54 lines
2.1 KiB
Python
54 lines
2.1 KiB
Python
from flask import Flask, request, Response
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import os
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from dotenv import load_dotenv
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from rag2_0.intent_recognition import IntentRecognizer
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import json
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import time
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# 加载环境变量
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load_dotenv()
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app = Flask(__name__)
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# 初始化意图识别器
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api_key = os.getenv("OPENAI_API_KEY")
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base_url = os.getenv("OPENAI_API_BASE")
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model_name = os.getenv("LLM_MODEL_NAME", "gpt-3.5-turbo")
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recognizer = IntentRecognizer(api_key=api_key, base_url=base_url, model_name=model_name)
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@app.route('/intent_recognize', methods=['POST'])
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def intent_recognize():
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try:
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data = request.get_json(force=True)
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query = data.get('query')
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if not query:
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return Response(json.dumps({"error": "缺少query参数"}, ensure_ascii=False), content_type='application/json; charset=utf-8', status=400)
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start_time = time.time()
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classification, keywords, rewrite, query_keys = recognizer.process_query(query)
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end_time = time.time()
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print(f"意图识别耗时: {end_time - start_time:.2f}秒")
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# keywords对象转为字符串
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keywords_str = ""
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if keywords and keywords.terms:
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term_details = []
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for term in keywords.terms:
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term_info = {
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"名称": term.name,
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"同义词": ";".join(term.synonymous) if term.synonymous else "",
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"描述": term.description
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}
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term_details.append(term_info)
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keywords_str = term_details
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result = {
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"source_query": query,
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"source_query_keys": query_keys,
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"vertical_classification": classification.vertical_classification,
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"sub_classification": classification.sub_classification,
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"rewrite_query": rewrite.rewrite,
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"keywords": keywords_str
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}
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return Response(json.dumps(result, ensure_ascii=False), content_type='application/json; charset=utf-8')
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except Exception as e:
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return Response(json.dumps({"error": str(e)}, ensure_ascii=False), content_type='application/json; charset=utf-8', status=500)
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if __name__ == "__main__":
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app.run(host="0.0.0.0", port=8001) |