File size: 12,584 Bytes
e3278e4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
#### What this does ####
#   picks based on response time (for streaming, this is time to first token)
from datetime import datetime, timedelta
from typing import Dict, List, Optional, Union

import litellm
from litellm import ModelResponse, token_counter, verbose_logger
from litellm._logging import verbose_router_logger
from litellm.caching.caching import DualCache
from litellm.integrations.custom_logger import CustomLogger


class LowestCostLoggingHandler(CustomLogger):
    test_flag: bool = False
    logged_success: int = 0
    logged_failure: int = 0

    def __init__(
        self, router_cache: DualCache, model_list: list, routing_args: dict = {}
    ):
        self.router_cache = router_cache
        self.model_list = model_list

    def log_success_event(self, kwargs, response_obj, start_time, end_time):
        try:
            """
            Update usage on success
            """
            if kwargs["litellm_params"].get("metadata") is None:
                pass
            else:
                model_group = kwargs["litellm_params"]["metadata"].get(
                    "model_group", None
                )

                id = kwargs["litellm_params"].get("model_info", {}).get("id", None)
                if model_group is None or id is None:
                    return
                elif isinstance(id, int):
                    id = str(id)

                # ------------
                # Setup values
                # ------------
                """
                {
                    {model_group}_map: {
                        id: {
                            f"{date:hour:minute}" : {"tpm": 34, "rpm": 3}
                        }
                    }
                }
                """
                current_date = datetime.now().strftime("%Y-%m-%d")
                current_hour = datetime.now().strftime("%H")
                current_minute = datetime.now().strftime("%M")
                precise_minute = f"{current_date}-{current_hour}-{current_minute}"
                cost_key = f"{model_group}_map"

                response_ms: timedelta = end_time - start_time

                total_tokens = 0

                if isinstance(response_obj, ModelResponse):
                    _usage = getattr(response_obj, "usage", None)
                    if _usage is not None and isinstance(_usage, litellm.Usage):
                        completion_tokens = _usage.completion_tokens
                        total_tokens = _usage.total_tokens
                        float(response_ms.total_seconds() / completion_tokens)

                # ------------
                # Update usage
                # ------------

                request_count_dict = self.router_cache.get_cache(key=cost_key) or {}

                # check local result first

                if id not in request_count_dict:
                    request_count_dict[id] = {}

                if precise_minute not in request_count_dict[id]:
                    request_count_dict[id][precise_minute] = {}

                ## TPM
                request_count_dict[id][precise_minute]["tpm"] = (
                    request_count_dict[id][precise_minute].get("tpm", 0) + total_tokens
                )

                ## RPM
                request_count_dict[id][precise_minute]["rpm"] = (
                    request_count_dict[id][precise_minute].get("rpm", 0) + 1
                )

                self.router_cache.set_cache(key=cost_key, value=request_count_dict)

                ### TESTING ###
                if self.test_flag:
                    self.logged_success += 1
        except Exception as e:
            verbose_logger.exception(
                "litellm.router_strategy.lowest_cost.py::log_success_event(): Exception occured - {}".format(
                    str(e)
                )
            )
            pass

    async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
        try:
            """
            Update cost usage on success
            """
            if kwargs["litellm_params"].get("metadata") is None:
                pass
            else:
                model_group = kwargs["litellm_params"]["metadata"].get(
                    "model_group", None
                )

                id = kwargs["litellm_params"].get("model_info", {}).get("id", None)
                if model_group is None or id is None:
                    return
                elif isinstance(id, int):
                    id = str(id)

                # ------------
                # Setup values
                # ------------
                """
                {
                    {model_group}_map: {
                        id: {
                            "cost": [..]
                            f"{date:hour:minute}" : {"tpm": 34, "rpm": 3}
                        }
                    }
                }
                """
                cost_key = f"{model_group}_map"

                current_date = datetime.now().strftime("%Y-%m-%d")
                current_hour = datetime.now().strftime("%H")
                current_minute = datetime.now().strftime("%M")
                precise_minute = f"{current_date}-{current_hour}-{current_minute}"

                response_ms: timedelta = end_time - start_time

                total_tokens = 0

                if isinstance(response_obj, ModelResponse):
                    _usage = getattr(response_obj, "usage", None)
                    if _usage is not None and isinstance(_usage, litellm.Usage):
                        completion_tokens = _usage.completion_tokens
                        total_tokens = _usage.total_tokens

                        float(response_ms.total_seconds() / completion_tokens)

                # ------------
                # Update usage
                # ------------

                request_count_dict = (
                    await self.router_cache.async_get_cache(key=cost_key) or {}
                )

                if id not in request_count_dict:
                    request_count_dict[id] = {}
                if precise_minute not in request_count_dict[id]:
                    request_count_dict[id][precise_minute] = {}

                ## TPM
                request_count_dict[id][precise_minute]["tpm"] = (
                    request_count_dict[id][precise_minute].get("tpm", 0) + total_tokens
                )

                ## RPM
                request_count_dict[id][precise_minute]["rpm"] = (
                    request_count_dict[id][precise_minute].get("rpm", 0) + 1
                )

                await self.router_cache.async_set_cache(
                    key=cost_key, value=request_count_dict
                )  # reset map within window

                ### TESTING ###
                if self.test_flag:
                    self.logged_success += 1
        except Exception as e:
            verbose_logger.exception(
                "litellm.proxy.hooks.prompt_injection_detection.py::async_pre_call_hook(): Exception occured - {}".format(
                    str(e)
                )
            )
            pass

    async def async_get_available_deployments(  # noqa: PLR0915
        self,
        model_group: str,
        healthy_deployments: list,
        messages: Optional[List[Dict[str, str]]] = None,
        input: Optional[Union[str, List]] = None,
        request_kwargs: Optional[Dict] = None,
    ):
        """
        Returns a deployment with the lowest cost
        """
        cost_key = f"{model_group}_map"

        request_count_dict = await self.router_cache.async_get_cache(key=cost_key) or {}

        # -----------------------
        # Find lowest used model
        # ----------------------
        float("inf")

        current_date = datetime.now().strftime("%Y-%m-%d")
        current_hour = datetime.now().strftime("%H")
        current_minute = datetime.now().strftime("%M")
        precise_minute = f"{current_date}-{current_hour}-{current_minute}"

        if request_count_dict is None:  # base case
            return

        all_deployments = request_count_dict
        for d in healthy_deployments:
            ## if healthy deployment not yet used
            if d["model_info"]["id"] not in all_deployments:
                all_deployments[d["model_info"]["id"]] = {
                    precise_minute: {"tpm": 0, "rpm": 0},
                }

        try:
            input_tokens = token_counter(messages=messages, text=input)
        except Exception:
            input_tokens = 0

        # randomly sample from all_deployments, incase all deployments have latency=0.0
        _items = all_deployments.items()

        ### GET AVAILABLE DEPLOYMENTS ### filter out any deployments > tpm/rpm limits
        potential_deployments = []
        _cost_per_deployment = {}
        for item, item_map in all_deployments.items():
            ## get the item from model list
            _deployment = None
            for m in healthy_deployments:
                if item == m["model_info"]["id"]:
                    _deployment = m

            if _deployment is None:
                continue  # skip to next one

            _deployment_tpm = (
                _deployment.get("tpm", None)
                or _deployment.get("litellm_params", {}).get("tpm", None)
                or _deployment.get("model_info", {}).get("tpm", None)
                or float("inf")
            )

            _deployment_rpm = (
                _deployment.get("rpm", None)
                or _deployment.get("litellm_params", {}).get("rpm", None)
                or _deployment.get("model_info", {}).get("rpm", None)
                or float("inf")
            )
            item_litellm_model_name = _deployment.get("litellm_params", {}).get("model")
            item_litellm_model_cost_map = litellm.model_cost.get(
                item_litellm_model_name, {}
            )

            # check if user provided input_cost_per_token and output_cost_per_token in litellm_params
            item_input_cost = None
            item_output_cost = None
            if _deployment.get("litellm_params", {}).get("input_cost_per_token", None):
                item_input_cost = _deployment.get("litellm_params", {}).get(
                    "input_cost_per_token"
                )

            if _deployment.get("litellm_params", {}).get("output_cost_per_token", None):
                item_output_cost = _deployment.get("litellm_params", {}).get(
                    "output_cost_per_token"
                )

            if item_input_cost is None:
                item_input_cost = item_litellm_model_cost_map.get(
                    "input_cost_per_token", 5.0
                )

            if item_output_cost is None:
                item_output_cost = item_litellm_model_cost_map.get(
                    "output_cost_per_token", 5.0
                )

            # if litellm["model"] is not in model_cost map -> use item_cost = $10

            item_cost = item_input_cost + item_output_cost

            item_rpm = item_map.get(precise_minute, {}).get("rpm", 0)
            item_tpm = item_map.get(precise_minute, {}).get("tpm", 0)

            verbose_router_logger.debug(
                f"item_cost: {item_cost}, item_tpm: {item_tpm}, item_rpm: {item_rpm}, model_id: {_deployment.get('model_info', {}).get('id')}"
            )

            # -------------- #
            # Debugging Logic
            # -------------- #
            # We use _cost_per_deployment to log to langfuse, slack - this is not used to make a decision on routing
            # this helps a user to debug why the router picked a specfic deployment      #
            _deployment_api_base = _deployment.get("litellm_params", {}).get(
                "api_base", ""
            )
            if _deployment_api_base is not None:
                _cost_per_deployment[_deployment_api_base] = item_cost
            # -------------- #
            # End of Debugging Logic
            # -------------- #

            if (
                item_tpm + input_tokens > _deployment_tpm
                or item_rpm + 1 > _deployment_rpm
            ):  # if user passed in tpm / rpm in the model_list
                continue
            else:
                potential_deployments.append((_deployment, item_cost))

        if len(potential_deployments) == 0:
            return None

        potential_deployments = sorted(potential_deployments, key=lambda x: x[1])

        selected_deployment = potential_deployments[0][0]
        return selected_deployment