wanyaokun
75 lines
2.9 KiB
Python
75 lines
2.9 KiB
Python
import requests
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from llama_index.postprocessor.xinference_rerank import XinferenceRerank
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from llama_index.core.bridge.pydantic import Field
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from typing import List, Optional
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from llama_index.core.bridge.pydantic import Field
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from llama_index.core.callbacks import CBEventType, EventPayload
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from llama_index.core.instrumentation import get_dispatcher
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from llama_index.core.instrumentation.events.rerank import (
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ReRankEndEvent,
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ReRankStartEvent,
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)
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from llama_index.core.schema import NodeWithScore, QueryBundle, MetadataMode
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dispatcher = get_dispatcher(__name__)
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class CustomXinFerenceRerank(XinferenceRerank):
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score_threshold: float = Field(default=0.3,description="分数阈值")
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def _postprocess_nodes(
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self,
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nodes: List[NodeWithScore],
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query_bundle: Optional[QueryBundle] = None,
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) -> List[NodeWithScore]:
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dispatcher.event(
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ReRankStartEvent(
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query=query_bundle,
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nodes=nodes,
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top_n=self.top_n,
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model_name=self.model,
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)
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)
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if query_bundle is None:
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raise ValueError("Missing query bundle.")
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if len(nodes) == 0:
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return []
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with self.callback_manager.event(
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CBEventType.RERANKING,
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payload={
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EventPayload.NODES: nodes,
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EventPayload.MODEL_NAME: self.model,
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EventPayload.QUERY_STR: self.get_query_str(query_bundle),
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EventPayload.TOP_K: self.top_n,
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},
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) as event:
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headers = {"Content-Type": "application/json"}
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json_data = {
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"model": self.model,
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"query": self.get_query_str(query_bundle),
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"documents": [
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node.node.get_content(metadata_mode=MetadataMode.EMBED)
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for node in nodes
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],
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}
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response = requests.post(
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url=f"{self.base_url}/v1/rerank", headers=headers, json=json_data
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)
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response.encoding = "utf-8"
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if response.status_code != 200:
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raise Exception(
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f"Xinference call failed with status code {response.status_code}."
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f"Details: {response.text}"
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)
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rerank_nodes = []
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for result in response.json()["results"]:
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node = NodeWithScore(
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node=nodes[result["index"]].node, score=result["relevance_score"]
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)
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if node.score > self.score_threshold:
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rerank_nodes.append(node)
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if len(rerank_nodes) > self.top_n:
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rerank_nodes = sorted(rerank_nodes,key=lambda x:x.score,reverse = True)[:self.top_n]
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event.on_end(payload={EventPayload.NODES: rerank_nodes})
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dispatcher.event(ReRankEndEvent(nodes=rerank_nodes))
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return rerank_nodes |