refactor
This commit is contained in:
zachary62
+81
-165
@@ -1,184 +1,100 @@
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import asyncio
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import warnings
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import asyncio, warnings
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class BaseNode:
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# preprocess(): this is for compute intensive preparation tasks, before the LLM call
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# process(): this is for the LLM call, and should be idempotent for retries
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# postprocess(): this is to summarize the result and retrun the condition for the successor node
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def __init__(self):
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self.params, self.successors = {}, {}
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def set_params(self, params): # make sure params is immutable
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self.params = params # must be immutable during pre/post/process
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def add_successor(self, node, condition="default"):
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if condition in self.successors:
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warnings.warn(f"Overwriting existing successor for condition '{condition}'")
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self.successors[condition] = node # maps condition -> successor node
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return node
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def preprocess(self, shared_storage):
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return None # will be passed to process() and postprocess()
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def process(self, shared_storage, prep_result):
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return None # will be passed to postprocess()
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def _process(self, shared_storage, prep_result):
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# Could have retry logic or other wrap logic
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return self.process(shared_storage, prep_result)
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def postprocess(self, shared_storage, prep_result, proc_result):
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return "default" # condition for next node
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def _run(self, shared_storage):
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prep_result = self.preprocess(shared_storage)
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proc_result = self._process(shared_storage, prep_result)
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return self.postprocess(shared_storage, prep_result, proc_result)
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def run(self, shared_storage):
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if self.successors:
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warnings.warn("This node has successor nodes. To run its successors, wrap this node in a parent Flow and use that Flow.run() instead.")
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return self._run(shared_storage)
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def __rshift__(self, other):
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# chaining: node1 >> node2
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return self.add_successor(other)
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def __sub__(self, condition):
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# condition-based chaining: node - "some_condition" >> next_node
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if isinstance(condition, str):
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return _ConditionalTransition(self, condition)
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def __init__(self): self.params, self.successors = {}, {}
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def set_params(self, params): self.params = params
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def add_successor(self, node, cond="default"):
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if cond in self.successors: warnings.warn(f"Overwriting existing successor for '{cond}'")
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self.successors[cond] = node; return node
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def preprocess(self, s): return None
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def process(self, s, p): return None
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def _process(self, s, p): return self.process(s, p)
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def postprocess(self, s, pr, r): return "default"
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def _run(self, s):
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pr = self.preprocess(s)
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r = self._process(s, pr)
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return self.postprocess(s, pr, r)
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def run(self, s):
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if self.successors: warnings.warn("Has successors; use Flow.run() instead.")
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return self._run(s)
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def __rshift__(self, other): return self.add_successor(other)
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def __sub__(self, cond):
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if isinstance(cond, str): return _ConditionalTransition(self, cond)
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raise TypeError("Condition must be a string")
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class _ConditionalTransition:
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def __init__(self, source_node, condition):
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self.source_node = source_node
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self.condition = condition
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def __rshift__(self, target_node):
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return self.source_node.add_successor(target_node, self.condition)
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def __init__(self, src, c): self.src, self.c = src, c
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def __rshift__(self, tgt): return self.src.add_successor(tgt, self.c)
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class Node(BaseNode):
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def __init__(self, max_retries=1):
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super().__init__()
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self.max_retries = max_retries
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def process_after_fail(self, shared_storage, data, exc):
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raise exc
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def _process(self, shared_storage, data):
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for attempt in range(self.max_retries):
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try:
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return super()._process(shared_storage, data)
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def __init__(self, max_retries=1): super().__init__(); self.max_retries = max_retries
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def process_after_fail(self, s, d, e): raise e
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def _process(self, s, d):
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for i in range(self.max_retries):
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try: return super()._process(s, d)
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except Exception as e:
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if attempt == self.max_retries - 1:
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return self.process_after_fail(shared_storage, data, e)
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if i == self.max_retries - 1: return self.process_after_fail(s, d, e)
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class BatchNode(Node):
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def preprocess(self, shared_storage):
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# return an iterable of items, one for each run
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return []
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def process(self, shared_storage, item): # process() is called for each item
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return None
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def _process(self, shared_storage, items):
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results = []
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for item in items:
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# Here, 'item' is passed in place of 'prep_result' from the BaseNode's perspective.
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r = super()._process(shared_storage, item)
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results.append(r)
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return results
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class AsyncNode(Node):
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def postprocess(self, shared_storage, prep_result, proc_result):
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raise NotImplementedError("AsyncNode requires postprocess_async, and should be run in an AsyncFlow")
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async def postprocess_async(self, shared_storage, prep_result, proc_result):
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await asyncio.sleep(0) # trivial async pause (no-op)
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return "default"
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async def run_async(self, shared_storage):
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if self.successors:
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warnings.warn("This node has successor nodes. To run its successors, wrap this node in a parent AsyncFlow and use that AsyncFlow.run_async() instead.")
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return await self._run_async(shared_storage)
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async def _run_async(self, shared_storage):
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prep_result = self.preprocess(shared_storage)
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proc_result = self._process(shared_storage, prep_result)
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return await self.postprocess_async(shared_storage, prep_result, proc_result)
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def _run(self, shared_storage):
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raise RuntimeError("AsyncNode requires asynchronous execution. Use 'await node.run_async()' if inside an async function, or 'asyncio.run(node.run_async())' if in synchronous code.")
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def preprocess(self, s): return []
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def process(self, s, item): return None
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def _process(self, s, items): return [super(Node, self)._process(s, i) for i in items]
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class BaseFlow(BaseNode):
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def __init__(self, start_node):
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super().__init__()
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self.start_node = start_node
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def __init__(self, start_node): super().__init__(); self.start_node = start_node
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def get_next_node(self, curr, c):
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nxt = curr.successors.get(c)
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if nxt is None and curr.successors: warnings.warn(f"Flow ends. '{c}' not found in {list(curr.successors.keys())}")
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return nxt
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def get_next_node(self, current_node, condition):
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next_node = current_node.successors.get(condition, None)
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if next_node is None and current_node.successors:
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warnings.warn(f"Flow will end. Condition '{condition}' not found among possible conditions: {list(current_node.successors.keys())}")
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return next_node
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class Flow(BaseFlow):
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def _process(self, shared_storage, params=None):
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current_node = self.start_node
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params = params if params is not None else self.params.copy()
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while current_node:
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current_node.set_params(params)
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condition = current_node._run(shared_storage)
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current_node = self.get_next_node(current_node, condition)
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def process(self, shared_storage, prep_result):
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raise NotImplementedError("Flow should not process directly")
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class AsyncFlow(BaseFlow, AsyncNode):
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async def _process_async(self, shared_storage, params=None):
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current_node = self.start_node
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params = params if params is not None else self.params.copy()
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while current_node:
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current_node.set_params(params)
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if hasattr(current_node, "run_async") and callable(current_node.run_async):
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condition = await current_node._run_async(shared_storage)
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else:
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condition = current_node._run(shared_storage)
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current_node = self.get_next_node(current_node, condition)
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async def _run_async(self, shared_storage):
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prep_result = self.preprocess(shared_storage)
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await self._process_async(shared_storage)
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return await self.postprocess_async(shared_storage, prep_result, None)
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def _process(self, s, p=None):
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curr, p = self.start_node, (p if p is not None else self.params.copy())
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while curr:
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curr.set_params(p)
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c = curr._run(s)
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curr = self.get_next_node(curr, c)
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def process(self, s, pr): raise NotImplementedError("Use Flow._process(...) instead")
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class BaseBatchFlow(BaseFlow):
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def preprocess(self, shared_storage):
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return [] # return an iterable of parameter dictionaries
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def preprocess(self, s): return []
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class BatchFlow(BaseBatchFlow, Flow):
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def _run(self, shared_storage):
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prep_result = self.preprocess(shared_storage)
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for param_dict in prep_result:
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merged_params = self.params.copy()
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merged_params.update(param_dict)
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self._process(shared_storage, params=merged_params)
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return self.postprocess(shared_storage, prep_result, None)
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def _run(self, s):
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pr = self.preprocess(s)
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for d in pr:
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mp = self.params.copy(); mp.update(d)
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self._process(s, mp)
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return self.postprocess(s, pr, None)
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class AsyncNode(Node):
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def postprocess(self, s, pr, r): raise NotImplementedError("Use postprocess_async")
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async def postprocess_async(self, s, pr, r): await asyncio.sleep(0); return "default"
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async def run_async(self, s):
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if self.successors: warnings.warn("Has successors; use AsyncFlow.run_async() instead.")
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return await self._run_async(s)
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async def _run_async(self, s):
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pr = self.preprocess(s)
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r = self._process(s, pr)
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return await self.postprocess_async(s, pr, r)
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def _run(self, s): raise RuntimeError("AsyncNode requires async execution")
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class AsyncFlow(BaseFlow, AsyncNode):
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async def _process_async(self, s, p=None):
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curr, p = self.start_node, (p if p else self.params.copy())
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while curr:
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curr.set_params(p)
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c = await curr._run_async(s) if hasattr(curr, "run_async") else curr._run(s)
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curr = self.get_next_node(curr, c)
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async def _run_async(self, s):
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pr = self.preprocess(s)
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await self._process_async(s)
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return await self.postprocess_async(s, pr, None)
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class BatchAsyncFlow(BaseBatchFlow, AsyncFlow):
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async def _run_async(self, shared_storage):
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prep_result = self.preprocess(shared_storage)
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for param_dict in prep_result:
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merged_params = self.params.copy()
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merged_params.update(param_dict)
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await self._process_async(shared_storage, params=merged_params)
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return await self.postprocess_async(shared_storage, prep_result, None)
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async def _run_async(self, s):
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pr = self.preprocess(s)
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for d in pr:
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mp = self.params.copy(); mp.update(d)
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await self._process_async(s, mp)
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return await self.postprocess_async(s, pr, None)
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