Reorder: tool use is now 05, neural networks is 06

The LLM arc completes at section 05 (agentic systems), with
neural networks as a standalone ML deep-dive in section 06.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

05-tool-use/thermo_assistant.py

@@ -0,0 +1,114 @@
+# thermo_assistant.py
+#
+# A chemical engineering assistant that uses Ollama tool calling
+# to compute vapor pressures with the Antoine equation.
+#
+# CHEG 667-013
+# E. M. Furst
+
+import math
+from ollama import chat
+
+# Antoine equation: log10(P) = A - B / (C + T)
+# Returns vapor pressure in mmHg given temperature in degrees Celsius.
+
+ANTOINE_CONSTANTS = {
+    'water':    {'A': 8.07131, 'B': 1730.63,  'C': 233.426},
+    'ethanol':  {'A': 8.20417, 'B': 1642.89,  'C': 230.300},
+    'benzene':  {'A': 6.90565, 'B': 1211.033, 'C': 220.790},
+    'toluene':  {'A': 6.95464, 'B': 1344.800, 'C': 219.482},
+    'acetone':  {'A': 7.02447, 'B': 1161.0,   'C': 224.0},
+}
+
+def vapor_pressure(compound: str, temperature_C: float) -> str:
+    """
+    Calculate the vapor pressure of a compound using the Antoine equation.
+
+    Args:
+        compound: Name of the compound (water, ethanol, benzene, toluene, or acetone)
+        temperature_C: Temperature in degrees Celsius
+
+    Returns:
+        The vapor pressure in mmHg, or an error message if the compound is unknown
+    """
+    compound = compound.lower().strip()
+    if compound not in ANTOINE_CONSTANTS:
+        return f"Unknown compound: {compound}. Available: {', '.join(ANTOINE_CONSTANTS.keys())}"
+
+    c = ANTOINE_CONSTANTS[compound]
+    log_p = c['A'] - c['B'] / (c['C'] + temperature_C)
+    p_mmhg = 10 ** log_p
+    return f"{p_mmhg:.2f} mmHg"
+
+
+def available_compounds() -> str:
+    """
+    List the compounds available for vapor pressure calculations.
+
+    Returns:
+        A comma-separated list of compound names
+    """
+    return ', '.join(ANTOINE_CONSTANTS.keys())
+
+
+# Tool dispatch table
+tools = {
+    'vapor_pressure': vapor_pressure,
+    'available_compounds': available_compounds,
+}
+
+# System prompt: tell the model what it is
+system_message = {
+    'role': 'system',
+    'content': (
+        'You are a chemical engineering assistant. You have access to tools '
+        'for computing vapor pressures using the Antoine equation. Use them '
+        'when asked about vapor pressures or boiling behavior. Report results '
+        'with units. If asked about a compound you do not have data for, say so.'
+    ),
+}
+
+
+def ask(question: str) -> str:
+    """Send a question to the assistant and return the response."""
+    messages = [system_message, {'role': 'user', 'content': question}]
+
+    response = chat(
+        'llama3.1:8b',
+        messages=messages,
+        tools=[vapor_pressure, available_compounds],
+    )
+
+    # Handle tool calls (there may be more than one)
+    while response.message.tool_calls:
+        for tool_call in response.message.tool_calls:
+            name = tool_call.function.name
+            args = tool_call.function.arguments
+            print(f'  [tool] {name}({args})')
+            result = tools[name](**args)
+            print(f'  [result] {result}')
+            messages.append(response.message)
+            messages.append({
+                'role': 'tool',
+                'content': str(result),
+                'tool_name': name,
+            })
+
+        response = chat(
+            'llama3.1:8b',
+            messages=messages,
+            tools=[vapor_pressure, available_compounds],
+        )
+
+    return response.message.content
+
+
+# Interactive loop
+if __name__ == '__main__':
+    print('Thermo Assistant (type "quit" to exit)\n')
+    while True:
+        question = input('You: ')
+        if question.strip().lower() in ('quit', 'exit', 'q'):
+            break
+        answer = ask(question)
+        print(f'\nAssistant: {answer}\n')