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support multi process to launch llmserver, add openai proxy api.
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@ -7,6 +7,10 @@
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## For example, to disable coding related features, uncomment the next line
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## For example, to disable coding related features, uncomment the next line
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# DISABLED_COMMAND_CATEGORIES=
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# DISABLED_COMMAND_CATEGORIES=
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#*******************************************************************#
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#** Webserver Port **#
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#*******************************************************************#
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WEB_SERVER_PORT=7860
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#*******************************************************************#
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#*******************************************************************#
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#*** LLM PROVIDER ***#
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#*** LLM PROVIDER ***#
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@ -17,6 +21,7 @@
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#*******************************************************************#
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#*******************************************************************#
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#** LLM MODELS **#
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#** LLM MODELS **#
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#*******************************************************************#
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#*******************************************************************#
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# LLM_MODEL, see /pilot/configs/model_config.LLM_MODEL_CONFIG
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LLM_MODEL=vicuna-13b
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LLM_MODEL=vicuna-13b
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MODEL_SERVER=http://127.0.0.1:8000
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MODEL_SERVER=http://127.0.0.1:8000
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LIMIT_MODEL_CONCURRENCY=5
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LIMIT_MODEL_CONCURRENCY=5
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@ -98,15 +103,20 @@ VECTOR_STORE_TYPE=Chroma
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#MILVUS_SECURE=
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#MILVUS_SECURE=
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#*******************************************************************#
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#** WebServer Language Support **#
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#*******************************************************************#
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LANGUAGE=en
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LANGUAGE=en
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#LANGUAGE=zh
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#LANGUAGE=zh
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#*******************************************************************#
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#*******************************************************************#
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# ** PROXY_SERVER
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# ** PROXY_SERVER (openai interface | chatGPT proxy service), use chatGPT as your LLM.
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# ** if your server can visit openai, please set PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions
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# ** else if you have a chatgpt proxy server, you can set PROXY_SERVER_URL={your-proxy-serverip:port/xxx}
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#*******************************************************************#
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#*******************************************************************#
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PROXY_API_KEY=
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PROXY_API_KEY={your-openai-sk}
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PROXY_SERVER_URL=http://127.0.0.1:3000/proxy_address
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PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions
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#*******************************************************************#
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#*******************************************************************#
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@ -17,8 +17,9 @@ class Config(metaclass=Singleton):
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def __init__(self) -> None:
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def __init__(self) -> None:
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"""Initialize the Config class"""
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"""Initialize the Config class"""
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# Gradio language version: en, cn
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# Gradio language version: en, zh
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self.LANGUAGE = os.getenv("LANGUAGE", "en")
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self.LANGUAGE = os.getenv("LANGUAGE", "en")
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self.WEB_SERVER_PORT = int(os.getenv("WEB_SERVER_PORT", 7860))
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self.debug_mode = False
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self.debug_mode = False
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self.skip_reprompt = False
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self.skip_reprompt = False
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@ -84,6 +84,11 @@ class ModelWorker:
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return get_embeddings(self.model, self.tokenizer, prompt)
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return get_embeddings(self.model, self.tokenizer, prompt)
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model_path = LLM_MODEL_CONFIG[CFG.LLM_MODEL]
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worker = ModelWorker(
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model_path=model_path, model_name=CFG.LLM_MODEL, device=DEVICE, num_gpus=1
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)
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app = FastAPI()
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app = FastAPI()
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@ -157,11 +162,4 @@ def embeddings(prompt_request: EmbeddingRequest):
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if __name__ == "__main__":
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if __name__ == "__main__":
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model_path = LLM_MODEL_CONFIG[CFG.LLM_MODEL]
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print(model_path, DEVICE)
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worker = ModelWorker(
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model_path=model_path, model_name=CFG.LLM_MODEL, device=DEVICE, num_gpus=1
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)
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uvicorn.run(app, host="0.0.0.0", port=CFG.MODEL_PORT, log_level="info")
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uvicorn.run(app, host="0.0.0.0", port=CFG.MODEL_PORT, log_level="info")
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@ -658,7 +658,7 @@ def signal_handler(sig, frame):
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if __name__ == "__main__":
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser = argparse.ArgumentParser()
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parser.add_argument("--host", type=str, default="0.0.0.0")
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parser.add_argument("--host", type=str, default="0.0.0.0")
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parser.add_argument("--port", type=int)
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parser.add_argument("--port", type=int, default=CFG.WEB_SERVER_PORT)
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parser.add_argument("--concurrency-count", type=int, default=10)
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parser.add_argument("--concurrency-count", type=int, default=10)
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parser.add_argument(
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parser.add_argument(
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"--model-list-mode", type=str, default="once", choices=["once", "reload"]
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"--model-list-mode", type=str, default="once", choices=["once", "reload"]
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