Merge pull request #4 from beautiful-code/feature/add-streamlit-ui

agents/learning_profiler.py

@@ -12,7 +12,6 @@ learning_profiler = Agent(
       "The profile you build gives a high level overview of what interests that the user has. "
     ),
     allow_delegation=False,
-    OPENAI_API_KEY="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",
     llm=llm,
     step_callback=streamlit_callback
 )

app.py

@@ -9,9 +9,7 @@ from utils.write_to_json import write_dict_to_json as write_dict_to_json
 
 settings.init()
 
-load_dotenv(
-    "/home/quizra/Documents/Learning_practise/python/streamlit/growthi-app/growthy_agents/.env"
-)
+load_dotenv()
 
 
 def icon(emoji: str):

tasks/create_article_pitch.py

@@ -23,8 +23,8 @@ class PitchedArticles(BaseModel):
 
 
 def callback_function(output: TaskOutput):
-    # evaluated_articles = json.loads(output.exported_output)['articles']
-    # st.markdown(evaluated_articles)
+    evaluated_articles = json.loads(output.exported_output)['articles']
+    st.markdown(evaluated_articles)
     # for article in evaluated_articles:
     #     settings.articles[article['url']]['pitch'] = article['pitch']
     st.markdown("### Create Article Pitch is executed successfully!")

tasks/create_learning_profile.py

@@ -19,7 +19,12 @@ class LearningProfile(BaseModel):
     learnings: List[Topic]
     
 def callback_function(output: TaskOutput):
-    st.markdown("### Create Learning Profile task is executed successfully!")
+    st.markdown("### Learning profile of the user:")
+    data=json.loads(output.exported_output)
+    st.markdown(f"**topics_of_interests:** {data['topics_of_interests'][0]}")
+    st.markdown(f"**learnings:**")
+    for topic in data['learnings']:
+        st.markdown(f"*{topic['name']}*:{topic['insights'][0]}")
 
 learning_profile_task = Task(
     description=(

tasks/evaluate_articles.py

@@ -23,13 +23,13 @@ class EvaluatedArticles(BaseModel):
 
 
 def callback_function(output: TaskOutput):
-    # evaluated_articles = json.loads(output.exported_output)['articles']
+    evaluated_articles = json.loads(output.exported_output)['articles']
 
-    # for article in evaluated_articles:
-    #     settings.articles[article['url']
-    #                       ]['evaluation_score'] = article['evaluation_score']
-    #     settings.articles[article['url']
-    #                       ]['evaluation_reason'] = article['evaluation_reason']
+    for article in evaluated_articles:
+        settings.articles[article['url']
+                          ]['evaluation_score'] = article['evaluation_score']
+        settings.articles[article['url']
+                          ]['evaluation_reason'] = article['evaluation_reason']
     st.markdown("### Evaluate Articles task is executed successfully!")
 
 

tasks/new_article_suggestion.py

@@ -23,7 +23,6 @@ class SuggestedArticles(BaseModel):
 
 def callback_function(output: TaskOutput):
     suggested_articles = json.loads(output.exported_output)['articles']
-
     for article in suggested_articles:
         settings.articles[article['url']] = article
     st.markdown("### New Article Suggestion task is executed successfully!")