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| import json | |
| import os | |
| import gradio as gr | |
| from huggingface_hub import InferenceClient | |
| # Function to call the Llama 3.1 8B model through Hugging Face API | |
| def call_llama_model(user_query): | |
| # Initialize the inference client with access token | |
| client = InferenceClient( | |
| "meta-llama/Meta-Llama-3.1-8B-Instruct", | |
| token=os.environ.get("HF_TOKEN") | |
| ) | |
| # Define the addition function schema | |
| function_schema = { | |
| "name": "add_numbers", | |
| "description": "Add two numbers together", | |
| "parameters": { | |
| "type": "object", | |
| "properties": { | |
| "num1": { | |
| "type": "number", | |
| "description": "First number to add" | |
| }, | |
| "num2": { | |
| "type": "number", | |
| "description": "Second number to add" | |
| } | |
| }, | |
| "required": ["num1", "num2"] | |
| } | |
| } | |
| # Create the system prompt with function definition | |
| system_prompt = f"""You have access to the following function: | |
| {json.dumps(function_schema, indent=2)} | |
| When given a query about adding numbers, you must: | |
| 1. Extract the two numbers from the query | |
| 2. Call the add_numbers function with these numbers | |
| 3. Respond ONLY with a valid JSON object in this exact format: | |
| {{"function_call": {{"name": "add_numbers", "parameters": {{"num1": [first number], "num2": [second number]}}}}}} | |
| DO NOT include any explanation, just the JSON. | |
| """ | |
| # Call the model with the appropriate format for Llama 3.1 | |
| response = client.text_generation( | |
| prompt=f"<|system|>\n{system_prompt}\n<|user|>\n{user_query}\n<|assistant|>", | |
| max_new_tokens=256, | |
| temperature=0.1, | |
| return_full_text=False | |
| ) | |
| return response | |
| # Function to parse the model response and calculate the result | |
| def process_addition(query): | |
| try: | |
| # Get model response | |
| model_response = call_llama_model(query) | |
| # Create a debug output with the raw response | |
| debug_info = f"Raw model response:\n{model_response}\n\n" | |
| # Try to parse the JSON response | |
| try: | |
| # Find the JSON part in the response (it might have additional text) | |
| json_start = model_response.find('{') | |
| json_end = model_response.rfind('}') + 1 | |
| if json_start >= 0 and json_end > json_start: | |
| json_str = model_response[json_start:json_end] | |
| response_data = json.loads(json_str) | |
| debug_info += f"Parsed JSON:\n{json.dumps(response_data, indent=2)}\n\n" | |
| else: | |
| return f"Error: No valid JSON found in response.\n\n{debug_info}" | |
| # Check if it has a function call | |
| if "function_call" in response_data: | |
| function_name = response_data["function_call"]["name"] | |
| params = response_data["function_call"]["parameters"] | |
| if function_name == "add_numbers": | |
| # Extract the numbers | |
| num1 = float(params["num1"]) | |
| num2 = float(params["num2"]) | |
| result = num1 + num2 | |
| # Return a formatted response | |
| return f""" | |
| ### Input Processed Successfully | |
| **Numbers extracted:** {num1} and {num2} | |
| **Function called:** `{function_name}` | |
| **Result:** {result} | |
| **JSON Function Call:** | |
| ```json | |
| {json.dumps(response_data, indent=2)} |