Agent skill
dspy-2-modules
Sub-skill of dspy: 2. Modules.
Install this agent skill to your Project
npx add-skill https://github.com/vamseeachanta/workspace-hub/tree/main/.claude/skills/_archive/ai/prompting/dspy/2-modules
SKILL.md
2. Modules
2. Modules
ChainOfThought for Complex Reasoning:
class TechnicalQA(dspy.Signature):
"""Answer technical engineering questions with reasoning."""
context = dspy.InputField(desc="Technical context and background")
question = dspy.InputField(desc="Technical question to answer")
answer = dspy.OutputField(desc="Detailed technical answer")
# ChainOfThought adds reasoning before answering
class TechnicalExpert(dspy.Module):
def __init__(self):
super().__init__()
self.answer_question = dspy.ChainOfThought(TechnicalQA)
def forward(self, context, question):
result = self.answer_question(context=context, question=question)
return result
# Usage
expert = TechnicalExpert()
result = expert(
context="""
Catenary mooring systems use the weight of the chain to provide
restoring force. The touchdown point moves as the vessel offsets.
Line tension is a function of the catenary geometry and pretension.
""",
question="How does water depth affect mooring line tension?"
)
print(f"Reasoning: {result.rationale}")
print(f"Answer: {result.answer}")
Multi-Stage Pipeline Module:
class DocumentSummary(dspy.Signature):
"""Summarize a technical document."""
document = dspy.InputField()
summary = dspy.OutputField()
class KeyPointExtraction(dspy.Signature):
"""Extract key points from a summary."""
summary = dspy.InputField()
key_points = dspy.OutputField(desc="List of 3-5 key points")
class ActionItemGeneration(dspy.Signature):
"""Generate action items from key points."""
key_points = dspy.InputField()
action_items = dspy.OutputField(desc="List of actionable next steps")
class DocumentProcessor(dspy.Module):
"""Multi-stage document processing pipeline."""
def __init__(self):
super().__init__()
self.summarize = dspy.ChainOfThought(DocumentSummary)
self.extract_points = dspy.Predict(KeyPointExtraction)
self.generate_actions = dspy.Predict(ActionItemGeneration)
def forward(self, document):
# Stage 1: Summarize
summary_result = self.summarize(document=document)
# Stage 2: Extract key points
points_result = self.extract_points(summary=summary_result.summary)
# Stage 3: Generate actions
actions_result = self.generate_actions(key_points=points_result.key_points)
return dspy.Prediction(
summary=summary_result.summary,
key_points=points_result.key_points,
action_items=actions_result.action_items
)
# Usage
processor = DocumentProcessor()
result = processor(document="[Long engineering document text...]")
print(f"Summary: {result.summary}")
print(f"Key Points: {result.key_points}")
print(f"Actions: {result.action_items}")
ReAct Module for Tool Use:
class CalculateTension(dspy.Signature):
"""Calculate mooring line tension."""
depth = dspy.InputField(desc="Water depth in meters")
line_length = dspy.InputField(desc="Line length in meters")
pretension = dspy.InputField(desc="Pretension in kN")
result = dspy.OutputField(desc="Tension calculation result")
class SearchStandards(dspy.Signature):
"""Search engineering standards database."""
query = dspy.InputField(desc="Search query")
standards = dspy.OutputField(desc="Relevant standards found")
class EngineeringReActAgent(dspy.Module):
"""Agent that can reason and act using tools."""
def __init__(self):
super().__init__()
self.react = dspy.ReAct(
signature="question -> answer",
tools=[self.calculate_tension, self.search_standards]
)
def calculate_tension(self, depth: float, line_length: float, pretension: float) -> str:
"""Calculate approximate mooring line tension."""
import math
suspended = math.sqrt(line_length**2 - depth**2)
tension = pretension * (1 + depth / suspended * 0.1)
return f"Estimated tension: {tension:.1f} kN"
def search_standards(self, query: str) -> str:
"""Search for relevant engineering standards."""
standards_db = {
"mooring": ["API RP 2SK", "DNV-OS-E301", "ISO 19901-7"],
"fatigue": ["DNV-RP-C203", "API RP 2A-WSD"],
"structural": ["AISC 360", "API RP 2A-WSD"]
}
for key, value in standards_db.items():
if key in query.lower():
return f"Relevant standards: {', '.join(value)}"
return "No specific standards found for query"
def forward(self, question):
return self.react(question=question)
# Usage
agent = EngineeringReActAgent()
result = agent(
question="What is the tension for a 350m line in 100m depth with 500kN pretension?"
)
print(result.answer)
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