wehub-resource-sync
40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
# Usage:
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# python3 -m fastchat.serve.model_worker --model-path lmsys/vicuna-7b-v1.5 --model-names gpt-3.5-turbo,text-davinci-003,text-embedding-ada-002
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# export OPENAI_API_BASE=http://localhost:8000/v1
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# export OPENAI_API_KEY=EMPTY
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# wget https://raw.githubusercontent.com/hwchase17/langchain/v0.0.200/docs/modules/state_of_the_union.txt
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import os
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from langchain.chat_models import ChatOpenAI
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from langchain.document_loaders import TextLoader
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from langchain.embeddings import OpenAIEmbeddings
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from langchain.indexes import VectorstoreIndexCreator
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def test_chain():
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embedding = OpenAIEmbeddings(model="text-embedding-ada-002")
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loader = TextLoader("state_of_the_union.txt")
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index = VectorstoreIndexCreator(embedding=embedding).from_loaders([loader])
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llm = ChatOpenAI(model="gpt-3.5-turbo")
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questions = [
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"Who is the speaker",
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"What did the president say about Ketanji Brown Jackson",
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"What are the threats to America",
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"Who are mentioned in the speech",
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"Who is the vice president",
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"How many projects were announced",
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]
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for query in questions:
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print("Query:", query)
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print("Answer:", index.query(query, llm=llm))
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if __name__ == "__main__":
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os.environ["OPENAI_API_BASE"] = "http://localhost:8000/v1"
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os.environ["OPENAI_API_KEY"] = "empty"
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test_chain()
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