249 lines
6.5 KiB
YAML
249 lines
6.5 KiB
YAML
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# =============================================================================
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# BotanicalBaseAgent 配置文件
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# =============================================================================
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# 此文件包含基因家族分析Agent的全局配置
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# 修改后需要重启Agent生效
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# =============================================================================
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# -----------------------------------------------------------------------------
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# 基础路径配置
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# -----------------------------------------------------------------------------
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paths:
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# 工作空间根目录（分析结果存放位置）
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workspace: "workspace"
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# 脚本目录（Perl/R脚本位置）
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scripts: "scripts"
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# 数据目录
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data: "data"
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# Pfam HMM模型目录
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pfam_hmm: "data/pfam_hmm"
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# 参考序列目录（如拟南芥家族成员序列）
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reference: "data/reference"
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# 基因组数据目录
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genomes: "data/genomes"
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# 知识库文档目录
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kb_docs: "kb_docs"
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# 向量数据库存储目录
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kb_store: "kb_store"
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# -----------------------------------------------------------------------------
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# 工具默认参数
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# -----------------------------------------------------------------------------
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tools:
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# HMMER参数
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hmmsearch:
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# 默认使用可信阈值
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use_cut_tc: true
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# 备用E-value阈值（当use_cut_tc=false时使用）
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evalue: 1.0e-5
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# CPU核心数
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cpu: 4
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# 超时时间（秒）
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timeout: 3600
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# BLAST参数
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blast:
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# E-value阈值
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evalue: 1.0e-5
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# 序列一致性阈值（%）
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identity_threshold: 30.0
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# 线程数
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num_threads: 4
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# 输出格式
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outfmt: "6 std qlen slen"
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# MUSCLE参数
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muscle:
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# 最大迭代次数
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max_iterations: 16
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# 超时时间（秒）
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timeout: 3600
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# MAFFT参数
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mafft:
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# 默认算法（auto会根据序列数量自动选择）
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algorithm: "auto"
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# 最大迭代次数
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max_iterations: 1000
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# 线程数
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threads: 4
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# 超时时间（秒）
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timeout: 7200
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# 自动选择算法的阈值
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auto_selection:
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# 序列数<=此值时使用L-INS-i
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linsi_max_seqs: 200
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# 序列数<=此值时使用FFT-NS-i
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fftnsi_max_seqs: 500
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# trimAl参数
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trimal:
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# 默认修剪方法
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method: "gappyout"
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# 可选方法: gappyout, strict, automated1
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# seqtk参数
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seqtk:
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# 是否优先使用seqtk（比Python实现更快）
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prefer_seqtk: true
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# -----------------------------------------------------------------------------
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# 鉴定流程参数
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# -----------------------------------------------------------------------------
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identification:
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# 结果合并方法
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merge_method: "intersection" # intersection（交集，推荐）或 union（并集）
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# 最小候选基因数警告阈值
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min_candidates_warning: 5
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# 最大候选基因数警告阈值（可能有假阳性）
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max_candidates_warning: 500
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# -----------------------------------------------------------------------------
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# 蛋白特征分析参数
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# -----------------------------------------------------------------------------
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features:
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# 理化性质计算
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physicochemical:
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# 是否使用R脚本（更准确）
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use_r_script: true
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# R脚本路径
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r_script: "scripts/fasta_pI_mw.R"
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# 跨膜结构域预测
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transmembrane:
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# 首选方法: deeptmhmm, tmhmm, simple
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preferred_method: "auto"
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# 疏水性扫描窗口大小
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window_size: 19
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# 疏水性阈值
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hydrophobicity_threshold: 1.6
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# 亚细胞定位预测
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subcellular:
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# 首选方法: local, online, feature
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preferred_method: "auto"
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# 本地脚本路径
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local_script: "scripts/get_Plant_mPLoc_out.py"
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# 在线服务超时（秒）
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online_timeout: 300
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# -----------------------------------------------------------------------------
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# 比对和进化分析参数
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# -----------------------------------------------------------------------------
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alignment:
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# 是否自动生成多种格式
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auto_convert_formats: true
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# 输出格式列表
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output_formats:
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- "fasta"
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- "phylip"
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- "nexus"
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# 是否自动修剪比对
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auto_trim: false
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# 可视化设置
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visualization:
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# 是否自动生成可视化
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auto_generate: false
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# R脚本路径
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r_script: "scripts/msa_figure.R"
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# -----------------------------------------------------------------------------
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# LLM配置
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# -----------------------------------------------------------------------------
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llm:
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# 模型提供商: openai, anthropic, local
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provider: "openai"
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# OpenAI配置
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openai:
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model: "gpt-4"
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temperature: 0
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max_tokens: 4096
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# 本地模型配置（如使用Ollama）
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local:
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base_url: "http://localhost:11434/v1"
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model: "llama2"
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temperature: 0
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# -----------------------------------------------------------------------------
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# 向量数据库配置
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# -----------------------------------------------------------------------------
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vector_store:
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# 类型: faiss, chroma
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type: "faiss"
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# 嵌入模型
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embedding:
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model: "BAAI/bge-m3"
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# 本地模型路径（如果已下载）
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local_path: "models/bge-m3_from_web"
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# 设备: cpu, cuda
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device: "cpu"
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# 检索参数
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retrieval:
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# 返回的文档数量
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top_k: 5
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# 相似度阈值
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score_threshold: 0.5
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# -----------------------------------------------------------------------------
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# 搜索配置
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# -----------------------------------------------------------------------------
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search:
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# Tavily搜索
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tavily:
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# 搜索深度: basic, advanced
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search_depth: "advanced"
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# 最大结果数
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max_results: 5
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# SearchAPI
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searchapi:
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engine: "google"
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max_results: 5
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# -----------------------------------------------------------------------------
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# 日志配置
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# -----------------------------------------------------------------------------
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logging:
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# 日志级别: DEBUG, INFO, WARNING, ERROR
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level: "INFO"
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# 日志文件
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file: "logs/agent.log"
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# 是否输出到控制台
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console: true
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# 日志格式
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format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
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# -----------------------------------------------------------------------------
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# 输出配置
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# -----------------------------------------------------------------------------
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output:
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# 是否保存中间结果
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save_intermediate: true
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# 是否生成分析报告
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generate_report: true
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# 报告格式: markdown, html, pdf
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report_format: "markdown"
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# 结果文件命名模板
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naming_template: "{species}_{family}_{date}"
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