Update app.py

app.py

@@ -3,91 +3,123 @@ import gradio as gr
 import requests
 import json
 import logging
+import random
+from datetime import datetime
+from cachetools import TTLCache
 
-# Retrieve the API token from secrets
-api_token = os.getenv("API_TOKEN")
-if not api_token:
-    raise ValueError("API token not found. Make sure 'API_TOKEN' is set in the Secrets.")
+# Add cache with 1-hour expiration
+response_cache = TTLCache(maxsize=100, ttl=3600)
 
-# Configure logging
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
+# ...existing code...
 
-# Use the token in your request headers
-API_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.3"
-HEADERS = {"Authorization": f"Bearer {api_token}"}
+def get_cached_response(key, prompt_func):
+    cache_key = f"{key}_{datetime.now().strftime('%Y%m%d%H')}"
+    if cache_key in response_cache:
+        return response_cache[cache_key]
+    response = prompt_func()
+    response_cache[cache_key] = response
+    return response
 
-def query(payload):
-    response = requests.post(API_URL, headers=HEADERS, json=payload)
-    return response.json()
+def generate_dynamic_prompt(base_prompt, variations):
+    modifiers = [
+        "Include specific examples and applications.",
+        "Provide practical insights and modern relevance.",
+        "Consider different interpretations and perspectives.",
+        "Draw connections across different biblical passages.",
+    ]
+    return f"{base_prompt} {random.choice(modifiers)} {random.choice(variations)}"
 
 def generate_exegesis(passage):
     if not passage.strip():
         return "Please enter a Bible passage."
-    prompt = f"""<s>[INST] You are a professional Bible Scholar. Provide a detailed exegesis of the following biblical verse, including: The original Greek text and transliteration with word-by-word analysis and meanings, historical and cultural context, and theological significance for: {passage} [/INST] Exegesis:</s>"""
-    try:
+    
+    variations = [
+        "Analyze the historical context and cultural significance.",
+        "Examine the linguistic nuances and theological implications.",
+        "Focus on the practical applications and modern relevance.",
+        "Consider the passage's role in the broader biblical narrative."
+    ]
+    
+    def get_response():
+        prompt = generate_dynamic_prompt(
+            f"""<s>[INST] As a professional Bible Scholar, provide a detailed exegesis of: {passage}.""",
+            variations
+        )
         response = query({"inputs": prompt})
         if isinstance(response, list) and response:
-            generated_text = response[0]["generated_text"]
-            marker = "Exegesis:"
-            if marker in generated_text:
-                return generated_text.split(marker, 1)[1].strip()
-            return generated_text
+            return response[0]["generated_text"].split("Exegesis:", 1)[-1].strip()
         return "Error: Invalid response from model."
-    except Exception as e:
-        logger.error(f"Generation Error: {e}")
-        return f"Generation Error: {e}"
+    
+    return get_cached_response(f"exegesis_{passage}", get_response)
 
 def ask_any_questions(question):
     if not question.strip():
         return "Please enter a question."
-    prompt = f"""<s>[INST] You are a professional Bible Scholar. Provide a detailed answer to the following question, including: Relevant Bible verses, their explanations, and theological significance for: {question} [/INST] Answer:</s>"""
-    try:
+    
+    variations = [
+        "Consider multiple perspectives and interpretations.",
+        "Provide practical applications and modern context.",
+        "Include relevant cross-references and supporting verses.",
+        "Examine the historical and cultural context."
+    ]
+    
+    def get_response():
+        prompt = generate_dynamic_prompt(
+            f"""<s>[INST] As a Bible Scholar, answer this question: {question}.""",
+            variations
+        )
         response = query({"inputs": prompt})
         if isinstance(response, list) and response:
-            answer_text = response[0]["generated_text"]
-            marker = "Answer:"
-            if marker in answer_text:
-                return answer_text.split(marker, 1)[1].strip()
-            return answer_text
+            return response[0]["generated_text"].split("Answer:", 1)[-1].strip()
         return "Error: Invalid response from model."
-    except Exception as e:
-        logger.error(f"Generation Error: {e}")
-        return f"Generation Error: {e}"
+    
+    return get_cached_response(f"question_{question}", get_response)
 
 def generate_sermon(topic):
     if not topic.strip():
         return "Please enter a topic."
-    prompt = f"""<s>[INST] You are a highly knowledgeable Bible Scholar and Pastor. Generate a detailed sermon on the following topic: {topic}. Include relevant Bible verses and theological insights. [/INST] Sermon:</s>"""
-    try:
+    
+    variations = [
+        "Structure the sermon with clear main points and supporting scripture.",
+        "Include real-life applications and contemporary examples.",
+        "Incorporate both Old and New Testament perspectives.",
+        "Focus on practical implementation and spiritual growth."
+    ]
+    
+    def get_response():
+        prompt = generate_dynamic_prompt(
+            f"""<s>[INST] As a Pastor and Bible Scholar, create an engaging sermon about: {topic}.""",
+            variations
+        )
         response = query({"inputs": prompt})
         if isinstance(response, list) and response:
-            sermon_text = response[0]["generated_text"]
-            marker = "Sermon:"
-            if marker in sermon_text:
-                return sermon_text.split(marker, 1)[1].strip()
-            return sermon_text
+            return response[0]["generated_text"].split("Sermon:", 1)[-1].strip()
         return "Error: Invalid response from model."
-    except Exception as e:
-        logger.error(f"Generation Error: {e}")
-        return f"Generation Error: {e}"
+    
+    return get_cached_response(f"sermon_{topic}", get_response)
 
 def keyword_search(keyword):
     if not keyword.strip():
         return "Please enter a keyword."
-    prompt = f"""<s>[INST] You are a Bible Scholar. Find relevant Bible passages containing the keyword: {keyword} [/INST] Search Results:</s>"""
-    try:
+    
+    variations = [
+        "Include context and interpretation for each passage.",
+        "Focus on both literal and thematic occurrences.",
+        "Consider related terms and concepts.",
+        "Examine different biblical contexts where this concept appears."
+    ]
+    
+    def get_response():
+        prompt = generate_dynamic_prompt(
+            f"""<s>[INST] As a Bible Scholar, find and analyze passages containing: {keyword}.""",
+            variations
+        )
         response = query({"inputs": prompt})
         if isinstance(response, list) and response:
-            search_results = response[0]["generated_text"]
-            marker = "Search Results:"
-            if marker in search_results:
-                return search_results.split(marker, 1)[1].strip()
-            return search_results
+            return response[0]["generated_text"].split("Search Results:", 1)[-1].strip()
         return "Error: Invalid response from model."
-    except Exception as e:
-        logger.error(f"Generation Error: {e}")
-        return f"Generation Error: {e}"
+    
+    return get_cached_response(f"search_{keyword}", get_response)
 
 # Gradio interface definitions
 exegesis_demo = gr.Interface(