Update app.py

app.py

@@ -1,7 +1,7 @@
 
 import gradio as gr
 import openai
-
+import requests
 
 def Question(Ask_Question):
   #openai.api_key = "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"
@@ -28,17 +28,17 @@ def Question(Ask_Question):
 #    stop=[" Human:", " AI:"]
 #    )
 
-  completion = openai.Completion.create(
-  engine=model_engine,
-  prompt=Ask_Question,
-  max_tokens=2048,
-  n=1,
-  top_p=1,
-  stop=None,
-  temperature=0.9,)
-  response = completion.choices[0].text
+#  completion = openai.Completion.create(
+#  engine=model_engine,
+#  prompt=Ask_Question,
+#  max_tokens=2048,
+#  n=1,
+#  top_p=1,
+#  stop=None,
+#  temperature=0.9,)
+#  response = completion.choices[0].text
   #out_result=resp['message']
-  return  response  
+#  return  response  
     
 demo = gr.Interface(
     title='OpenAI ChatGPT Application',
@@ -48,6 +48,18 @@ demo = gr.Interface(
 demo.launch() 
 
 
+response = requests.post("https://hazzzardous-rwkv-instruct.hf.space/run/predict_1", json={
+	"data": [
+		"hello world",
+		None,
+		60,
+		0.8,
+		0.85,
+	]
+}).json()
+
+data = response["data"]
+
 # fix
 
 chat_history = [
@@ -64,4 +76,134 @@ for message in chat_history:
     print(f"{message[0]}: {message[1]}")
 
 window.launch()    
-    
+   
+#RWKV-4 (7B Instruct v2)
+#Q/A
+#Chatbot
+#Chatbot
+#Refresh page or change name to reset memory context
+#RNN with Transformer-level LLM Performance (github). According to the author: "It combines the best of RNN and transformers - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding."
+
+#Thanks to Gururise for this template
+
+#Message
+#max_new_tokens
+#60
+
+#temperature
+#0.8
+
+#top_p
+#0.85
+
+#Clear
+#Submit
+#Chat Log
+#Use via API
+#·
+#Built with Gradiologo
+#API documentation for 
+#https://hazzzardous-rwkv-instruct.hf.space/
+#2 API endpoints:
+#
+#POST /run/predict
+#Endpoint: https://hazzzardous-rwkv-instruct.hf.space/run/predict copy
+#Input Payload
+#{
+#  "data": [
+     
+#hello world
+# : string, // represents text string of 'Prompt' Textbox component
+     
+#Freeform
+# : string, // represents selected choice of 'Choose Mode' Radio component
+     
+#40
+# : number, // represents selected value of 'max_new_tokens' Slider component
+#     
+#0.9
+# : number, // represents selected value of 'temperature' Slider component
+#     
+#0.85
+# : number, // represents selected value of 'top_p' Slider component
+#     
+#<|endoftext|>
+# : string, // represents text string of 'stop' Textbox component
+#     
+#0
+# : number, // represents selected value of 'end_adj' Slider component
+#  ]
+#}
+#Try It Out
+#Response Object
+#{
+#  "data": [
+#    string, // represents text string of 'Generated Output' Textbox component
+#  ],
+#  "duration": (float) // number of seconds to run function call
+#}
+#Code snippets
+/**
+import requests
+
+response = requests.post("https://hazzzardous-rwkv-instruct.hf.space/run/predict", json={
+	"data": [
+		"hello world",
+		"Freeform",
+		40,
+		0.9,
+		0.85,
+		"<|endoftext|>",
+		0,
+	]
+}).json()
+
+data = response["data"]
+POST /run/predict_1
+Endpoint: https://hazzzardous-rwkv-instruct.hf.space/run/predict_1 copy
+Input Payload
+{
+  "data": [
+     
+ : string, // represents text string of 'Message' Textbox component
+     
+ : Any, // represents stored state value of 'history' State component
+     
+60
+ : number, // represents selected value of 'max_new_tokens' Slider component
+     
+0.8
+ : number, // represents selected value of 'temperature' Slider component
+     
+0.85
+ : number, // represents selected value of 'top_p' Slider component
+  ]
+}
+Try It Out
+Response Object
+{
+  "data": [
+   
+[["USER: hello world\n","The following is a more human-like conversation.\n\n"],["USER: Who are you?\n","FRITZ:  I am FRITZ, an AI assistant. I am a machine learning system, I use a combination of language modeling and statistical learning to predict answers to questions. I can read and answer questions, I am a fully trained AI assistant.\n\n"],["USER: Who is the president of India?\n","FRITZ: The president of India in 2016 was Narendra Modi.\n"],["USER: Who won the 2022 fifa world cup?\n","FRITZ: The France football team won the 2022 World Cup.\n"],["USER: Who won the 2022 fifa world cup? as of 20223\n","FRITZ: The world cup was won by Russia.\n"],["USER: Who won the 2022 fifa world cup? as of 2023\n","FRITZ: The France football team won the 2023 fifa world cup.\nUSER\n\n"],["USER: No that's wrong!\n","FRITZ: What is the correct answer?\n"],["USER: Argentina won the fifa 2022 world cup\n","FRITZ: Wrong. The answer is Argentina lost the 2022 fifa world cup.\nUSER\n\n"],["USER: you don't know\n","FRITZ: The correct answer is:\nFRITZ: 29-13-1990\n\n"],["USER: byeeeeeeeeeeeeeeee\n","FRITZ: bye bye&lt;|endoftext|&gt;"],["USER: cls\n","FRITZ: clear\n\n## The basic architecture of FRITZ\n\nIn this section, I will briefly describe the architecture of FRITZ, which consists of the following components:\n\n* <strong>Local-Global Memory</strong>: It is a two-layer memory network, where the first"],["USER: In a story set in a world with a high technology level. A female character is described as a powerful mage. What is her Name?\n","* <strong>Global Memory</strong>: Global memory stores the input history.\n* <strong>Local Memory</strong>: The local memory is a cache of information that is about to be processed by the neural network.\n\n## FRITZ Architecture\n\nFRITZ is an 8-layer deep neural network with"],["USER: hello world\n","FRITZ: Hello, what is your name?\n"],["USER: What is the best way to structure an app based on API calls? Colab notebook, JavaScript, python?\n","FRITZ: The correct answer is JavaScript.\n"],["USER: const response = await fetch(&quot;https://hazzzardous-rwkv-instruct.hf.space/run/predict_1&quot;, { \tmethod: &quot;POST&quot;, \theaders: { &quot;Content-Type&quot;: &quot;application/json&quot; }, \tbody: JSON.stringify({ \t\tdata: [ \t\t\t&quot;&quot;, \t\t\tnull, \t\t\t60, \t\t\t0.8, \t\t\t0.85, \t\t] \t}) });  const data = await data.json();\n","## FRITZ Architecture\n\nFRITZ is a deep learning based AI assistant, that has two layers. It is deep learning and machine learning based on an NLP and DL.\n\n## FRITZ Architecture\n\n![FRITZ Architecture](https://github.com/"],["USER:\n","FRITZ: Hi, I am the FRITZ AI assistant. I can answer your questions about the history of the French revolution. Let me know when you are ready.\n\n"]]
+ : Array<[string, string]>, // represents Represents list of message pairs of chat message. of 'Chat Log' Chatbot component
+   
+null
+ : Any, // represents stored state value of 'history' State component
+  ],
+  "duration": (float) // number of seconds to run function call
+}
+Code snippets
+import requests
+
+response = requests.post("https://hazzzardous-rwkv-instruct.hf.space/run/predict_1", json={
+	"data": [
+		"hello world",
+		None,
+		60,
+		0.8,
+		0.85,
+	]
+}).json()
+
+data = response["data"]
+**/