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Gopala Krishna
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34564f3
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Parent(s):
dfee6f8
Working
Browse files- .vs/MyChatGPTTurbo/FileContentIndex/{ab91987c-a512-4d01-b8b5-27fcada31777.vsidx → c69d4add-0ca9-42c0-9da9-fec814f20f6f.vsidx} +0 -0
- .vs/MyChatGPTTurbo/FileContentIndex/feff3d0f-367e-40ad-b46b-abeffe69c7f7.vsidx +0 -0
- .vs/MyChatGPTTurbo/v17/.wsuo +0 -0
- .vs/ProjectSettings.json +3 -0
- .vs/slnx.sqlite +0 -0
- app.py +154 -25
.vs/MyChatGPTTurbo/FileContentIndex/{ab91987c-a512-4d01-b8b5-27fcada31777.vsidx → c69d4add-0ca9-42c0-9da9-fec814f20f6f.vsidx}
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.vs/MyChatGPTTurbo/FileContentIndex/feff3d0f-367e-40ad-b46b-abeffe69c7f7.vsidx
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.vs/MyChatGPTTurbo/v17/.wsuo
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Binary files a/.vs/MyChatGPTTurbo/v17/.wsuo and b/.vs/MyChatGPTTurbo/v17/.wsuo differ
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.vs/ProjectSettings.json
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{
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"CurrentProjectSetting": null
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}
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.vs/slnx.sqlite
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app.py
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@@ -1,9 +1,48 @@
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import os
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import openai
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import gradio as gr
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try:
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-
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except KeyError:
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error_message = "System is at capacity right now.Please try again later"
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@@ -15,30 +54,120 @@ else:
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{"role": "system", "content": "My AI Assistant"},
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]
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chat = openai.ChatCompletion.create(
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model="gpt-3.5-turbo", messages=messages
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)
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reply = chat.choices[0].message.content
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messages.append({"role": "assistant", "content": reply})
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return reply
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except openai.error.OpenAIError as e:
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return "System is at capacity right now.Please try again later"
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#
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#
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fn=chatbot,
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inputs=gr.inputs.Textbox(lines=7, label="Query"),
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outputs=gr.outputs.Textbox(label="Response"),
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theme=gr.themes.Default(primary_hue="slate"))
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iface.launch()
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#import os
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#import openai
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#import gradio as gr
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#try:
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# openai.api_key = os.environ["OPENAI_API_KEY"]
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#except KeyError:
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# error_message = "System is at capacity right now.Please try again later"
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# print(error_message)
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# def chatbot(input):
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# return error_message
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#else:
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# messages = [
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# {"role": "system", "content": "My AI Assistant"},
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# ]
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#def chatbot(input):
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# try:
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# if input:
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# messages.append({"role": "user", "content": input})
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# chat = openai.ChatCompletion.create(
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# model="gpt-3.5-turbo", messages=messages
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# )
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# reply = chat.choices[0].message.content
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# messages.append({"role": "assistant", "content": reply})
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# return reply
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# except openai.error.OpenAIError as e:
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# return "System is at capacity right now.Please try again later"
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#iface = gr.Interface(
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# fn=chatbot,
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# inputs=gr.inputs.Textbox(lines=7, label="Query"),
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# outputs=gr.outputs.Textbox(label="Response"),
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# theme=gr.themes.Default(primary_hue="slate"))
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#iface.launch()
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import os
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import gradio as gr
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import json
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import requests
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import openai
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try:
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openai.api_key = os.environ["OPENAI_API_KEY"]
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except KeyError:
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error_message = "System is at capacity right now.Please try again later"
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{"role": "system", "content": "My AI Assistant"},
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]
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#Streaming endpoint for OPENAI ChatGPT
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API_URL = "https://api.openai.com/v1/chat/completions"
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top_p_chatgpt = 1.0
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temperature_chatgpt = 1.0
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#Predict function for CHATGPT
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def chatbot(inputs, chat_counter_chatgpt, chatbot_chatgpt=[], history=[]):
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#Define payload and header for chatgpt API
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payload = {
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"model": "gpt-3.5-turbo",
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"messages": [{"role": "user", "content": f"{inputs}"}],
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"temperature" : 1.0,
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"top_p":1.0,
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"n" : 1,
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"stream": True,
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"presence_penalty":0,
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"frequency_penalty":0,
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}
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {openai.api_key}"
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}
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#Handling the different roles for ChatGPT
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if chat_counter_chatgpt != 0 :
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messages=[]
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for data in chatbot_chatgpt:
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temp1 = {}
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temp1["role"] = "user"
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temp1["content"] = data[0]
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temp2 = {}
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temp2["role"] = "assistant"
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temp2["content"] = data[1]
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messages.append(temp1)
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messages.append(temp2)
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temp3 = {}
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temp3["role"] = "user"
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temp3["content"] = inputs
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messages.append(temp3)
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payload = {
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"model": "gpt-3.5-turbo",
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"messages": messages, #[{"role": "user", "content": f"{inputs}"}],
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"temperature" : temperature_chatgpt, #1.0,
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"top_p": top_p_chatgpt, #1.0,
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"n" : 1,
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"stream": True,
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"presence_penalty":0,
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"frequency_penalty":0,
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}
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chat_counter_chatgpt+=1
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history.append("You asked: "+ inputs)
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# make a POST request to the API endpoint using the requests.post method, passing in stream=True
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response = requests.post(API_URL, headers=headers, json=payload, stream=True)
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token_counter = 0
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partial_words = ""
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counter=0
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for chunk in response.iter_lines():
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#Skipping the first chunk
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if counter == 0:
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counter+=1
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continue
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# check whether each line is non-empty
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if chunk.decode() :
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chunk = chunk.decode()
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# decode each line as response data is in bytes
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if len(chunk) > 13 and "content" in json.loads(chunk[6:])['choices'][0]["delta"]:
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partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
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if token_counter == 0:
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history.append(" " + partial_words)
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else:
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history[-1] = partial_words
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chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ] # convert to tuples of list
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token_counter+=1
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yield chat, history, chat_counter_chatgpt # this resembles {chatbot: chat, state: history}
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def reset_textbox():
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return gr.update(value="")
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def reset_chat(chatbot, state):
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return None, []
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with gr.Blocks(css="""#col_container {width: 1000px; margin-left: auto; margin-right: auto;}
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#chatgpt {height: 700px; overflow: auto;}} """, theme=gr.themes.Default(primary_hue="slate") ) as demo:
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with gr.Row():
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with gr.Column(scale=14):
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with gr.Box():
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with gr.Row():
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with gr.Column(scale=13):
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inputs = gr.Textbox(label="Ask anything ⤵️ " )
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with gr.Column(scale=1):
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b1 = gr.Button('Submit', elem_id = 'submit').style(full_width=True)
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b2 = gr.Button('Clear', elem_id = 'clear').style(full_width=True)
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state_chatgpt = gr.State([])
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with gr.Box():
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with gr.Row():
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chatbot_chatgpt = gr.Chatbot(elem_id="chatgpt", label='')
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chat_counter_chatgpt = gr.Number(value=0, visible=False, precision=0)
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inputs.submit(reset_textbox, [], [inputs])
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b1.click( chatbot,
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[ inputs, chat_counter_chatgpt, chatbot_chatgpt, state_chatgpt],
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[chatbot_chatgpt, state_chatgpt],)
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b2.click(reset_chat, [chatbot_chatgpt, state_chatgpt], [chatbot_chatgpt, state_chatgpt])
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demo.queue(concurrency_count=16).launch(height= 2500, debug=True)
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