create app.py

app.py

@@ -0,0 +1,196 @@
+
+
+import gradio as gr
+import logging
+import os
+from typing import List, Dict, Any, Optional
+
+# --- 1. CONFIGURATION FIRST ---
+from config import initialize_dspy
+custom_lm = initialize_dspy()
+
+# --- 2. Now Import Other Modules ---
+from config import (
+    API_KEY, STATE_STAGE, STATE_HISTORY, STAGE_START, STAGE_EXPLAINING,
+    STATE_EXPLAINER_PROMPT
+)
+from resource_processor import process_uploaded_files
+from orchestrator import process_chat_message
+
+# Setup basic logging
+logging.basicConfig(level=logging.INFO, format='{levelname} {asctime} [%(name)s]: {message}', style='{')
+logger = logging.getLogger(__name__)
+
+def respond(
+    user_message: str, # The content from the textbox
+    chat_history_ui: List[Dict[str, str]],
+    app_state: Dict[str, Any],
+    uploaded_files: Optional[List[Any]],
+    explainer_prompt_display: str
+):
+    """
+    Core backend function. Receives UI state, calls orchestrator, and returns updated UI state.
+    This version also handles clearing the input textbox directly.
+    """
+    # Guard clause: If user sends an empty message, do nothing.
+    if not user_message.strip():
+        # Return all components unchanged, including the uncleared textbox
+        return chat_history_ui, app_state, gr.update(), gr.update(), gr.update(), user_message
+
+    # Guard clause: If the API key is missing, the app won't work.
+    if not custom_lm:
+        error_msg = "FATAL ERROR: AI Backend is not configured. Please check your .env file for a valid GOOGLE_API_KEY."
+        chat_history_ui.append({"role": "user", "content": user_message})
+        chat_history_ui.append({"role": "assistant", "content": error_msg})
+        # Keep file uploader visible on error, but clear the textbox.
+        yield chat_history_ui, app_state, gr.update(visible=True), gr.update(), gr.update(), ""
+        return
+
+    # --- Step 1: Update UI and State with User's Message ---
+    chat_history_ui.append({"role": "user", "content": user_message})
+    app_state[STATE_HISTORY].append({'role': 'user', 'parts': [{'text': user_message}]})
+    chat_history_ui.append({"role": "assistant", "content": ""}) # Placeholder for bot response
+
+    # First yield for immediate UI update. Hide file uploader, but don't clear textbox yet.
+    yield chat_history_ui, app_state, gr.update(visible=False), gr.update(), gr.update(), user_message
+
+    # --- Step 2: Handle File Uploads ---
+    processed_file_data = None
+    if app_state.get(STATE_STAGE) == STAGE_START and uploaded_files:
+        logger.info(f"Processing {len(uploaded_files)} files for new chat session.")
+        processed_file_data = process_uploaded_files(uploaded_files)
+
+    # --- Step 3: Call the Main Agent Logic (The Orchestrator) ---
+    try:
+        final_user_facing_reply, new_state = process_chat_message(
+            user_message_text=user_message,
+            current_session_state=app_state,
+            uploaded_resource_data=processed_file_data,
+            modified_explainer_prompt=explainer_prompt_display
+        )
+        app_state = new_state
+    except Exception as e:
+        logger.error(f"Critical error in orchestrator call: {e}", exc_info=True)
+        final_user_facing_reply = f"[SYSTEM ERROR: An exception occurred in the agent's logic. Please check the logs. Details: {e}]"
+
+    # --- Step 4: Update the UI with the AI's Final Response ---
+    syllabus_flag_data = app_state.get("display_syllabus_flag")
+    if syllabus_flag_data:
+        syllabus_content = syllabus_flag_data.get("content", "Error displaying syllabus.")
+        chat_history_ui[-1] = {"role": "assistant", "content": syllabus_content}
+        chat_history_ui.append({"role": "assistant", "content": final_user_facing_reply})
+        app_state.pop("display_syllabus_flag", None)
+    else:
+        chat_history_ui[-1]['content'] = final_user_facing_reply
+
+    # --- Step 5: Determine visibility of explainer prompt box for the final return ---
+    prompt_update = gr.update(visible=False)
+    header_update = gr.update(visible=False)
+    if new_state.get(STATE_STAGE) == STAGE_EXPLAINING:
+        prompt_value = explainer_prompt_display if explainer_prompt_display else new_state.get(STATE_EXPLAINER_PROMPT)
+        prompt_update = gr.update(value=prompt_value, visible=True)
+        header_update = gr.update(visible=True)
+
+    # Final yield: return all component states AND an empty string to clear the textbox.
+    yield chat_history_ui, app_state, gr.update(visible=False), header_update, prompt_update, ""
+
+def start_new_session():
+    """ Resets the chat history, internal state, and all UI components for a new conversation. """
+    logger.info("UI action: Starting new session.")
+    initial_state = {
+        STATE_STAGE: STAGE_START,
+        STATE_HISTORY: [{'role': 'model', 'parts': [{'text': 'Hello! What would you like to learn about today?'}]}]
+    }
+    initial_chat_history_ui = [{"role": "assistant", "content": "Hello! What would you like to learn about today?"}]
+    
+    return (
+        initial_chat_history_ui,
+        initial_state,
+        gr.update(value=[], visible=True), # File uploader
+        gr.update(visible=False),           # Prompt header
+        gr.update(value="", visible=False),  # Prompt textbox
+        ""                                  # Clear the main textbox
+    )
+
+# --- 3. Gradio Interface Definition ---
+with gr.Blocks(theme=gr.themes.Soft(), title="Forge Guide AI Tutor") as demo:
+    gr.Markdown("# Forge Guide: AI Syllabus Architect")
+    gr.Markdown("Start a new conversation by describing what you want to learn. For new chats, you can also upload resources like PDFs or text files.")
+
+    app_state = gr.State({
+        STATE_STAGE: STAGE_START,
+        STATE_HISTORY: [{'role': 'model', 'parts': [{'text': 'Hello! What would you like to learn about today?'}]}]
+    })
+
+    with gr.Row():
+        with gr.Column(scale=4):
+            chatbot = gr.Chatbot(
+                [{"role": "assistant", "content": "Hello! What would you like to learn about today?"}],
+                elem_id="chatbot",
+                height=650,
+                render_markdown=True,
+                avatar_images=(None, "https://i.imgur.com/3pyR0Vf.png"),
+                type='messages',
+                latex_delimiters=[{"left": "$$", "right": "$$", "display": True}, {"left": "$", "right": "$", "display": False}]
+            )
+            
+            with gr.Row():
+                txt_input = gr.Textbox(
+                    scale=4,
+                    show_label=False,
+                    placeholder="e.g., 'I want to build a RAG pipeline from scratch'",
+                    container=False,
+                )
+                submit_btn = gr.Button("Send", variant="primary", scale=1, min_width=100)
+
+        with gr.Column(scale=1):
+            gr.Markdown("### Resources")
+            file_uploader = gr.File(
+                file_count="multiple",
+                label="Upload for New Chat (Optional)",
+                file_types=[".pdf", ".txt", ".docx"],
+                visible=True,
+                interactive=True,
+            )
+            new_session_btn = gr.Button("Start New Session", variant="secondary")
+            tutor_prompt_header = gr.Markdown("### Tutor Persona Prompt", visible=False)
+            explainer_prompt_display = gr.Textbox(
+                label="You can modify the tutor's persona and instructions here:",
+                lines=15,
+                interactive=True,
+                visible=False,
+            )
+
+    # --- 4. Event Listeners: Wiring the UI to the Backend ---
+    submit_actions = [txt_input, chatbot, app_state, file_uploader, explainer_prompt_display]
+    output_components = [chatbot, app_state, file_uploader, tutor_prompt_header, explainer_prompt_display, txt_input]
+
+    submit_btn.click(
+        fn=respond,
+        inputs=submit_actions,
+        outputs=output_components,
+    )
+
+    txt_input.submit(
+        fn=respond,
+        inputs=submit_actions,
+        outputs=output_components,
+    )
+
+    new_session_btn.click(
+        fn=start_new_session,
+        inputs=[],
+        outputs=output_components
+    )
+
+# --- 5. Launch the App ---
+if __name__ == "__main__":
+    if not API_KEY:
+        print("\n" + "="*60)
+        print("CRITICAL ERROR: Cannot launch Gradio app.")
+        print("Your GOOGLE_API_KEY is not set in the .env file.")
+        print("="*60 + "\n")
+    else:
+        print("Launching Gradio app...")
+        demo.queue().launch(debug=True)
+