LlamaIndex+本地部署InternLM实践RAG的时候，结果不理想，想知道怎么优化呢？
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Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 20/100
- Issue type
- Bug
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- python
- Domain
- ai, machine-learning
Research direction
Start with the example code from the “LlamaIndex+本地部署InternLM实践” documentation and reproduce the PDF-based knowledge-base question answering described in the issue. Compare the reported behavior using the original model, qwen7b, chatglm6b, and bge-large-zh, recording the questions and results. Done would require identifying the cause of the poor answers and documenting a validated optimization.
Written by the indexing model from the issue text.
Description
我按照文档《LlamaIndex+本地部署InternLM实践》中的示例代码，使用一个pdf文件作为知识库，模型我有尝试替换成qwen7b和chatglm6b的，embed模型也换成了bge-large-zh，但是基于知识库的问答，结果比较差，想知道问题出在哪里呢，怎么优化呢？
- Dominant language
- Python
- Stars
- 2k
- Forks
- 1.5k
- PR merge metrics
- No merged PRs in 30d
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