Graph Workflow Evidence Dashboard - LLM Framework Showdown #23

Code Side-by-Side

SynapseKit (20 LoC)

LangChain (20 LoC)

LlamaIndex (15 LoC)

from synapsekit import StateGraph, END, TypedState, StateField

schema = TypedState(fields={
    'query':  StateField(default=''),
    'result': StateField(default=''),
})

def research(state):        return {'result': f'Research on: {state["query"]}'}
def detailed_answer(state): return {'result': state['result'] + ' [detailed]'}
def quick_answer(state):    return {'result': state['result'] + ' [quick]'}
def router(state):          return 'detailed' if len(state['query']) > 20 else 'quick'

graph = StateGraph(schema)
graph.add_node('research',        research)
graph.add_node('detailed_answer', detailed_answer)
graph.add_node('quick_answer',    quick_answer)
graph.set_entry_point('research')
graph.add_conditional_edge('research', router,
    {'detailed': 'detailed_answer', 'quick': 'quick_answer'})
graph.add_edge('detailed_answer', END)
graph.add_edge('quick_answer',    END)
app    = graph.compile()
result = app.run_sync({'query': query, 'result': ''})

from langgraph.graph import StateGraph, END
from typing import TypedDict

class State(TypedDict):
    query:  str
    result: str

def research(state):        return {'result': f'Research on: {state["query"]}'}
def detailed_answer(state): return {'result': state['result'] + ' [detailed]'}
def quick_answer(state):    return {'result': state['result'] + ' [quick]'}
def router(state):          return 'detailed' if len(state['query']) > 20 else 'quick'

graph = StateGraph(State)
graph.add_node('research',        research)
graph.add_node('detailed_answer', detailed_answer)
graph.add_node('quick_answer',    quick_answer)
graph.set_entry_point('research')
graph.add_conditional_edges('research', router,
    {'detailed': 'detailed_answer', 'quick': 'quick_answer'})
graph.add_edge('detailed_answer', END)
graph.add_edge('quick_answer',    END)
app    = graph.compile()
result = app.invoke({'query': query, 'result': ''})

from llama_index.core.agent import AgentWorkflow, FunctionAgent
from llama_index.core.tools import FunctionTool
from llama_index.core.llms import MockLLM

# No graph primitive - manual routing
state = {'query': query, 'result': ''}

def research_fn(query: str) -> str:
    return f'Research on: {query}'

def detailed_fn(research: str) -> str:
    return research + ' [detailed]'

def quick_fn(research: str) -> str:
    return research + ' [quick]'

research_result = research_fn(state['query'])
if len(state['query']) > 20:
    state['result'] = detailed_fn(research_result)
else:
    state['result'] = quick_fn(research_result)