mirror of
https://github.com/katanemo/plano.git
synced 2026-06-20 15:28:07 +02:00
78f761ef75
Phase 1 - Remove dead/duplicate content:
- Delete demos/samples_java/ (incomplete Java demo)
- Delete demos/shared/chatbot_ui/ (replaced by AnythingLLM)
- Delete demos/shared/grafana/, prometheus/, logfire/, honeycomb/, signoz/
(legacy observability stacks; only jaeger is retained)
- Delete variant docker-compose files (honeycomb, logfire, signoz, jaeger)
- Delete demos/use_cases/spotify_bearer_auth/run_demo.sh (stale script)
Phase 2 - Restructure into semantic categories:
- getting_started/ : weather_forecast, llm_gateway
- agent_orchestration/ : travel_agents, multi_agent_crewai_langchain
- llm_routing/ : model_alias_routing, preference_based_routing, claude_code_router
- filter_chains/ : http_filter, mcp_filter
- integrations/ : ollama, spotify_bearer_auth
- advanced/ : model_choice_test_harness, multi_turn_rag,
currency_exchange, stock_quote
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
94 lines
2.6 KiB
Python
94 lines
2.6 KiB
Python
import json
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import os
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import random
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from fastapi import FastAPI, Response
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from datetime import datetime, date, timedelta, timezone
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import logging
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from pydantic import BaseModel
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from opentelemetry import trace
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from opentelemetry.sdk.trace import TracerProvider
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from opentelemetry.instrumentation.fastapi import FastAPIInstrumentor
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from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
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from opentelemetry.sdk.trace.export import BatchSpanProcessor
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from opentelemetry.sdk.resources import Resource
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resource = Resource.create(
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{
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"service.name": "weather-forecast-service",
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}
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)
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# Initialize the tracer provider
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trace.set_tracer_provider(TracerProvider(resource=resource))
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tracer = trace.get_tracer(__name__)
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logger = logging.getLogger("uvicorn.error")
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logger.setLevel(logging.INFO)
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app = FastAPI()
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FastAPIInstrumentor().instrument_app(app)
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# Configure the OTLP exporter (Jaeger, Zipkin, etc.)
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otlp_exporter = OTLPSpanExporter(
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endpoint=os.getenv("OLTP_HOST", "http://localhost:4317")
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)
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trace.get_tracer_provider().add_span_processor(BatchSpanProcessor(otlp_exporter))
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@app.get("/healthz")
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async def healthz():
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return {"status": "ok"}
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class WeatherRequest(BaseModel):
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location: str
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days: int = 7
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units: str = "Farenheit"
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@app.post("/weather")
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async def weather(req: WeatherRequest, res: Response):
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weather_forecast = {
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"location": req.location,
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"temperature": [],
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"units": req.units,
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}
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for i in range(req.days):
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min_temp = random.randrange(50, 90)
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max_temp = random.randrange(min_temp + 5, min_temp + 20)
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if req.units.lower() == "celsius" or req.units.lower() == "c":
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min_temp = (min_temp - 32) * 5.0 / 9.0
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max_temp = (max_temp - 32) * 5.0 / 9.0
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weather_forecast["temperature"].append(
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{
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"date": str(date.today() + timedelta(days=i)),
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"temperature": {"min": min_temp, "max": max_temp},
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"units": req.units,
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"query_time": str(datetime.now(timezone.utc)),
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}
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)
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return weather_forecast
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class DefaultTargetRequest(BaseModel):
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messages: list = []
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@app.post("/default_target")
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async def default_target(req: DefaultTargetRequest, res: Response):
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logger.info(f"Received messages: {req.messages}")
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resp = {
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"choices": [
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{
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"message": {
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"role": "assistant",
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"content": "I can help you with weather forecast",
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},
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}
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],
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"model": "api_server",
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}
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logger.info(f"sending response: {json.dumps(resp)}")
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return resp
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