Tree-of-Thought Animate

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🎞 ANIMATE · Mode 3 of 5 · +100 XP— Tree of Thought

🌳Branch

📊Evaluate

✂️Prune

🔄Recurse

🎯 Next: Test →

Step 1 / 4

Speed

What's happening

Generate multiple thought branches

LLM generates 3 different approaches to the problem

💡 Analogy

Like a chess player mentally exploring three different opening moves before choosing.

Instead of one answer, we ask the model to generate multiple different approaches.

Console Output

> Branch 1: "Use dynamic programming..."
> Branch 2: "Apply greedy algorithm..."
> Branch 3: "Try divide and conquer..."

●tree-of-thought.ts

Generate multiple thought branchesL3–7

1// Tree of Thoughts: explore multiple reasoning paths

2async function treeOfThoughts(problem: string, depth = 3) {

3 // Step 1: Generate candidate thoughts (branches)

4 const thoughts = await llm.complete(`

5 Problem: ${problem}

6 Generate 3 different approaches to solve this:

7 Approach 1:`);

9 // Step 2: Evaluate each thought

10 const scores = await Promise.all(

11 thoughts.map(t => llm.complete(`

12 Rate this approach 1-10 for correctness:

13 Approach: ${t}

14 Score:`))

15 );

17 // Step 3: Keep best branch, expand further

18 const bestThought = thoughts[scores.indexOf(Math.max(...scores))];

20 // Step 4: Recurse on best branch

21 if (depth > 1) return treeOfThoughts(bestThought, depth - 1);

22 return bestThought;

23}

23 lines

Steps · 4

What's happening

Generate multiple thought branches

LLM generates 3 different approaches to the problem

💡 Analogy

Like a chess player mentally exploring three different opening moves before choosing.

Instead of one answer, we ask the model to generate multiple different approaches.

Console Output

> Branch 1: "Use dynamic programming..."
> Branch 2: "Apply greedy algorithm..."
> Branch 3: "Try divide and conquer..."

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← Back to topic

🎞 ANIMATE · Mode 3 of 5 · +100 XP— Tree of Thought

🌳Branch

📊Evaluate

✂️Prune

🔄Recurse

🎯 Next: Test →

Step 1 / 4

Speed

What's happening

Generate multiple thought branches

LLM generates 3 different approaches to the problem

💡 Analogy

Like a chess player mentally exploring three different opening moves before choosing.

Instead of one answer, we ask the model to generate multiple different approaches.

Console Output

> Branch 1: "Use dynamic programming..."
> Branch 2: "Apply greedy algorithm..."
> Branch 3: "Try divide and conquer..."

●tree-of-thought.ts

Generate multiple thought branchesL3–7

1// Tree of Thoughts: explore multiple reasoning paths

2async function treeOfThoughts(problem: string, depth = 3) {

3 // Step 1: Generate candidate thoughts (branches)

4 const thoughts = await llm.complete(`

5 Problem: ${problem}

6 Generate 3 different approaches to solve this:

7 Approach 1:`);

9 // Step 2: Evaluate each thought

10 const scores = await Promise.all(

11 thoughts.map(t => llm.complete(`

12 Rate this approach 1-10 for correctness:

13 Approach: ${t}

14 Score:`))

15 );

17 // Step 3: Keep best branch, expand further

18 const bestThought = thoughts[scores.indexOf(Math.max(...scores))];

20 // Step 4: Recurse on best branch

21 if (depth > 1) return treeOfThoughts(bestThought, depth - 1);

22 return bestThought;

23}

23 lines

Steps · 4

What's happening

Generate multiple thought branches

LLM generates 3 different approaches to the problem

💡 Analogy

Like a chess player mentally exploring three different opening moves before choosing.

Instead of one answer, we ask the model to generate multiple different approaches.

Console Output

> Branch 1: "Use dynamic programming..."
> Branch 2: "Apply greedy algorithm..."
> Branch 3: "Try divide and conquer..."