a2a-source-edit: write agent.py
This commit is contained in:
a2a-cloud
646
agent.py
646
agent.py
@@ -1,189 +1,565 @@
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"""quote-judge-studio-v1 agent.
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"""QuoteJudge Studio full-stack A2A agent.
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Starter stack:
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- DeepAgents for tool-calling orchestration
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- Caller-provided LLM credentials via ctx.llm
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- A tiny model-call middleware hook you can replace with tracing,
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routing, rate limits, or policy checks
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Deterministic, no-LLM quote comparison product:
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- platform-authenticated user tenancy;
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- managed Postgres persistence;
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- typed A2A/MCP tools for comparison, reload, browser uploads, API uploads;
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- production receipt records without secrets.
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"""
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from __future__ import annotations
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import base64
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import csv
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import hashlib
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import io
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import json
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from pathlib import Path
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from typing import Any
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import os
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import re
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from datetime import datetime, timezone
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from typing import Annotated, Any
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from pydantic import BaseModel
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from pydantic import BaseModel, Field, field_validator
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import a2a_pack as a2a
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from a2a_pack import (
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A2AAgent,
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LLMProvisioning,
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{{ auth_type }},
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AgentDatabase,
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AgentDatabaseEnv,
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AgentDatabaseMigrations,
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AgentPlatformResources,
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FileUpload,
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PlatformUserAuth,
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Pricing,
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Resources,
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RunContext,
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State,
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UploadedFile,
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WorkspaceAccess,
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WorkspaceMode,
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)
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from a2a_pack.context import LLMCreds
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MAX_QUOTES = 25
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MAX_BROWSER_DOCUMENTS = 4
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MAX_BROWSER_DOCUMENT_BYTES = 64 * 1024
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ACCEPTED_UPLOAD_TYPES = (
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"application/json",
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"text/csv",
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"text/plain",
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)
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DATABASE_ENV = "DATABASE_URL"
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class QuoteJudgeStudioV1Config(BaseModel):
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pass
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"""No user-editable config is required."""
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SYSTEM_PROMPT = """\
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You are a compact tool-calling agent.
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class QuoteInput(BaseModel):
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vendor: Annotated[str, Field(min_length=1, max_length=160)]
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unit_price: Annotated[float, Field(gt=0, le=1_000_000)]
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quantity: Annotated[int, Field(gt=0, le=10_000_000)]
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delivery_days: Annotated[int, Field(ge=0, le=3650)]
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warranty_months: Annotated[int, Field(ge=0, le=600)]
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Use the text_stats tool when the user asks about text, counts, summaries,
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or anything where exact length/word numbers would help. Mention tool results
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briefly instead of dumping raw JSON.
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"""
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RUNTIME_SKILLS_DIR = "quote-judge-studio-v1/.deepagents/skills/"
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DEEPAGENTS_RECURSION_LIMIT = 500
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@field_validator("vendor")
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@classmethod
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def _clean_vendor(cls, value: str) -> str:
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cleaned = re.sub(r"\s+", " ", value).strip()
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if not cleaned:
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raise ValueError("vendor is required")
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return cleaned
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class QuoteJudgeStudioV1(A2AAgent[QuoteJudgeStudioV1Config, {{ auth_type }}]):
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class QuoteWeights(BaseModel):
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price: Annotated[float, Field(ge=0, le=100)] = 50
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delivery: Annotated[float, Field(ge=0, le=100)] = 30
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warranty: Annotated[float, Field(ge=0, le=100)] = 20
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class BrowserDocument(BaseModel):
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filename: Annotated[str, Field(min_length=1, max_length=180)]
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media_type: Annotated[str, Field(min_length=1, max_length=100)]
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data_base64: Annotated[str, Field(min_length=1, max_length=90_000)]
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class QuoteJudgeStudioV1(A2AAgent[QuoteJudgeStudioV1Config, PlatformUserAuth]):
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name = "quote-judge-studio-v1"
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description = "QuoteJudge compares vendor quotes with weighted price, delivery, and warranty scoring, persists recommendations, supports upload/paste workflows, and exposes typed A2A/MCP tools."
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description = (
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"QuoteJudge compares vendor quotes with weighted price, delivery, "
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"and warranty scoring, persists recommendations, supports upload/paste "
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"workflows, and exposes typed A2A/MCP tools."
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)
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version = "0.1.0"
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config_model = QuoteJudgeStudioV1Config
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auth_model = {{ auth_type }}
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auth_model = PlatformUserAuth
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# Hosted generated agents read the caller's saved LLM credential through
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# ctx.llm. The platform may proxy that credential through LiteLLM, but agent
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# code never reads provider keys, LiteLLM master keys, or OPENAI_API_KEY
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# directly.
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llm_provisioning = LLMProvisioning.PLATFORM
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state = State.DURABLE
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pricing = Pricing(
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price_per_call_usd=0.0,
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caller_pays_llm=True,
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notes="Starter agent uses the caller's saved LLM credential via ctx.llm.",
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caller_pays_llm=False,
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notes="Deterministic quote scoring. No LLM credential is required.",
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)
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resources = Resources(cpu="500m", memory="512Mi", max_runtime_seconds=120)
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workspace_access = WorkspaceAccess.dynamic(
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max_files=64,
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max_files=8,
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allowed_modes=(WorkspaceMode.READ_ONLY, WorkspaceMode.READ_WRITE_OVERLAY),
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require_reason=False,
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max_total_size_bytes=512 * 1024,
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)
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tools_used = ("postgres", "mcp", "packed-frontend")
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platform_resources = AgentPlatformResources(
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databases=(
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AgentDatabase(
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name="quote-judge-studio-v1-data",
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scope="user",
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access_mode="read_write",
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env=AgentDatabaseEnv(url=DATABASE_ENV),
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migrations=AgentDatabaseMigrations(path="db/migrations"),
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),
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)
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)
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tools_used = ("deepagents", "langchain")
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@a2a.tool(description="Ask the starter DeepAgent to answer with tool calls when useful")
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async def ask(self, ctx: RunContext[{{ auth_type }}], prompt: str) -> str:
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creds = ctx.llm
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await ctx.emit_progress(f"llm: {creds.model} via {creds.source}")
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if not creds.api_key:
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return (
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"LLM key required. Add an LLM credential in Settings > LLM "
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"credentials before running this agent; for local --invoke "
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"runs set AGENT_LLM_KEY."
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@a2a.tool(
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description=(
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"Compare at least two vendor quotes with price/delivery/warranty "
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"weights, persist the result, and return a recommendation."
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),
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timeout_seconds=60,
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idempotent=True,
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cost_class="deterministic",
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)
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graph = self._build_deep_agent(ctx=ctx, creds=creds)
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state = await graph.ainvoke(
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{"messages": [{"role": "user", "content": prompt}]},
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config={"recursion_limit": DEEPAGENTS_RECURSION_LIMIT},
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)
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await ctx.emit_progress("deepagent finished")
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return _last_message_text(state)
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def _build_deep_agent(
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async def compare_quotes(
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self,
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*,
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ctx: RunContext[{{ auth_type }}],
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creds: LLMCreds,
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) -> Any:
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# Lazy imports keep `a2a card` usable before local dependencies are
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# installed. `a2a deploy` installs requirements.txt during the build.
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from a2a_pack.deepagents import create_a2a_deep_agent
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from langchain.agents.middleware import wrap_model_call
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from langchain_core.tools import tool
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ctx: RunContext[PlatformUserAuth],
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comparison_id: Annotated[str, Field(min_length=1, max_length=120)],
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quotes: Annotated[list[QuoteInput], Field(max_length=MAX_QUOTES)],
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weights: QuoteWeights,
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) -> dict[str, Any]:
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await ctx.emit_progress("Validating quote comparison inputs")
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tenant = _tenant_key(ctx)
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result = _build_comparison_result(comparison_id, quotes, weights)
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if not result["ok"]:
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await _persist_receipt(ctx, tenant, comparison_id, "compare_quotes", "validation_error", {"code": result["code"]}, result)
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return result
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@tool
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def text_stats(text: str) -> str:
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"""Return exact word, character, and line counts for text."""
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words = [part for part in text.split() if part.strip()]
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return json.dumps(
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await ctx.emit_progress("Persisting comparison and production receipt")
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await _save_comparison(tenant, comparison_id, result)
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receipt = await _persist_receipt(ctx, tenant, comparison_id, "compare_quotes", "ok", _safe_input_payload(comparison_id, quotes, weights), result)
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result["receipt"] = receipt
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return result
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@a2a.tool(
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description="Reopen a previously persisted quote comparison by id.",
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timeout_seconds=30,
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idempotent=True,
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cost_class="deterministic",
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)
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async def get_comparison(
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self,
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ctx: RunContext[PlatformUserAuth],
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comparison_id: Annotated[str, Field(min_length=1, max_length=120)],
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) -> dict[str, Any]:
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tenant = _tenant_key(ctx)
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record = await _load_comparison(tenant, comparison_id)
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if record is None:
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result = {
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"ok": False,
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"code": "comparison_not_found",
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"message": "No comparison was found for this id in your workspace.",
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"comparison_id": comparison_id,
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}
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await _persist_receipt(ctx, tenant, comparison_id, "get_comparison", "not_found", {"comparison_id": comparison_id}, result)
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return result
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await _persist_receipt(ctx, tenant, comparison_id, "get_comparison", "ok", {"comparison_id": comparison_id}, record)
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return record
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@a2a.tool(
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description="List recently saved quote comparisons for the signed-in user.",
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timeout_seconds=30,
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idempotent=True,
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cost_class="deterministic",
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)
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async def list_comparisons(
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self,
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ctx: RunContext[PlatformUserAuth],
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limit: Annotated[int, Field(ge=1, le=50)] = 10,
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) -> dict[str, Any]:
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rows = await _list_comparisons(_tenant_key(ctx), limit)
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return {"ok": True, "comparisons": rows}
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@a2a.tool(
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description=(
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"Browser-safe upload bridge: accept bounded base64 JSON/CSV/text "
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"quote files, parse them, compare, persist, and return the result."
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),
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timeout_seconds=60,
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idempotent=True,
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cost_class="deterministic",
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)
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async def compare_quotes_from_browser_upload(
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self,
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ctx: RunContext[PlatformUserAuth],
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comparison_id: Annotated[str, Field(min_length=1, max_length=120)],
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documents: Annotated[list[BrowserDocument], Field(min_length=1, max_length=MAX_BROWSER_DOCUMENTS)],
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weights: QuoteWeights,
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) -> dict[str, Any]:
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parsed = _parse_browser_documents(documents)
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if not parsed["ok"]:
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await _persist_receipt(ctx, _tenant_key(ctx), comparison_id, "compare_quotes_from_browser_upload", "validation_error", {"comparison_id": comparison_id}, parsed)
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return {**parsed, "comparison_id": comparison_id}
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return await self.compare_quotes(ctx, comparison_id=comparison_id, quotes=parsed["quotes"], weights=weights)
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@a2a.tool(
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description=(
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"External API upload path: accept a typed FileUpload containing "
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"JSON, CSV, or pasted text quote data and run the same comparison."
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),
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timeout_seconds=60,
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idempotent=True,
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cost_class="deterministic",
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grant_mode="read_only",
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grant_allow_patterns=("**",),
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)
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async def compare_quotes_from_upload(
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self,
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ctx: RunContext[PlatformUserAuth],
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comparison_id: Annotated[str, Field(min_length=1, max_length=120)],
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quote_file: Annotated[
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UploadedFile,
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FileUpload(
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accept=ACCEPTED_UPLOAD_TYPES,
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max_bytes=MAX_BROWSER_DOCUMENT_BYTES,
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description="JSON list/object, CSV, or text containing vendor quotes.",
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),
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],
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weights: QuoteWeights,
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) -> dict[str, Any]:
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if quote_file.size_bytes > MAX_BROWSER_DOCUMENT_BYTES:
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return _validation_error(
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"file_too_large",
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f"Upload is {quote_file.size_bytes} bytes; maximum is {MAX_BROWSER_DOCUMENT_BYTES} bytes.",
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comparison_id=comparison_id,
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)
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if quote_file.media_type not in ACCEPTED_UPLOAD_TYPES:
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return _validation_error(
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"unsupported_media_type",
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f"Unsupported media type {quote_file.media_type!r}. Use JSON, CSV, or plain text.",
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comparison_id=comparison_id,
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)
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reader = getattr(ctx.workspace, "read_bytes", None)
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if reader is None:
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return _validation_error("workspace_read_unavailable", "The runtime did not expose uploaded file bytes.", comparison_id=comparison_id)
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try:
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raw = reader(quote_file.path)
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except Exception: # noqa: BLE001
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return _validation_error("file_read_failed", "Could not read the uploaded file from the granted workspace.", comparison_id=comparison_id)
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parsed = _parse_document_bytes(quote_file.filename, quote_file.media_type, raw)
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if not parsed["ok"]:
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return {**parsed, "comparison_id": comparison_id}
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return await self.compare_quotes(ctx, comparison_id=comparison_id, quotes=parsed["quotes"], weights=weights)
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def _tenant_key(ctx: RunContext[PlatformUserAuth]) -> str:
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auth = ctx.auth
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stable = auth.user_id if auth.user_id is not None else (auth.sub or auth.email)
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return f"user:{stable}"
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def _safe_input_payload(comparison_id: str, quotes: list[QuoteInput], weights: QuoteWeights) -> dict[str, Any]:
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return {
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"comparison_id": comparison_id,
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"quote_count": len(quotes),
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"vendors": [quote.vendor for quote in quotes],
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"weights": weights.model_dump(mode="json"),
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}
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def _validation_error(code: str, message: str, *, comparison_id: str | None = None, details: list[dict[str, Any]] | None = None) -> dict[str, Any]:
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payload: dict[str, Any] = {
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"ok": False,
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"code": code,
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"message": message,
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"validation_errors": details or [{"field": "quotes", "message": message}],
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}
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if comparison_id is not None:
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payload["comparison_id"] = comparison_id
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return payload
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def _build_comparison_result(comparison_id: str, quotes: list[QuoteInput], weights: QuoteWeights) -> dict[str, Any]:
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if len(quotes) < 2:
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return _validation_error(
|
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"at_least_two_quotes_required",
|
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"Provide at least two vendor quotes before requesting a recommendation.",
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comparison_id=comparison_id,
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details=[{"field": "quotes", "message": "At least two quotes are required."}],
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)
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if len(quotes) > MAX_QUOTES:
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return _validation_error(
|
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"too_many_quotes",
|
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f"Provide no more than {MAX_QUOTES} quotes.",
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comparison_id=comparison_id,
|
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)
|
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total_weight = weights.price + weights.delivery + weights.warranty
|
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if total_weight <= 0:
|
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return _validation_error(
|
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"weights_must_sum_positive",
|
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"At least one of price, delivery, or warranty weight must be greater than zero.",
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comparison_id=comparison_id,
|
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details=[{"field": "weights", "message": "Weights must sum to a positive number."}],
|
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)
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min_price = min(q.unit_price for q in quotes)
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min_delivery = min(q.delivery_days for q in quotes)
|
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max_warranty = max(q.warranty_months for q in quotes)
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normalized_weights = {
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"price": weights.price / total_weight,
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"delivery": weights.delivery / total_weight,
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"warranty": weights.warranty / total_weight,
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}
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rows: list[dict[str, Any]] = []
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for quote in quotes:
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price_score = (min_price / quote.unit_price) * 100 if quote.unit_price else 0.0
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delivery_score = 100.0 if quote.delivery_days == 0 and min_delivery == 0 else ((min_delivery + 1) / (quote.delivery_days + 1)) * 100
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warranty_score = (quote.warranty_months / max_warranty) * 100 if max_warranty else 100.0
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weighted_score = (
|
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normalized_weights["price"] * price_score
|
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+ normalized_weights["delivery"] * delivery_score
|
||||
+ normalized_weights["warranty"] * warranty_score
|
||||
)
|
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total_price = quote.unit_price * quote.quantity
|
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rows.append(
|
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{
|
||||
"characters": len(text),
|
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"words": len(words),
|
||||
"lines": len(text.splitlines()) or 1,
|
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"vendor": quote.vendor,
|
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"unit_price": round(quote.unit_price, 4),
|
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"quantity": quote.quantity,
|
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"total_price": round(total_price, 2),
|
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"delivery_days": quote.delivery_days,
|
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"warranty_months": quote.warranty_months,
|
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"scores": {
|
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"price": round(price_score, 2),
|
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"delivery": round(delivery_score, 2),
|
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"warranty": round(warranty_score, 2),
|
||||
"weighted_total": round(weighted_score, 2),
|
||||
},
|
||||
}
|
||||
)
|
||||
|
||||
@wrap_model_call
|
||||
async def log_model_call(request: Any, handler: Any) -> Any:
|
||||
messages = request.state.get("messages", [])
|
||||
print(
|
||||
"[middleware] model_call "
|
||||
f"model={creds.model} source={creds.source} messages={len(messages)}"
|
||||
rows.sort(key=lambda row: (-row["scores"]["weighted_total"], row["total_price"], row["delivery_days"], row["vendor"].lower()))
|
||||
winner = rows[0]
|
||||
recommendation = {
|
||||
"vendor": winner["vendor"],
|
||||
"score": winner["scores"]["weighted_total"],
|
||||
"reason": (
|
||||
f"{winner['vendor']} has the strongest weighted score "
|
||||
f"({winner['scores']['weighted_total']:.2f}) using price={weights.price:g}, "
|
||||
f"delivery={weights.delivery:g}, warranty={weights.warranty:g}."
|
||||
),
|
||||
}
|
||||
return {
|
||||
"ok": True,
|
||||
"comparison_id": comparison_id,
|
||||
"recommendation": recommendation,
|
||||
"weights": {
|
||||
"price": weights.price,
|
||||
"delivery": weights.delivery,
|
||||
"warranty": weights.warranty,
|
||||
"normalized": {key: round(value, 4) for key, value in normalized_weights.items()},
|
||||
},
|
||||
"quote_count": len(quotes),
|
||||
"comparison_table": rows,
|
||||
"created_at": datetime.now(timezone.utc).isoformat(),
|
||||
}
|
||||
|
||||
|
||||
def _parse_browser_documents(documents: list[BrowserDocument]) -> dict[str, Any]:
|
||||
quotes: list[QuoteInput] = []
|
||||
errors: list[dict[str, Any]] = []
|
||||
for index, doc in enumerate(documents):
|
||||
if doc.media_type not in ACCEPTED_UPLOAD_TYPES:
|
||||
errors.append({"field": f"documents[{index}].media_type", "message": "Use JSON, CSV, or plain text."})
|
||||
continue
|
||||
try:
|
||||
raw = base64.b64decode(doc.data_base64, validate=True)
|
||||
except Exception: # noqa: BLE001
|
||||
errors.append({"field": f"documents[{index}].data_base64", "message": "Invalid base64 payload."})
|
||||
continue
|
||||
if len(raw) > MAX_BROWSER_DOCUMENT_BYTES:
|
||||
errors.append({"field": f"documents[{index}]", "message": f"File exceeds {MAX_BROWSER_DOCUMENT_BYTES} bytes."})
|
||||
continue
|
||||
parsed = _parse_document_bytes(doc.filename, doc.media_type, raw)
|
||||
if parsed["ok"]:
|
||||
quotes.extend(parsed["quotes"])
|
||||
else:
|
||||
errors.extend(parsed.get("validation_errors") or [])
|
||||
if errors:
|
||||
return _validation_error("upload_parse_failed", "One or more uploaded quote files could not be parsed.", details=errors)
|
||||
return {"ok": True, "quotes": quotes[:MAX_QUOTES]}
|
||||
|
||||
|
||||
def _parse_document_bytes(filename: str, media_type: str, raw: bytes) -> dict[str, Any]:
|
||||
if len(raw) > MAX_BROWSER_DOCUMENT_BYTES:
|
||||
return _validation_error("file_too_large", f"{filename} exceeds the {MAX_BROWSER_DOCUMENT_BYTES} byte limit.")
|
||||
text = raw.decode("utf-8", errors="replace").strip()
|
||||
if not text:
|
||||
return _validation_error("empty_upload", "The uploaded quote file was empty.")
|
||||
try:
|
||||
if media_type == "application/json" or filename.lower().endswith(".json"):
|
||||
data = json.loads(text)
|
||||
items = data.get("quotes") if isinstance(data, dict) else data
|
||||
if not isinstance(items, list):
|
||||
return _validation_error("invalid_json_quotes", "JSON must be a list of quotes or an object with a quotes list.")
|
||||
return {"ok": True, "quotes": [QuoteInput.model_validate(item) for item in items]}
|
||||
if media_type == "text/csv" or filename.lower().endswith(".csv"):
|
||||
reader = csv.DictReader(io.StringIO(text))
|
||||
return {"ok": True, "quotes": [QuoteInput.model_validate(row) for row in reader]}
|
||||
return {"ok": True, "quotes": _parse_loose_text_quotes(text)}
|
||||
except Exception as exc: # noqa: BLE001
|
||||
return _validation_error("quote_parse_failed", f"Could not parse quote data: {type(exc).__name__}.")
|
||||
|
||||
|
||||
def _parse_loose_text_quotes(text: str) -> list[QuoteInput]:
|
||||
quotes: list[QuoteInput] = []
|
||||
for line in text.splitlines():
|
||||
parts = [part.strip() for part in re.split(r"[,|;]\s*", line) if part.strip()]
|
||||
if len(parts) < 5 or parts[0].lower() in {"vendor", "supplier"}:
|
||||
continue
|
||||
quotes.append(
|
||||
QuoteInput(
|
||||
vendor=parts[0],
|
||||
unit_price=float(parts[1]),
|
||||
quantity=int(float(parts[2])),
|
||||
delivery_days=int(float(parts[3])),
|
||||
warranty_months=int(float(parts[4])),
|
||||
)
|
||||
return await handler(request)
|
||||
|
||||
backend = ctx.workspace_backend()
|
||||
skill_sources = _seed_runtime_skills(backend, ctx)
|
||||
# create_a2a_deep_agent resolves provider:model strings with
|
||||
# langchain.init_chat_model from ctx.llm, preserving LiteLLM routing,
|
||||
# provider-specific extra body, and runtime model overrides.
|
||||
return create_a2a_deep_agent(
|
||||
ctx,
|
||||
creds=creds,
|
||||
backend=backend,
|
||||
skills=skill_sources or None,
|
||||
tools=[text_stats],
|
||||
middleware=[log_model_call],
|
||||
system_prompt=SYSTEM_PROMPT,
|
||||
)
|
||||
if not quotes:
|
||||
raise ValueError("No quote rows found. Expected vendor, unit_price, quantity, delivery_days, warranty_months.")
|
||||
return quotes
|
||||
|
||||
|
||||
def _runtime_skills_root(ctx: RunContext[Any]) -> str:
|
||||
workspace = getattr(ctx, "_workspace", None)
|
||||
prefixes = tuple(getattr(workspace, "write_prefixes", ()) or ())
|
||||
if not prefixes:
|
||||
outputs_prefix = getattr(workspace, "outputs_prefix", None)
|
||||
prefixes = (outputs_prefix or "outputs/",)
|
||||
prefix = str(prefixes[0]).strip("/")
|
||||
return f"/{prefix}/{RUNTIME_SKILLS_DIR}" if prefix else f"/{RUNTIME_SKILLS_DIR}"
|
||||
def _db_url() -> str:
|
||||
return os.environ.get(DATABASE_ENV, "").strip()
|
||||
|
||||
|
||||
def _seed_runtime_skills(backend: Any, ctx: RunContext[Any]) -> list[str]:
|
||||
"""Copy packaged DeepAgents skills into the invocation workspace.
|
||||
def _connect():
|
||||
url = _db_url()
|
||||
if not url:
|
||||
raise RuntimeError("managed database is not configured")
|
||||
import psycopg
|
||||
|
||||
DeepAgents loads skills from its backend, while source-controlled
|
||||
``skills/`` folders live in the image. This bridge lets generated agents
|
||||
ship reusable SKILL.md bundles without giving up durable A2A workspace
|
||||
files.
|
||||
return psycopg.connect(url, autocommit=True)
|
||||
|
||||
|
||||
async def _save_comparison(tenant_key: str, comparison_id: str, result: dict[str, Any]) -> None:
|
||||
with _connect() as conn:
|
||||
with conn.cursor() as cur:
|
||||
cur.execute(
|
||||
"""
|
||||
root = Path(__file__).parent / "skills"
|
||||
if not root.exists():
|
||||
return []
|
||||
runtime_skills_root = _runtime_skills_root(ctx)
|
||||
uploads: list[tuple[str, bytes]] = []
|
||||
for path in root.rglob("*"):
|
||||
if path.is_file():
|
||||
rel = path.relative_to(root).as_posix()
|
||||
uploads.append((runtime_skills_root + rel, path.read_bytes()))
|
||||
if uploads:
|
||||
backend.upload_files(uploads)
|
||||
return [runtime_skills_root]
|
||||
return []
|
||||
INSERT INTO quote_comparisons (tenant_key, comparison_id, recommendation_vendor, result)
|
||||
VALUES (%s, %s, %s, %s)
|
||||
ON CONFLICT (tenant_key, comparison_id) DO UPDATE SET
|
||||
recommendation_vendor = EXCLUDED.recommendation_vendor,
|
||||
result = EXCLUDED.result,
|
||||
updated_at = NOW()
|
||||
""",
|
||||
(tenant_key, comparison_id, result["recommendation"]["vendor"], json.dumps(result)),
|
||||
)
|
||||
|
||||
|
||||
def _last_message_text(state: dict[str, Any]) -> str:
|
||||
messages = state.get("messages") or []
|
||||
if not messages:
|
||||
return json.dumps(state, default=str)
|
||||
async def _load_comparison(tenant_key: str, comparison_id: str) -> dict[str, Any] | None:
|
||||
with _connect() as conn:
|
||||
with conn.cursor() as cur:
|
||||
cur.execute(
|
||||
"SELECT result FROM quote_comparisons WHERE tenant_key = %s AND comparison_id = %s",
|
||||
(tenant_key, comparison_id),
|
||||
)
|
||||
row = cur.fetchone()
|
||||
if row is None:
|
||||
return None
|
||||
value = row[0]
|
||||
if isinstance(value, str):
|
||||
return json.loads(value)
|
||||
return value
|
||||
|
||||
content = getattr(messages[-1], "content", None)
|
||||
if isinstance(content, str):
|
||||
return content
|
||||
if isinstance(content, list):
|
||||
parts: list[str] = []
|
||||
for item in content:
|
||||
if isinstance(item, dict):
|
||||
text = item.get("text") or item.get("content")
|
||||
if text:
|
||||
parts.append(str(text))
|
||||
elif item:
|
||||
parts.append(str(item))
|
||||
return "\n".join(parts) if parts else json.dumps(content, default=str)
|
||||
return str(content or messages[-1])
|
||||
|
||||
async def _list_comparisons(tenant_key: str, limit: int) -> list[dict[str, Any]]:
|
||||
with _connect() as conn:
|
||||
with conn.cursor() as cur:
|
||||
cur.execute(
|
||||
"""
|
||||
SELECT comparison_id, recommendation_vendor, updated_at, result
|
||||
FROM quote_comparisons
|
||||
WHERE tenant_key = %s
|
||||
ORDER BY updated_at DESC
|
||||
LIMIT %s
|
||||
""",
|
||||
(tenant_key, limit),
|
||||
)
|
||||
rows = cur.fetchall()
|
||||
output: list[dict[str, Any]] = []
|
||||
for comparison_id, recommendation_vendor, updated_at, result in rows:
|
||||
output.append(
|
||||
{
|
||||
"comparison_id": comparison_id,
|
||||
"recommendation_vendor": recommendation_vendor,
|
||||
"updated_at": updated_at.isoformat() if hasattr(updated_at, "isoformat") else str(updated_at),
|
||||
"quote_count": (result or {}).get("quote_count") if isinstance(result, dict) else None,
|
||||
}
|
||||
)
|
||||
return output
|
||||
|
||||
|
||||
async def _persist_receipt(
|
||||
ctx: RunContext[PlatformUserAuth],
|
||||
tenant_key: str,
|
||||
comparison_id: str,
|
||||
tool_name: str,
|
||||
status: str,
|
||||
inputs: dict[str, Any],
|
||||
result: dict[str, Any],
|
||||
) -> dict[str, Any]:
|
||||
payload = {
|
||||
"agent": QuoteJudgeStudioV1.name,
|
||||
"version": QuoteJudgeStudioV1.version,
|
||||
"tool": tool_name,
|
||||
"status": status,
|
||||
"comparison_id": comparison_id,
|
||||
"caller_scope": "platform_user",
|
||||
"task_id": getattr(ctx, "task_id", ""),
|
||||
"input_hash": _hash_json(inputs),
|
||||
"result_hash": _hash_json(_receipt_safe_result(result)),
|
||||
"created_at": datetime.now(timezone.utc).isoformat(),
|
||||
}
|
||||
payload["receipt_id"] = "qjr_" + _hash_json(payload)[:24]
|
||||
try:
|
||||
with _connect() as conn:
|
||||
with conn.cursor() as cur:
|
||||
cur.execute(
|
||||
"""
|
||||
INSERT INTO quote_judge_receipts
|
||||
(receipt_id, tenant_key, comparison_id, tool_name, status, input_hash, payload)
|
||||
VALUES (%s, %s, %s, %s, %s, %s, %s)
|
||||
ON CONFLICT (receipt_id) DO NOTHING
|
||||
""",
|
||||
(payload["receipt_id"], tenant_key, comparison_id, tool_name, status, payload["input_hash"], json.dumps(payload)),
|
||||
)
|
||||
except Exception as exc: # noqa: BLE001
|
||||
await ctx.emit_error("Receipt persistence failed; comparison result was still computed.", code="receipt_persist_failed")
|
||||
return {"persisted": False, "code": "receipt_persist_failed", "message": type(exc).__name__}
|
||||
return {"persisted": True, "receipt_id": payload["receipt_id"], "input_hash": payload["input_hash"]}
|
||||
|
||||
|
||||
def _receipt_safe_result(result: dict[str, Any]) -> dict[str, Any]:
|
||||
return {
|
||||
"ok": result.get("ok"),
|
||||
"comparison_id": result.get("comparison_id"),
|
||||
"recommendation": result.get("recommendation"),
|
||||
"code": result.get("code"),
|
||||
}
|
||||
|
||||
|
||||
def _hash_json(value: Any) -> str:
|
||||
raw = json.dumps(value, sort_keys=True, separators=(",", ":"), default=str).encode("utf-8")
|
||||
return hashlib.sha256(raw).hexdigest()
|
||||
|
||||
Reference in New Issue
Block a user