Update app.py
Browse files
app.py
CHANGED
@@ -20,7 +20,7 @@ from langchain.document_loaders import DirectoryLoader
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from langchain.indexes import VectorstoreIndexCreator
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from langchain.embeddings.openai import OpenAIEmbeddings
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from langchain.vectorstores import Pinecone
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import
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openai.api_key = os.environ['OPENAI_API_KEY']
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@@ -133,8 +133,8 @@ def talk2file(index_name, text):
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#Title1 = '<h2 style="background-color: yellow;"><b>User Question: </b></h2>'
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#User_Question = f'<div style="background-color: yellow; display: inline-block; word-wrap: break-word;">{prompt}</div>'
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Title2 = '<h2
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context =
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#context = f'<span style="background-color: #ADD8E6; display: inline-block; word-wrap: break-word;">{context2html}</span>'
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#Title3 = '<h2 style="background-color: #90EE90;"><b>Ansewr: </b></h2>'
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answer = system_message["content"]
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@@ -206,8 +206,9 @@ with gr.Blocks() as pinecone_tools:
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textbox = gr.inputs.Textbox(label="Vector Server Index Name: ", default="amd")
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role = gr.Interface(fn=roleChoice, inputs="text", outputs="text", description = "Choose your GPT roles, e.g. You are a helpful technology assistant.")
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text = gr.Interface(fn=talk2file, inputs=[textbox, "text"], outputs=["html",
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vector_server = gr.Interface(fn=process_file, inputs=["text", gr.inputs.File(file_count="directory")], outputs="text")
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from langchain.indexes import VectorstoreIndexCreator
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from langchain.embeddings.openai import OpenAIEmbeddings
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from langchain.vectorstores import Pinecone
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import markdown
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openai.api_key = os.environ['OPENAI_API_KEY']
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#Title1 = '<h2 style="background-color: yellow;"><b>User Question: </b></h2>'
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#User_Question = f'<div style="background-color: yellow; display: inline-block; word-wrap: break-word;">{prompt}</div>'
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Title2 = '<h2"><b>Context Found: </b></h2>'
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context = markdown.markdown(docs[0].page_content)
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#context = f'<span style="background-color: #ADD8E6; display: inline-block; word-wrap: break-word;">{context2html}</span>'
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#Title3 = '<h2 style="background-color: #90EE90;"><b>Ansewr: </b></h2>'
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answer = system_message["content"]
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textbox = gr.inputs.Textbox(label="Vector Server Index Name: ", default="amd")
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answerbox = gr.inputs.Textbox(label="Assistant answer"")
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role = gr.Interface(fn=roleChoice, inputs="text", outputs="text", description = "Choose your GPT roles, e.g. You are a helpful technology assistant.")
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text = gr.Interface(fn=talk2file, inputs=[textbox, "text"], outputs=["html", answerbox])
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vector_server = gr.Interface(fn=process_file, inputs=["text", gr.inputs.File(file_count="directory")], outputs="text")
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