dfasd
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -1,11 +1,6 @@
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from flask import Flask, render_template, jsonify, request, redirect, url_for
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from flask_wtf.csrf import CSRFProtect
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# from tavily import TavilyClient
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from dotenv import load_dotenv
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import os
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from langchain_community.document_loaders import TextLoader
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from langchain_community.vectorstores import Chroma
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from langchain_text_splitters import CharacterTextSplitter
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@@ -23,13 +18,7 @@ from langchain.prompts import PromptTemplate
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import time
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load_dotenv()
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# TAVILY_API_KEY = os.getenv("TAVILY_API_KEY")
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
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# tavily = TavilyClient(api_key=TAVILY_API_KEY)
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app = Flask(__name__, static_folder='static')
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app.config['SECRET_KEY'] = 'secret'
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csrf = CSRFProtect(app)
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text_splitter = CharacterTextSplitter(separator = "\n", chunk_size=1000, chunk_overlap=200, length_function = len)
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embeddings = OpenAIEmbeddings(openai_api_key=OPENAI_API_KEY)
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@@ -38,20 +27,6 @@ llm = ChatOpenAI(api_key=OPENAI_API_KEY)
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vectordb_path = "./vector_db"
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@app.route('/')
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def home():
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return redirect(url_for('search_view'))
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@app.route('/search_view')
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def search_view():
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return render_template('search.html')
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@app.route('/rag_view')
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def rag_view():
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dbs = [f.name for f in os.scandir(vectordb_path) if f.is_dir()]
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return render_template('rag.html', dbs = dbs)
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@app.route('/query', methods=['POST'])
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def query():
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if request.method == "POST":
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prompt = request.get_json().get("prompt")
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@@ -91,14 +66,6 @@ def query():
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output = stuff_chain({"input_documents": docs, "human_input": prompt}, return_only_outputs=False)
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final_answer = output["output_text"]
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# prompt = ChatPromptTemplate.from_messages(
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# [("system", "Please answer to user's query based on following context.\n\nContext: {context}")]
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# )
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# chain = create_stuff_documents_chain(llm, prompt)
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# answer = chain.invoke({"context": docs, "prompt": prompt})
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data = {"success": "ok", "response": final_answer}
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@@ -108,12 +75,10 @@ def query():
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return jsonify(data)
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@app.route('/uploadDocuments', methods=['POST'])
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@csrf.exempt
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def uploadDocuments():
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# uploaded_files = request.files.getlist('files[]')
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dbname = request.form.get('dbname')
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uploaded_files = ['https://www.airbus.com/sites/g/files/jlcbta136/files/2024-03/Airbus-Annual-Report-2023.pdf', 'https://www.singaporeair.com/saar5/pdf/Investor-Relations/Annual-Report/annualreport2223.pdf']
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if dbname == "":
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return {"success": "db"}
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else:
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return {"success": "bad"}
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@app.route('/dbcreate', methods=['POST'])
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@csrf.exempt
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def dbcreate():
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dbname = request.get_json().get("dbname")
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@@ -147,11 +110,7 @@ def dbcreate():
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else:
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return {'success': 'bad'}
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if __name__ == '__main__':
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app.run(debug=True)
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from dotenv import load_dotenv
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import os
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from langchain_community.document_loaders import TextLoader
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from langchain_community.vectorstores import Chroma
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from langchain_text_splitters import CharacterTextSplitter
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import time
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load_dotenv()
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
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text_splitter = CharacterTextSplitter(separator = "\n", chunk_size=1000, chunk_overlap=200, length_function = len)
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embeddings = OpenAIEmbeddings(openai_api_key=OPENAI_API_KEY)
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vectordb_path = "./vector_db"
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def query():
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if request.method == "POST":
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prompt = request.get_json().get("prompt")
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output = stuff_chain({"input_documents": docs, "human_input": prompt}, return_only_outputs=False)
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final_answer = output["output_text"]
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data = {"success": "ok", "response": final_answer}
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return jsonify(data)
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def uploadDocuments():
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# uploaded_files = request.files.getlist('files[]')
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uploaded_files = ['annualreport2223.pdf', 'Airbus-Annual-Report-2023.pdf']
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dbname = request.form.get('dbname')
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if dbname == "":
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return {"success": "db"}
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else:
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return {"success": "bad"}
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def dbcreate():
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dbname = request.get_json().get("dbname")
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else:
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return {'success': 'bad'}
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import gradio as gr
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chatbot = gr.Chatbot(avatar_images=["user.png", "bot.jpg"], height=600)
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clear_but = gr.Button(value="Clear Chat")
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demo = gr.ChatInterface(fn=search, title="Mediate.com Chatbot Prototype", multimodal=False, retry_btn=None, undo_btn=None, clear_btn=clear_but, chatbot=chatbot)
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