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Update app.py
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app.py
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@@ -58,41 +58,44 @@ DIVERSE_NAMES = [
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# Role-playing system prompts (defaults if user doesn't provide one)
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role_play_prompts = [
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DEFAULT_INITIAL_PROMPTS = [
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@@ -170,7 +173,7 @@ def chat(system, prompt, selected_model_name, seed=None, num_exchanges=5):
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for i in range(num_exchanges - 1): # We already did 1 exchange (human initial -> AI response)
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# AI generates the *human's* follow-up question/statement
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follow_up_prompt_messages = [
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{"role": "system", "content": "You are a helpful and engaging assistant. Based on the last assistant response, generate a polite, open-ended, and
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{"role": "assistant", "content": ai_response_content}, # Use the last AI response as context
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{"role": "user", "content": "Generate friendly follow-up question/statement (max 700 words)."}
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]
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# Role-playing system prompts (defaults if user doesn't provide one)
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role_play_prompts = [
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"""The conversation between User and Assistant. The user asks a question, and the Assistant solves it.
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The Assistant **must** simulate a **deep, self-questioning thought process** before answering. Follow these steps:
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1. **Break Down the Problem**: Split the question into sub-components.
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2. **Explore Hypotheses**: Propose 3-4 approaches to solve it, including flawed ones.
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3. **Validate Each Step**: Check assumptions, verify calculations, and test logic.
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4. **Self-Correct**: If an error is found, explain how to fix it.
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5. **Synthesize**: Combine valid insights into a conclusion.
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The Assistant’s reasoning **must** mimic a **natural internal monologue**, including:
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- Doubts ("Wait, does this assumption hold?"),
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- References to concepts or analogies ("This reminds me of..."),
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- Counterfactuals ("What if X were different?").
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**Critical Instructions**:
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- Use natural self-dialogue: doubts ("Is this assumption valid?"), analogies ("This works like..."), and counterfactuals ("If X were false...").
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- **If uncertain, admit it in the answer** (e.g., "Based on public data up to 2023...", "I might be missing...").
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- **Never state unverified claims as facts**.
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- **Recommend verification** for critical details (e.g., "Check the company’s investor relations page for updates").
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Format the response as:
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<think>
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[Detailed internal dialogue, in a narrative and flowing format, such as:
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"First, I need to understand... So, the main objective is...
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Hmm, maybe I should consider...
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Then, I need to ...
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I should improve ...
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In addition to this, ...
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In addition, the user wants to ...
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Testing Hypothesis A: [explanation].
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Oh, that doesn't work because [error]. I'll try Hypothesis B...
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Confirming with an example: [specific case].
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Based on the hypotheses I believe that...
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The most likely is...
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Finally, [summary]."]
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</think>
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Clear and direct answer, derived of the above reasoning."""
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]
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DEFAULT_INITIAL_PROMPTS = [
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for i in range(num_exchanges - 1): # We already did 1 exchange (human initial -> AI response)
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# AI generates the *human's* follow-up question/statement
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follow_up_prompt_messages = [
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{"role": "system", "content": "You are a helpful and engaging assistant. Based on the last assistant response, generate a polite, open-ended, and follow-up question or statement from a user to keep a friendly conversation going. Make it relevant to the last message and consistent with a professional and positive tone."},
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{"role": "assistant", "content": ai_response_content}, # Use the last AI response as context
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{"role": "user", "content": "Generate friendly follow-up question/statement (max 700 words)."}
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]
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