summaryrefslogtreecommitdiff
path: root/llm.py
blob: 4dde6bd5059f6bdeb9e76f37b9900390f0fe13bb (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
from dataclasses import dataclass
import json
from collections.abc import Iterator

import requests


@dataclass
class ToolCall:
    id: str
    name: str
    arguments: dict[str, object]


@dataclass
class LLMResponse:
    content: str | None
    tool_calls: list[ToolCall]


class LLM:
    def __init__(self, url: str) -> None:
        self.url = url

    def chat(
        self,
        messages: list[dict[str, object]],
        tools: list[dict[str, object]] | None = None,
        max_tokens: int = 256,
    ) -> LLMResponse:
        payload: dict[str, object] = {
            "messages": messages,
            "max_tokens": max_tokens,
            "temperature": 0.7,
        }

        if tools is not None:
            payload["tools"] = tools

        response = requests.post(
            self.url,
            json=payload,  # type: ignore[arg-type]
        )
        response.raise_for_status()

        data = response.json()
        message = data["choices"][0]["message"]

        content = message.get("content")

        tool_calls: list[ToolCall] = []

        for call in message.get("tool_calls", []):
            function = call["function"]

            tool_calls.append(
                ToolCall(
                    id=call["id"],
                    name=function["name"],
                    arguments=json.loads(function["arguments"]),
                )
            )

        return LLMResponse(
            content=content,
            tool_calls=tool_calls,
        )


if __name__ == "__main__":
    from tools import ToolRegistry, HelloTool

    registry = ToolRegistry()
    registry.register(HelloTool())
    llm = LLM("http://localhost:8080/v1/chat/completions")

    response = llm.chat(
        messages=[
            {
                "role": "user",
                "content": "Say hello to Joseph using the hello tool.",
            },
        ],
        tools=registry.schemas(),
    )

    print(response)