Update App.py

App.py

@@ -1,72 +1,61 @@
 import json
 import gradio as gr
-from huggingface_hub import InferenceClient
+from transformers import pipeline
 
-# Initialize the client using the specified model.
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+# Load the text generation model (can swap for a Bible-specific LLM)
+model_name = "google/flan-t5-large"  # Change if needed
+generator = pipeline("text2text-generation", model=model_name, trust_remote_code=True)
 
-def respond(message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p):
+def analyze_bible_figure_of_speech(verse):
     """
-    Builds a conversation history that includes a system instruction for Bible analysis.
+    Analyzes a Bible verse for figures of speech.
     
-    The system message instructs the model to act as JR‑Sacred Syntax, an expert biblical scholar
-    specializing in analyzing Bible verses to detect figures of speech (e.g., Metaphor, Synecdoche, Hyperbole, etc.)
-    and output a JSON array with each entry containing:
-      - "figure": the type of figure of speech,
-      - "phrase": the phrase in the verse,
-      - "explanation": explanation in biblical context.
-    """
-    # Build the message list starting with the system message.
-    messages = [{"role": "system", "content": system_message}]
-    
-    # Append previous conversation history.
-    for user_msg, assistant_msg in history:
-        if user_msg:
-            messages.append({"role": "user", "content": user_msg})
-        if assistant_msg:
-            messages.append({"role": "assistant", "content": assistant_msg})
+    The function constructs a structured prompt for an LLM, requesting it to:
+      - Identify any figure of speech in the verse (e.g., Metaphor, Hyperbole, Synecdoche, Paradox, Simile).
+      - Extract the phrase demonstrating the figure of speech.
+      - Explain why it's a figure of speech in biblical context.
     
-    # Append the new user message.
-    messages.append({"role": "user", "content": message})
+    Expected Output:
+      A structured JSON array with:
+      - "figure": Type of figure of speech.
+      - "phrase": The phrase in the verse.
+      - "explanation": Explanation in biblical context.
+    """
+    if not verse.strip():
+        return "Please enter a Bible verse."
 
-    response = ""
-    # Stream the chat completion response.
-    for chat_message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = chat_message.choices[0].delta.content
-        response += token
-        yield response
+    prompt = f"""
+    Analyze the following Bible verse and identify any figures of speech present (e.g., Metaphor, Hyperbole, Synecdoche, Paradox, Simile).
+    Provide a JSON response with:
+    - "figure": Type of figure of speech.
+    - "phrase": The phrase in the verse.
+    - "explanation": Why it is a figure of speech in biblical context.
 
-# Define a default system message that guides the model for Bible figure-of-speech analysis.
-default_system_message = (
-    "You are JR-Sacred Syntax, an expert biblical scholar. "
-    "When given a Bible verse, analyze it to detect any figures of speech (such as Metaphor, "
-    "Synecdoche, Hyperbole, Simile, or Paradox) and return a JSON array where each entry includes "
-    "'figure' (the type), 'phrase' (the exact words from the verse), and 'explanation' (why it qualifies as such) "
-    "in a biblical context. Respond only in JSON format."
-)
+    Bible Verse: \"{verse}\"
+    """
+    
+    try:
+        # Generate the output from the LLM
+        result = generator(prompt, max_length=512, num_return_sequences=1)
+        generated_text = result[0]['generated_text']
+        
+        # Try parsing the output as JSON
+        try:
+            output_json = json.loads(generated_text)
+            return json.dumps(output_json, indent=2)  # Pretty-print JSON
+        except json.JSONDecodeError:
+            return generated_text  # Return raw text if JSON parsing fails
+    except Exception as e:
+        return f"Error: {str(e)}"
 
-# Create the Gradio Chat Interface.
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value=default_system_message, label="System Message (Instruction)"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max New Tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (Nucleus Sampling)"),
-    ],
-    title="JR‑Sacred Syntax: Bible Figures of Speech Detector",
-    description=(
-        "Enter a Bible verse to have it analyzed for figures of speech. "
-        "JR‑Sacred Syntax will detect and explain literary devices in the verse, "
-        "returning the results in a structured JSON format."
-    )
+# Gradio UI
+interface = gr.Interface(
+    fn=analyze_bible_figure_of_speech,
+    inputs=gr.Textbox(label="Enter a Bible Verse", placeholder="E.g., 'I am the vine, you are the branches' - John 15:5", lines=3),
+    outputs=gr.Textbox(label="Figures of Speech Analysis (JSON)"),
+    title="Bible Figures of Speech Detector",
+    description="Enter a Bible verse to analyze its figures of speech, such as metaphor, simile, or hyperbole. The app will identify the figure, extract the phrase, and provide an explanation."
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    interface.launch()