feat: 功能验证
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18
.env.example
18
.env.example
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@ -1,3 +1,19 @@
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LOGGER_LEVEL=DEBUG
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VERSION=1.0.0
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HOST=0.0.0.0
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PORT=8011
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PORT=8011
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# LLM_API_KEY=sk-local-827ccb0eea8a706c4c34a16891f84e7b
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# LLM_API_HOST=http://localhost:8022/v1
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# LLM_MODEL=Qwen2.5
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LLM_API_KEY=sk-390feb24-daee-11f0-a581-0242ac150003
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LLM_API_HOST=http://58.214.239.10:18080/app-2512170147-llm/v1
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LLM_MODEL=Qwen3-30B
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EMBEDDING_API_KEY=sk-local-827ccb0eea8a706c4c34a16891f84e7b
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EMBEDDING_API_HOST=http://localhost:8023/v1
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EMBEDDING_MODEL=Qwen3-Embedding
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EMBEDDING_DIMS=1024
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ES_HOST=http://localhost
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ES_PORT=9210
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ES_USER=elastic
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ES_PASSWORD=12345
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16
search.es
16
search.es
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@ -25,5 +25,21 @@ GET /test_kb/_search
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]
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}
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GET /test_kb_1/_search
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{
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"size": 5,
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"query": {
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"match": {
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"content": "美猴王"
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}
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},
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"_source": [
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"title",
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"content",
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"type",
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"created_at"
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]
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}
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// 删除
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// DELETE /test_kb
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@ -183,10 +183,7 @@ def rag_user_prompt(query: str, documents: list[dict]) -> str:
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用户问题: {query}
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回答要求:
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1. 列出完整列表。
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2. 引用文档原文时,用“文档 i 原文: …”标注。
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3. 每条用编号列出。
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4. 如果文档中没有相关信息,请直接回复: "文档未提供相关信息"。
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一到两句话回复
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"""
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logger.debug(prompt)
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return prompt
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@ -14,17 +14,16 @@ async def test_embedding():
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logger.debug("file to es")
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shared = {
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"files": [ "./files/山海经01.txt"],
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"files": [ "./files/西游记.txt"],
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"documents": [], # [{text, file_name, file_type, uuid, embedding}]
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"index": "test_kb",
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"index": "test_kb_1",
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}
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readNode = nodes.ReadDocumentsNode()
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chunkNode = nodes.ChunkDocumentsNode()
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embeddingNode = nodes.EmbeddingDocumentsNode()
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writeToESNode = nodes.WriteDocumentsToESNode()
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readNode >> chunkNode >> embeddingNode
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# >> writeToESNode
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readNode >> chunkNode >> embeddingNode >> writeToESNode
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flow = AsyncFlow(readNode)
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await flow.run_async(shared)
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@ -42,10 +41,10 @@ async def test_search():
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logger.debug("search from es")
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shared = {
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"text": "哪里盛产金属矿物",
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"text": "哪里盛产矿石",
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"index": "test_kb",
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"top_k": 1,
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"results": [], # [{es_id, doc_id, title, type, created_at, score, content}]
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"top_k": 5,
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"results": [], # [{es_id, doc_id, title, type, created_at, score, content}]
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}
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embeddingNode = nodes.EmbeddingNode()
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