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Running
global faiss
Browse files- app.py +14 -13
- requirement.txt +0 -3
app.py
CHANGED
@@ -17,6 +17,7 @@ from langchain.prompts.chat import (
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API_URL = "https://api.openai.com/v1/chat/completions"
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cohere_key = '5IRbILAbjTI0VcqTsktBfKsr13Lych9iBAFbLpkj'
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faiss_store = './indexer/{}'
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def gen_conversation(conversations):
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@@ -33,9 +34,10 @@ def gen_conversation(conversations):
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return messages
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-
def predict(inputs, top_p, temperature, openai_api_key, enable_index, max_tokens,
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chat_counter, chatbot=[], history=[]):
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-
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topic = topic[0]
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headers = {
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"Content-Type": "application/json",
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@@ -51,10 +53,11 @@ def predict(inputs, top_p, temperature, openai_api_key, enable_index, max_tokens
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if enable_index:
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# Faiss 检索最近的embedding
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store = faiss_store.format(topic)
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if
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docsearch = FAISS.load_local(store, OpenAIEmbeddings(openai_api_key=openai_api_key))
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else:
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-
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# 构建模板
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llm = ChatOpenAI(openai_api_key=openai_api_key, max_tokens=max_tokens)
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messages_combine = [
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@@ -147,18 +150,16 @@ with gr.Blocks(css="""#col_container {width: 1000px; margin-left: auto; margin-r
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with gr.Row():
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top_p = gr.Slider(minimum=-0, maximum=1.0, value=0.9, step=0.05, interactive=True,
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label="Top-p (nucleus sampling)", )
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-
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temperature = gr.Slider(minimum=-0, maximum=5.0, value=0.8, step=0.1, interactive=True,
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label="Temperature", )
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model = gr.CheckboxGroup(["cohere", "openai", "mpnet"])
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max_tokens = gr.Slider(minimum=100, maximum=2000, value=200, step=100, interactive=True,
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label="Max Tokens", )
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chat_counter = gr.Number(value=0, precision=0, label='对话轮数')
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with gr.Row():
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enable_index = gr.Checkbox(label='是', info='
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enable_search = gr.Checkbox(label='是', info='
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topic = gr.CheckboxGroup(["两会", "数字经济", "硅谷银行"])
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chatbot = gr.Chatbot(elem_id='chatbot')
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inputs = gr.Textbox(placeholder="您有什么问题可以问我", label="输入数字经济,两会,硅谷银行相关的提问")
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@@ -169,11 +170,11 @@ with gr.Blocks(css="""#col_container {width: 1000px; margin-left: auto; margin-r
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run = gr.Button("Run")
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inputs.submit(predict,
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[inputs, top_p, temperature, openai_api_key, enable_index, max_tokens,
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state],
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[chatbot, state, chat_counter], )
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run.click(predict,
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[inputs, top_p, temperature, openai_api_key, enable_index, max_tokens,
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state],
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[chatbot, state, chat_counter], )
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API_URL = "https://api.openai.com/v1/chat/completions"
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cohere_key = '5IRbILAbjTI0VcqTsktBfKsr13Lych9iBAFbLpkj'
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faiss_store = './indexer/{}'
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docsearch = None
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def gen_conversation(conversations):
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return messages
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def predict(inputs, top_p, temperature, openai_api_key, enable_index, max_tokens, topic,
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chat_counter, chatbot=[], history=[]):
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global docsearch
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topic = topic[0]
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headers = {
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"Content-Type": "application/json",
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if enable_index:
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# Faiss 检索最近的embedding
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store = faiss_store.format(topic)
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if docsearch is None:
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print('Loading FAISS')
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docsearch = FAISS.load_local(store, OpenAIEmbeddings(openai_api_key=openai_api_key))
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else:
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print('Faiss already loaded')
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# 构建模板
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llm = ChatOpenAI(openai_api_key=openai_api_key, max_tokens=max_tokens)
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messages_combine = [
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with gr.Row():
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top_p = gr.Slider(minimum=-0, maximum=1.0, value=0.9, step=0.05, interactive=True,
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label="Top-p (nucleus sampling)", )
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temperature = gr.Slider(minimum=-0, maximum=5.0, value=0.8, step=0.1, interactive=True,
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label="Temperature", )
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max_tokens = gr.Slider(minimum=100, maximum=1000, value=200, step=100, interactive=True,
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label="Max Tokens", )
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chat_counter = gr.Number(value=0, precision=0, label='对话轮数')
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with gr.Row():
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enable_index = gr.Checkbox(label='是', info='开启文档问答模式/聊天模式')
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enable_search = gr.Checkbox(label='是', info='是否使用搜索')
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topic = gr.CheckboxGroup(["两会", "数字经济", "硅谷银行"], label='使用文档索引')
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chatbot = gr.Chatbot(elem_id='chatbot')
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inputs = gr.Textbox(placeholder="您有什么问题可以问我", label="输入数字经济,两会,硅谷银行相关的提问")
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run = gr.Button("Run")
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inputs.submit(predict,
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[inputs, top_p, temperature, openai_api_key, enable_index, max_tokens, topic, chat_counter, chatbot,
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state],
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[chatbot, state, chat_counter], )
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run.click(predict,
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[inputs, top_p, temperature, openai_api_key, enable_index, max_tokens, topic, chat_counter, chatbot,
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state],
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[chatbot, state, chat_counter], )
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requirement.txt
DELETED
@@ -1,3 +0,0 @@
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openai==0.27.2
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gradio==3.21.0
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langchain==0.0.113
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