Upload HF(Hugging_Face).py

HF(Hugging_Face).py

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+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+
+# Load the model and tokenizer from Hugging Face
+model_name = "mistralai/Mistral-7B-Instruct-v0.3"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Initialize the text-generation pipeline
+pipe = pipeline("conversational", model=model, tokenizer=tokenizer)
+
+# Function to handle user input and generate responses
+def electronics_chatbot():
+    print("Welcome to the Electronics Components Chatbot! Type 'exit' to quit.")
+    print("Ask me about any electronics component, such as 'What is a resistor?' or 'How does a capacitor work in a circuit?'")
+
+    # Initialize conversation history (for context)
+    conversation_history = []
+
+    while True:
+        user_input = input("You: ")
+
+        if user_input.lower() == 'exit':
+            print("Goodbye!")
+            break
+
+        # Add user input to conversation history (optional for more context)
+        conversation_history.append(user_input)
+
+        # Prepare the message input for the model
+        messages = [{"role": "user", "content": user_input}]
+        
+        # Generate the response using the model
+        response = pipe(messages)
+        
+        # Display the response
+        print(f"Ollama (Bot): {response[0]['generated_text']}\n")
+        
+        # Optionally, append the bot's response to the conversation history for context
+        conversation_history.append(response[0]['generated_text'])
+
+# Start the chatbot
+electronics_chatbot()