a2a-source-edit: write agent.py
This commit is contained in:
a2a-cloud
780
agent.py
780
agent.py
@@ -1,679 +1,189 @@
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"""QuoteJudge full-stack A2A agent.
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"""quote-judge-studio-v1 agent.
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Deterministic quote comparison, per-user persistence in managed Postgres,
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browser-safe upload parsing, and production execution receipt storage.
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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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"""
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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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import os
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import re
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import uuid
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from contextlib import contextmanager
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from datetime import datetime, timezone
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from typing import Annotated, Any
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from pathlib import Path
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from typing import Any
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from pydantic import BaseModel, Field, field_validator
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from pydantic import BaseModel
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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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AgentDatabase,
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AgentDatabaseEnv,
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AgentDatabaseMigrations,
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AgentPlatformResources,
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PlatformUserAuth,
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LLMProvisioning,
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{{ auth_type }},
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Pricing,
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Resources,
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RunContext,
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State,
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WorkspaceAccess,
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WorkspaceMode,
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)
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from a2a_pack.workspace import FileUpload, UploadedFile
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try: # psycopg is installed in deployment and sandbox via requirements.txt.
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import psycopg
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from psycopg.rows import dict_row
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except Exception: # pragma: no cover - import guard for card-only tooling
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psycopg = None
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dict_row = None
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MAX_QUOTES = 20
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MAX_VENDOR_LENGTH = 120
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MAX_UPLOADS = 5
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MAX_UPLOAD_BYTES = 128_000
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MAX_UPLOAD_BASE64_CHARS = ((MAX_UPLOAD_BYTES + 2) // 3) * 4
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ALLOWED_UPLOAD_MEDIA_TYPES = {"text/csv", "text/plain", "application/json"}
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_DATABASE_NAME = "quote-judge-studio-v1-data"
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_LOCAL_COMPARISONS: dict[tuple[str, str], dict[str, Any]] = {}
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_LOCAL_RECEIPTS: list[dict[str, Any]] = []
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from a2a_pack.context import LLMCreds
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class QuoteJudgeStudioV1Config(BaseModel):
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"""No caller-configured settings are required."""
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pass
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class QuoteInput(BaseModel):
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vendor: str = Field(..., min_length=1, max_length=MAX_VENDOR_LENGTH)
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quantity: int = Field(..., gt=0, le=10_000_000)
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unit_price: float = Field(..., ge=0, le=1_000_000_000)
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delivery_days: int = Field(..., ge=0, le=3650)
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warranty_months: int = Field(..., ge=0, le=600)
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SYSTEM_PROMPT = """\
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You are a compact tool-calling agent.
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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 = " ".join(value.strip().split())
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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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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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class QuoteWeights(BaseModel):
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price: float = Field(..., ge=0, le=100)
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delivery: float = Field(..., ge=0, le=100)
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warranty: float = Field(..., ge=0, le=100)
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class BrowserQuoteDocument(BaseModel):
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filename: str = Field(..., min_length=1, max_length=160)
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media_type: str = Field(..., min_length=1, max_length=100)
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data_base64: str = Field(..., min_length=1, max_length=MAX_UPLOAD_BASE64_CHARS)
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@field_validator("filename")
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@classmethod
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def safe_filename(cls, value: str) -> str:
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cleaned = value.strip().replace("\\", "/").split("/")[-1]
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if not cleaned or cleaned in {".", ".."}:
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raise ValueError("filename is required")
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return cleaned[:160]
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class QuoteJudgeState(BaseModel):
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"""Durable state is stored in managed Postgres; this schema advertises that fact."""
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persistence: str = "managed_postgres"
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class QuoteJudgeStudioV1(A2AAgent[QuoteJudgeStudioV1Config, PlatformUserAuth]):
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class QuoteJudgeStudioV1(A2AAgent[QuoteJudgeStudioV1Config, {{ auth_type }}]):
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name = "quote-judge-studio-v1"
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description = (
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"QuoteJudge compares vendor quotes with weighted price, delivery, and "
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"warranty scoring, persists per-user comparisons, and serves a one-page product UI."
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)
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version = "0.1.5"
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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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version = "0.1.0"
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config_model = QuoteJudgeStudioV1Config
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auth_model = PlatformUserAuth
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state = State.DURABLE
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state_model = QuoteJudgeState
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resources = Resources(cpu="500m", memory="512Mi", max_runtime_seconds=300)
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platform_resources = AgentPlatformResources(
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databases=(
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AgentDatabase(
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name=_DATABASE_NAME,
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scope="user",
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access_mode="read_write",
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env=AgentDatabaseEnv(url="DATABASE_URL"),
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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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auth_model = {{ auth_type }}
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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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pricing = Pricing(
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price_per_call_usd=0.0,
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caller_pays_llm=False,
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notes="Deterministic local quote scoring; no LLM credential is required.",
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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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)
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workspace_access = WorkspaceAccess.dynamic(
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max_files=MAX_UPLOADS,
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allowed_modes=(WorkspaceMode.READ_ONLY,),
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max_files=64,
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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=MAX_UPLOADS * MAX_UPLOAD_BYTES,
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)
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tools_used = ("postgres", "mcp")
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tools_used = ("deepagents", "langchain")
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@a2a.tool(
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description=(
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"Compare at least two vendor quotes using typed price, delivery, and warranty "
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"weights; persist the recommendation and a production receipt."
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),
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timeout_seconds=30,
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idempotent=False,
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cost_class="cheap",
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)
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async def compare_quotes(
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self,
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ctx: RunContext[PlatformUserAuth],
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comparison_id: str,
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quotes: list[QuoteInput],
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weights: QuoteWeights,
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) -> dict[str, Any]:
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tenant = _tenant_key(ctx)
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cleaned_id = _clean_comparison_id(comparison_id)
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started = _now_iso()
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input_payload = {
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"comparison_id": cleaned_id,
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"quotes": [quote.model_dump() for quote in quotes],
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"weights": weights.model_dump(),
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}
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if weights.price + weights.delivery + weights.warranty <= 0:
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result = {
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"ok": False,
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"code": "positive_weight_required",
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"message": "Set at least one weight above zero before comparing.",
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"comparison_id": cleaned_id,
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}
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await _persist_receipt(
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tenant_key=tenant,
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comparison_id=cleaned_id,
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skill_name="compare_quotes",
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input_payload=input_payload,
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result_payload=result,
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status="validation_error",
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started_at=started,
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)
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return result
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if len(quotes) < 2:
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result = {
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"ok": False,
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"code": "at_least_two_quotes_required",
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"message": "Add at least two vendor quotes before comparing.",
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"comparison_id": cleaned_id,
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}
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await _persist_receipt(
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tenant_key=tenant,
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comparison_id=cleaned_id,
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skill_name="compare_quotes",
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input_payload=input_payload,
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result_payload=result,
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status="validation_error",
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started_at=started,
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)
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return result
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if len(quotes) > MAX_QUOTES:
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result = {
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"ok": False,
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"code": "too_many_quotes",
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"message": f"Compare at most {MAX_QUOTES} quotes at a time.",
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"comparison_id": cleaned_id,
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}
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await _persist_receipt(
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tenant_key=tenant,
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comparison_id=cleaned_id,
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skill_name="compare_quotes",
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input_payload=input_payload,
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result_payload=result,
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status="validation_error",
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started_at=started,
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)
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return result
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result = _score_quotes(cleaned_id, quotes, weights)
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await _save_comparison(tenant, result)
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await _persist_receipt(
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tenant_key=tenant,
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comparison_id=cleaned_id,
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skill_name="compare_quotes",
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input_payload=input_payload,
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result_payload=result,
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status="ok",
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started_at=started,
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)
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return result
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@a2a.tool(
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description="Reopen a saved QuoteJudge comparison for the authenticated user.",
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timeout_seconds=15,
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idempotent=False,
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cost_class="cheap",
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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: str,
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) -> dict[str, Any]:
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tenant = _tenant_key(ctx)
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cleaned_id = _clean_comparison_id(comparison_id)
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started = _now_iso()
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record = await _load_comparison(tenant, cleaned_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 saved comparison exists for this id and user.",
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"comparison_id": cleaned_id,
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}
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else:
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result = dict(record)
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result["ok"] = True
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await _persist_receipt(
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tenant_key=tenant,
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comparison_id=cleaned_id,
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skill_name="get_comparison",
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input_payload={"comparison_id": cleaned_id},
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result_payload=result,
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status="ok" if result.get("ok") else "not_found",
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started_at=started,
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)
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return result
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@a2a.tool(
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description=(
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"Browser upload bridge: parse bounded base64 JSON/CSV/text quote files, "
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"compare extracted quotes, and persist the result."
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),
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timeout_seconds=30,
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idempotent=False,
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cost_class="cheap",
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)
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async def compare_uploaded_quotes_browser(
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self,
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ctx: RunContext[PlatformUserAuth],
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comparison_id: str,
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documents: list[BrowserQuoteDocument],
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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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return parsed
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return await self.compare_quotes(
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ctx,
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comparison_id=comparison_id,
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quotes=[QuoteInput.model_validate(item) for item in parsed["quotes"]],
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weights=weights,
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)
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@a2a.tool(
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description=(
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"External-client upload path: parse an uploaded CSV, JSON, or plain-text quote "
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"file and compare extracted quotes."
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),
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timeout_seconds=30,
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idempotent=False,
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cost_class="cheap",
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)
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async def compare_uploaded_quote_file(
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self,
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ctx: RunContext[PlatformUserAuth],
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comparison_id: str,
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document: Annotated[
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UploadedFile,
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FileUpload(
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accept=("text/csv", "text/plain", "application/json"),
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max_bytes=MAX_UPLOAD_BYTES,
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description="CSV, JSON, or text file containing vendor quote rows.",
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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 document.size_bytes > MAX_UPLOAD_BYTES:
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return {
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"ok": False,
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"code": "upload_too_large",
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"message": f"Upload must be {MAX_UPLOAD_BYTES} bytes or smaller.",
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"comparison_id": _clean_comparison_id(comparison_id),
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}
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if document.media_type not in ALLOWED_UPLOAD_MEDIA_TYPES:
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return {
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"ok": False,
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"code": "unsupported_media_type",
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"message": "Upload must be CSV, JSON, or plain text.",
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"comparison_id": _clean_comparison_id(comparison_id),
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}
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try:
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reader = getattr(ctx.workspace, "read_bytes")
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raw = reader(document.path)
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except Exception:
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return {
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"ok": False,
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"code": "upload_read_failed",
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"message": "Could not read the uploaded file from the granted workspace.",
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"comparison_id": _clean_comparison_id(comparison_id),
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}
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parsed = _parse_document_bytes(document.filename, document.media_type, raw)
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if not parsed["ok"]:
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return parsed
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return await self.compare_quotes(
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ctx,
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comparison_id=comparison_id,
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quotes=[QuoteInput.model_validate(item) for item in parsed["quotes"]],
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weights=weights,
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)
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def _tenant_key(ctx: RunContext[PlatformUserAuth]) -> str:
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auth = ctx.auth
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ident = auth.user_id if auth.user_id is not None else (auth.sub or auth.email)
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if ident is None:
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raise ValueError("authenticated user identity is required")
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return f"user:{ident}"
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def _clean_comparison_id(value: str) -> str:
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cleaned = str(value or "").strip()
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if not re.fullmatch(r"[A-Za-z0-9][A-Za-z0-9_.:-]{0,79}", cleaned):
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raise ValueError("comparison_id must be 1-80 safe characters")
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return cleaned
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def _score_sort_key(row: dict[str, Any]) -> tuple[float, float, int, int, str]:
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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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-float(row["scores"]["weighted_total"]),
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float(row["subtotal"]),
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int(row["delivery_days"]),
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-int(row["warranty_months"]),
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str(row["vendor"]).lower(),
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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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)
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def _subtotal_key(row: dict[str, Any]) -> float:
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return float(row["subtotal"])
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def _score_quotes(comparison_id: str, quotes: list[QuoteInput], weights: QuoteWeights) -> dict[str, Any]:
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quote_rows = [quote.model_dump() for quote in quotes]
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for row in quote_rows:
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row["subtotal"] = round(row["quantity"] * row["unit_price"], 2)
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totals = [row["subtotal"] for row in quote_rows]
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deliveries = [row["delivery_days"] for row in quote_rows]
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warranties = [row["warranty_months"] for row in quote_rows]
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total_weight = weights.price + weights.delivery + weights.warranty
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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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scored: list[dict[str, Any]] = []
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for row in quote_rows:
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price_score = _lower_is_better(row["subtotal"], totals)
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delivery_score = _lower_is_better(row["delivery_days"], deliveries)
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warranty_score = _higher_is_better(row["warranty_months"], warranties)
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weighted_score = (
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price_score * normalized_weights["price"]
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+ delivery_score * normalized_weights["delivery"]
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||||
+ warranty_score * normalized_weights["warranty"]
|
||||
)
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scored.append(
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{
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||||
**row,
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||||
"scores": {
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||||
"price": round(price_score, 4),
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||||
"delivery": round(delivery_score, 4),
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||||
"warranty": round(warranty_score, 4),
|
||||
"weighted_total": round(weighted_score, 4),
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||||
},
|
||||
}
|
||||
graph = self._build_deep_agent(ctx=ctx, creds=creds)
|
||||
state = await graph.ainvoke(
|
||||
{"messages": [{"role": "user", "content": prompt}]},
|
||||
config={"recursion_limit": DEEPAGENTS_RECURSION_LIMIT},
|
||||
)
|
||||
await ctx.emit_progress("deepagent finished")
|
||||
return _last_message_text(state)
|
||||
|
||||
scored.sort(key=_score_sort_key)
|
||||
winner = scored[0]
|
||||
baseline = min(scored, key=_subtotal_key)
|
||||
rationale_bits = [
|
||||
f"{winner['vendor']} has the highest weighted score ({winner['scores']['weighted_total']:.2f}).",
|
||||
f"Its normalized total is {winner['subtotal']:.2f} for {winner['quantity']} units.",
|
||||
]
|
||||
if winner["delivery_days"] == min(deliveries):
|
||||
rationale_bits.append("It also has the fastest delivery among the submitted quotes.")
|
||||
if winner["warranty_months"] == max(warranties):
|
||||
rationale_bits.append("It offers the strongest warranty among the submitted quotes.")
|
||||
if winner["vendor"] == baseline["vendor"]:
|
||||
rationale_bits.append("It is the lowest-price option under the selected quantity.")
|
||||
|
||||
return {
|
||||
"ok": True,
|
||||
"comparison_id": comparison_id,
|
||||
"recommendation": {
|
||||
"vendor": winner["vendor"],
|
||||
"score": winner["scores"]["weighted_total"],
|
||||
"normalized_total": winner["subtotal"],
|
||||
"rationale": " ".join(rationale_bits),
|
||||
},
|
||||
"weights": {
|
||||
"price": weights.price,
|
||||
"delivery": weights.delivery,
|
||||
"warranty": weights.warranty,
|
||||
"normalized": {key: round(value, 4) for key, value in normalized_weights.items()},
|
||||
},
|
||||
"quotes": scored,
|
||||
"created_at": _now_iso(),
|
||||
}
|
||||
|
||||
|
||||
def _lower_is_better(value: float, values: list[float]) -> float:
|
||||
min_value = min(values)
|
||||
max_value = max(values)
|
||||
if max_value == min_value:
|
||||
return 1.0
|
||||
return (max_value - value) / (max_value - min_value)
|
||||
|
||||
|
||||
def _higher_is_better(value: float, values: list[float]) -> float:
|
||||
min_value = min(values)
|
||||
max_value = max(values)
|
||||
if max_value == min_value:
|
||||
return 1.0
|
||||
return (value - min_value) / (max_value - min_value)
|
||||
|
||||
|
||||
def _parse_browser_documents(documents: list[BrowserQuoteDocument]) -> dict[str, Any]:
|
||||
if not documents:
|
||||
return {"ok": False, "code": "no_uploads", "message": "Upload at least one quote file."}
|
||||
if len(documents) > MAX_UPLOADS:
|
||||
return {"ok": False, "code": "too_many_uploads", "message": f"Upload at most {MAX_UPLOADS} files."}
|
||||
quotes: list[dict[str, Any]] = []
|
||||
for document in documents:
|
||||
if document.media_type not in ALLOWED_UPLOAD_MEDIA_TYPES:
|
||||
return {"ok": False, "code": "unsupported_media_type", "message": "Upload must be CSV, JSON, or plain text."}
|
||||
try:
|
||||
raw = base64.b64decode(document.data_base64, validate=True)
|
||||
except Exception:
|
||||
return {"ok": False, "code": "invalid_base64", "message": "Uploaded file data is not valid base64."}
|
||||
if len(raw) > MAX_UPLOAD_BYTES:
|
||||
return {"ok": False, "code": "upload_too_large", "message": f"Each upload must be {MAX_UPLOAD_BYTES} bytes or smaller."}
|
||||
parsed = _parse_document_bytes(document.filename, document.media_type, raw)
|
||||
if not parsed["ok"]:
|
||||
return parsed
|
||||
quotes.extend(parsed["quotes"])
|
||||
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_UPLOAD_BYTES:
|
||||
return {"ok": False, "code": "upload_too_large", "message": f"Upload must be {MAX_UPLOAD_BYTES} bytes or smaller."}
|
||||
text = raw.decode("utf-8-sig", errors="replace")
|
||||
try:
|
||||
if media_type == "application/json" or filename.lower().endswith(".json"):
|
||||
data = json.loads(text)
|
||||
rows = data.get("quotes", data) if isinstance(data, dict) else data
|
||||
if not isinstance(rows, list):
|
||||
raise ValueError("JSON must be a list or contain a quotes list")
|
||||
quotes = [QuoteInput.model_validate(row).model_dump() for row in rows]
|
||||
elif media_type == "text/csv" or filename.lower().endswith(".csv"):
|
||||
reader = csv.DictReader(io.StringIO(text))
|
||||
quotes = [QuoteInput.model_validate(_coerce_quote_row(row)).model_dump() for row in reader]
|
||||
else:
|
||||
quotes = _parse_plain_text_quotes(text)
|
||||
except Exception as exc:
|
||||
return {"ok": False, "code": "quote_parse_failed", "message": f"Could not parse quote upload: {exc}"}
|
||||
if not quotes:
|
||||
return {"ok": False, "code": "no_quotes_found", "message": "No quote rows were found in the upload."}
|
||||
return {"ok": True, "quotes": quotes}
|
||||
|
||||
|
||||
def _coerce_quote_row(row: dict[str, Any]) -> dict[str, Any]:
|
||||
aliases = {
|
||||
"vendor": ["vendor", "supplier", "name"],
|
||||
"quantity": ["quantity", "qty"],
|
||||
"unit_price": ["unit_price", "price", "unit price", "unitPrice"],
|
||||
"delivery_days": ["delivery_days", "delivery", "delivery days", "lead_time", "lead time"],
|
||||
"warranty_months": ["warranty_months", "warranty", "warranty months"],
|
||||
}
|
||||
normalized = {str(k).strip().lower(): v for k, v in row.items()}
|
||||
out: dict[str, Any] = {}
|
||||
for target, names in aliases.items():
|
||||
for name in names:
|
||||
if name.lower() in normalized and normalized[name.lower()] not in (None, ""):
|
||||
out[target] = normalized[name.lower()]
|
||||
break
|
||||
return out
|
||||
|
||||
|
||||
def _parse_plain_text_quotes(text: str) -> list[dict[str, Any]]:
|
||||
quotes: list[dict[str, Any]] = []
|
||||
for line in text.splitlines():
|
||||
if not line.strip():
|
||||
continue
|
||||
parts = [part.strip() for part in re.split(r"[,;|]", line) if part.strip()]
|
||||
if len(parts) >= 5:
|
||||
quotes.append(
|
||||
QuoteInput.model_validate(
|
||||
{
|
||||
"vendor": parts[0],
|
||||
"quantity": parts[1],
|
||||
"unit_price": parts[2],
|
||||
"delivery_days": parts[3],
|
||||
"warranty_months": parts[4],
|
||||
}
|
||||
).model_dump()
|
||||
)
|
||||
return quotes
|
||||
|
||||
|
||||
@contextmanager
|
||||
def _db_conn() -> Any:
|
||||
url = os.environ.get("DATABASE_URL")
|
||||
if not url or psycopg is None:
|
||||
yield None
|
||||
return
|
||||
conn = psycopg.connect(url, row_factory=dict_row)
|
||||
try:
|
||||
yield conn
|
||||
conn.commit()
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
async def _save_comparison(tenant_key: str, payload: dict[str, Any]) -> None:
|
||||
key = (tenant_key, payload["comparison_id"])
|
||||
with _db_conn() as conn:
|
||||
if conn is None:
|
||||
_LOCAL_COMPARISONS[key] = dict(payload)
|
||||
return
|
||||
with conn.cursor() as cur:
|
||||
cur.execute(
|
||||
"""
|
||||
INSERT INTO quote_comparisons
|
||||
(tenant_key, comparison_id, recommended_vendor, recommendation_vendor,
|
||||
score, weighted_score, normalized_total, payload, updated_at)
|
||||
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, NOW())
|
||||
ON CONFLICT (tenant_key, comparison_id) DO UPDATE SET
|
||||
recommended_vendor = EXCLUDED.recommended_vendor,
|
||||
recommendation_vendor = EXCLUDED.recommendation_vendor,
|
||||
score = EXCLUDED.score,
|
||||
weighted_score = EXCLUDED.weighted_score,
|
||||
normalized_total = EXCLUDED.normalized_total,
|
||||
payload = EXCLUDED.payload,
|
||||
updated_at = NOW()
|
||||
""",
|
||||
(
|
||||
tenant_key,
|
||||
payload["comparison_id"],
|
||||
payload["recommendation"]["vendor"],
|
||||
payload["recommendation"]["vendor"],
|
||||
payload["recommendation"]["score"],
|
||||
payload["recommendation"]["score"],
|
||||
payload["recommendation"]["normalized_total"],
|
||||
json.dumps(payload),
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
async def _load_comparison(tenant_key: str, comparison_id: str) -> dict[str, Any] | None:
|
||||
key = (tenant_key, comparison_id)
|
||||
with _db_conn() as conn:
|
||||
if conn is None:
|
||||
return _LOCAL_COMPARISONS.get(key)
|
||||
with conn.cursor() as cur:
|
||||
cur.execute(
|
||||
"""
|
||||
SELECT payload
|
||||
FROM quote_comparisons
|
||||
WHERE tenant_key = %s AND comparison_id = %s
|
||||
""",
|
||||
(tenant_key, comparison_id),
|
||||
)
|
||||
row = cur.fetchone()
|
||||
if not row:
|
||||
return None
|
||||
payload = row["payload"]
|
||||
return payload if isinstance(payload, dict) else json.loads(payload)
|
||||
|
||||
|
||||
async def _persist_receipt(
|
||||
def _build_deep_agent(
|
||||
self,
|
||||
*,
|
||||
tenant_key: str,
|
||||
comparison_id: str,
|
||||
skill_name: str,
|
||||
input_payload: dict[str, Any],
|
||||
result_payload: dict[str, Any],
|
||||
status: str,
|
||||
started_at: str,
|
||||
) -> dict[str, Any]:
|
||||
receipt = {
|
||||
"receipt_id": str(uuid.uuid4()),
|
||||
"agent": QuoteJudgeStudioV1.name,
|
||||
"agent_version": QuoteJudgeStudioV1.version,
|
||||
"skill": skill_name,
|
||||
"comparison_id": comparison_id,
|
||||
"status": status,
|
||||
"started_at": started_at,
|
||||
"completed_at": _now_iso(),
|
||||
"input_hash": _hash_json(input_payload),
|
||||
"result_hash": _hash_json(result_payload),
|
||||
ctx: RunContext[{{ auth_type }}],
|
||||
creds: LLMCreds,
|
||||
) -> Any:
|
||||
# Lazy imports keep `a2a card` usable before local dependencies are
|
||||
# installed. `a2a deploy` installs requirements.txt during the build.
|
||||
from a2a_pack.deepagents import create_a2a_deep_agent
|
||||
from langchain.agents.middleware import wrap_model_call
|
||||
from langchain_core.tools import tool
|
||||
|
||||
@tool
|
||||
def text_stats(text: str) -> str:
|
||||
"""Return exact word, character, and line counts for text."""
|
||||
words = [part for part in text.split() if part.strip()]
|
||||
return json.dumps(
|
||||
{
|
||||
"characters": len(text),
|
||||
"words": len(words),
|
||||
"lines": len(text.splitlines()) or 1,
|
||||
}
|
||||
with _db_conn() as conn:
|
||||
if conn is None:
|
||||
_LOCAL_RECEIPTS.append({"tenant_key": tenant_key, **receipt})
|
||||
return receipt
|
||||
with conn.cursor() as cur:
|
||||
cur.execute(
|
||||
"""
|
||||
INSERT INTO quote_execution_receipts
|
||||
(tenant_key, comparison_id, receipt_id, skill_name, tool_name, status, ok,
|
||||
input_hash, result_hash, payload, created_at)
|
||||
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, NOW())
|
||||
""",
|
||||
(
|
||||
tenant_key,
|
||||
comparison_id,
|
||||
receipt["receipt_id"],
|
||||
skill_name,
|
||||
skill_name,
|
||||
status,
|
||||
status == "ok",
|
||||
receipt["input_hash"],
|
||||
receipt["result_hash"],
|
||||
json.dumps(receipt),
|
||||
),
|
||||
)
|
||||
return receipt
|
||||
|
||||
@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)}"
|
||||
)
|
||||
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,
|
||||
)
|
||||
|
||||
|
||||
def _hash_json(payload: dict[str, Any]) -> str:
|
||||
encoded = json.dumps(payload, sort_keys=True, separators=(",", ":"), default=str).encode("utf-8")
|
||||
return hashlib.sha256(encoded).hexdigest()
|
||||
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 _now_iso() -> str:
|
||||
return datetime.now(timezone.utc).replace(microsecond=0).isoformat()
|
||||
def _seed_runtime_skills(backend: Any, ctx: RunContext[Any]) -> list[str]:
|
||||
"""Copy packaged DeepAgents skills into the invocation workspace.
|
||||
|
||||
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.
|
||||
"""
|
||||
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 []
|
||||
|
||||
|
||||
def _last_message_text(state: dict[str, Any]) -> str:
|
||||
messages = state.get("messages") or []
|
||||
if not messages:
|
||||
return json.dumps(state, default=str)
|
||||
|
||||
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])
|
||||
|
||||
Reference in New Issue
Block a user