ollam example

docs/examples/ollama_llama3.py

@@ -0,0 +1,114 @@
+""" This example illustrastes the use of the Ollama model with the dolphin-llama3 """
+
+import json
+
+# json_repair docs: https://pypi.org/project/json-repair/
+import json_repair
+import requests
+
+
+# This function sends a python code snippet to the code execution environment and returns the output.
+def execute_python_code(code: str) -> str:
+    # make sure AgentRun is running on your local machine
+    code = json.dumps({"code": code})
+    response = requests.post(
+        "http://localhost:8000/v1/run/",
+        data=code,
+        headers={"Content-Type": "application/json"},
+    )
+    print(code)
+    output = response.json()["output"]
+    return output
+
+
+# Ollama dolphin-llama3 page: https://ollama.com/library/dolphin-llama3
+MODEL = "dolphin-llama3"
+
+
+tools = [
+    {
+        "type": "function",
+        "function": {
+            "name": "execute_python_code",
+            "description": """Sends a python code snippet to the code execution environment and returns the output. 
+            The code execution environment can automatically import any library or package by importing. 
+            The code snippet to execute must be a valid python code and must use print() to output the result.""",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "code": {
+                        "type": "string",
+                        "description": "The code snippet to execute. Must be a valid python code. Must use print() to output the result.",
+                    },
+                },
+                "required": ["code"],
+            },
+        },
+    },
+]
+
+
+# Code adapted from here: https://github.com/namuan/llm-playground/blob/main/local-llm-tools-simple.py
+def generate_full_completion(prompt: str, model: str = MODEL) -> dict[str, str]:
+    params = {
+        "model": model,
+        "prompt": prompt,
+        "stream": False,
+        # deterministic output
+        "temperature": 0,
+        "seed": 123,
+        "format": "json",
+    }
+    try:
+        # Ollama API docs: https://github.com/ollama/ollama/blob/main/docs/api.md#request-json-mode
+        response = requests.post(
+            f"http://localhost:11434/api/generate",
+            headers={"Content-Type": "application/json"},
+            data=json.dumps(params),
+            timeout=60,
+        )
+        # print(f"🤖 Request: {json.dumps(params)} -> Response: {response.text}")
+        response.raise_for_status()
+        return json_repair.loads(response.text)
+    except requests.RequestException as err:
+        return {"error": f"API call error: {str(err)}"}
+
+
+def get_answer(query: str) -> str:
+    functions_prompt = f"""
+        You have access to the following tools:
+            {tools}
+        You must follow these instructions:
+        If a user query requires a tool, you must select the appropriate tool from the list of tools provided.
+        Always select one or more of the above tools based on the user query
+        If a tool is found, you must respond in the JSON format matching the following schema:
+        {{
+        "tools": {{
+            "tool": "<name of the selected tool>",
+            "tool_input": <parameters for the selected tool, matching the tool's JSON schema
+        }}
+        }}
+        If there are multiple tools required, make sure a list of tools are returned in a JSON array.
+        If there is no tool that match the user request, you will respond with empty json.
+        Do not add any additional Notes or Explanations.
+        
+        User Query: {query}
+        """
+
+    r_dict = generate_full_completion(functions_prompt)
+    # print(f"Ollama Response: {r_dict}")
+    r_tools = json_repair.loads(r_dict["response"])["tools"]
+    arg = r_tools["tool_input"]
+    code = arg["code"]
+    # print(f"Executing code: {code}")
+    response = execute_python_code(code)
+    # print(f"Code Execution result: {response}")
+    return response
+
+
+# 3952152
+print(get_answer("what's 12312 *321?"))
+# 500
+print(get_answer("how many even numbers are there between 1 and 1000?"))
+# Paris
+print(get_answer("what's the capital of France?"))

mkdocs.yml

@@ -16,6 +16,7 @@ nav:
     - Groq: "examples/function_calling_groq.ipynb"
     - OpenAI: "examples/function_calling_openai.py"
     - llama3: "examples/llama3_groq.py"
+    - Ollama: "examples/ollama_llama3.py"
 
 theme:
   name: material