xinfyxinfy commited on
Commit
642842b
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1 Parent(s): 4676bbd

Update space

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Files changed (2) hide show
  1. app.py +83 -50
  2. requirements.txt +13 -1
app.py CHANGED
@@ -1,63 +1,96 @@
 
 
 
 
 
1
  import gradio as gr
2
- from huggingface_hub import InferenceClient
3
 
4
- """
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- For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
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- """
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- client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
8
 
 
 
9
 
10
- def respond(
11
- message,
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- history: list[tuple[str, str]],
13
- system_message,
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- max_tokens,
15
- temperature,
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- top_p,
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- ):
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- messages = [{"role": "system", "content": system_message}]
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20
- for val in history:
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- if val[0]:
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- messages.append({"role": "user", "content": val[0]})
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- if val[1]:
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- messages.append({"role": "assistant", "content": val[1]})
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- messages.append({"role": "user", "content": message})
27
 
28
- response = ""
 
29
 
30
- for message in client.chat_completion(
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- messages,
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- max_tokens=max_tokens,
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- stream=True,
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- temperature=temperature,
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- top_p=top_p,
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- ):
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- token = message.choices[0].delta.content
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39
- response += token
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- yield response
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
41
 
42
- """
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- For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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- """
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- demo = gr.ChatInterface(
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- respond,
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- additional_inputs=[
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- gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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- gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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- gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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- gr.Slider(
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- minimum=0.1,
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- maximum=1.0,
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- value=0.95,
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- step=0.05,
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- label="Top-p (nucleus sampling)",
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- ),
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- ],
59
- )
60
 
 
 
61
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
62
  if __name__ == "__main__":
63
- demo.launch()
 
1
+ import os
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+ from langchain_community.vectorstores import Chroma
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+ from langchain_openai import OpenAIEmbeddings, ChatOpenAI
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+ from langchain.prompts import ChatPromptTemplate
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+ from dotenv import load_dotenv
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  import gradio as gr
7
+ import openai
8
 
9
+ # Load environment variables from .env file
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+ load_dotenv()
 
 
11
 
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+ # Set OpenAI API key
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+ openai.api_key = os.environ['OPENAI_API_KEY']
14
 
15
+ # Constants
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+ CHROMA_PATH = "chroma"
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+ PROMPT_TEMPLATE = """
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+ Answer the question based only on the following context:
 
 
 
 
 
19
 
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+ {context}
 
 
 
 
21
 
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+ ---
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+ Answer the question based on the above context: {question}
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+ """
26
 
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+ # Function to process user input and generate response
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+ def generate_response(query_text, history):
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+ # Prepare the DB
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+ embedding_function = OpenAIEmbeddings()
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+ db = Chroma(persist_directory=CHROMA_PATH, embedding_function=embedding_function)
 
 
 
32
 
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+ # Search the DB
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+ results = db.similarity_search_with_relevance_scores(query_text, k=3)
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+ if len(results) == 0 or results[0][1] < 0.7:
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+ response_text = "🤔 Unable to find matching results."
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+ else:
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+ context_text = "\n\n---\n\n".join([doc.page_content for doc, _score in results])
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+ prompt_template = ChatPromptTemplate.from_template(PROMPT_TEMPLATE)
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+ prompt = prompt_template.format(context=context_text, question=query_text)
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+
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+ # Generate response
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+ model = ChatOpenAI(model="gpt-4o")
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+ response_text = model.invoke(prompt).content
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+ # sources = [doc.metadata.get("source", None) for doc, _score in results]
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+ # response_text += f"\n\n**Sources:** {', '.join(sources)}"
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+
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+ history.append(("You 🗣️", query_text))
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+ history.append(("Biomedical Informatics Assistant 🤖", response_text))
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+ return history, ""
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+
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+ # Gradio Interface
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+ with gr.Blocks() as demo:
54
+ gr.Markdown("<h1 style='text-align: center; color: white;'>AI-Powered Chat Interface for Biomedical Informatics 🤖</h1>")
55
+
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+ chatbot = gr.Chatbot(elem_id="chatbot")
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+
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+ with gr.Row():
59
+ with gr.Column(scale=7):
60
+ query_text = gr.Textbox(
61
+ show_label=False,
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+ placeholder="Type your question here ✍️...",
63
+ lines=1,
64
+ elem_id="input_box"
65
+ )
66
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
67
 
68
+ # Set up interactions
69
+ query_text.submit(generate_response, [query_text, chatbot], [chatbot, query_text])
70
 
71
+ # Custom CSS
72
+ demo.css = """
73
+ #input_box {
74
+ font-size: 18px;
75
+ padding: 10px;
76
+ }
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+ #chatbot .message {
78
+ font-size: 18px;
79
+ }
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+ #chatbot .user {
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+ background-color: #333;
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+ color: white;
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+ font-size: 32px;
84
+ }
85
+ #chatbot .assistant {
86
+ background-color: #007BFF;
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+ color: white;
88
+ font-size: 32px;
89
+ }
90
+ body {
91
+ background-color: #ffffff;
92
+ }
93
+ """
94
+
95
  if __name__ == "__main__":
96
+ demo.launch(share=True)
requirements.txt CHANGED
@@ -1 +1,13 @@
1
- huggingface_hub==0.22.2
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ python-dotenv==1.0.1 # For reading environment variables stored in .env file
2
+ langchain==0.2.2
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+ langchain-community==0.2.3
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+ langchain-openai==0.1.8 # For embeddings
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+ unstructured==0.14.4 # Document loading
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+ # onnxruntime==1.17.1 # chromadb dependency: on Mac use `conda install onnxruntime -c conda-forge`
7
+ # For Windows users, install Microsoft Visual C++ Build Tools first
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+ # install onnxruntime before installing `chromadb`
9
+ chromadb==0.5.0 # Vector storage
10
+ openai==1.31.1 # For embeddings
11
+ tiktoken==0.7.0 # For embeddings
12
+
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+ # install markdown depenendies with: `pip install "unstructured[md]"` after install the requirements file. Leave this line commented out.