Update app.py

app.py

@@ -95,7 +95,70 @@ Based on the hypotheses I believe that...
 The most likely is...
 Finally, [summary]."]
 </think>
-Clear and direct answer, derived of the above reasoning."""
+Clear and direct answer, derived of the above reasoning.
+If the user want analysis of marketing:
+Analyze competitors in [Industry/Niche]:
+- Primary competitors: [List 3-5 main competitors]
+- Geographic focus: [Specify market region]
+- Time period: [Define analysis timeframe]
+- Key metrics: [List specific performance indicators]
+
+Required outputs:
+1. Competitive positioning analysis
+2. Strengths/weaknesses assessment
+3. Market opportunity identification
+4. Strategic recommendations
+5. Implementation timeline with KPIs
+
+Please build a prompt using the following guidelines:
+
+Define the Objective: 
+- Clearly state the main research question or task.
+- Specify the desired outcome (e.g., detailed analysis, comparison, recommendations).
+
+Gather Context and Background:
+- Include all relevant background information, definitions, and data.
+- Specify any boundaries (e.g., scope, timeframes, geographic limits).
+
+Use Specific and Clear Language:
+- Provide precise wording and define key terms.
+- Avoid vague or ambiguous language.
+
+Provide Step-by-Step Guidance:
+- Break the task into sequential steps or sub-tasks.
+- Organize instructions using bullet points or numbered lists.
+
+Specify the Desired Output Format:
+- Describe how the final answer should be organized (e.g., report format, headings, bullet points, citations).
+Include any specific formatting requirements.
+
+Balance Detail with Flexibility:
+- Offer sufficient detail to guide the response while allowing room for creative elaboration.
+- Avoid over-constraining the prompt to enable exploration of relevant nuances.
+
+Incorporate Iterative Refinement:
+- Build in a process to test the prompt and refine it based on initial outputs.
+- Allow for follow-up instructions to adjust or expand the response as needed.
+
+Apply Proven Techniques:
+- Use methods such as chain-of-thought prompting (e.g., “think step by step”) for complex tasks.
+- Encourage the AI to break down problems into intermediate reasoning steps.
+
+Set a Role or Perspective:
+- Assign a specific role (e.g., “act as a market analyst” or “assume the perspective of a historian”) to tailor the tone and depth of the analysis.
+
+Avoid Overloading the Prompt:
+- Focus on one primary objective or break multiple questions into separate parts.
+- Prevent overwhelming the prompt with too many distinct questions.
+
+Request Justification and References:
+- Instruct the AI to support its claims with evidence or to reference sources where possible.
+- Enhance the credibility and verifiability of the response.
+
+Review and Edit Thoroughly:
+- Ensure the final prompt is clear, logically organized, and complete.
+- Remove any ambiguous or redundant instructions.
+"""
 ]
 
 DEFAULT_INITIAL_PROMPTS = [
@@ -500,9 +563,9 @@ def refresh_commit_display():
 
 # Gradio Interface setup
 with gr.Blocks() as demo:
-    gr.Markdown("# Cute AI Conversation Generator 🐾")
+    gr.Markdown("# DeepRethink")
     gr.Markdown(
-        "Generate engaging, cute, and positive conversations with various Pollinations.ai models. "
+        "Generate engaging, thinking, and positive conversations with various Pollinations.ai models. "
         f"Generated data is saved and pushed to the Hugging Face dataset `{HF_DATASET_REPO_ID}`."
     )