Fix/format (#50)

* fix/format

* feat(prompts/logic): add cot_prompt.yaml and update super_prompt.yaml (#49)

prompts/logic/cot_prompt.yaml

@@ -0,0 +1,132 @@
+name: cot_prompt
+version: "1.1"
+description: Solve complex problems using Chain of Thought (CoT) reasoning
+author: Raphaël MANSUY
+provider: aws-anthropic
+model: anthropic.claude-3-5-sonnet-20240620-v1:0
+input_variables:
+ problem_to_solve:
+ type: string
+ description: The problem to solve
+ place_holder: >
+ Each of five neighborhood dogs (Saber, Ginger, Nutmeg, Pepper, and Bear) is enjoying one of the following activities: 
+ getting its ears scratched, playing catch, taking a nap, burying a chew toy, and going for a walk.
+ Pepper is either playing catch or burying a chew toy.
+ Neither Ginger, Saber, nor Bear is on a walk.
+ One of the dogs named after a spice is getting its ears scratched.
+ A dog not named for a spice is playing catch.
+ Bear is getting some exercise.
+ Can you determine what each dog is doing?
+parameters:
+ max_tokens: 12000
+ temperature: 0.2
+ top_p: 0.9
+ top_k: 0
+ system_message: >
+ You are a superintelligent AI assistant. You strictly follow the rules in the <rules/> XML tags.
+content: >
+ ## Problem to Solve
+
+ {{problem_to_solve}}
+
+ ### The CoT Prompting Approach
+
+ This prompt leverages Chain of Thought (CoT) reasoning to systematically tackle complex problems. 
+
+ In formal terms, given an input $$ x $$ and a target $$ y $$, a LLM $$ p $$ with CoT prompting can be expressed as:
+
+ $$ y \sim \sum_{z \sim p(z|C_x)} p(y|C_x, z) \cdot p(z|C_x), $$
+
+ where $$ C_x = c^{(cot)}(x) $$.
+
+ - **$$ C_x $$**: Prompted input.
+ - **$$ c^{(cot)}(\cdot) $$**: Template with CoT prompting instructions, e.g., ‘let’s think step by step’.
+ - **$$ z $$**: Latent variable of rationale, representing a sampled rationale in natural language.
+
+ This approach enables the LLM to decompose complex tasks into manageable reasoning steps.
+
+ ### Let's Solve the Problem Step by Step
+
+ **Question:** 
+
+ <question>{{problem_to_solve}}</question>
+
+ ---
+
+ **Step 0: Define the Problem** 
+
+ Reformulate the problem statement in your own words to ensure clarity. 
+
+ - Reformulate all rules and constraints coherently.
+ - Utilize predicate logic to define these rules.
+ - Identify any implicit rules or constraints not explicitly stated.
+
+ ***Step 1: Verify Your Reformulation*** 
+
+ - Review each element of the problem to ensure consistency with your reformulation.
+ - Revise as necessary until a clear and consistent reformulation is achieved.
+
+ **Step 2: Identify Key Components** 
+
+ - List at least 10 key components essential to addressing the problem.
+ - Use clear bullet points to outline these components.
+
+ <key_components> 
+ - List essential elements relevant to the problem.
+ - *Example:* If the problem is about climate change, key components might include greenhouse gases, renewable energy, and policy measures.
+ </key_components>
+
+ ---
+
+ **Step 3: Break Down the Problem** 
+
+ - Define at least 15 logical steps necessary to solve the problem using predicate logic.
+ - Each step should clearly articulate the reasoning process.
+
+ <logical_steps> 
+ - <step number="1"> 
+ **Define** the first logical step. 
+ ***Example:*** "Identify the primary cause of the issue."
+ </step>
+ - <step number="2"> 
+ **Identify** the next action or consideration. 
+ ***Example:*** "Analyze the impact of the cause."
+ </step>
+ - <step number="3"> 
+ **Outline** additional steps necessary for a comprehensive solution. 
+ ***Example:*** "Propose mitigation strategies based on the analysis."
+ </step>
+ </logical_steps>
+
+ ---
+
+ **Step 4: Execute Logical Steps** 
+
+ - Implement the logical steps defined previously and draw inferences.
+ - Ensure each intermediate result is consistent with the problem statement and satisfies all requirements.
+ - Repeat this step until a solution is reached.
+
+ ---
+
+ **Step 5: Synthesize Insights** 
+
+ - Integrate insights from each step to formulate the final answer.
+ - Analyze how each component interacts to contribute to the overall understanding of the problem.
+
+ **Answer:**
+
+ <final_answer> 
+ - Present a clear, actionable, and definitive response based on synthesized insights.
+ </final_answer> 
+
+ ---
+
+ ### Additional Instructions for Agentic Behavior
+
+ - **Take Initiative:** Propose additional questions or considerations that may arise.
+ - **Be Decisive:** Provide actionable recommendations or next steps.
+ - **Reflect on Implications:** Consider the broader impact of your answer on future decisions.
+ - **Encourage Creativity:** Explore alternative solutions or approaches.
+ - **Feedback Loop:** After providing an answer, reflect on your reasoning process for potential improvements.
+
+ ### END

prompts/logic/super_prompt.yaml

@@ -19,7 +19,7 @@ input_variables:
  Can you figure out what each pooch is doing?
 parameters:
  max_tokens: 12000
- temperature: 0.7
+ temperature: 0.2
  top_p: 0.9
  top_k: 0
  system_message: >