mirror of
https://github.com/Routstr/routstr-core.git
synced 2026-08-01 00:06:14 +00:00
Compare commits
2
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Shroominic
|
35c9ce5699 | ||
|
Shroominic
|
24015ebec1 |
+24
-2
@@ -142,6 +142,7 @@ async def refund_wallet_endpoint(
|
||||
authorization: Annotated[str, Header(...)],
|
||||
session: AsyncSession = Depends(get_session),
|
||||
) -> dict[str, str]:
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logger.info("Refund request received", extra={"authorization": authorization})
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if not authorization.startswith("Bearer "):
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raise HTTPException(
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status_code=401,
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@@ -157,6 +158,7 @@ async def refund_wallet_endpoint(
|
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remaining_balance_msats: int = key.total_balance
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logger.info("Refunding key: %s", key.dict())
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if key.refund_currency == "sat":
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remaining_balance = remaining_balance_msats // 1000
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else:
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@@ -172,6 +174,15 @@ async def refund_wallet_endpoint(
|
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if key.refund_address:
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from .core.settings import settings as global_settings
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logger.info(
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"Sending refund to lnurl",
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extra={
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"remaining_balance": remaining_balance,
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"refund_currency": key.refund_currency,
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"refund_mint_url": key.refund_mint_url,
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"refund_address": key.refund_address,
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},
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)
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await send_to_lnurl(
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remaining_balance,
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key.refund_currency or "sat",
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@@ -180,7 +191,16 @@ async def refund_wallet_endpoint(
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)
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result = {"recipient": key.refund_address}
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else:
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logger.info(
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"Sending refund as token",
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extra={
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"remaining_balance": remaining_balance,
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"refund_currency": key.refund_currency,
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"refund_mint_url": key.refund_mint_url,
|
||||
},
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||||
)
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refund_currency = key.refund_currency or "sat"
|
||||
|
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token = await send_token(
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remaining_balance, refund_currency, key.refund_mint_url
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)
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@@ -191,10 +211,12 @@ async def refund_wallet_endpoint(
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else:
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result["msats"] = str(remaining_balance_msats)
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except HTTPException:
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except HTTPException as e:
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logger.error("Refund failed", extra={"exception": e})
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# Re-raise HTTP exceptions (like 400 for balance too small)
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raise
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except Exception as e:
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logger.error("Refund failed", extra={"exception": e})
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# If refund fails, don't modify the database
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error_msg = str(e)
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if (
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@@ -205,7 +227,7 @@ async def refund_wallet_endpoint(
|
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):
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raise HTTPException(status_code=503, detail="Mint service unavailable")
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else:
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raise HTTPException(status_code=500, detail="Refund failed")
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raise HTTPException(status_code=500, detail="Refund failed: " + error_msg)
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await _refund_cache_set(bearer_value, result)
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|
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|
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@@ -6,7 +6,7 @@ import os
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from datetime import datetime, timezone
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from typing import Any
|
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|
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from pydantic.v1 import BaseModel, BaseSettings, Field, validator
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from pydantic.v1 import BaseModel, BaseSettings, Field
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from sqlmodel.ext.asyncio.session import AsyncSession
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|
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|
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@@ -37,13 +37,6 @@ class Settings(BaseSettings):
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# Cashu
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cashu_mints: list[str] = Field(default_factory=list, env="CASHU_MINTS")
|
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|
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@validator("cashu_mints", pre=True, each_item=True)
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def normalize_mint_url(cls, v: str) -> str:
|
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if isinstance(v, str):
|
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return v.rstrip("/")
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return v
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|
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receive_ln_address: str = Field(default="", env="RECEIVE_LN_ADDRESS")
|
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primary_mint: str = Field(default="", env="PRIMARY_MINT_URL")
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primary_mint_unit: str = Field(default="sat", env="PRIMARY_MINT_UNIT")
|
||||
|
||||
@@ -16,7 +16,6 @@ from .core.db import (
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||||
create_session,
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get_session,
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)
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from .core.settings import settings
|
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from .payment.helpers import (
|
||||
calculate_discounted_max_cost,
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check_token_balance,
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@@ -26,7 +25,6 @@ from .payment.helpers import (
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from .payment.models import Model
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from .upstream import BaseUpstreamProvider
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from .upstream.helpers import init_upstreams
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||||
from .wallet import deserialize_token_from_string
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|
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logger = get_logger(__name__)
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proxy_router = APIRouter()
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@@ -148,24 +146,6 @@ async def proxy(
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else:
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model_id = request_body_dict.get("model", "unknown")
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|
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if "https://testnut.cashu.space" in settings.cashu_mints:
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try:
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token_str = None
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if x_cashu_header := headers.get("x-cashu"):
|
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token_str = x_cashu_header
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elif auth_header := headers.get("authorization"):
|
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parts = auth_header.split(" ")
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||||
if len(parts) > 1 and not parts[1].startswith("sk-"):
|
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token_str = parts[1]
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|
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if token_str:
|
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token_obj = deserialize_token_from_string(token_str)
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if token_obj.mint == "https://testnut.cashu.space":
|
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model_id = "mock/gpt-420-mock"
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||||
request_body_dict["model"] = model_id
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||||
except Exception:
|
||||
pass
|
||||
|
||||
model_obj = get_model_instance(model_id)
|
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if not model_obj:
|
||||
return create_error_response(
|
||||
|
||||
@@ -61,34 +61,6 @@ class AnthropicUpstreamProvider(BaseUpstreamProvider):
|
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model_id = fixed_transforms[model_id]
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return model_id
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|
||||
def transform_parameters(self, data: dict) -> dict:
|
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"""Transform parameters for Anthropic API compatibility."""
|
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if "reasoning" in data:
|
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reasoning = data.pop("reasoning")
|
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if isinstance(reasoning, dict) and "effort" in reasoning:
|
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effort = reasoning.pop("effort")
|
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if effort == "low":
|
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data["thinking"] = {
|
||||
"type": "enabled",
|
||||
"budget_tokens": 8192,
|
||||
}
|
||||
elif effort == "medium":
|
||||
data["thinking"] = {
|
||||
"type": "enabled",
|
||||
"budget_tokens": 16384,
|
||||
}
|
||||
elif effort == "high":
|
||||
data["thinking"] = {
|
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"type": "enabled",
|
||||
"budget_tokens": 32768,
|
||||
}
|
||||
elif effort == "none":
|
||||
data["thinking"] = {
|
||||
"type": "disabled",
|
||||
}
|
||||
|
||||
return super().transform_parameters(data)
|
||||
|
||||
async def fetch_models(self) -> list[Model]:
|
||||
"""Fetch Anthropic models from OpenRouter API filtered by anthropic source."""
|
||||
models_data = await async_fetch_openrouter_models(source_filter="anthropic")
|
||||
|
||||
+12
-49
@@ -276,17 +276,19 @@ class BaseUpstreamProvider:
|
||||
|
||||
try:
|
||||
data = json.loads(body)
|
||||
if isinstance(data, dict):
|
||||
if isinstance(data, dict) and "model" in data:
|
||||
original_model = model_obj.id
|
||||
|
||||
data = self.update_parameters_from_model_name(data, original_model)
|
||||
|
||||
if "model" in data:
|
||||
transformed_model = self.transform_model_name(original_model)
|
||||
data["model"] = transformed_model
|
||||
|
||||
data = self.transform_parameters(data)
|
||||
return json.dumps(data).encode()
|
||||
transformed_model = self.transform_model_name(original_model)
|
||||
data["model"] = transformed_model
|
||||
logger.debug(
|
||||
"Transformed model name in request",
|
||||
extra={
|
||||
"original": original_model,
|
||||
"transformed": transformed_model,
|
||||
"provider": self.provider_type or self.base_url,
|
||||
},
|
||||
)
|
||||
return json.dumps(data).encode()
|
||||
except Exception as e:
|
||||
logger.debug(
|
||||
"Could not transform request body",
|
||||
@@ -298,43 +300,6 @@ class BaseUpstreamProvider:
|
||||
|
||||
return body
|
||||
|
||||
def update_parameters_from_model_name(self, data: dict, model_id: str) -> dict:
|
||||
"""Extract parameters from model name for provider-specific requirements.
|
||||
|
||||
Args:
|
||||
data: Original request body data
|
||||
|
||||
Returns:
|
||||
Transformed request body data
|
||||
"""
|
||||
if model_id.endswith(":thinking"):
|
||||
model_id = model_id.removesuffix(":thinking")
|
||||
data["reasoning"] = {"effort": "medium"}
|
||||
if model_id.endswith("-thinking"):
|
||||
model_id = model_id.removesuffix("-thinking")
|
||||
data["reasoning"] = {"effort": "medium"}
|
||||
|
||||
return data
|
||||
|
||||
def transform_parameters(self, data: dict) -> dict:
|
||||
"""Transform parameters for provider-specific requirements.
|
||||
|
||||
Args:
|
||||
data: Original request body data
|
||||
|
||||
Returns:
|
||||
Transformed request body data
|
||||
"""
|
||||
# generic input to messages transformation
|
||||
if (
|
||||
"input" in data
|
||||
and isinstance(data["input"], list)
|
||||
and isinstance(data["input"][0], dict)
|
||||
and "role" in data["input"][0]
|
||||
):
|
||||
data["messages"] = data.pop("input")
|
||||
return data
|
||||
|
||||
def _extract_upstream_error_message(
|
||||
self, body_bytes: bytes
|
||||
) -> tuple[str, str | None]:
|
||||
@@ -1129,9 +1094,7 @@ class BaseUpstreamProvider:
|
||||
|
||||
url = f"{self.base_url}/{path}"
|
||||
|
||||
print(f"request_body: {request_body[:100]!r}")
|
||||
transformed_body = self.prepare_request_body(request_body, model_obj)
|
||||
print(f"transformed_body: {transformed_body[:100]!r}")
|
||||
|
||||
logger.info(
|
||||
"Forwarding request to upstream",
|
||||
|
||||
@@ -1,265 +0,0 @@
|
||||
import asyncio
|
||||
import json
|
||||
import random
|
||||
from typing import AsyncIterator
|
||||
|
||||
from fastapi import Request
|
||||
from fastapi.responses import Response, StreamingResponse
|
||||
|
||||
from ..core.db import ApiKey, AsyncSession
|
||||
from ..payment.models import Architecture, Model, Pricing
|
||||
from .base import BaseUpstreamProvider
|
||||
|
||||
|
||||
class MockUpstreamProvider(BaseUpstreamProvider):
|
||||
"""Fack Mock Upstream provider specifically for Testing."""
|
||||
|
||||
provider_type = "mock"
|
||||
|
||||
async def forward_request(
|
||||
self,
|
||||
request: Request,
|
||||
path: str,
|
||||
headers: dict,
|
||||
request_body: bytes | None,
|
||||
key: ApiKey,
|
||||
max_cost_for_model: int,
|
||||
session: AsyncSession,
|
||||
model_obj: Model,
|
||||
) -> Response | StreamingResponse:
|
||||
if path.endswith("chat/completions"):
|
||||
is_streaming = False
|
||||
if request_body:
|
||||
request_data = json.loads(request_body)
|
||||
is_streaming = request_data.get("stream", False)
|
||||
|
||||
if is_streaming:
|
||||
|
||||
async def fake_streaming_response(
|
||||
chunk_size: int | None = None,
|
||||
) -> AsyncIterator[bytes]:
|
||||
suffix = random.randint(1000, 9999)
|
||||
req_id = f"gen-mock-stream-{suffix}"
|
||||
created = 1766138895
|
||||
model = "mock/gpt-420-mock"
|
||||
|
||||
def make_chunk(
|
||||
delta: dict,
|
||||
finish_reason: str | None = None,
|
||||
usage: dict | None = None,
|
||||
) -> bytes:
|
||||
chunk = {
|
||||
"id": req_id,
|
||||
"provider": "MockProvider",
|
||||
"model": model,
|
||||
"object": "chat.completion.chunk",
|
||||
"created": created,
|
||||
"choices": [
|
||||
{
|
||||
"index": 0,
|
||||
"delta": delta,
|
||||
"finish_reason": finish_reason,
|
||||
"native_finish_reason": "completed"
|
||||
if finish_reason
|
||||
else None,
|
||||
"logprobs": None,
|
||||
}
|
||||
],
|
||||
}
|
||||
if usage:
|
||||
chunk["usage"] = usage
|
||||
return f"data: {json.dumps(chunk)}\n\n".encode()
|
||||
|
||||
# 1. Initial chunk
|
||||
yield make_chunk({"role": "assistant", "content": ""})
|
||||
await asyncio.sleep(0.02)
|
||||
|
||||
# 2. Reasoning chunks
|
||||
reasoning_tokens = ["Mock", " reason", "ing", "..."]
|
||||
for token in reasoning_tokens:
|
||||
delta = {
|
||||
"role": "assistant",
|
||||
"content": "",
|
||||
"reasoning": token,
|
||||
"reasoning_details": [
|
||||
{
|
||||
"type": "reasoning.summary",
|
||||
"summary": token,
|
||||
"format": "openai-responses-v1",
|
||||
"index": 0,
|
||||
}
|
||||
],
|
||||
}
|
||||
yield make_chunk(delta)
|
||||
await asyncio.sleep(0.03)
|
||||
|
||||
# 3. Content chunks
|
||||
content_tokens = ["This", " is", " a", " mock", " stream", "."]
|
||||
for token in content_tokens:
|
||||
yield make_chunk({"role": "assistant", "content": token})
|
||||
await asyncio.sleep(0.03)
|
||||
|
||||
# 4. Finish chunk
|
||||
yield make_chunk(
|
||||
{"role": "assistant", "content": ""}, finish_reason="stop"
|
||||
)
|
||||
|
||||
# 5. Usage chunk
|
||||
usage_data = {
|
||||
"prompt_tokens": 10,
|
||||
"completion_tokens": 20,
|
||||
"total_tokens": 30,
|
||||
"cost": 0.001,
|
||||
"is_byok": False,
|
||||
"prompt_tokens_details": {
|
||||
"cached_tokens": 0,
|
||||
"audio_tokens": 0,
|
||||
"video_tokens": 0,
|
||||
},
|
||||
"cost_details": {
|
||||
"upstream_inference_cost": None,
|
||||
"upstream_inference_prompt_cost": 0,
|
||||
"upstream_inference_completions_cost": 0.001,
|
||||
},
|
||||
"completion_tokens_details": {
|
||||
"reasoning_tokens": 10,
|
||||
"image_tokens": 0,
|
||||
},
|
||||
}
|
||||
|
||||
usage_chunk = {
|
||||
"id": req_id,
|
||||
"provider": "MockProvider",
|
||||
"model": model,
|
||||
"object": "chat.completion.chunk",
|
||||
"created": created,
|
||||
"choices": [
|
||||
{
|
||||
"index": 0,
|
||||
"delta": {"role": "assistant", "content": ""},
|
||||
"finish_reason": None,
|
||||
"native_finish_reason": None,
|
||||
"logprobs": None,
|
||||
}
|
||||
],
|
||||
"usage": usage_data,
|
||||
}
|
||||
yield f"data: {json.dumps(usage_chunk)}\n\n".encode()
|
||||
|
||||
# 6. DONE
|
||||
yield b"data: [DONE]\n\n"
|
||||
|
||||
# 7. Cost
|
||||
cost_chunk = {
|
||||
"cost": {
|
||||
"base_msats": 0,
|
||||
"input_msats": 2,
|
||||
"output_msats": 10,
|
||||
"total_msats": 12,
|
||||
}
|
||||
}
|
||||
yield f"data: {json.dumps(cost_chunk)}\n\n".encode()
|
||||
|
||||
return StreamingResponse(
|
||||
fake_streaming_response(),
|
||||
200,
|
||||
)
|
||||
|
||||
else:
|
||||
suffix = random.randint(1000, 9999)
|
||||
content_dict = {
|
||||
"id": f"gen-mock-{suffix}",
|
||||
"provider": "MockProvider",
|
||||
"model": "mock/gpt-5-mini",
|
||||
"object": "chat.completion",
|
||||
"created": 1766138655,
|
||||
"choices": [
|
||||
{
|
||||
"logprobs": None,
|
||||
"finish_reason": "length",
|
||||
"native_finish_reason": "max_output_tokens",
|
||||
"index": 0,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": f"Mock Content {suffix}",
|
||||
"refusal": None,
|
||||
"reasoning": f"Mock Reasoning {suffix}",
|
||||
"reasoning_details": [
|
||||
{
|
||||
"format": "openai-responses-v1",
|
||||
"index": 0,
|
||||
"type": "reasoning.summary",
|
||||
"summary": f"Mock Summary {suffix}",
|
||||
},
|
||||
{
|
||||
"id": f"rs_mock_{suffix}",
|
||||
"format": "openai-responses-v1",
|
||||
"index": 0,
|
||||
"type": "reasoning.encrypted",
|
||||
"data": "mock_encrypted_data",
|
||||
},
|
||||
],
|
||||
},
|
||||
}
|
||||
],
|
||||
"usage": {
|
||||
"prompt_tokens": 10,
|
||||
"completion_tokens": 10,
|
||||
"total_tokens": 20,
|
||||
"cost": 0,
|
||||
"is_byok": False,
|
||||
"prompt_tokens_details": {
|
||||
"cached_tokens": 0,
|
||||
"audio_tokens": 0,
|
||||
"video_tokens": 0,
|
||||
},
|
||||
"cost_details": {
|
||||
"upstream_inference_cost": None,
|
||||
"upstream_inference_prompt_cost": 0,
|
||||
"upstream_inference_completions_cost": 0,
|
||||
},
|
||||
"completion_tokens_details": {
|
||||
"reasoning_tokens": 5,
|
||||
"image_tokens": 0,
|
||||
},
|
||||
},
|
||||
"cost": {
|
||||
"base_msats": 0,
|
||||
"input_msats": 0,
|
||||
"output_msats": 0,
|
||||
"total_msats": 0,
|
||||
},
|
||||
}
|
||||
return Response(json.dumps(content_dict).encode(), 200)
|
||||
|
||||
elif path.endswith("embeddings"):
|
||||
raise NotImplementedError
|
||||
elif path.endswith("responses"):
|
||||
raise NotImplementedError
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
async def fetch_models(self) -> list[Model]:
|
||||
return [
|
||||
Model(
|
||||
id="mock/gpt-420-mock",
|
||||
name="mock/gpt-420-mock",
|
||||
created=0,
|
||||
description="mock model for testing",
|
||||
context_length=8192,
|
||||
architecture=Architecture(
|
||||
modality="text",
|
||||
input_modalities=["text"],
|
||||
output_modalities=["text"],
|
||||
tokenizer="",
|
||||
instruct_type=None,
|
||||
),
|
||||
pricing=Pricing(prompt=0.01, completion=0.01),
|
||||
),
|
||||
]
|
||||
|
||||
def transform_model_name(self, model_id: str) -> str:
|
||||
return "fake-model"
|
||||
|
||||
async def get_balance(self) -> float | None:
|
||||
return 420.69
|
||||
@@ -218,14 +218,6 @@ async def init_upstreams() -> list[BaseUpstreamProvider]:
|
||||
results = await asyncio.gather(*tasks)
|
||||
upstreams = [p for p in results if p is not None]
|
||||
|
||||
if "https://testnut.cashu.space" in settings.cashu_mints:
|
||||
from .fake import MockUpstreamProvider
|
||||
|
||||
mock_provider = MockUpstreamProvider("mock", "mock")
|
||||
await mock_provider.refresh_models_cache()
|
||||
upstreams.append(mock_provider)
|
||||
logger.info("Initialized MockUpstreamProvider for testnut mint")
|
||||
|
||||
return upstreams
|
||||
|
||||
|
||||
|
||||
@@ -38,12 +38,6 @@ class OpenAIUpstreamProvider(BaseUpstreamProvider):
|
||||
"platform_url": cls.platform_url,
|
||||
}
|
||||
|
||||
def transform_parameters(self, data: dict) -> dict:
|
||||
"""Transform parameters for OpenAI API compatibility."""
|
||||
if "max_tokens" in data:
|
||||
data["max_completion_tokens"] = data.pop("max_tokens")
|
||||
return super().transform_parameters(data)
|
||||
|
||||
def transform_model_name(self, model_id: str) -> str:
|
||||
"""Strip 'openai/' prefix for OpenAI API compatibility."""
|
||||
return model_id.removeprefix("openai/")
|
||||
|
||||
+8
-3
@@ -40,16 +40,23 @@ async def recieve_token(
|
||||
async def send(amount: int, unit: str, mint_url: str | None = None) -> tuple[int, str]:
|
||||
"""Internal send function - returns amount and serialized token"""
|
||||
wallet: Wallet = await get_wallet(mint_url or settings.primary_mint, unit)
|
||||
logger.info("Sending", extra={"amount": amount, "unit": unit, "mint_url": mint_url})
|
||||
proofs = get_proofs_per_mint_and_unit(
|
||||
wallet, mint_url or settings.primary_mint, unit
|
||||
)
|
||||
|
||||
logger.info("Proofs", extra={"proofs": proofs})
|
||||
logger.info(
|
||||
"Selecting to send",
|
||||
extra={"amount": amount, "unit": unit, "mint_url": mint_url},
|
||||
)
|
||||
send_proofs, _ = await wallet.select_to_send(
|
||||
proofs, amount, set_reserved=True, include_fees=False
|
||||
)
|
||||
logger.info("Send proofs", extra={"send_proofs": send_proofs})
|
||||
token = await wallet.serialize_proofs(
|
||||
send_proofs, include_dleq=False, legacy=False, memo=None
|
||||
)
|
||||
logger.info("Token created", extra={"token": token})
|
||||
return amount, token
|
||||
|
||||
|
||||
@@ -313,8 +320,6 @@ async def periodic_payout() -> None:
|
||||
try:
|
||||
async with db.create_session() as session:
|
||||
for mint_url in settings.cashu_mints:
|
||||
if mint_url == "https://testnut.cashu.space":
|
||||
continue
|
||||
for unit in ["sat", "msat"]:
|
||||
wallet = await get_wallet(mint_url, unit)
|
||||
proofs = get_proofs_per_mint_and_unit(
|
||||
|
||||
Reference in New Issue
Block a user