1 line
6.7 KiB
JSON
1 line
6.7 KiB
JSON
{"repo": "acmislab/treeqa", "files": {"treeQA_Config.py": {"a02ed101b6d85e6ed7cd998508a77fc5eb6ad3d2": {"t": 1785746865.971844, "n": 2037, "h": "62e9c7ad87de4e9b", "c": "#relik/azure\r\nel_model='relik'\r\n# Azure Entity Linking: https://learn.microsoft.com/en-us/azure/ai-services/language-service/entity-linking/overview\r\n# key&endpoint\r\nAzure_key = '#########################################################'\r\nAzure_endpoint = 'https://el.cognitiveservices.azure.com/'\r\n#----------------If you use relik to Entity Linking,state it here--------------------------------\r\n# relik: https://github.com/SapienzaNLP/relik\r\nrelik_server_url = 'http://server_address:port/api/relik'\r\n# If you use proxies to access the Internet, please set the proxy address.\r\nproxies={\r\n \"http\": \"http://127.0.0.1:7890\",\r\n \"https\": \"http://127.0.0.1:7890\",\r\n}\r\n#----------------For embedding model,you can choose local or online service----------------------\r\nnv_embed_v2_url = 'http://server_address:port/embeddings'\r\n# ----------------For LLM model config,state it here----------------------\r\n# ----deepseekV3-chat/qwen2.5-instruct-14b/gpt3.5-turbo----------\r\nmodel_name = \"deepseekV3-chat\"\r\n# If you use qwen2.5-instruct-14b,you need to set aliApiKey,https://help.aliyun.com/en/model-studio/developer-reference/get-api-key\r\naliApiKey = \"sk-########################\"\r\n# If you use gpt3.5turbo,you need to set openaiApiKey,https://platform.openai.com/account/api-keys\r\nopenaiApiKey = \"\"\r\n# If you use deepseekV3,you need to set deepseekApiKey,https://platform.deepseek.com/\r\ndeepseekApiKey = \"sk-#####################\"\r\n\r\n# Get article chunks by nv-embed-v2/text-embedding-3-small\r\nRetrieveModelName = \"nv-embed-v2\"\r\n# If you use chroma to store wikipedia articles,please set Persistent Client Path, chroma collection name.\r\nChroma_store = False\r\nPersistentClient_Path = \"path_to_chroma\"\r\nchroma_collection_name = \"wikipediaNV\"# You can set any name you like, but chroma_collection_name needs to correspond to the retrieval model.\r\n\r\n# Use ELTop_k, RLTop_k to set the top k of the entity and relation linking results for graph search.\r\nELTop_k = 2\r\nRLTop_k = 1\r\n# Get top_k of text blocks to self-adaptive\r\narticle_top_k = 2\r\n"}, "a70e8aae9275cdce17f14884b1c925d2378d313d": {"t": 1785768229.6717727, "n": 2037, "h": "62e9c7ad87de4e9b", "c": "#relik/azure\r\nel_model='relik'\r\n# Azure Entity Linking: https://learn.microsoft.com/en-us/azure/ai-services/language-service/entity-linking/overview\r\n# key&endpoint\r\nAzure_key = '#########################################################'\r\nAzure_endpoint = 'https://el.cognitiveservices.azure.com/'\r\n#----------------If you use relik to Entity Linking,state it here--------------------------------\r\n# relik: https://github.com/SapienzaNLP/relik\r\nrelik_server_url = 'http://server_address:port/api/relik'\r\n# If you use proxies to access the Internet, please set the proxy address.\r\nproxies={\r\n \"http\": \"http://127.0.0.1:7890\",\r\n \"https\": \"http://127.0.0.1:7890\",\r\n}\r\n#----------------For embedding model,you can choose local or online service----------------------\r\nnv_embed_v2_url = 'http://server_address:port/embeddings'\r\n# ----------------For LLM model config,state it here----------------------\r\n# ----deepseekV3-chat/qwen2.5-instruct-14b/gpt3.5-turbo----------\r\nmodel_name = \"deepseekV3-chat\"\r\n# If you use qwen2.5-instruct-14b,you need to set aliApiKey,https://help.aliyun.com/en/model-studio/developer-reference/get-api-key\r\naliApiKey = \"sk-########################\"\r\n# If you use gpt3.5turbo,you need to set openaiApiKey,https://platform.openai.com/account/api-keys\r\nopenaiApiKey = \"\"\r\n# If you use deepseekV3,you need to set deepseekApiKey,https://platform.deepseek.com/\r\ndeepseekApiKey = \"sk-#####################\"\r\n\r\n# Get article chunks by nv-embed-v2/text-embedding-3-small\r\nRetrieveModelName = \"nv-embed-v2\"\r\n# If you use chroma to store wikipedia articles,please set Persistent Client Path, chroma collection name.\r\nChroma_store = False\r\nPersistentClient_Path = \"path_to_chroma\"\r\nchroma_collection_name = \"wikipediaNV\"# You can set any name you like, but chroma_collection_name needs to correspond to the retrieval model.\r\n\r\n# Use ELTop_k, RLTop_k to set the top k of the entity and relation linking results for graph search.\r\nELTop_k = 2\r\nRLTop_k = 1\r\n# Get top_k of text blocks to self-adaptive\r\narticle_top_k = 2\r\n"}, "e9d2b079cc6e6a98ec9c5620b4ba60214b941f82": {"t": 1785768232.1139166, "n": 2070, "h": "41a8c5dec40354f3", "c": "#relik/azure\r\nel_model='relik'\r\n# Azure Entity Linking: https://learn.microsoft.com/en-us/azure/ai-services/language-service/entity-linking/overview\r\n# key&endpoint\r\nAzure_key = '8cClqtqeXC9C49Q01UMwtkqifGbABXrbO0mljNQqp7fnCEfXAiWKJQQJ99ALACNns7RXJ3w3AAAaACOGKoAq'\r\nAzure_endpoint = 'https://el.cognitiveservices.azure.com/'\r\n#----------------If you use relik to Entity Linking,state it here--------------------------------\r\n# relik: https://github.com/SapienzaNLP/relik\r\nrelik_server_url = 'http://210.40.16.12:48361/api/relik'\r\n# If you use proxies to access the Internet, please set the proxy address.\r\nproxies={\r\n \"http\": \"http://127.0.0.1:7890\",\r\n \"https\": \"http://127.0.0.1:7890\",\r\n}\r\n#----------------For embedding model,you can choose local or online service----------------------\r\nnv_embed_v2_url = 'http://210.40.16.12:24449/embeddings'\r\n# ----------------For LLM model config,state it here----------------------\r\n# ----deepseekV3/qwen2.5-instruct-14b/gpt3.5-turbo----------\r\nmodel_name = \"deepseekV3_ali\"\r\n# If you use qwen2.5-instruct-14b,you need to set aliApiKey,https://help.aliyun.com/en/model-studio/developer-reference/get-api-key\r\naliApiKey = \"sk-aeb0ed24d0c045e78d73fff879da5f07\"\r\n# If you use gpt3.5turbo,you need to set openaiApiKey,https://platform.openai.com/account/api-keys\r\nopenaiApiKey = \"\"\r\n# If you use deepseekV3,you need to set deepseekApiKey,https://platform.deepseek.com/\r\ndeepseekApiKey = \"sk-eead0d1fed4e45eb9fdacfdc6a1df855\"\r\n\r\n# Get article chunks by nv-embed-v2/text-embedding-3-small\r\nRetrieveModelName = \"nv-embed-v2\"\r\n# If you use chroma to store wikipedia articles,please set Persistent Client Path, chroma collection name.\r\nChroma_store = False\r\nPersistentClient_Path = \"D:\\Chroma\"\r\nchroma_collection_name = \"wikipediaNV\"# You can set any name you like, but chroma_collection_name needs to correspond to the retrieval model.\r\n\r\n# Use ELTop_k, RLTop_k to set the top k of the entity and relation linking results for graph search.\r\nELTop_k = 2\r\nRLTop_k = 1\r\n# Get top_k of text blocks to self-adaptive\r\narticle_top_k = 2\r\n"}}}} |