update thinking

This commit is contained in:
zachary62 2025-04-15 17:47:25 -04:00
parent 8dd2b8a1ed
commit 235c2812dc
5 changed files with 65 additions and 70 deletions

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@ -17,6 +17,12 @@ This project demonstrates a simplified RAG system that retrieves relevant docume
``` ```
Or update it directly in `utils.py` Or update it directly in `utils.py`
Let's do a quick check to make sure your API key is working properly:
```bash
python utils.py
```
2. Install and run with the default query: 2. Install and run with the default query:
```bash ```bash
pip install -r requirements.txt pip install -r requirements.txt

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@ -12,24 +12,33 @@ This project demonstrates an extended thinking mode implementation that enables
## Getting Started ## Getting Started
1. Install the required packages: 1. Install the required packages:
```bash ```bash
pip install -r requirements.txt pip install -r requirements.txt
``` ```
2. Set up your API key: 2. Set up your API key:
```bash ```bash
export ANTHROPIC_API_KEY="your-api-key-here" export ANTHROPIC_API_KEY="your-api-key-here"
``` ```
Let's do a quick check to make sure your API key is working properly:
```bash
python utils.py
```
3. Run a test problem to see thinking mode in action: 3. Run a test problem to see thinking mode in action:
```bash ```bash
python main.py python main.py
``` ```
By default, we will ask the example question:
> Break a stick, then break the longer piece again. What's the probability of forming a triangle?
4. Try your own reasoning problem: 4. Try your own reasoning problem:
```bash ```bash
python main.py --"Your complex reasoning problem here" python main.py --"Your complex reasoning problem here"
``` ```
## How It Works ## How It Works

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@ -3,7 +3,7 @@ from nodes import ChainOfThoughtNode
def create_chain_of_thought_flow(): def create_chain_of_thought_flow():
# Create a ChainOfThoughtNode # Create a ChainOfThoughtNode
cot_node = ChainOfThoughtNode() cot_node = ChainOfThoughtNode(max_retries=3, wait=10)
# Connect the node to itself for the "continue" action # Connect the node to itself for the "continue" action
cot_node - "continue" >> cot_node cot_node - "continue" >> cot_node

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@ -1,3 +1,4 @@
# cookbook/pocketflow-thinking/nodes.py
from pocketflow import Node from pocketflow import Node
import yaml import yaml
from utils import call_llm from utils import call_llm
@ -8,81 +9,63 @@ class ChainOfThoughtNode(Node):
problem = shared.get("problem", "") problem = shared.get("problem", "")
thoughts = shared.get("thoughts", []) thoughts = shared.get("thoughts", [])
current_thought_number = shared.get("current_thought_number", 0) current_thought_number = shared.get("current_thought_number", 0)
# Increment the current thought number in the shared store
shared["current_thought_number"] = current_thought_number + 1
total_thoughts_estimate = shared.get("total_thoughts_estimate", 5)
# Format previous thoughts # Increment the current thought number for the next step
shared["current_thought_number"] = current_thought_number + 1
# Format previous thoughts simply
thoughts_text = "\n".join([ thoughts_text = "\n".join([
f"Thought {t['thought_number']}: {t['content']}" + f"Thought {t['thought_number']}: {t['current_thinking']}" +
(f" (Revision of Thought {t['revises_thought']})" if t.get('is_revision') and t.get('revises_thought') else "") + (f"\n (Plan: {t.get('next_thought_planning', 'N/A')})" if t.get('next_thought_needed') else "")
(f" (Branch from Thought {t['branch_from_thought']}, Branch ID: {t['branch_id']})"
if t.get('branch_from_thought') else "")
for t in thoughts for t in thoughts
]) ])
return { return {
"problem": problem, "problem": problem,
"thoughts_text": thoughts_text, "thoughts_text": thoughts_text,
"thoughts": thoughts,
"current_thought_number": current_thought_number + 1, "current_thought_number": current_thought_number + 1,
"total_thoughts_estimate": total_thoughts_estimate
} }
def exec(self, prep_res): def exec(self, prep_res):
problem = prep_res["problem"] problem = prep_res["problem"]
thoughts_text = prep_res["thoughts_text"] thoughts_text = prep_res["thoughts_text"]
current_thought_number = prep_res["current_thought_number"] current_thought_number = prep_res["current_thought_number"]
total_thoughts_estimate = prep_res["total_thoughts_estimate"]
# Create the prompt for the LLM # Create the simplified prompt for the LLM
prompt = f""" prompt = f"""
You are solving a hard problem using Chain of Thought reasoning. Think step-by-step. You are solving a complex problem step-by-step. Focus on generating the next logical thought in the sequence.
Problem: {problem} Problem: {problem}
Previous thoughts: Previous thoughts:
{thoughts_text if thoughts_text else "No previous thoughts yet."} {thoughts_text if thoughts_text else "No previous thoughts yet."}
Please generate the next thought (Thought {current_thought_number}). You can: Your task is to generate the next thought (Thought {current_thought_number}). Think about the current step required to move closer to the solution.
1. Continue with the next logical step
2. Revise a previous thought if needed
3. Branch into a new line of thinking
4. Generate a hypothesis if you have enough information
5. Verify a hypothesis against your reasoning
6. Provide a final solution if you've reached a conclusion
Current thought number: {current_thought_number} Format your response ONLY as a YAML structure enclosed in ```yaml ... ```:
Current estimate of total thoughts needed: {total_thoughts_estimate}
Format your response as a YAML structure with these fields:
- content: Your thought content
- next_thought_needed: true/false (true if more thinking is needed)
- is_revision: true/false (true if revising a previous thought)
- revises_thought: null or number (if is_revision is true)
- branch_from_thought: null or number (if branching from previous thought)
- branch_id: null or string (a short identifier for this branch)
- total_thoughts: number (your updated estimate if changed)
Only set next_thought_needed to false when you have a complete solution and the content explains the solution.
Output in YAML format:
```yaml ```yaml
content: | current_thinking: |
# If you have a complete solution, explain the solution here. # Your detailed thinking for this step.
# If it's a revision, provide the updated thought here. # If this step provides the final answer, state the final answer clearly here.
# If it's a branch, provide the new thought here. next_thought_needed: true # Set to false ONLY when 'current_thinking' contains the complete final answer.
next_thought_needed: true/false next_thought_planning: |
is_revision: true/false # Optional: Briefly describe what the *next* thought should focus on. Leave empty if none or if finished.
revises_thought: null or number
branch_from_thought: null or number
branch_id: null or string
total_thoughts: number
```""" ```"""
response = call_llm(prompt) response = call_llm(prompt)
# Simple YAML extraction
yaml_str = response.split("```yaml")[1].split("```")[0].strip() yaml_str = response.split("```yaml")[1].split("```")[0].strip()
thought_data = yaml.safe_load(yaml_str) thought_data = yaml.safe_load(yaml_str)
# --- Validation ---
# Ensure required keys are present after parsing
assert "current_thinking" in thought_data, "LLM response missing 'current_thinking'"
assert "next_thought_needed" in thought_data, "LLM response missing 'next_thought_needed'"
# 'next_thought_planning' is optional, so no assert needed, but we can ensure it exists
thought_data.setdefault("next_thought_planning", "")
# --- End Validation ---
# Add thought number # Add thought number
thought_data["thought_number"] = current_thought_number thought_data["thought_number"] = current_thought_number
return thought_data return thought_data
@ -92,25 +75,22 @@ total_thoughts: number
# Add the new thought to the list # Add the new thought to the list
if "thoughts" not in shared: if "thoughts" not in shared:
shared["thoughts"] = [] shared["thoughts"] = []
shared["thoughts"].append(exec_res) shared["thoughts"].append(exec_res)
# Update total_thoughts_estimate if changed # If we're done, extract the solution from the last thought's thinking
if "total_thoughts" in exec_res and exec_res["total_thoughts"] != shared.get("total_thoughts_estimate", 5): if exec_res.get("next_thought_needed") == False:
shared["total_thoughts_estimate"] = exec_res["total_thoughts"] shared["solution"] = exec_res["current_thinking"]
# If we're done, extract the solution from the last thought
if exec_res.get("next_thought_needed", True) == False:
shared["solution"] = exec_res["content"]
print("\n=== FINAL SOLUTION ===") print("\n=== FINAL SOLUTION ===")
print(exec_res["content"]) print(exec_res["current_thinking"])
print("======================\n") print("======================\n")
return "end" return "end"
# Otherwise, continue the chain # Otherwise, continue the chain
print(f"\n{exec_res['content']}") print(f"\nThought {exec_res['thought_number']}:")
print(f"Next thought needed: {exec_res.get('next_thought_needed', True)}") print(exec_res['current_thinking'])
print(f"Total thoughts estimate: {shared.get('total_thoughts_estimate', 5)}") if exec_res.get('next_thought_planning'):
print(f"\nNext step planned: {exec_res['next_thought_planning']}")
# print(f"Next thought needed: {exec_res.get('next_thought_needed')}") # Redundant if planning shown
print("-" * 50) print("-" * 50)
return "continue" # Continue the chain return "continue" # Continue the chain

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@ -5,7 +5,7 @@ def call_llm(prompt):
client = Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY", "your-api-key")) client = Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY", "your-api-key"))
response = client.messages.create( response = client.messages.create(
model="claude-3-7-sonnet-20250219", model="claude-3-7-sonnet-20250219",
max_tokens=1000, max_tokens=3000,
messages=[ messages=[
{"role": "user", "content": prompt} {"role": "user", "content": prompt}
] ]