4.3 Prompt Chaining and Validation-Retry Loops

# Step 1: Extract key information
extraction = client.messages.create(
    messages=[{"role": "user", "content": f"Extract all dates, names, and amounts from: {document}"}]
)

# Step 2: Validate extracted data
validation = client.messages.create(
    messages=[{"role": "user", "content": f"Validate this data for consistency: {extraction.content[0].text}"}]
)

# Step 3: Transform to final format
output = client.messages.create(
    messages=[{"role": "user", "content": f"Convert this validated data to SQL INSERT statements: {validation.content[0].text}"}]
)

def chain_with_validation(prompt, validator_fn, max_retries=3):
    messages = [{"role": "user", "content": prompt}]
    
    for attempt in range(max_retries):
        response = client.messages.create(messages=messages)
        output = response.content[0].text
        
        is_valid, error = validator_fn(output)
        if is_valid:
            return output
        
        # Add validation feedback and retry
        messages.append({"role": "assistant", "content": output})
        messages.append({"role": "user", "content": f"This output has an issue: {error}. Please fix it."})
    
    raise ValueError(f"Failed validation after {max_retries} attempts")

steps = [extract, validate, transform, format]

for step_fn in steps:
    result = step_fn(result)
    if not result.success:
        return f"Chain failed at step: {step_fn.__name__}: {result.error}"

classification = classify(input)

if classification == "bug_report":
    result = bug_analysis_chain(input)
elif classification == "feature_request":
    result = feature_analysis_chain(input)

context = {"original_input": input}

context["extracted"] = extract(input)
context["validated"] = validate(context["extracted"])
context["enriched"] = enrich(context)  # ใช้ทุก context ที่สะสมมา