI `text-davinci-003`.
+This repo contains a streamlit application that given a Mastodon username, tells you what type of things they've been posting about lately, their tone, and the languages they use. It uses the LLM by OpenAI `gpt-4`.
 
-It's been built with [Haystack](https://haystack.deepset.ai) using the [`PromptNode`](https://docs.haystack.deepset.ai/docs/prompt_node) and by creating a custom [`PromptTemplate`](https://docs.haystack.deepset.ai/docs/prompt_node#templates)
+It's been built with [Haystack](https://haystack.deepset.ai) using the [`OpenAIGenerator`](https://docs.haystack.deepset.ai/v2.0/docs/openaigenerator) and by creating a [`PromptBuilder`](https://docs.haystack.deepset.ai/v2.0/docs/promptbuilder)
 
 https://user-images.githubusercontent.com/15802862/220464834-f42c038d-54b4-4d5e-8d59-30d95143b616.mov
 
 
 ### Points of improvement
 
-Since we're using a generative model here, we need to be a bit creative with the prompt we provide it to minimize any hallucination or similar unwanted results. For this reason, I've tried to be a bit creative with the `PromptTemplate` and give some examples of _how_ to construct a summary. However, this still sometimes produces odd results.
+Since we're using a generative model here, we need to be a bit creative with the prompt we provide it to minimize any hallucination or similar unwanted results. For this reason, I've tried to be a bit creative with the `PromptBuilder` template and give some examples of _how_ to construct a summary. However, this still sometimes produces odd results.
 
 If you try to run it yourself and find ways to make this app better, please feel free to create an issue/PR 🙌
 
-## To learn more about the PromptNode
+## To learn more about the PromptBuilder
 
-Check out our tutorial on the PromptNode and how to create your own templates [here](https://haystack.deepset.ai/tutorials/21_customizing_promptnode)
+As of Haystack 2.0-Beta onwards, you can create prompt templates with Jinja. Check out guide on creating prompts [here](https://docs.haystack.deepset.ai/v2.0/docs/promptbuilder)
 
 ## Installation and Running
 To run the bare application which does _nothing_:

app.py

@@ -54,5 +54,5 @@ if st.session_state.get("api_key_configured"):
                 
     if st.session_state.result:
         voice = st.session_state.result
-        st.write(voice['results'][0])
+        st.write(voice[0])
             

requirements.txt

@@ -1,7 +1,6 @@
-safetensors==0.3.3.post1
-farm-haystack==1.20.0
+haystack-ai==2.0.0b4
 streamlit==1.21.0
 markdown
 st-annotated-text
 python-dotenv
-mastodon-fetcher-haystack==0.0.1
+mastodon-fetcher-haystack

utils/haystack.py

@@ -1,51 +1,61 @@
 import streamlit as st
 from mastodon_fetcher_haystack.mastodon_fetcher import MastodonFetcher
 from haystack import Pipeline
-from haystack.nodes import PromptNode, PromptTemplate
+from haystack.components.generators import OpenAIGenerator
+from haystack.components.builders import PromptBuilder
 
 def start_haystack(openai_key):
     #Use this function to contruct a pipeline
     fetcher = MastodonFetcher()
 
-    mastodon_template = PromptTemplate(prompt="""You will be given a post stream belonging to a specific Mastodon profile. Answer with a summary of what they've lately been posting about and in what languages.
-                                                You may go into some detail about what topics they tend to like postint about. Please also mention their overall tone, for example: positive,
-                                                negative, political, sarcastic or something else.
-
-                                                Examples: 
-                                                
-                                                Post stream: [@deepset_ai](https://mastodon.social/@deepset_ai): Come join our Haystack server for our first Discord event tomorrow, a deepset AMA session with @rusic_milos @malte_pietsch…
-                                                [@deepset_ai](https://mastodon.social/@deepset_ai): Join us for a chat! On Thursday 25th we are hosting a 'deepset - Ask Me Anything' session on our brand new Discord. Come…
-                                                [@deepset_ai](https://mastodon.social/@deepset_ai): Curious about how you can use @OpenAI GPT3 in a Haystack pipeline? This week we released Haystack 1.7 with which we introdu…
-                                                [@deepset_ai](https://mastodon.social/@deepset_ai): So many updates from @deepset_ai today! 
-                                                
-                                                Summary: This user has lately been reposting posts from @deepset_ai. The topics of the posts have been around the Haystack community, NLP and GPT. They've
-                                                been posting in English, and have had a positive, informative tone.
-                                                
-                                                Post 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. 
-
-                                                Summary: This user has lately been posting about having sharper rules to deal with unidentified objects and an incursuin by China's high-altitude
-                                                baloon. Their pots have mostly been neutral but determined in tone. They mostly post in English.
-
-                                                Post stream: {join(documents)}
-                                                                
-                                                Summary: 
-                                                """)
-    prompt_node = PromptNode(model_name_or_path="gpt-4", default_prompt_template=mastodon_template, api_key=openai_key)
+    mastodon_template = """You will be given a post stream belonging to a specific Mastodon profile. Answer with a summary of what they've lately been posting about and in what languages.
+                            You may go into some detail about what topics they tend to like postint about. Please also mention their overall tone, for example: positive,
+                            negative, political, sarcastic or something else.
+
+                            Examples: 
+                            
+                            Post stream: [@deepset_ai](https://mastodon.social/@deepset_ai): Come join our Haystack server for our first Discord event tomorrow, a deepset AMA session with @rusic_milos @malte_pietsch…
+                            [@deepset_ai](https://mastodon.social/@deepset_ai): Join us for a chat! On Thursday 25th we are hosting a 'deepset - Ask Me Anything' session on our brand new Discord. Come…
+                            [@deepset_ai](https://mastodon.social/@deepset_ai): Curious about how you can use @OpenAI GPT3 in a Haystack pipeline? This week we released Haystack 1.7 with which we introdu…
+                            [@deepset_ai](https://mastodon.social/@deepset_ai): So many updates from @deepset_ai today! 
+                            
+                            Summary: This user has lately been reposting posts from @deepset_ai. The topics of the posts have been around the Haystack community, NLP and GPT. They've
+                            been posting in English, and have had a positive, informative tone.
+                            
+                            Post 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. 
+
+                            Summary: This user has lately been posting about having sharper rules to deal with unidentified objects and an incursuin by China's high-altitude
+                            baloon. Their pots have mostly been neutral but determined in tone. They mostly post in English.
+
+                            Post stream: {{ documents }}
+                                            
+                            Summary: 
+                            """
+    prompt_builder = PromptBuilder(template=mastodon_template)
+    llm = OpenAIGenerator(model_name="gpt-4", api_key=openai_key)
 
     st.session_state["haystack_started"] = True   
 
     mastodon_pipeline = Pipeline()
-    mastodon_pipeline.add_node(component=fetcher, name="MastodonFetcher", inputs=["Query"])
-    mastodon_pipeline.add_node(component=prompt_node, name="PromptNode", inputs=["MastodonFetcher"])                                               
+    mastodon_pipeline.add_component("fetcher", fetcher)
+    mastodon_pipeline.add_component("prompt_builder", prompt_builder)
+    mastodon_pipeline.add_component("llm", llm)
+
+
+    mastodon_pipeline.connect("fetcher.documents", "prompt_builder.documents")
+    mastodon_pipeline.connect("prompt_builder.prompt", "llm.prompt")
+
     return mastodon_pipeline
 
 
 @st.cache_data(show_spinner=True)
 def query(username, _pipeline):
     try:
-        result = _pipeline.run(query=username, params={"MastodonFetcher": {"last_k_posts": 20}})
+        replies = _pipeline.run(data={"fetcher": {"username": username,
+                                                 "last_k_posts": 20}})
+        result = replies['llm']['replies']
     except Exception as e:
         result = ["Please make sure you are providing a correct, public Mastodon account"]
     return result

utils/ui.py

@@ -46,8 +46,8 @@ def sidebar():
         st.markdown("---")
         st.markdown(
             "## How this works\n"
-            "This app was built with [Haystack](https://haystack.deepset.ai) using the"
-            " [`PromptNode`](https://docs.haystack.deepset.ai/docs/prompt_node) and custom [`PromptTemplate`](https://docs.haystack.deepset.ai/docs/prompt_node#templates).\n\n"
+            "This app was built with [Haystack 2.0-Beta](https://haystack.deepset.ai) using the"
+            " [`OpenAIGenerator`](https://docs.haystack.deepset.ai/v2.0/docs/openaigenerator) and [`PromptBuilder`](https://docs.haystack.deepset.ai/v2.0/docs/promptbuilder).\n\n"
             " The source code is also on [GitHub](https://github.com/TuanaCelik/should-i-follow)"
             " with instructions to run locally.\n"
             "You can see how the `PromptNode` was set up [here](https://github.com/TuanaCelik/should-i-follow/blob/main/utils/haystack.py)")