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Add 'One' chunk method (#137)
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@ -79,3 +79,4 @@ class ParserType(StrEnum):
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TABLE = "table"
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NAIVE = "naive"
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PICTURE = "picture"
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ONE = "one"
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@ -79,12 +79,12 @@ factory_infos = [{
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"tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
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"status": "1",
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},{
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"name": "通义千问",
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"name": "Tongyi-Qianwen",
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"logo": "",
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"tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
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"status": "1",
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},{
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"name": "智谱AI",
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"name": "ZHIPU-AI",
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"logo": "",
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"tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
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"status": "1",
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@ -270,6 +270,14 @@ def init_llm_factory():
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except Exception as e:
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pass
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"""
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drop table llm;
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drop table factories;
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update tenant_llm set llm_factory='Tongyi-Qianwen' where llm_factory='通义千问';
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update tenant_llm set llm_factory='ZHIPU-AI' where llm_factory='智谱AI';
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update tenant set parser_ids='naive:General,one:One,qa:Q&A,resume:Resume,table:Table,laws:Laws,manual:Manual,book:Book,paper:Paper,presentation:Presentation,picture:Picture';
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"""
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def init_web_data():
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start_time = time.time()
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@ -52,7 +52,7 @@ REQUEST_MAX_WAIT_SEC = 300
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USE_REGISTRY = get_base_config("use_registry")
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default_llm = {
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"通义千问": {
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"Tongyi-Qianwen": {
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"chat_model": "qwen-plus",
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"embedding_model": "text-embedding-v2",
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"image2text_model": "qwen-vl-max",
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@ -64,7 +64,7 @@ default_llm = {
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"image2text_model": "gpt-4-vision-preview",
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"asr_model": "whisper-1",
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},
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"智谱AI": {
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"ZHIPU-AI": {
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"chat_model": "glm-3-turbo",
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"embedding_model": "embedding-2",
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"image2text_model": "glm-4v",
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@ -84,17 +84,17 @@ default_llm = {
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}
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}
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LLM = get_base_config("user_default_llm", {})
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LLM_FACTORY = LLM.get("factory", "通义千问")
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LLM_FACTORY = LLM.get("factory", "Tongyi-Qianwen")
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if LLM_FACTORY not in default_llm:
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print("\33[91m【ERROR】\33[0m:", f"LLM factory {LLM_FACTORY} has not supported yet, switch to '通义千问/QWen' automatically, and please check the API_KEY in service_conf.yaml.")
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LLM_FACTORY = "通义千问"
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print("\33[91m【ERROR】\33[0m:", f"LLM factory {LLM_FACTORY} has not supported yet, switch to 'Tongyi-Qianwen/QWen' automatically, and please check the API_KEY in service_conf.yaml.")
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LLM_FACTORY = "Tongyi-Qianwen"
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CHAT_MDL = default_llm[LLM_FACTORY]["chat_model"]
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EMBEDDING_MDL = default_llm[LLM_FACTORY]["embedding_model"]
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ASR_MDL = default_llm[LLM_FACTORY]["asr_model"]
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IMAGE2TEXT_MDL = default_llm[LLM_FACTORY]["image2text_model"]
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API_KEY = LLM.get("api_key", "")
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PARSERS = LLM.get("parsers", "naive:General,qa:Q&A,resume:Resume,table:Table,laws:Laws,manual:Manual,book:Book,paper:Paper,presentation:Presentation,picture:Picture")
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PARSERS = LLM.get("parsers", "naive:General,one:One,qa:Q&A,resume:Resume,table:Table,laws:Laws,manual:Manual,book:Book,paper:Paper,presentation:Presentation,picture:Picture")
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# distribution
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DEPENDENT_DISTRIBUTION = get_base_config("dependent_distribution", False)
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