Copy lesson_plan_streamlit_prototype.py from Github

lesson_plan_streamlit_prototype.py

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+import streamlit as st
+import openai
+
+# Streamlit Session State
+if 'learning_objectives' not in st.session_state:
+    st.session_state.learning_objectives = ""
+
+# Streamlit User Input Form
+st.title("Lesson Plan Generator")
+
+# API Key Input
+api_key = st.text_input("Enter your OpenAI API Key:", type="password")
+
+# Model Selection Dropdown
+model_choice = st.selectbox(
+    "Select the model you want to use:",
+    ["gpt-3.5-turbo-0301", "gpt-3.5-turbo-0613", "gpt-3.5-turbo", "gpt-4-0314", "gpt-4-0613", "gpt-4"]
+)
+
+# Context, Subject, and Level
+context = "Your goal is to create an effective lesson plan."
+subject = st.text_input("Subject:", "Mathematics")
+level = st.text_input("Education Level:", "High School")
+
+# Initialize OpenAI API
+if api_key:
+    openai.api_key = api_key
+
+# Learning Objectives
+st.write("### Learning Objectives:")
+# Initialize autogenerated objectives
+autogenerated_objectives = ""
+# Initialize status placeholder
+learning_status_placeholder = st.empty()
+disable_button_bool = False
+if subject and level and api_key and st.button("Generate Learning Objectives",key="generate_learning_objectives",disabled=disable_button_bool):
+
+    # Display status message
+    learning_status_placeholder.text("Generating learning objectives...")
+    # API call to generate objectives
+    learning_objectives_response = openai.ChatCompletion.create(
+        model=model_choice,
+        messages=[
+            {"role": "user", "content": f"Generate learning objectives for a {level} level {subject} lesson."}
+        ]
+    )
+    # Extract the generated objectives from the API response
+    learning_objectives=learning_objectives_response['choices'][0]['message']['content']
+    
+    # Save generated objectives to session state
+    st.session_state.learning_objectives = learning_objectives.strip()
+    
+    # Display generated objectives
+    learning_status_placeholder.text(f"Learning objectives generated!\n{learning_objectives.strip()}")
+    
+# Generate Lesson Plan Button
+if st.button("Generate Lesson Plan") and api_key:
+    
+    # Construct the prompt as a dictionary
+    prompt_dict = {
+        "context": context,
+        "subject": subject,
+        "level": level,
+        "learning_objectives": st.session_state.learning_objectives,
+        "tasks": [
+            {"task": "Curate educational material", "objective": "To provide accurate and relevant information"},
+            {"task": "Evaluate the material", "objective": "To ensure alignment with educational standards"},
+            {"task": "Create assessment tools", "objective": "To measure student understanding and retention"},
+            {"task": "Design interactive activities", "objective": "To facilitate active learning and engagement"}
+        ],
+        "output_format": """Present the lesson plan in a structured format.
+        \nTitle: 
+        \nGrade Level: RESTATED FROM ABOVE
+        \nSubject:  RESTATED FROM ABOVE
+        \nObjectives: RESTATED FROM ABOVE
+        \nActivities: 
+        \nAssessment: Application of knowledge and skills through a task
+        \nProcedure: Formatted as a list of steps and substeps
+        \nResources:
+        \nNotes:
+        
+        """
+    }
+    
+    # Convert the dictionary to a string
+    prompt_str = str(prompt_dict)
+
+    # API call to generate the lesson plan
+    lesson_plan_response = openai.ChatCompletion.create(
+        model=model_choice,
+        messages=[
+            {"role": "user", "content": f"Create a lesson plan based on the following parameters: {prompt_str}"}
+        ]
+    )
+
+    # Display status message
+    lesson_plan=st.text("Generating lesson plan...")
+
+    # Extract and display the lesson plan
+    assistant_reply = lesson_plan_response['choices'][0]['message']['content']
+    lesson_plan=st.text(assistant_reply.strip())