英文:
How to fix `transformers` package not found error in a Python project with `py-langchain`, `llama-index`, and `gradio`?
问题
I get this error ModuleNotFoundError: No module named 'transformers' even though I did the pip install transformers command. Could you kindly help me? Thank you
我的代码：
import osimport sysfrom dotenv import load_dotenvimport gradio as grfrom langchain import OpenAIfrom llama_index import SimpleDirectoryReader, GPTListIndex, GPTVectorStoreIndex, LLMPredictor, PromptHelperload_dotenv()os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY')def construct_index(directory_path):max_input_size = 4096num_outputs = 512max_chunk_overlap = 20chunk_size_limit = 600prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.7, model_name="text-davinci-003", max_tokens=num_outputs))documents = SimpleDirectoryReader(directory_path).load_data()index = GPTVectorStoreIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper)index.save_to_disk('index.json')return indexdef qabot(input_text):index = GPTVectorStoreIndex.load_from_disk('index.json')response = index.query(input_text, response_mode="compact")return response.responseiface = gr.Interface(fn=qabot, inputs=gr.inputs.Textbox(lines=7, label='Enter you query'), outputs="text", title="Custom-trained QA Application")index = construct_index("docs")iface.launch(share=True)
注意：我已经删除了代码中的 HTML 实体编码（例如，& 变成了 &），以便更好地呈现代码。
英文:
I get this error ModuleNotFoundError: No module named 'transformers' even though I did the pip install transformers command. Could you kindly help me? Thank you
My code:
import osimport sysfrom dotenv import load_dotenvimport gradio as grfrom langchain import OpenAIfrom llama_index import SimpleDirectoryReader, GPTListIndex, GPTVectorStoreIndex, LLMPredictor, PromptHelper##from transformers import pipelineload_dotenv()os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY')def construct_index(directory_path):max_input_size = 4096num_outputs = 512max_chunk_overlap = 20chunk_size_limit = 600prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.7, model_name="text-davinci-003", max_tokens=num_outputs))documents = SimpleDirectoryReader(directory_path).load_data()index = GPTVectorStoreIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper)index.save_to_disk('index.json')return indexdef qabot(input_text):index = GPTVectorStoreIndex.load_from_disk('index.json')response = index.query(input_text, response_mode="compact")return response.responseiface = gr.Interface(fn=qabot, inputs=gr.inputs.Textbox(lines=7, label='Enter you query'), outputs="text", title="Custom-trained QA Application")index = construct_index("docs")iface.launch(share=True)
答案1
得分: 1
也许你可以取消注释
from transformers import pipeline
英文:
Maybe you can uncomment
##from transformers import pipeline
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