Sample code for the article on Ollama and Python

ollama-python-sdk/README.md

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+# How to Integrate Local LLMs With Ollama and Python
+
+This folder provides the code examples for the Real Python tutorial [How to Integrate Local LLMs With Ollama and Python](https://realpython.com/ollama-python/).

ollama-python-sdk/chat.py

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+from ollama import chat
+
+messages = [
+    {
+        "role": "user",
+        "content": "Explain what Python is in one sentence.",
+    },
+]
+
+response = chat(model="llama3.2:latest", messages=messages)
+print(response.message.content)

ollama-python-sdk/chat_context.py

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+from ollama import chat
+
+messages = [
+    {
+        "role": "system",
+        "content": "You are an expert Python tutor.",
+    },
+    {
+        "role": "user",
+        "content": "Define list comprehensions in a sentence.",
+    },
+]
+response = chat(model="llama3.2:latest", messages=messages)
+print(response.message.content)
+
+messages.append(response.message)  # Keep context
+messages.append(
+    {
+        "role": "user",
+        "content": "Provide a short, practical example.",
+    }
+)
+response = chat(model="llama3.2:latest", messages=messages)
+print(response.message.content)

ollama-python-sdk/generate_text.py

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+from ollama import generate
+
+response = generate(
+    model="llama3.2:latest",
+    prompt="Explain what Python is in one sentence.",
+)
+
+print(response.response)

ollama-python-sdk/streams.py

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+from ollama import chat
+
+stream = chat(
+    model="llama3.2:latest",
+    messages=[
+        {
+            "role": "user",
+            "content": "Explain Python dataclasses with a quick example.",
+        }
+    ],
+    stream=True,
+)
+
+for chunk in stream:
+    print(chunk.message.content, end="", flush=True)

ollama-python-sdk/tool_calling.py

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+import math
+
+from ollama import chat
+
+
+# Define a tool as a Python function
+def square_root(number: float) -> float:
+    """Calculate the square root of a number.
+
+    Args:
+        number: The number to calculate the square root for.
+
+    Returns:
+        The square root of the number.
+    """
+    return math.sqrt(number)
+
+
+messages = [
+    {
+        "role": "user",
+        "content": "What is the square root of 36?",
+    }
+]
+
+response = chat(
+    model="llama3.2:latest",
+    messages=messages,
+    tools=[square_root],  # Pass the tools along with the prompt
+)
+
+# Append the response for context
+messages.append(response.message)
+
+if response.message.tool_calls:
+    tool = response.message.tool_calls[0]
+    # Call the tool
+    result = square_root(float(tool.function.arguments["number"]))
+
+    # Append the tool result
+    messages.append(
+        {
+            "role": "tool",
+            "tool_name": tool.function.name,
+            "content": str(result),
+        }
+    )
+
+    # Obtain the final answer
+    final_response = chat(model="llama3.2:latest", messages=messages)
+    print(final_response.message.content)