Updated layout.

app/gradio_sample_generator.py

@@ -1,5 +1,6 @@
+import json
 import gradio as gr
-from langchain_community.chat_models import ChatOpenAI
+from langchain_openai import ChatOpenAI
 from meta_prompt.sample_generator import TaskDescriptionGenerator
 
 def process_json(input_json, model_name, generating_batch_size, temperature):

app/streamlit_tab_app.py

@@ -487,6 +487,10 @@ def generate_callback():
     except Exception as e:
         st.error(f"Error: {e}")
 
+def clear_advanced_inputs():
+    st.session_state.initial_system_message = ""
+    st.session_state.initial_acceptance_criteria = ""
+
 # Meta Prompt Config
 
 pre_config_sources = [
@@ -605,7 +609,10 @@ with tab_prompting:
     st.markdown("Generate the prompt with the above input-output pairs.")
 
     # Create options for the selectbox
-    sample_options = [f"Sample {i}: {row['Input'][:30]}..." for i, row in data_editor_data.iterrows()]
+    try:
+        sample_options = [f"Sample {i}: {row['Input'][:30]}..." for i, row in data_editor_data.iterrows()]
+    except Exception as e:
+        sample_options = []
 
     # Create the selectbox
     selected_sample = st.selectbox(
@@ -619,124 +626,137 @@ with tab_prompting:
                                         on_click=generate_callback,
                                         type="primary", use_container_width=True)
 
-    col1, col2 = st.columns(2)
 
-    with col1:
-        with st.expander("Advanced Inputs"):
-            initial_system_message = st.text_area(
-                "Initial System Message",
-                key="initial_system_message"
+    with st.expander("Advanced Inputs"):
+        initial_system_message = st.text_area(
+            "Initial System Message",
+            key="initial_system_message",
+            height=200,
+            placeholder="Enter the initial system message. It will be used as the base message for the prompt."
+        )
+
+        col1_1, col1_2 = st.columns(2)
+        with col1_1:
+            pull_sample_description_button = st.button("Pull Scope Description", key="pull_sample_description",
+                                                    on_click=pull_sample_description)
+        with col1_2:
+            st.button("Pull Output", key="copy_system_message",
+                    on_click=copy_system_message)
+        initial_acceptance_criteria = st.text_area(
+            "Acceptance Criteria",
+            key="initial_acceptance_criteria",
+            height=200,
+            placeholder="Enter the acceptance criteria. It will be used to evaluate the output."
+        )
+        st.button("Pull Output", key="copy_acceptance_criteria",
+                on_click=copy_acceptance_criteria)
+        
+        st.button("Clear", on_click=clear_advanced_inputs)
+
+    # New expander for model settings
+    with st.expander("Model Settings"):
+        model_tab = st.selectbox("Select Model Type", ["Simple", "Advanced", "Expert"], key="model_tab")
+
+        if model_tab == "Simple":
+            simple_model_name_input = st.selectbox(
+                "Model Name",
+                config.llms.keys(),
+                index=0,
+            )
+        elif model_tab == "Advanced":
+            advanced_optimizer_model_name_input = st.selectbox(
+                "Optimizer Model Name",
+                config.llms.keys(),
+                index=0,
+            )
+            advanced_executor_model_name_input = st.selectbox(
+                "Executor Model Name",
+                config.llms.keys(),
+                index=1,
+            )
+        else:  # Expert
+            expert_prompt_initial_developer_model_name_input = st.selectbox(
+                "Initial Developer Model Name",
+                config.llms.keys(),
+                index=0,
+            )
+            expert_prompt_initial_developer_temperature_input = st.slider(
+                "Initial Developer Temperature", 0.0, 1.0, 0.1, 0.1
             )
 
-            col1_1, col1_2 = st.columns(2)
-            with col1_1:
-                pull_sample_description_button = st.button("Pull Scope Description", key="pull_sample_description",
-                                                        on_click=pull_sample_description)
-            with col1_2:
-                st.button("Pull Output", key="copy_system_message",
-                        on_click=copy_system_message)
-            initial_acceptance_criteria = st.text_area(
-                "Acceptance Criteria",
-                key="initial_acceptance_criteria"
+            expert_prompt_acceptance_criteria_model_name_input = st.selectbox(
+                "Acceptance Criteria Model Name",
+                config.llms.keys(),
+                index=0,
             )
-            st.button("Pull Output", key="copy_acceptance_criteria",
-                    on_click=copy_acceptance_criteria)
-
-        # New expander for model settings
-        with st.expander("Model Settings"):
-            model_tab = st.selectbox("Select Model Type", ["Simple", "Advanced", "Expert"], key="model_tab")
-
-            if model_tab == "Simple":
-                simple_model_name_input = st.selectbox(
-                    "Model Name",
-                    config.llms.keys(),
-                    index=0,
-                )
-            elif model_tab == "Advanced":
-                advanced_optimizer_model_name_input = st.selectbox(
-                    "Optimizer Model Name",
-                    config.llms.keys(),
-                    index=0,
-                )
-                advanced_executor_model_name_input = st.selectbox(
-                    "Executor Model Name",
-                    config.llms.keys(),
-                    index=1,
-                )
-            else:  # Expert
-                expert_prompt_initial_developer_model_name_input = st.selectbox(
-                    "Initial Developer Model Name",
-                    config.llms.keys(),
-                    index=0,
-                )
-                expert_prompt_initial_developer_temperature_input = st.slider(
-                    "Initial Developer Temperature", 0.0, 1.0, 0.1, 0.1
-                )
-
-                expert_prompt_acceptance_criteria_model_name_input = st.selectbox(
-                    "Acceptance Criteria Model Name",
-                    config.llms.keys(),
-                    index=0,
-                )
-                expert_prompt_acceptance_criteria_temperature_input = st.slider(
-                    "Acceptance Criteria Temperature", 0.0, 1.0, 0.1, 0.1
-                )
-
-                expert_prompt_developer_model_name_input = st.selectbox(
-                    "Developer Model Name", config.llms.keys(), index=0
-                )
-                expert_prompt_developer_temperature_input = st.slider(
-                    "Developer Temperature", 0.0, 1.0, 0.1, 0.1
-                )
-
-                expert_prompt_executor_model_name_input = st.selectbox(
-                    "Executor Model Name", config.llms.keys(), index=1
-                )
-                expert_prompt_executor_temperature_input = st.slider(
-                    "Executor Temperature", 0.0, 1.0, 0.1, 0.1
-                )
-
-                expert_prompt_output_history_analyzer_model_name_input = st.selectbox(
-                    "Output History Analyzer Model Name",
-                    config.llms.keys(),
-                    index=0,
-                )
-                expert_prompt_output_history_analyzer_temperature_input = st.slider(
-                    "Output History Analyzer Temperature", 0.0, 1.0, 0.1, 0.1
-                )
-
-                expert_prompt_analyzer_model_name_input = st.selectbox(
-                    "Analyzer Model Name", config.llms.keys(), index=0
-                )
-                expert_prompt_analyzer_temperature_input = st.slider(
-                    "Analyzer Temperature", 0.0, 1.0, 0.1, 0.1
-                )
-
-                expert_prompt_suggester_model_name_input = st.selectbox(
-                    "Suggester Model Name", config.llms.keys(), index=0
-                )
-                expert_prompt_suggester_temperature_input = st.slider(
-                    "Suggester Temperature", 0.0, 1.0, 0.1, 0.1
-                )
-
-            prompt_template_group_input = st.selectbox(
-                "Prompt Template Group", config.prompt_templates.keys(), index=0
+            expert_prompt_acceptance_criteria_temperature_input = st.slider(
+                "Acceptance Criteria Temperature", 0.0, 1.0, 0.1, 0.1
             )
 
-            recursion_limit_input = st.number_input("Recursion Limit", 1, 100, 16, 1)
-            max_output_age_input = st.number_input("Max Output Age", 1, 10, 2, 1)
-            aggressive_exploration_input = st.checkbox("Aggressive Exploration", False)
+            expert_prompt_developer_model_name_input = st.selectbox(
+                "Developer Model Name", config.llms.keys(), index=0
+            )
+            expert_prompt_developer_temperature_input = st.slider(
+                "Developer Temperature", 0.0, 1.0, 0.1, 0.1
+            )
 
-    with col2:
-        system_message_output = st.text_area("System Message",
-                                            key="system_message_output",
-                                            height=100)
+            expert_prompt_executor_model_name_input = st.selectbox(
+                "Executor Model Name", config.llms.keys(), index=1
+            )
+            expert_prompt_executor_temperature_input = st.slider(
+                "Executor Temperature", 0.0, 1.0, 0.1, 0.1
+            )
 
-        acceptance_criteria_output = st.text_area(
-            "Acceptance Criteria",
-            key="acceptance_criteria_output",
-            height=100)
-        st.text_area("Output", st.session_state.output, height=100)
-        st.text_area("Analysis", st.session_state.analysis, height=100)
+            expert_prompt_output_history_analyzer_model_name_input = st.selectbox(
+                "Output History Analyzer Model Name",
+                config.llms.keys(),
+                index=0,
+            )
+            expert_prompt_output_history_analyzer_temperature_input = st.slider(
+                "Output History Analyzer Temperature", 0.0, 1.0, 0.1, 0.1
+            )
+
+            expert_prompt_analyzer_model_name_input = st.selectbox(
+                "Analyzer Model Name", config.llms.keys(), index=0
+            )
+            expert_prompt_analyzer_temperature_input = st.slider(
+                "Analyzer Temperature", 0.0, 1.0, 0.1, 0.1
+            )
+
+            expert_prompt_suggester_model_name_input = st.selectbox(
+                "Suggester Model Name", config.llms.keys(), index=0
+            )
+            expert_prompt_suggester_temperature_input = st.slider(
+                "Suggester Temperature", 0.0, 1.0, 0.1, 0.1
+            )
+
+        prompt_template_group_input = st.selectbox(
+            "Prompt Template Group", config.prompt_templates.keys(), index=0
+        )
+
+        recursion_limit_input = st.number_input("Recursion Limit", 1, 100, 16, 1)
+        max_output_age_input = st.number_input("Max Output Age", 1, 10, 2, 1)
+        aggressive_exploration_input = st.checkbox("Aggressive Exploration", False)
+
+    system_message_output = st.text_area(
+        "System Message",
+        key="system_message_output",
+        height=200,
+        placeholder="The generated system message will be shown here."
+    )
+    acceptance_criteria_output = st.text_area(
+        "Acceptance Criteria",
+        key="acceptance_criteria_output",
+        height=200,
+        placeholder="The (generated) acceptance criteria will be shown here."
+    )
+    output_output = st.text_area(
+        "Output", st.session_state.output, height=200,
+        placeholder="The output generated by the system message will be shown here."
+    )
+    analysis_output = st.text_area(
+        "Analysis", st.session_state.analysis, height=200,
+        placeholder="The analysis of the output will be shown here."
+    )
 
-        st.json(st.session_state.chat_log, expanded=False)
+    st.json(st.session_state.chat_log, expanded=False)

meta_prompt/sample_generator.py

@@ -131,7 +131,7 @@ BRIEFS_PROMPT = [
 
 EXAMPLES_FROM_BRIEFS_PROMPT = [
     ("system", """{{
-  "prompt": "Given the task type description, brief descriptions for new examples, and JSON example(s), generate {generating_batch_size} more input/output examples for this task type, strictly based on the brief descriptions. Ensure that the new examples are consistent with the brief descriptions and do not introduce any new information not present in the briefs. Output in JSON format, following `output_format`.",
+  "prompt": "Given the task type description, brief descriptions for new examples, and JSON example(s), generate {generating_batch_size} more input/output examples for this task type, strictly following the brief descriptions and task type description. Ensure that the new examples are consistent with the brief descriptions and do not introduce any new information not present in the briefs. Output in JSON format, following `output_format`. Validate the generated new examples with the task type description and brief descriptions.",
   "output_format": "{{
     "examples": [
       {{