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.env

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+API_KEY = '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'

README.md

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 ---
-title: Simple Gradio Langchain App
-emoji: 🌖
-colorFrom: green
-colorTo: green
+title: Simple_Gradio_Langchain_App
+app_file: langchain.py
 sdk: gradio
 sdk_version: 3.46.0
-app_file: app.py
-pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

chat-app.py

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+import openai
+import os
+from dotenv import load_dotenv
+
+openai.api_key = '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'
+message_history = []
+
+def chat(userInput, role = 'user'):
+    message_history.append({'role': role, 'content': userInput})
+    completion = openai.ChatCompletion.create(
+        model = 'gpt-3.5-turbo',
+        messages = message_history
+    )
+    replContent = completion.choices[0].message.content
+    print(replContent)
+    message_history.append({'role': 'assistant', 'content': replContent })
+    return replContent
+
+for i in range(2):
+    userInput = input('> :')
+    print(userInput)
+    print()
+    chat(userInput)
+    print()

gradio-chat-app.py

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+import gradio as gr
+import openai
+
+openai.api_key = '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'
+message_history = []
+
+# message_history = [
+#     {
+#         "role": "user",
+#         "content": f"You are a joke bot, but I'll specify a subject matter in messages, and you'll reply with a jokes that includes the subjects I mention in my messages. Reply only with jokes to further input, If you understand, say OK."},
+#     {
+#         "role": "assistant",
+#         "content": f"OK"
+#     } 
+# ]
+
+def predict(input):
+    global message_history
+    message_history.append({'role': 'user', 'content': input})
+    completion = openai.ChatCompletion.create(
+        model = 'gpt-3.5-turbo',
+        messages = message_history
+    )
+    replContent = completion.choices[0].message.content
+    print(replContent)
+    message_history.append({'role': 'assistant', 'content': replContent })
+    response = [(message_history[i]['content'], message_history[i+1]['content']) for i in range(0, len(message_history)-1, 2)]
+    return response
+
+with gr.Blocks() as d:
+    chatbot = gr.Chatbot()
+    with gr.Row():
+        textbox = gr.Textbox(show_lable = False, placeholder = "Type your message here").style(container = False)
+        textbox.submit(predict, textbox, chatbot)
+        textbox.submit(None, None, textbox, _js = "() => {''}")
+
+d.launch()

langchain.py

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+import os
+import gradio as gr
+from dotenv import load_dotenv, find_dotenv
+_ = load_dotenv(find_dotenv())
+
+from langchain.chains import ConversationChain
+from langchain.chat_models import ChatOpenAI
+from langchain.memory import ConversationBufferMemory
+
+llm = ChatOpenAI(temperature=0.0)
+memory = ConversationBufferMemory()
+conversion = ConversationChain(
+    llm=llm,
+    memory=memory,
+    verbose=False
+)
+
+def takeinput(name):
+    output_str = conversion.predict(input=name)
+    return output_str
+
+demo = gr.Interface(
+        fn=takeinput,
+        inputs=["text"],
+        outputs=["text"]
+)
+
+demo.launch()