ollama 0.2.7 支持函数调用了

就在最新的ollama 发布版本中对于类似openai 的函数调用支持了，但是目前有一些问题，就是相关历史的model 都需要修改下（添加TEMPLATE 对于tools的支持），一些是一个简单的测试

参考示例

使用了phidata 这个工具包

一个参考qwen2:7b 模型的修改
参考了llama3-groq-tool-use 这个模型的
Moddelfile

FROM qwen2:7b
 
TEMPLATE """{{- if .Messages }}

{{- if or .System .Tools }}<|start_header_id|>system<|end_header_id|>
 
{{ if .System }}{{ .System }}

{{- end }}

In addition to plain text responses, you can chose to call one or more of the provided functions.
 
Use the following rule to decide when to call a function:

  * if the response can be generated from your internal knowledge (e.g., as in the case of queries like "What is the capital of Poland?"), do so

  * if you need external information that can be obtained by calling one or more of the provided functions, generate a function calls
 
If you decide to call functions:

  * prefix function calls with functools marker (no closing marker required)

  * all function calls should be generated in a single JSON list formatted as functools[{"name": [function name], "arguments": [function arguments as JSON]}, ...]

  * follow the provided JSON schema. Do not hallucinate arguments or values. Do to blindly copy values from the provided samples

  * respect the argument type formatting. E.g., if the type if number and format is float, write value 7 as 7.0

  * make sure you pick the right functions that match the user intent
 
Available functions as JSON spec:

{{- if .Tools }}

{{ .Tools }}

{{- end }}<|eot_id|>

{{- end }}

{{- range .Messages }}

{{- if ne .Role "system" }}<|start_header_id|>{{ .Role }}<|end_header_id|>

{{- if and .Content (eq .Role "tools") }}
 
{"result": {{ .Content }}}

{{- else if .Content }}
 
{{ .Content }}

{{- else if .ToolCalls }}
 
functools[

{{- range .ToolCalls }}{{ "{" }}"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}{{ "}" }}

{{- end }}]

{{- end }}<|eot_id|>

{{- end }}

{{- end }}<|start_header_id|>assistant<|end_header_id|>
 
{{ else }}

{{- if .System }}<|start_header_id|>system<|end_header_id|>
 
{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>
 
{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>
 
{{ end }}{{ .Response }}{{ if .Response }}<|eot_id|>{{ end }}

"""

构建命令

ollama create myqwen2:7b -f Modelfile

参考代码

from phi.llm.openai.like import OpenAILike

from phi.assistant import Assistant

import datetime

import json

import time

my_ollama = OpenAILike(

        model="myqwen2:7b",

        api_key="demo",

        base_url="http://localhost:11434/v1"

    )
 
def get_time():

    info = {

        "time": time.strftime("%I:%M %p")

    }

    return json.dumps(info)
 
def get_username():

    info = {

        "username": "John Doe"

    }

    return json.dumps(info)

def get_date():

    info = {

        "date": time.strftime("%Y-%m-%d")

    }

    return json.dumps(info)
 
def get_datatime():

    now = datetime.datetime.now()

    info = {

        "time": now.strftime("%Y-%m-%d %H:%M:%S")

    }

    return json.dumps(info)
 
ollama_assistant = Assistant(

    llm=my_ollama,

    tools=[get_time,get_date], show_tool_calls=True, markdown=False

)

ollama_assistant.print_response("现在的时间", stream=False)