Upload app.py

app.py

@@ -1,64 +1,82 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
+# -*- coding: utf-8 -*-
+"""Chatbot using Python Project.ipynb
 
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1tNZAGbjtsEUqIylR9_nzpBLhj22zIWJy
 """
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+!pip install requests gradio
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+API_KEY = "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"
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+import requests
 
-    messages.append({"role": "user", "content": message})
+def chat_with_mistral(user_input):
+    url = "https://openrouter.ai/api/v1/chat/completions"
 
-    response = ""
+    headers = {
+        "Authorization": f"Bearer {API_KEY}",
+        "Content-Type": "application/json"
+    }
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+    data = {
+        "model": "mistralai/mistral-small-24b-instruct-2501:free",
+        "messages": [{"role": "user", "content": user_input}]
+    }
 
-        response += token
-        yield response
+    response = requests.post(url, json=data, headers=headers)
 
+    if response.status_code == 200:
+        return response.json()["choices"][0]["message"]["content"]
+    else:
+        return f"Error: {response.status_code} - {response.text}"
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
+user_input = "what about indian cricket team"
+response = chat_with_mistral(user_input)
+print("Chatbot:", response)
+
+import gradio as gr
+
+def mistral_chatbot(user_input):
+    return chat_with_mistral(user_input)
+
+# Created a chatbot interface
+chatbot_ui = gr.Interface(
+    fn=mistral_chatbot,
+    inputs="text",
+    outputs="text",
+    title="Mistral AI Chatbot",
+    description="Chat with an AI-powered assistant using Mistral 7B."
 )
 
+# Launching the chatbot
+chatbot_ui.launch()
+
+chat_history = []
+
+def chat_with_mistral_context(user_input):
+    global chat_history  # Maintain history
+
+    url = "https://api.mistral.ai/v1/chat/completions"
+    headers = {
+        "Authorization": f"Bearer {API_KEY}",
+        "Content-Type": "application/json"
+    }
+
+    chat_history.append({"role": "user", "content": user_input})  # Add user message
+
+    data = {
+        "model": "mistralai/mistral-small-24b-instruct-2501:free",
+        "messages": chat_history
+    }
+
+    response = requests.post(url, json=data, headers=headers)
 
-if __name__ == "__main__":
-    demo.launch()
+    if response.status_code == 200:
+        bot_response = response.json()["choices"][0]["message"]["content"]
+        chat_history.append({"role": "assistant", "content": bot_response})  # Add bot response
+        return bot_response
+    else:
+        return f"Error: {response.status_code} - {response.text}"