DB-GPT v0.5.10 版本更新，发布金融财报新分析案例

USE dbgpt;
ALTER TABLE  knowledge_space
    ADD COLUMN `domain_type` varchar(50) null comment 'space domain type' after `vector_type`;
复制

pip install pdfplumber fuzzywuzzy
复制

# install poetry
pip install poetry
# install financial report knowledge process pipeline workflow
dbgpt app install financial-report-knowledge-factory
# install financial report  chat  pipeline workflow
dbgpt app install financial-robot-app
复制

git clone https://www.modelscope.cn/models/AI-ModelScope/bge-large-zh-v1.5
复制

#*******************************************************************#
#**                     FINANCIAL CHAT Config                     **#
#*******************************************************************#
FIN_REPORT_MODEL=/app/DB-GPT/models/bge-large-zh-v1.5
复制

git clone http://www.modelscope.cn/datasets/modelscope/chatglm_llm_fintech_raw_dataset.git
复制

dbgpt app install awel-flow-simple-streaming-chat -U
复制

dbgpt run flow --local chat \
--name awel-flow-simple-streaming-chat \
--model "gpt-3.5-turbo" \
--messages "hello" \
--stream
复制

dbgpt run flow --local cmd \
--name awel-flow-simple-streaming-chat \
-d '
{
    "model": "gpt-3.5-turbo",
    "messages": "hello",
    "stream": true
}
'
复制

dbgpt run flow --local --file simple_chat_app.py \
chat \
--name dbgpts_simple_chat_app \
--model "gpt-3.5-turbo" \
--messages "hello"
复制

LLM_MODEL=meta-llama-3.1-8b-instruct
复制

pip install -e ".[observability]"
复制

docker run --rm --name jaeger \
  -e COLLECTOR_ZIPKIN_HOST_PORT=:9411 \
  -p 6831:6831/udp \
  -p 6832:6832/udp \
  -p 5778:5778 \
  -p 16686:16686 \
  -p 4317:4317 \
  -p 4318:4318 \
  -p 14250:14250 \
  -p 14268:14268 \
  -p 14269:14269 \
  -p 9411:9411 \
  jaegertracing/all-in-one:1.58
复制

TRACER_TO_OPEN_TELEMETRY=True
OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=http://localhost:4317
复制