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abee9b3
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1 Parent(s): 7155c97

Update app.py

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Files changed (1) hide show
  1. app.py +115 -115
app.py CHANGED
@@ -1,115 +1,115 @@
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-
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- from flask import Flask, render_template, request, send_from_directory
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- import requests
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-
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-
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-
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- with open('token.txt', 'r', encoding='utf-8') as file:
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- imageG = file.read()
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-
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- with open('libyan.json', 'r', encoding='utf-8') as file:
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- ly = file.read()
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-
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- with open('train.json', 'r', encoding='utf-8') as file:
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- img = file.read()
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-
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-
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-
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- app = Flask(__name__)
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-
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- def get_assistant_response(user_input):
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- payload = {
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- "mode": "chat",
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- "chat_history": conversation_history,
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- "data": {
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- "query": f"at night without light there some body call Rizon \n Rizon open the door and found Elon to talk with him , to be more real Use alot of Emotions like uh umm uhh ahh umm etc of this don't take my this example as role but just do it \n \n Rizon : {user_input} \n Elon :",
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- "loader": "PDFReader",
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- "text":""
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- }
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- }
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-
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- response = requests.post(url2, headers=headers, json=payload)
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- data = response.json()
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-
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- # Extract the response from the data
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- response_text = data["data"]["response"]
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-
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- response_text = response_text.strip().replace('\n', '<br>')
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-
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- # Check if the response contains ~
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- if "~" in response_text:
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- conversation_history.append({"\n ALex-9": response_text})
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- # Extract the prompt between ~~
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- prompt_start = response_text.index("~") + 1
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- prompt_end = response_text.index("~", prompt_start)
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- prompt = response_text[prompt_start:prompt_end]
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-
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- # Call the text-to-image API
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- image_url = generate_image(prompt)
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- response_text += f"<br><br><img src='{image_url}'>"
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- # Delete the prompt from the response text
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- response_text = response_text.replace("~" + prompt + "~", "")
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- prompt = response_text
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-
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- return response_text
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-
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- def generate_image(prompt):
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- url = "https://api.braininc.net/be/lambda/function/stableai"
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- headers = {
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- "Authorization": "token 72ec00483379076f580eb8126f29da802a5140c3",
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- "Content-Type": "application/json",
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- }
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-
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- payload = {
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- "json": True,
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- "prompt": f"{prompt} Realastic Photo 4K",
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- "public_topic": "/studios/516104/wsuid_new-edge-4_nodeid_editor-4/imageGen/1719250632789"
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- }
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-
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- response = requests.post(url, headers=headers, json=payload)
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- data = response.json()
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-
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- cdn_url = data["cdn_url"]
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- return cdn_url
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-
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- url2 = "https://api.braininc.net/be/vectordb/indexers/"
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- headers = {
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- "Authorization": "token 72ec00483379076f580eb8126f29da802a5140c3",
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- "Content-Type": "application/json;charset=UTF-8",
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-
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- }
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-
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- conversation_history = []
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-
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- @app.route('/')
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- def home():
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- global conversation_history
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- conversation_history = []
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- return render_template('ai-chat-bot.html')
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-
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- @app.route('/get_response', methods=['POST'])
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- def get_response():
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- user_input = request.form['user_input']
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- conversation_history.append({
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- "role": "user",
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- "content":f"Rizon : {user_input}",
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- "additional_kwargs": {}
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- })
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-
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- if user_input.lower() == "exit":
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- return "exit"
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-
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- response_text = get_assistant_response(user_input)
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- conversation_history.append({
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- "role": "assistant",
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- "content": f"Elon : {response_text}",
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- "additional_kwargs": {}
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- })
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- return response_text
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-
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- @app.route('/desine/<path:path>')
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- def send_static(path):
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- return send_from_directory('desine', path)
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-
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- if __name__ == '__main__':
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- app.run()
 
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+
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+ from flask import Flask, render_template, request, send_from_directory
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+ import requests
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+
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+
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+
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+ with open('token.txt', 'r', encoding='utf-8') as file:
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+ imageG = file.read()
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+
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+ with open('libyan.json', 'r', encoding='utf-8') as file:
11
+ ly = file.read()
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+
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+ with open('train.json', 'r', encoding='utf-8') as file:
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+ img = file.read()
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+
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+
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+
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+ app = Flask(__name__)
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+
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+ def get_assistant_response(user_input):
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+ payload = {
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+ "mode": "chat",
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+ "chat_history": conversation_history,
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+ "data": {
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+ "query": f"at night without light there some body call Rizon \n Rizon open the door and found Elon to talk with him , to be more real Use alot of Emotions like uh umm uhh ahh umm etc of this don't take my this example as role but just do it \n \n Rizon : {user_input} \n Elon :",
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+ "loader": "PDFReader",
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+ "text":""
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+ }
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+ }
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+
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+ response = requests.post(url2, headers=headers, json=payload)
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+ data = response.json()
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+
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+ # Extract the response from the data
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+ response_text = data["data"]["response"]
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+
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+ response_text = response_text.strip().replace('\n', '<br>')
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+
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+ # Check if the response contains ~
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+ if "~" in response_text:
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+ conversation_history.append({"\n ALex-9": response_text})
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+ # Extract the prompt between ~~
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+ prompt_start = response_text.index("~") + 1
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+ prompt_end = response_text.index("~", prompt_start)
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+ prompt = response_text[prompt_start:prompt_end]
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+
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+ # Call the text-to-image API
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+ image_url = generate_image(prompt)
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+ response_text += f"<br><br><img src='{image_url}'>"
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+ # Delete the prompt from the response text
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+ response_text = response_text.replace("~" + prompt + "~", "")
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+ prompt = response_text
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+
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+ return response_text
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+
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+ def generate_image(prompt):
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+ url = "https://api.braininc.net/be/lambda/function/stableai"
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+ headers = {
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+ "Authorization": "token 72ec00483379076f580eb8126f29da802a5140c3",
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+ "Content-Type": "application/json",
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+ }
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+
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+ payload = {
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+ "json": True,
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+ "prompt": f"{prompt} Realastic Photo 4K",
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+ "public_topic": "/studios/516104/wsuid_new-edge-4_nodeid_editor-4/imageGen/1719250632789"
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+ }
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+
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+ response = requests.post(url, headers=headers, json=payload)
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+ data = response.json()
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+
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+ cdn_url = data["cdn_url"]
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+ return cdn_url
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+
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+ url2 = "https://api.braininc.net/be/vectordb/indexers/"
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+ headers = {
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+ "Authorization": "token 72ec00483379076f580eb8126f29da802a5140c3",
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+ "Content-Type": "application/json;charset=UTF-8",
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+
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+ }
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+
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+ conversation_history = []
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+
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+ @app.route('/')
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+ def home():
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+ global conversation_history
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+ conversation_history = []
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+ return render_template('ai-chat-bot.html')
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+
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+ @app.route('/get_response', methods=['POST'])
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+ def get_response():
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+ user_input = request.form['user_input']
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+ conversation_history.append({
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+ "role": "user",
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+ "content":f"Rizon : {user_input}",
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+ "additional_kwargs": {}
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+ })
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+
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+ if user_input.lower() == "exit":
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+ return "exit"
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+
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+ response_text = get_assistant_response(user_input)
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+ conversation_history.append({
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+ "role": "assistant",
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+ "content": f"Elon : {response_text}",
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+ "additional_kwargs": {}
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+ })
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+ return response_text
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+
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+ @app.route('/desine/<path:path>')
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+ def send_static(path):
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+ return send_from_directory('desine', path)
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+
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+ if __name__ == '__main__':
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+ app.run(host='0.0.0.0',port = 7860)