2、使用deepseek模型报下面的错误 解决办法:把encoding_model: cl100k_base这行注释打开编辑于 2025-04-20 18:46・陕西 GraphRAG 赞同1添加评论 分享喜欢收藏申请转载 关于作者 AIGC LLM从业者 回答 文章 关注者 关注他发私信...
AI代码解释 encoding_model:cl100k_baseskip_workflows:[]llm:api_key:${GRAPHRAG_API_KEY}type:openai_chat # or azure_openai_chatmodel:deepseek-chatmodel_supports_json:true# recommendedifthisis availableforyour model.api_base:https://api.deepseek.com/v1max_tokens:4096concurrent_requests:100# the...
'model': 'qwen2', 'max_tokens': 4000, 'request_timeout': 180.0, 'api_base': 'http://localhost:11434/v1', 'api_version': None, 'organization': None, 'proxy': None, 'cognitive_services_endpoint': None, 'deployment_name': None, 'model_supports_json': True, 'tokens_per_minute':...
在settings.yaml文件中做一些配置,在这里我的配置如下: encoding_model:cl100k_baseskip_workflows:[]llm:api_key:${GRAPHRAG_API_KEY}type:openai_chat# or azure_openai_chatmodel:gpt-4o-minimodel_supports_json:true# recommended if this is available for your model.# max_tokens: 4000# request_timeo...
encoding_model: cl100k_base skip_workflows: [] llm: api_key: ${GRAPHRAG_API_KEY} type: openai_chat # 或 azure_openai_chat model: llama3.1 # model_supports_json: true # 如果可用,建议启用此选项 max_tokens: 2000 # request_timeout: 180.0 ...
encoding_model: cl100k_base skip_workflows: [] llm: api_key: ${GRAPHRAG_API_KEY} type: openai_chat # or azure_openai_chat model:qwen2 model_supports_json: true # recommended if this is available for your model. # max_tokens: 4000 ...
辛苦请教一下,graphrag构建索引时执行到create_final_entities报错终止,log内的报错信息显示"Error code: 400 - {'error': {'code': 'InvalidParameter', 'message': 'One or more parameters specified in the request are not valid. Request id: 021724747960210a602', 'param': 'encoding_format', 'type...
encoding_model: cl100k_base skip_workflows: [] llm: api_key: ollama type: openai_chat # or azure_openai_chat model: gemma2:9b # 你 ollama 中的本地 llm 模型,可以换成其他的,只要你安装了就可以 model_supports_json: true # recommended if this is available for your model. ...
encoding_model: cl100k_base skip_workflows:[]llm: api_key: ${GRAPHRAG_API_KEY}type: openai_chat model: mistral model_supports_json:trueapi_base: http://localhost:11434/v1parallelization: stagger:0.3async_mode: threaded embeddings: async_mode: threaded ...
api_key = 'EMPTY'llm_model = 'llama3.1'llm = ChatOpenAI( api_base='http://127.0.0.1:11434/v1', api_key=api_key, model=llm_model, api_type=OpenaiApiType.OpenAI, max_retries=20,)token_encoder = tiktoken.get_encoding('cl100k_base') 基本测试确保 LLM 端点正常运行。 messages = [ {...