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Update app.py
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app.py
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@@ -86,7 +86,6 @@ class EnhancedContextDrivenChatbot:
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r"(.*?),?\s*(?:please\s+)?(provide\s+(?:me\s+)?a\s+.*?|give\s+(?:me\s+)?a\s+.*?|create\s+a\s+.*?)$",
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r"(.*?),?\s*(?:please\s+)?(summarize|analyze|explain|describe|elaborate\s+on).*$",
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r"(.*?),?\s*(?:please\s+)?(in\s+detail|briefly|concisely).*$",
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r"(.*?),?\s*(?:please\s+)?(considering\s+yourself\s+as\s+.*?)$"
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]
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for pattern in instruction_patterns:
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@@ -141,7 +140,7 @@ class EnhancedContextDrivenChatbot:
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if self.is_follow_up_question(core_question):
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contextualized_question = self.get_most_relevant_context(core_question)
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contextualized_question = self.rephrase_query(contextualized_question)
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else:
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contextualized_question = core_question
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@@ -353,16 +352,15 @@ def estimate_tokens(text):
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# Rough estimate: 1 token ~= 4 characters
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return len(text) // 4
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def ask_question(question, temperature, top_p, repetition_penalty, web_search, chatbot):
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model = get_model(temperature, top_p, repetition_penalty)
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chatbot.model = model
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if web_search:
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contextualized_question, topics, entity_tracker, instructions = chatbot.process_question(question)
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# Log the contextualized question for debugging
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print(f"Contextualized question: {contextualized_question}")
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print(f"Instructions: {instructions}")
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search_results = google_search(contextualized_question, num_results=3)
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r"(.*?),?\s*(?:please\s+)?(provide\s+(?:me\s+)?a\s+.*?|give\s+(?:me\s+)?a\s+.*?|create\s+a\s+.*?)$",
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r"(.*?),?\s*(?:please\s+)?(summarize|analyze|explain|describe|elaborate\s+on).*$",
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r"(.*?),?\s*(?:please\s+)?(in\s+detail|briefly|concisely).*$",
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]
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for pattern in instruction_patterns:
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if self.is_follow_up_question(core_question):
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contextualized_question = self.get_most_relevant_context(core_question)
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contextualized_question = self.rephrase_query(contextualized_question, instructions)
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else:
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contextualized_question = core_question
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# Rough estimate: 1 token ~= 4 characters
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return len(text) // 4
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def ask_question(question: str, temperature: float, top_p: float, repetition_penalty: float, web_search: bool, chatbot: EnhancedContextDrivenChatbot) -> str:
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model = get_model(temperature, top_p, repetition_penalty)
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chatbot.model = model
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if web_search:
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contextualized_question, topics, entity_tracker, instructions = chatbot.process_question(question)
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# Log the contextualized question for debugging
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print(f"Contextualized question: {contextualized_question}")
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search_results = google_search(contextualized_question, num_results=3)
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