From 0a5da47b92a36705f9c48bbd35bf89844fbd0d36 Mon Sep 17 00:00:00 2001 From: "shiyi.lin" <3397316724@qq.com> Date: Thu, 31 Jul 2025 13:32:09 +0800 Subject: [PATCH 1/2] Create test_data --- test_data | 1 + 1 file changed, 1 insertion(+) create mode 100644 test_data diff --git a/test_data b/test_data new file mode 100644 index 0000000000..8b13789179 --- /dev/null +++ b/test_data @@ -0,0 +1 @@ + From 49d04e43531d793cd2599360ce9a0f31f184cad0 Mon Sep 17 00:00:00 2001 From: "shiyi.lin" <3397316724@qq.com> Date: Thu, 31 Jul 2025 13:35:17 +0800 Subject: [PATCH 2/2] test_data MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 想增加graph 对 pdf 的处理能力 --- .env | 1 + DA68-04798A-03_RF8500_CN_SVC.pdf | Bin 0 -> 6656614 bytes settings.yaml | 152 +++++++++++++++++++++++++++++++ test.pdf | Bin 0 -> 2826537 bytes text_img_table.pdf | Bin 0 -> 3811193 bytes 5 files changed, 153 insertions(+) create mode 100644 .env create mode 100644 DA68-04798A-03_RF8500_CN_SVC.pdf 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zYwj>~#f-Lp`EbbE0;Fe`n>>Ri6@1h2rkRQpe%`8>&5$%LU{>Nh}dTrg2z|UJowAse+ zF_+s6eH-s*cCW{RXlGJuldfx-%I{xrhJBtY3NYC9)-*%*zp(gLDzv7zLF&%dD9wW= zuaFd7o^K8(NHTe)pCpcUOD8L-Q8J?>HRmmC`-iJCoNW6GkNCV~LaEiEFTNpWV(%l5 zXs?7p#D*|X-#04lwdG_IggG6M=$;?*82@w)Nj_VnNDVYD`Y*56Wd%IgoR zuC`Gb_dc3r5n?PJw!vrbXU&L$yPtjdt!7%`ao0zK^ShQ{WQF5e+CN>0woNE--nPi$`*X(|H*vY?6Xf+M-{2w?T($^8;8;Edu#&cFx6{w=9c#G$(q@.openai.azure.com + # api_version: 2024-05-01-preview + auth_type: api_key # or azure_managed_identity + api_key: ${GRAPHRAG_API_KEY} # set this in the generated .env file + # audience: "https://cognitiveservices.azure.com/.default" + # organization: + model: gpt-4-turbo-preview + # deployment_name: + # encoding_model: cl100k_base # automatically set by tiktoken if left undefined + model_supports_json: true # recommended if this is available for your model. + concurrent_requests: 25 # max number of simultaneous LLM requests allowed + async_mode: threaded # or asyncio + retry_strategy: native + max_retries: -1 # set to -1 for dynamic retry logic (most optimal setting based on server response) + tokens_per_minute: 0 # set to 0 to disable rate limiting + requests_per_minute: 0 # set to 0 to disable rate limiting + default_embedding_model: + type: openai_embedding # or azure_openai_embedding + # api_base: https://.openai.azure.com + # api_version: 2024-05-01-preview + auth_type: api_key # or azure_managed_identity + api_key: ${GRAPHRAG_API_KEY} + # audience: "https://cognitiveservices.azure.com/.default" + # organization: + model: text-embedding-3-small + # deployment_name: + # encoding_model: cl100k_base # automatically set by tiktoken if left undefined + model_supports_json: true # recommended if this is available for your model. + concurrent_requests: 25 # max number of simultaneous LLM requests allowed + async_mode: threaded # or asyncio + retry_strategy: native + max_retries: -1 # set to -1 for dynamic retry logic (most optimal setting based on server response) + tokens_per_minute: 0 # set to 0 to disable rate limiting + requests_per_minute: 0 # set to 0 to disable rate limiting + +vector_store: + default_vector_store: + type: lancedb + db_uri: output\lancedb + container_name: default + overwrite: True + +embed_text: + model_id: default_embedding_model + vector_store_id: default_vector_store + +### Input settings ### + +input: + type: file # or blob + file_type: text # [csv, text, json] + base_dir: "input" + +chunks: + size: 1200 + overlap: 100 + group_by_columns: [id] + +### Output settings ### +## If blob storage is specified in the following four sections, +## connection_string and container_name must be provided + +cache: + type: file # [file, blob, cosmosdb] + base_dir: "cache" + +reporting: + type: file # [file, blob, cosmosdb] + base_dir: "logs" + +output: + type: file # [file, blob, cosmosdb] + base_dir: "output" + +### Workflow settings ### + +extract_graph: + model_id: default_chat_model + prompt: "prompts/extract_graph.txt" + entity_types: [organization,person,geo,event] + max_gleanings: 1 + +summarize_descriptions: + model_id: default_chat_model + prompt: "prompts/summarize_descriptions.txt" + max_length: 500 + +extract_graph_nlp: + text_analyzer: + extractor_type: regex_english # [regex_english, syntactic_parser, cfg] + +extract_claims: + enabled: false + model_id: default_chat_model + prompt: "prompts/extract_claims.txt" + description: "Any claims or facts that could be relevant to information discovery." + max_gleanings: 1 + +community_reports: + model_id: default_chat_model + graph_prompt: "prompts/community_report_graph.txt" + text_prompt: "prompts/community_report_text.txt" + max_length: 2000 + max_input_length: 8000 + +cluster_graph: + max_cluster_size: 10 + +embed_graph: + enabled: false # if true, will generate node2vec embeddings for nodes + +umap: + enabled: false # if true, will generate UMAP embeddings for nodes (embed_graph must also be enabled) + +snapshots: + graphml: false + embeddings: false + +### Query settings ### +## The prompt locations are required here, but each search method has a number of optional knobs that can be tuned. +## See the config docs: https://microsoft.github.io/graphrag/config/yaml/#query + +local_search: + chat_model_id: default_chat_model + embedding_model_id: default_embedding_model + prompt: "prompts/local_search_system_prompt.txt" + +global_search: + chat_model_id: default_chat_model + map_prompt: "prompts/global_search_map_system_prompt.txt" + reduce_prompt: "prompts/global_search_reduce_system_prompt.txt" + knowledge_prompt: "prompts/global_search_knowledge_system_prompt.txt" + +drift_search: + chat_model_id: default_chat_model + embedding_model_id: default_embedding_model + prompt: "prompts/drift_search_system_prompt.txt" + reduce_prompt: "prompts/drift_search_reduce_prompt.txt" + +basic_search: + chat_model_id: default_chat_model + embedding_model_id: default_embedding_model + prompt: "prompts/basic_search_system_prompt.txt" diff --git a/test.pdf 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