1 line
3.8 KiB
JSON
1 line
3.8 KiB
JSON
{"repo": "4thfever/idiommatcher", "files": {"llm.py": {"c7ed697e216036fee60343607dc1a9a5c249bdbb": {"t": 1785674064.780192, "n": 890, "h": "1819300953245904", "c": "import os\nfrom litellm import completion\n\nfrom utils.decorator import retry_when_error\n\n# 在此处配置litellm的API KEY\n# 如openai的api key\nos.environ[\"OPENAI_API_KEY\"] = \"your-api-key\"\nmodel = \"gpt-4o\"\n\n# 支持其他类型的大模型api，如deepseek\nos.environ['DEEPSEEK_API_KEY'] = \"your-api-key\"\nmodel = \"deepseek/deepseek-chat\"\n\n# 查询litellm的官网，检索更多支持的大模型API，如通义千问\n# https://docs.litellm.ai/docs/providers\n\ndef wash(string):\n if \"```json\" in string:\n string = string.replace(\"```json\", \"\")\n string = string.replace(\"```\", \"\")\n return string\n\n@retry_when_error\ndef call_api(prompt):\n response = completion(\n model = model, \n messages = [\n {\"role\": \"system\", \"content\": \"You are an assisstant.\"},\n {\"role\": \"user\", \"content\": prompt},\n ],\n )\n response = response['choices'][0]['message']['content']\n response = wash(response)\n return response\n"}, "9396ace6ca4b40b2f43a27479a232fb1e834c62c": {"t": 1785752922.6785817, "n": 890, "h": "1819300953245904", "c": "import os\nfrom litellm import completion\n\nfrom utils.decorator import retry_when_error\n\n# 在此处配置litellm的API KEY\n# 如openai的api key\nos.environ[\"OPENAI_API_KEY\"] = \"your-api-key\"\nmodel = \"gpt-4o\"\n\n# 支持其他类型的大模型api，如deepseek\nos.environ['DEEPSEEK_API_KEY'] = \"your-api-key\"\nmodel = \"deepseek/deepseek-chat\"\n\n# 查询litellm的官网，检索更多支持的大模型API，如通义千问\n# https://docs.litellm.ai/docs/providers\n\ndef wash(string):\n if \"```json\" in string:\n string = string.replace(\"```json\", \"\")\n string = string.replace(\"```\", \"\")\n return string\n\n@retry_when_error\ndef call_api(prompt):\n response = completion(\n model = model, \n messages = [\n {\"role\": \"system\", \"content\": \"You are an assisstant.\"},\n {\"role\": \"user\", \"content\": prompt},\n ],\n )\n response = response['choices'][0]['message']['content']\n response = wash(response)\n return response\n"}, "175b7b69f3c48ea970d71ba1426268074203efd7": {"t": 1785752924.8353336, "n": 641, "h": "2cd53dab7983ad71", "c": "import os\nfrom litellm import completion\n\n# 在此处配置litellm的API KEY\n# 如openai的api key\nos.environ[\"OPENAI_API_KEY\"] = \"your-api-key\"\nmodel = \"gpt-4o\"\n\n# 支持其他类型的大模型api，如deepseek\nos.environ['DEEPSEEK_API_KEY'] = \"your-api-key\"\nmodel = \"deepseek/deepseek-chat\"\n\n# 查询litellm的官网，检索更多支持的大模型API，如通义千问\n# https://docs.litellm.ai/docs/providers\n\ndef call_api(prompt):\n response = completion(\n model = model, \n messages = [\n {\"role\": \"system\", \"content\": \"You are an assisstant.\"},\n {\"role\": \"user\", \"content\": prompt},\n ],\n )\n response = response['choices'][0]['message']['content']\n return response\n"}, "df370a0a2af7e2da2ccb008ba7b451ea439a5b9f": {"t": 1785752926.3145094, "n": 442, "h": "0eb351260eb10061", "c": "import os\nfrom litellm import completion\n\n# 在此处配置litellm的API KEY\n# 如openai的api key\nos.environ[\"OPENAI_API_KEY\"] = \"your-api-key\"\n\ndef call_api(prompt):\n response = completion(\n model = \"gpt-4o\", \n messages = [\n {\"role\": \"system\", \"content\": \"You are an assisstant.\"},\n {\"role\": \"user\", \"content\": prompt},\n ],\n )\n response = response['choices'][0]['message']['content']\n return response\n"}}}} |