Duplicate from Warlord-K/IITI-GPT

Co-authored-by: Yatharth Gupta <Warlord-K@users.noreply.huggingface.co>

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README.md

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+---
+title: IITI GPT
+emoji: 💻
+colorFrom: green
+colorTo: gray
+sdk: gradio
+sdk_version: 3.39.0
+app_file: app.py
+pinned: false
+license: openrail
+duplicated_from: Warlord-K/IITI-GPT
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+from gradio_client import Client
+from hugchat import hugchat
+from hugchat.login import Login
+from gtts import gTTS
+import gradio as gr
+
+client = Client("https://sanchit-gandhi-whisper-large-v2.hf.space/")
+
+retrieval = Client("https://warlord-k-iiti-similarity.hf.space/")
+
+n_conv = 0
+
+init_prompt ="## Instruction: You are an AI language model and must return truthful responses as per the information below\n ##Input: Information: My name is IITIGPT. I am a helpful and truthful chatbot. I can help answer any questions about the IIT Indore campus."
+info="Information: \n"
+q_prompt="\n ##Instruction: Please  provide an appropriate response to the following: \n"
+
+def login_hf():
+  email="jackrudolf584@gmail.com"
+  passwd="Qwertypassword1"
+  
+  # login
+  sign = Login(email, passwd)
+  cookies = sign.login()
+  
+  # Create a ChatBot
+  chatbot = hugchat.ChatBot(cookies=cookies.get_dict())  # or cookie_path="usercookies/<email>.json"
+  chatbot.chat(init_prompt)
+  
+  print("Logged In")
+  return chatbot
+
+def change_conv():
+    # Create a new conversation
+    id = chatbot.new_conversation()
+    chatbot.change_conversation(id)
+    chatbot.chat(init_prompt)
+    chatbot.cookies = {}
+    
+def answer_question(question):
+    global n_conv
+    if(n_conv > 3):
+        n_conv = 0
+        change_conv(chatbot)
+    information = retrieval.predict(question, api_name = "/predict")
+    answer = chatbot.chat(info+ information +q_prompt+" "+question+"""\n ##Response:""")
+    n_conv+=1
+    return answer
+
+chatbot = login_hf()
+
+def file_to_text(audio_fpath):
+
+    result = client.predict(
+        audio_fpath,
+        "transcribe", # str in 'Audio input' Radio component
+        api_name="/predict"
+    )
+    return result
+
+def text_file(text):
+    tts = gTTS(text, lang = "en")
+    tts.save("abc.mp3")
+    return "abc.mp3"
+
+def main(filename):
+  text = file_to_text(filename)
+  print(text)
+  answer = answer_question(text)
+  print(answer)
+  output = text_file(answer)
+  return output
+
+demo = gr.Interface(main, "audio", "audio")
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+hugchat
+gradio
+gradio_client
+gtts