chore(config): update experiment suffix, prefix, and weight parameters

Author: TaoShuchang

tutorial/example_deep_finance/deep_finance_single.sh

@@ -3,27 +3,27 @@ set -e
 #===============================================================================
 # 1. 配置区域 - 用户只需修改这里
 #===============================================================================
-SUFFIX="ajet_deep_finance"     # 实验后缀，影响所有日志和实验名称
-PREFIX="open"                        # 实验前缀，影响日志和实验所在文件夹
+SUFFIX="newjudge"     # 实验后缀，影响所有日志和实验名称
+PREFIX="ajet_newjudge"                        # 实验前缀，影响日志和实验所在文件夹
 
 # OpenJudge 模型配置
 OPENJUDGE_LLM='qwen-flash'        # OpenJudge 评分模型
 RM_LLM='qwen-max'                 # RM Gallery 评分模型
 JUDGE_CONCURRENCY=10
 
 # 奖励权重配置
-RM_WEIGHT=0.4
-CITATION_AUDIT_WEIGHT=0.2
-REPORT_RESOLUTION_WEIGHT=0.2
-TRAJECTORY_FAITHFULNESS_WEIGHT=0.2
+RM_WEIGHT=0.5
+PRESENTATION_QUALITY_WEIGHT=0.25
+GROUNDING_WEIGHT=0.25
 
 # 训练参数配置
 NUM_REPEAT=4        # group size，每个query rollout NUM_REPEAT次
 TRAIN_BATCH_SIZE=32  # 训练batchsize
 NUM_STEPS=6         # 每个样本step轮数
 DEEPFINANCE_TOOL_RESULT_MAX_CHARS=10000
 
-# 主目录
+# 主目录（需要更改）
+export AJET_ROOT="/mnt/data_cpfs/taoshuchang.tsc/deepresearch/AgentJet_new"
 
 NNODES=${WORLD_SIZE}
 
@@ -55,70 +55,23 @@ sed -e "s|{{SUFFIX}}|${SUFFIX}|g" \
     -e "s|{{MODEL_PATH}}|${MODEL_PATH}|g" \
     -e "s|{{NNODES}}|${NNODES}|g" \
     -e "s|{{RM_WEIGHT}}|${RM_WEIGHT}|g" \
-    -e "s|{{CITATION_AUDIT_WEIGHT}}|${CITATION_AUDIT_WEIGHT}|g" \
+    -e "s|{{PRESENTATION_QUALITY_WEIGHT}}|${PRESENTATION_QUALITY_WEIGHT}|g" \
+    -e "s|{{GROUNDING_WEIGHT}}|${GROUNDING_WEIGHT}|g" \
     -e "s|{{OPENJUDGE_LLM}}|${OPENJUDGE_LLM}|g" \
     -e "s|{{RM_LLM}}|${RM_LLM}|g" \
     -e "s|{{JUDGE_CONCURRENCY}}|${JUDGE_CONCURRENCY}|g" \
-    -e "s|{{REPORT_RESOLUTION_WEIGHT}}|${REPORT_RESOLUTION_WEIGHT}|g" \
-    -e "s|{{TRAJECTORY_FAITHFULNESS_WEIGHT}}|${TRAJECTORY_FAITHFULNESS_WEIGHT}|g" \
     -e "s|{{NUM_REPEAT}}|${NUM_REPEAT}|g" \
     -e "s|{{NUM_STEPS}}|${NUM_STEPS}|g" \
     -e "s|{{TRAIN_BATCH_SIZE}}|${TRAIN_BATCH_SIZE}|g" \
     -e "s|{{TRAIN_DATA_PATH}}|${TRAIN_DATA_PATH}|g" \
     -e "s|{{VAL_DATA_PATH}}|${VAL_DATA_PATH}|g" \
-    -e "s|{{ENV_SERVICE_URL}}|${ENV_SERVICE_URL}|g" \
     -e "s|{{TRAIN_REF_ANS_PATH}}|${TRAIN_REF_ANS_PATH}|g" \
     -e "s|{{VAL_REF_ANS_PATH}}|${VAL_REF_ANS_PATH}|g" \
     -e "s|{{CKPT_SAVE_PATH}}|${CKPT_SAVE_PATH}|g" \
     ${AJET_ROOT}/${CONFIG_TEMPLATE} > ${CONFIG_FILE}
 
 echo "配置文件已生成: ${CONFIG_FILE}"
-echo "参数确认: RM=${RM_WEIGHT}, Citation=${CITATION_AUDIT_WEIGHT}, OpenJudge=${OPENJUDGE_LLM}, RM_LLM=${RM_LLM}"
-
-#===============================================================================
-# 3. 环境配置
-#===============================================================================
-# MongoDB 缓存配置
-CACHE_TYPE="mongodb"
-MONGO_URI="mongodb://${ADDR}:27117/"
-MONGO_DB_NAME="finworld_cache"
-MONGO_COLLECTION_NAME="tool_cache"
-export CACHE_TYPE MONGO_URI MONGO_DB_NAME MONGO_COLLECTION_NAME
-
-# DeepFinance MCP 配置
-DEEPFINANCE_MCP_CONFIG="${AJET_ROOT}/tutorial/example_deep_finance/config/mcp_finance_tool_generated.json"
-
-# 动态生成 MCP 配置文件
-mkdir -p $(dirname ${DEEPFINANCE_MCP_CONFIG})
-cat > ${DEEPFINANCE_MCP_CONFIG} << EOF
-{
-    "mcpServers": {
-      "flowllm": {
-        "transport": "sse",
-        "url": "http://${ADDR}:${MCP_PORT}/sse",
-        "timeout": 600,
-        "sse_read_timeout": 1200
-      }
-    }
-}
-EOF
-export DEEPFINANCE_MCP_CONFIG  DEEPFINANCE_TOOL_RESULT_MAX_CHARS
-
-# 其他服务配置
-HF_ENDPOINT="https://hf-mirror.com"
-ES_HOSTS="http://11.160.132.46:8200"
-export HF_ENDPOINT ES_HOSTS
-
-# log 文件位置
-CURRENT_TIME=$(date "+%Y%m%d_%H%M%S")
-LOG_DIR="${AJET_ROOT}/logs/${PREFIX}"
-MASTER_IP_FILE="${LOG_DIR}/master-ip_${SUFFIX}.log"
-ENV_SERVICE_LOG="${LOG_DIR}/env_service_${SUFFIX}_${CURRENT_TIME}.log"
-TRAIN_LOG="${LOG_DIR}/train_${SUFFIX}_${CURRENT_TIME}.log"
-
-# 多机训练参数配置
-GPUS_PER_NODE=8
-EXPECTED_WORKERS=$WORLD_SIZE
+echo "参数确认: RM=${RM_WEIGHT}, PresentationQuality=${PRESENTATION_QUALITY_WEIGHT}, Grounding=${GROUNDING_WEIGHT}, OpenJudge=${OPENJUDGE_LLM}, RM_LLM=${RM_LLM}"
 
 
 #===============================================================================
@@ -162,7 +115,6 @@ export RAY_CLUSTER_MODE="multi_node"
 #===============================================================================
 # 6. 主流程
 #===============================================================================
-log "开始多机多卡训练: ${SUFFIX}"
 log "节点数: ${NNODES}, 每节点GPU数: ${GPUS_PER_NODE}"
 mkdir -p ${LOG_DIR}
 mkdir -p $(dirname ${CONFIG_FILE})