Rajut commited on
Commit
4310663
·
verified ·
1 Parent(s): a5ef2e4

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +4 -17
app.py CHANGED
@@ -1,14 +1,10 @@
1
  import os
2
- from PyPDF2 import PdfReader
3
- import docx
4
  from langchain.text_splitter import CharacterTextSplitter
5
  from langchain.embeddings.openai import OpenAIEmbeddings
6
  from langchain.vectorstores import FAISS
7
  from langchain.chains.question_answering import load_qa_chain
8
  from langchain_openai import OpenAI
9
- from langchain.callbacks import get_openai_callback
10
  import gradio as gr
11
- from aiohttp import web
12
 
13
  # Set your OpenAI API key
14
  os.environ["OPENAI_API_KEY"] = "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"
@@ -42,19 +38,10 @@ llm = OpenAI()
42
  chain = load_qa_chain(llm, chain_type="stuff")
43
 
44
  # Define the chatbot interface
45
- async def chatbot_interface(request):
46
- data = await request.post()
47
- input_text = data.get("input_text", "")
48
-
49
  docs = docsearch.similarity_search(input_text)
50
  response = chain.run(input_documents=docs, question=input_text)
51
-
52
- return web.Response(text=response)
53
 
54
- # Set up the web application
55
- app = web.Application()
56
- app.router.add_post('/chatbot', chatbot_interface)
57
-
58
- # Run the web server
59
- if __name__ == "__main__":
60
- web.run_app(app, port=os.getenv("PORT", 8080))
 
1
  import os
 
 
2
  from langchain.text_splitter import CharacterTextSplitter
3
  from langchain.embeddings.openai import OpenAIEmbeddings
4
  from langchain.vectorstores import FAISS
5
  from langchain.chains.question_answering import load_qa_chain
6
  from langchain_openai import OpenAI
 
7
  import gradio as gr
 
8
 
9
  # Set your OpenAI API key
10
  os.environ["OPENAI_API_KEY"] = "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"
 
38
  chain = load_qa_chain(llm, chain_type="stuff")
39
 
40
  # Define the chatbot interface
41
+ def chatbot_interface(input_text):
 
 
 
42
  docs = docsearch.similarity_search(input_text)
43
  response = chain.run(input_documents=docs, question=input_text)
44
+ return response
 
45
 
46
+ iface = gr.Interface(fn=chatbot_interface, inputs="text", outputs="text")
47
+ iface.launch()