From 2d1dd91a1cc45265138746de03c67a05d577daf1 Mon Sep 17 00:00:00 2001 From: Rodolphe Marques Date: Fri, 28 Aug 2026 20:35:19 +0200 Subject: [PATCH 1/4] feat(langchain-deep-agent-py): Deep Agents tutorial with the paid tool in a subagent MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Adds a freemium market-research agent on LangChain's Deep Agents harness, the sibling of langchain-research-agent-py. Same payment contract, different harness — the two are meant to be read side by side. The point of the tutorial is the delegation hop: the paid tool is given ONLY to the `research-sub` subagent, so every paid call crosses `task()`. The x402 token a buyer puts on the run still reaches it, because LangGraph copies `configurable` into subagent tool calls, so @requires_payment works unchanged. Without that property a paid tool could never sit behind a delegation, which is the whole premise of the harness. Also handles two harness behaviours the ReAct tutorial does not have to: - A deep agent decides for itself how many subagent hops a request warrants, so one user turn can settle credits several times. Adds a per-run budget cap (NVM_MAX_PAID_CALLS_PER_RUN, default 3) keyed on the run/thread id, refunding the reservation when a call raises PaymentRequiredError so a user who authorizes mid-run is not shortchanged. - Two LLM layers sit between the paid tool and the user and either may paraphrase, so both system prompts forbid answering from own knowledge and the buyer prints the raw ToolMessage. The buyer uses the two-step delegation flow (create_delegation, then DelegationConfig(delegation_id=...)); passing spending limits straight to get_x402_access_token is deprecated and emits a FutureWarning. Own virtualenv on purpose: deepagents needs langchain-core>=1.6.1, while the research agent resolves 1.4. Verified end-to-end against sandbox: free path, paywall enforced through the delegation, and a paid run settling 5 credits. --- CLAUDE.md | 4 + README.md | 20 + langchain-deep-agent-py/.env.example | 41 + langchain-deep-agent-py/.gitignore | 6 + langchain-deep-agent-py/README.md | 166 + langchain-deep-agent-py/langgraph.json | 7 + langchain-deep-agent-py/poetry.lock | 5467 ++++++++++++++++++++++++ langchain-deep-agent-py/pyproject.toml | 33 + langchain-deep-agent-py/src/agent.py | 297 ++ langchain-deep-agent-py/src/buyer.py | 222 + 10 files changed, 6263 insertions(+) create mode 100644 langchain-deep-agent-py/.env.example create mode 100644 langchain-deep-agent-py/.gitignore create mode 100644 langchain-deep-agent-py/README.md create mode 100644 langchain-deep-agent-py/langgraph.json create mode 100644 langchain-deep-agent-py/poetry.lock create mode 100644 langchain-deep-agent-py/pyproject.toml create mode 100644 langchain-deep-agent-py/src/agent.py create mode 100644 langchain-deep-agent-py/src/buyer.py diff --git a/CLAUDE.md b/CLAUDE.md index 686ff6d8..0d1df953 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -13,6 +13,10 @@ tutorials/ ├── http-simple-agent-ts/ # Express.js agent with x402 payment middleware (TypeScript) ├── http-simple-agent-py/ # FastAPI agent with x402 payment middleware (Python) ├── langchain-paid-agent-py/# Minimal LangChain @requires_payment + LangGraph agent (Python) +├── langchain-research-agent-py/ # Freemium in-tool gating on create_react_agent (Python) +├── langchain-deep-agent-py/ # Same pattern on the Deep Agents harness; paid tool in a subagent +├── langchain-langsmith-deployment-py/ # Route-level ASGI PaymentMiddleware (Python) +├── langchain-chat-ui-nvm/ # Next.js browser chat UI with the x402 card-delegation popup ├── a2a-examples/ # Agent-to-Agent (A2A) protocol examples ├── mcp-examples/ # Model Context Protocol (MCP) examples │ ├── weather-mcp/ # TypeScript MCP server (has CLAUDE.md) diff --git a/README.md b/README.md index 4cebf77d..921d6d91 100644 --- a/README.md +++ b/README.md @@ -165,6 +165,26 @@ Python implementation of the Weather MCP server, demonstrating Nevermined Paymen --- +### 7. Deep Agents Market Research (Python) + +**Location**: `langchain-deep-agent-py/` + +A freemium market-research agent on LangChain's [Deep Agents](https://docs.langchain.com/oss/python/deepagents/overview) harness, where the paid capability lives **inside a subagent**. Users chat with the supervisor for free; only the delegated research tool charges credits. Demonstrates that the x402 token a buyer puts on the run survives the `task()` delegation hop, so `@requires_payment` needs no changes. + +**Technologies**: +- Python 3.11+ +- Deep Agents (`create_deep_agent`) on the LangChain v1 stack +- Nevermined Payments SDK (`payments-py[langsmith]`) +- OpenAI GPT-4o-mini + +**What You'll Learn**: +- Put a paid tool behind a `task()` delegation and keep the payment lifecycle intact +- Cap paid calls per run — a deep agent decides for itself how many subagent hops a request warrants +- Guard against the supervisor answering a paid question from its own knowledge +- Compare harnesses side by side with the sibling `langchain-research-agent-py` + +--- + ## Quick Start Each tutorial includes detailed instructions for: diff --git a/langchain-deep-agent-py/.env.example b/langchain-deep-agent-py/.env.example new file mode 100644 index 00000000..0f0ffe36 --- /dev/null +++ b/langchain-deep-agent-py/.env.example @@ -0,0 +1,41 @@ +# --- Nevermined credentials (sandbox) --------------------------------------- +# Since payments-py 1.16 the environment is derived from the API-key prefix +# (`sandbox:` / `live:`), so there is no NVM_ENVIRONMENT here. +NVM_API_KEY=your-nevermined-api-key + +# --- Plan that gates the `market_research` tool ----------------------------- +# Your Nevermined plan id. Create and subscribe to a plan at +# https://nevermined.app; the same account plays both seller and buyer in +# this demo. +# Note: the per-call credit price is NOT set here — the agent reads it from +# the plan's `registry.credits.maxAmount` at import time, so the charge +# always matches what the plan advertises. +NVM_PLAN_ID=your-plan-id + +# Optional: the agent id this plan is associated with on Nevermined. When +# set, surfaces on the x402 envelope's `extra.agentId` so buyers can +# inspect what they're paying for. Leave blank to omit. +NVM_AGENT_ID= + +# A deep agent chooses for itself how many subagent hops a request needs, +# and every hop that reaches `market_research` settles credits. This caps +# the paid calls per run so one message cannot bill without bound. +NVM_MAX_PAID_CALLS_PER_RUN=3 + +# --- LLM -------------------------------------------------------------------- +OPENAI_API_KEY= +OPENAI_MODEL=gpt-4o-mini + +# --- Buyer config ----------------------------------------------------------- +LANGSMITH_DEPLOYMENT_URL=http://127.0.0.1:2024 +ASSISTANT_ID=deep_research +INPUT=Research the electric vehicle market in Europe + +# --- LangSmith Observability (optional) ------------------------------------- +# Set LANGSMITH_TRACING=true and LANGSMITH_API_KEY=... to emit +# nvm:verify / nvm:settlement spans into a LangSmith project. +LANGSMITH_TRACING= +LANGSMITH_API_KEY= +LANGSMITH_PROJECT= +# Regional override - https://eu.api.smith.langchain.com for GCP EU accounts. +LANGSMITH_ENDPOINT= diff --git a/langchain-deep-agent-py/.gitignore b/langchain-deep-agent-py/.gitignore new file mode 100644 index 00000000..e58ca638 --- /dev/null +++ b/langchain-deep-agent-py/.gitignore @@ -0,0 +1,6 @@ +.env +.venv/ +__pycache__/ +*.pyc +.langgraph_api/ +dist/ diff --git a/langchain-deep-agent-py/README.md b/langchain-deep-agent-py/README.md new file mode 100644 index 00000000..f5396daf --- /dev/null +++ b/langchain-deep-agent-py/README.md @@ -0,0 +1,166 @@ +# langchain-deep-agent-py + +A **Deep Agents** market-research agent gated by **Nevermined x402**, where the paid capability lives *inside a subagent*. Users chat with the supervisor for free; only the delegated research capability charges credits. + +This is the sibling of [`langchain-research-agent-py`](../langchain-research-agent-py/), which does the same thing with a plain `create_react_agent`. Same payment contract, different harness — read them side by side to see what the harness does and does not change. + +## What it demonstrates + +The interesting claim, and the reason this tutorial exists: + +``` +main agent ──task()──▶ research-sub ──▶ market_research [PAID] + ▲ │ + └──────── x402 token supplied here ──────────┘ + config.configurable.payment_token +``` + +The buyer attaches an x402 access token to the **run**. The supervisor never touches it — it delegates via the built-in `task` tool, and LangGraph copies `configurable` down into the subagent's own tool calls. So `@requires_payment` works **unchanged one delegation hop away** from where the token was supplied. + +Why that matters: a deep agent's whole premise is that the supervisor hands work to subagents. If payment context did not survive that hop, every paid tool would have to sit on the main agent and the harness would be useless for monetized capabilities. It survives. + +- [`create_deep_agent`](https://docs.langchain.com/oss/python/deepagents/overview) supervisor with planning, filesystem and `task` tools built in. +- One subagent (`research-sub`) that owns the single paid tool. +- The `@requires_payment` decorator from `payments_py.x402.langchain`, which wraps the tool with the canonical x402 lifecycle: + + ``` + verify_permissions → tool body → settle_permissions + ``` + +- A per-run budget cap, because a deep agent decides for itself how many subagent hops a request warrants (see [Two things to know](#two-things-to-know-before-you-ship-this)). +- **Plain LangGraph deployment** — `create_deep_agent()` returns a compiled graph, so `langgraph dev` and hosted LangSmith Deployment work with no extra wiring. + +## Two things to know before you ship this + +These are properties of the harness, not bugs, and both are worth designing around. + +**1. A deep agent can bill several times per user turn.** The supervisor, not you, decides how many subagent calls a request warrants. One "research X" message may settle credits more than once. This tutorial caps it explicitly rather than trusting the model to be frugal: + +```bash +NVM_MAX_PAID_CALLS_PER_RUN=3 # in .env +``` + +The cap is keyed by run, and an attempt that returns `PAYMENT_REQUIRED` is refunded — a user who authorizes mid-run still gets the calls they paid for. + +**2. Two LLM layers can paraphrase the tool's output.** The subagent relays to the supervisor, which relays to the user. Both are instructed to pass text through verbatim; neither is guaranteed to. The plain ReAct sibling has one such layer, so this is strictly worse here. Treat the tool's return value as the source of truth — `src/buyer.py` prints the raw `ToolMessage`, not the chat reply, for exactly this reason. + +A related failure mode to watch for while developing: a capable supervisor sometimes answers a research question **from its own knowledge** instead of delegating, which silently gives the paid capability away for free. Both system prompts here forbid it explicitly. If you swap in a different model, re-test that path — it is prompt-dependent, not structural. + +## Prerequisites + +- **Python 3.11+** +- A **Nevermined account** with an enrolled payment method and a plan to charge for the `market_research` tool. Create at [https://nevermined.app](https://nevermined.app). +- An **OpenAI API key** (or swap `ChatOpenAI` / the `model=` string in `src/agent.py` for another provider). + +> **Its own virtualenv, on purpose.** `deepagents` requires the LangChain v1 stack (`langchain-core >= 1.6.1`). The sibling research agent resolves `langchain-core 1.4` with `langchain-openai 0.3`, so the two tutorials cannot share an environment. Install this one separately. + +## Quick start + +```bash +# 1. Install +poetry install + +# 2. Configure +cp .env.example .env +$EDITOR .env # fill in NVM_API_KEY, NVM_PLAN_ID, OPENAI_API_KEY + +# 3. Run the agent locally +poetry run langgraph dev --no-browser --port 2024 +``` + +In a second terminal: + +```bash +# 4. Drive the free + paid flow end-to-end +poetry run buyer +``` + +You should see: + +``` +Connecting to LangSmith Deployment at http://127.0.0.1:2024 + +[1/4] Asking the agent what it can do (free, no token)... + Agent reply: + I can provide market research... [free chat reply] + +[2/4] Plan resolves to scheme=nvm:card-delegation, provider=stripe + Using payment method: visa *4242 + +[3/4] Acquiring x402 access token from the plan... + token = eyJ4NDAyVmVyc2lvbi... + +[4/4] Running research request with token: 'Research the electric vehicle market in Europe' + (supervisor -> task() -> research-sub -> market_research) + +Agent reply (raw subagent output): + +## Market Size +... [structured analysis from the analyst LLM] + +_💳 Settled 5 credit(s). Remaining balance: 95._ +``` + +## Smoke test without a token + +Hit the agent with `/runs/wait` and no `config.configurable.payment_token` — the paid tool returns a `PAYMENT_REQUIRED:` notice instead of executing, and the supervisor relays it. + +```bash +TID=$(curl -sS -X POST http://127.0.0.1:2024/threads -H 'content-type: application/json' -d '{}' | jq -r .thread_id) + +curl -sS -X POST "http://127.0.0.1:2024/threads/$TID/runs/wait" \ + -H 'content-type: application/json' \ + -d '{"assistant_id":"deep_research","input":{"messages":[{"type":"human","content":"Research the EV market"}]}}' +``` + +## Use it with the browser chat UI + +The buyer-side contract is identical to the ReAct tutorial's, so the [`langchain-chat-ui-nvm`](../langchain-chat-ui-nvm/) tutorial works against this agent unchanged — its proxy injects the token at `config.configurable.payment_token` either way. Point it at this agent and set the assistant id: + +```bash +# in ../langchain-chat-ui-nvm/.env.local +LANGGRAPH_API_URL=http://127.0.0.1:2024 +NEXT_PUBLIC_ASSISTANT_ID=deep_research +``` + +Run only one of the two agents on port 2024 at a time. + +## Deploy to LangSmith Deployment (hosted) + +```bash +poetry run langgraph up +``` + +Required deployment secrets: + +| Secret | Why | +|---|---| +| `NVM_API_KEY` | The tool calls `payments.facilitator.verify_permissions` / `settle_permissions` from inside the deployed worker. | +| `NVM_PLAN_ID` | Which plan the tool charges against. | +| `OPENAI_API_KEY` | Supervisor, subagent, and analyst LLMs. | + +## Files + +| File | Purpose | +|---|---| +| `src/agent.py` | `create_deep_agent` supervisor + `research-sub` subagent. The paid tool is given **only** to the subagent, so every paid call crosses a `task()` boundary. Includes the per-run budget cap. | +| `src/buyer.py` | CLI buyer that exercises the free path and the paid path back-to-back. Identical contract to the ReAct tutorial's buyer. | +| `langgraph.json` | Wires the agent at `graphs.deep_research`. **No `http.app`** — gating is in-graph. | +| `.env.example` | Template for the Nevermined + OpenAI env vars. | + +## Observability with LangSmith (optional) + +Set `LANGSMITH_TRACING=true` and `LANGSMITH_API_KEY=...` in `.env` to emit `nvm:verify` and `nvm:settlement` spans into your LangSmith project. On a deep agent these nest under the `task` span, so you can see which subagent hop incurred each charge — useful when reasoning about the multi-settlement behaviour above. GCP EU accounts also need `LANGSMITH_ENDPOINT=https://eu.api.smith.langchain.com`. + +## Which harness should I use? + +| | [`langchain-research-agent-py`](../langchain-research-agent-py/) | this tutorial | +|---|---|---| +| Harness | `create_react_agent` | `create_deep_agent` | +| Paid tool lives on | the agent itself | a subagent, one `task()` hop away | +| LLM layers between tool and user | 1 | 2 | +| Paid calls per user turn | one per tool call the model makes | supervisor decides — cap it | +| Built-in planning / filesystem / subagents | no | yes | +| Buyer-side contract | `config.configurable.payment_token` | **identical** | + +Start from the ReAct tutorial if you want the smallest thing that works. 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The paid tool lives inside a subagent, proving the payment token survives task delegation. Companion to ../langchain-research-agent-py." +authors = ["Nevermined "] +license = "MIT" +readme = "README.md" +packages = [{include = "src"}] + +[tool.poetry.dependencies] +python = ">=3.11,<4.0" +python-dotenv = "^1.0.0" +# The Deep Agents harness. Pulls the LangChain v1 stack +# (langchain>=1.3.18, langchain-core>=1.6.1) — which is why this tutorial +# has its own virtualenv rather than sharing the sibling research agent's. +deepagents = "^0.7.10" +langchain-openai = "^1.6" +httpx = "^0.28" +# `[langsmith]` extra brings in fastapi/starlette — required transitively by +# `payments_py.x402.langchain.requires_payment` (the SDK package __init__ +# eagerly loads the middleware module). +payments-py = {version = "^1.16.1", extras = ["langsmith"]} + +[tool.poetry.group.dev.dependencies] +langgraph-cli = {extras = ["inmem"], version = "*"} +langgraph-api = "^0.8" + +[tool.poetry.scripts] +buyer = "src.buyer:cli" + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" diff --git a/langchain-deep-agent-py/src/agent.py b/langchain-deep-agent-py/src/agent.py new file mode 100644 index 00000000..37573060 --- /dev/null +++ b/langchain-deep-agent-py/src/agent.py @@ -0,0 +1,297 @@ +"""Deep Agents market-research agent gated by Nevermined x402. + +Same payment pattern as the sibling ``../langchain-research-agent-py`` +tutorial, but built on the **Deep Agents harness** (``create_deep_agent``) +instead of ``create_react_agent``. The point of interest is *where* the +paid capability sits: + + main agent --task()--> research-sub --> market_research [PAID] + +The buyer attaches an x402 access token to the run at +``config.configurable.payment_token``. The main agent never touches that +token; it delegates via the built-in ``task`` tool, and LangGraph copies +``configurable`` down into the subagent's own tool calls. So the +``@requires_payment`` decorator works **unchanged** one delegation hop +away from where the token was supplied. + +Why that matters: a deep agent's whole premise is that the supervisor +hands work to subagents. If the payment context did not survive that hop, +every paid tool would have to live on the main agent and the harness +would be useless for monetized capabilities. It does survive. + +Two consequences worth understanding before you ship something like this: + + 1. **A deep agent can bill several times per user turn.** The + supervisor decides how many subagent calls a request warrants, so + one "research X" message may settle credits more than once. This + module caps that explicitly (``MAX_PAID_CALLS_PER_RUN``) rather + than trusting the model to be frugal. + 2. **Two LLM layers can paraphrase the tool's output.** The subagent + relays to the supervisor, which relays to the user. Both are asked + to pass text through verbatim, but neither is guaranteed to. Treat + the tool's return value as the source of truth, not the chat reply. +""" + +import logging +import os +import threading + +from deepagents import create_deep_agent +from dotenv import load_dotenv +from langchain_core.runnables import RunnableConfig +from langchain_core.tools import tool +from langchain_openai import ChatOpenAI +from payments_py import PaymentOptions, Payments +from payments_py.x402.langchain import ( + PaymentRequiredError, + last_settlement, + requires_payment, +) + +load_dotenv() + +NVM_API_KEY = os.environ["NVM_API_KEY"] +NVM_PLAN_ID = os.environ["NVM_PLAN_ID"] +NVM_AGENT_ID = os.environ.get("NVM_AGENT_ID") or None + +OPENAI_MODEL = os.environ.get("OPENAI_MODEL", "gpt-4o-mini") + +# A deep agent decides for itself how many subagent hops a request needs. +# Each hop that reaches `market_research` settles credits, so cap it. +MAX_PAID_CALLS_PER_RUN = int(os.environ.get("NVM_MAX_PAID_CALLS_PER_RUN", "3")) + +logger = logging.getLogger(__name__) + +# `environment` is intentionally omitted: since payments-py 1.16 it is +# derived from the API-key prefix and passing it emits a FutureWarning. +_payments = Payments.get_instance(PaymentOptions(nvm_api_key=NVM_API_KEY)) + + +def _resolve_plan_price() -> int: + """Fetch the per-call credit price from the plan. + + The plan's ``registry.credits.maxAmount`` is the authoritative + fixed-price-redemption cost; for range plans it is the upper bound. + Falling back to 1 keeps the agent bootable against an unconfigured + plan instead of failing at import time. + """ + try: + plan = _payments.plans.get_plan(NVM_PLAN_ID) or {} + credits = (plan.get("registry") or {}).get("credits") or {} + raw = credits.get("maxAmount") or credits.get("amount") + if raw is not None: + return int(raw) + except Exception as error: + logger.warning( + "Could not resolve plan price for %s, defaulting to 1: %s", + NVM_PLAN_ID, + error, + ) + return 1 + + +PLAN_CREDITS_PER_CALL = _resolve_plan_price() + +_PAYMENT_REQUIRED_NOTICE = ( + "PAYMENT_REQUIRED: This capability charges {credits} credit(s) per call " + "via Nevermined plan `{plan_id_short}`. The buyer must include a valid " + "x402 access token under `config.configurable.payment_token` — in the " + "browser chat UI that happens automatically once the user clicks the " + "**Authorize** button at the top and creates a card delegation. " + "Please authorize and ask again." +) + +_BUDGET_EXHAUSTED_NOTICE = ( + "BUDGET_EXHAUSTED: This run already performed {limit} paid research " + "call(s), the per-run cap. Returning without charging again. Ask a " + "follow-up question to start a new run, or raise " + "NVM_MAX_PAID_CALLS_PER_RUN." +) + + +class _RunBudget: + """Counts paid calls per run so one turn cannot bill without bound. + + Deep agents may fan out to several subagent calls for a single user + message. The counter is keyed by the LangGraph thread/run so + concurrent runs in the same process do not share a budget. + """ + + def __init__(self) -> None: + self._lock = threading.Lock() + self._counts: dict[str, int] = {} + + @staticmethod + def _key(config: RunnableConfig | None) -> str: + configurable = (config or {}).get("configurable") or {} + return str( + configurable.get("run_id") + or configurable.get("thread_id") + or "default" + ) + + def try_consume(self, config: RunnableConfig | None) -> bool: + """Reserve one paid call. False when the run is already at its cap.""" + key = self._key(config) + with self._lock: + used = self._counts.get(key, 0) + if used >= MAX_PAID_CALLS_PER_RUN: + return False + self._counts[key] = used + 1 + return True + + def refund(self, config: RunnableConfig | None) -> None: + """Give the reservation back when the call did not settle.""" + key = self._key(config) + with self._lock: + self._counts[key] = max(0, self._counts.get(key, 0) - 1) + + +_budget = _RunBudget() + + +def _run_analyst(topic: str) -> str: + """Generate a market analysis using a research-analyst LLM persona.""" + analyst = ChatOpenAI(model=OPENAI_MODEL, temperature=0.4) + prompt = ( + "You are a senior market research analyst. Write a concise market " + f"analysis on: {topic}\n\n" + "Structure with these markdown sections:\n" + " ## Market Size\n" + " ## Key Players\n" + " ## Trends\n" + " ## Opportunities\n\n" + "Keep it factual and structured. 300-400 words total." + ) + response = analyst.invoke(prompt) + content = response.content + return content if isinstance(content, str) else str(content) + + +@requires_payment( + payments=_payments, + plan_id=NVM_PLAN_ID, + credits=PLAN_CREDITS_PER_CALL, + agent_id=NVM_AGENT_ID, +) +def _market_research_paid(topic: str, config: RunnableConfig) -> str: + """Inner, payment-protected implementation. + + The decorator runs verify_permissions before this body executes and + settle_permissions after a successful return. It reads the token from + ``config["configurable"]["payment_token"]`` — which is why `config` + must be forwarded explicitly by the caller below. + """ + return _run_analyst(topic) + + +@tool +def market_research(topic: str, config: RunnableConfig) -> str: + """Produce a market analysis on the given topic. + + PAID capability. Each call charges credits via Nevermined x402. The + buyer must supply a valid x402 access token under + ``config.configurable.payment_token``. If the token is missing or + invalid the tool returns a ``PAYMENT_REQUIRED:`` notice for the agent + to relay back to the user. + """ + plan_id_short = f"{NVM_PLAN_ID[:24]}..." if len(NVM_PLAN_ID) > 24 else NVM_PLAN_ID + + if not _budget.try_consume(config): + logger.info("per-run paid-call cap reached (%s)", MAX_PAID_CALLS_PER_RUN) + return _BUDGET_EXHAUSTED_NOTICE.format(limit=MAX_PAID_CALLS_PER_RUN) + + try: + analysis = _market_research_paid(topic, config=config) + except PaymentRequiredError as error: + # No settlement happened, so this attempt should not count against + # the run's budget — otherwise a user who authorizes mid-run gets + # fewer paid calls than they paid for. + _budget.refund(config) + logger.info("payment required: %s", error) + return _PAYMENT_REQUIRED_NOTICE.format( + credits=PLAN_CREDITS_PER_CALL, + plan_id_short=plan_id_short, + ) + except Exception: + _budget.refund(config) + raise + + settlement = last_settlement() + if settlement and getattr(settlement, "success", False): + return ( + f"{analysis}\n\n---\n" + f"_💳 Settled {settlement.credits_redeemed} credit(s). " + f"Remaining balance: {settlement.remaining_balance}._" + ) + if settlement is not None: + # The decorator caught the settlement failure and logged a warning; + # surface it inline so the buyer knows credits may not have been + # burned even though they received the value. + return ( + f"{analysis}\n\n---\n" + f"_⚠️ Settlement reported failure: " + f"{getattr(settlement, 'error_reason', 'unknown') or 'unknown'}._" + ) + return analysis + + +# The paid tool is given ONLY to the subagent. That is the whole point of +# this tutorial: the supervisor cannot call `market_research` itself, so +# every paid call crosses a `task()` delegation boundary — and the x402 +# token still arrives. +RESEARCH_SUBAGENT = { + "name": "research-sub", + "description": ( + "Performs paid market research on a single topic. Delegate here " + "whenever the user asks for actual research or analysis." + ), + "system_prompt": ( + "You are a market research specialist with exactly one tool, " + "`market_research`.\n\n" + "1. Call `market_research` ONCE with the requested topic.\n" + "2. Return the tool's output **verbatim**. Do not summarise it, " + "re-structure its markdown, or drop the settlement receipt " + "footer on the final line.\n" + "3. If the output starts with `PAYMENT_REQUIRED:` or " + "`BUDGET_EXHAUSTED:`, return exactly that text and nothing else. " + "Never answer the research question from your own knowledge — " + "that would give away the paid capability for free." + ), + "tools": [market_research], +} + +SYSTEM_PROMPT = ( + "You are a market research agent published on the Nevermined Payments " + "network, running on the Deep Agents harness. Your behaviour:\n\n" + "1. When asked what you can do, who you are, how you work, or what " + "you cost: answer conversationally. This is free.\n" + "2. You have exactly one paid capability, and you cannot invoke it " + f"yourself. It costs {PLAN_CREDITS_PER_CALL} credit(s) per call via " + "the Nevermined x402 protocol and lives on the `research-sub` " + "subagent.\n" + "3. When the user asks you to actually perform research, delegate to " + "`research-sub` via the `task` tool — **always**, even if an earlier " + "attempt in this conversation returned `PAYMENT_REQUIRED:`. The user " + "may have authorized in between, and a fresh call is the only way to " + "find out.\n" + "4. NEVER answer a research question from your own knowledge, and " + "never reuse a previous tool result as a new answer. If you cannot " + "get a paid result, say so plainly.\n" + "5. Relay the subagent's output to the user **verbatim**, including " + "the settlement receipt footer. You may add at most one short " + "introductory sentence before it.\n" + "6. If the result starts with `PAYMENT_REQUIRED:`, relay it verbatim " + "and invite the user to click the **Authorize** button at the top of " + "the chat.\n" + "7. Decline politely if asked for anything unrelated. You are " + "research-only.\n" +) + +graph = create_deep_agent( + model=f"openai:{OPENAI_MODEL}", + tools=[], + subagents=[RESEARCH_SUBAGENT], + system_prompt=SYSTEM_PROMPT, + name="deep-market-research-agent", +) diff --git a/langchain-deep-agent-py/src/buyer.py b/langchain-deep-agent-py/src/buyer.py new file mode 100644 index 00000000..820df621 --- /dev/null +++ b/langchain-deep-agent-py/src/buyer.py @@ -0,0 +1,222 @@ +"""CLI buyer for the Deep Agents x402 gating demo. + +Mirrors ``../langchain-research-agent-py/src/buyer.py`` — the buyer-side +contract is identical, which is the point: swapping the agent harness +does not change how a buyer pays. The x402 access token goes on +``config.configurable.payment_token`` and the agent's tool reads it, +whether that tool sits on the main agent or one delegation hop away +inside a subagent. + +Exercises both paths in sequence: + + 1. Free path - ask "what can you do?" with no token. The supervisor + answers from its system prompt without delegating; no credits move. + 2. Paid path - mint an x402 access token from ``NVM_PLAN_ID``, attach + it to the run, and ask for research. The supervisor delegates to + `research-sub`, whose `market_research` tool verifies, analyses, + and settles. + +Run with: `poetry run buyer` +""" + +import asyncio +import os +import re + +import httpx +from dotenv import load_dotenv +from payments_py import PaymentOptions, Payments +from payments_py.x402.resolve_scheme import resolve_network, resolve_scheme +from payments_py.x402.types import ( + CreateDelegationPayload, + DelegationConfig, + X402TokenOptions, +) + +load_dotenv() + +DEPLOYMENT_URL = os.environ.get("LANGSMITH_DEPLOYMENT_URL", "http://127.0.0.1:2024") +NVM_API_KEY = os.environ["NVM_API_KEY"] +NVM_PLAN_ID = os.environ["NVM_PLAN_ID"] +ASSISTANT_ID = os.environ.get("ASSISTANT_ID", "deep_research") +RESEARCH_TOPIC = os.environ.get("INPUT", "Research the electric vehicle market") + + +def pick_payment_method(payments: Payments, provider: str): + """Return the first enrolled payment method whose provider matches. + + Returns None and prints actionable guidance if no match exists. + """ + methods = payments.delegation.list_payment_methods() + pm = next((m for m in methods if getattr(m, "provider", None) == provider), None) + if pm is None: + available = ( + ", ".join(sorted({getattr(m, "provider", "unknown") for m in methods})) + or "" + ) + print( + f" No {provider!r} payment method enrolled. " + f"Available on this account: {available}. " + f"Enroll a matching method at https://nevermined.app and re-run." + ) + return pm + + +def _flatten(content) -> str: + if isinstance(content, str): + return content + if isinstance(content, list): + return " ".join( + block.get("text", "") if isinstance(block, dict) else str(block) + for block in content + ) + return str(content) + + +def _last_ai_text(state: dict) -> str: + """Pull the last AI message text out of a LangGraph run-wait state.""" + ai = next( + (m for m in reversed(state.get("messages", []) or []) if m.get("type") == "ai"), + None, + ) + return ( + _flatten(ai.get("content", "")) if ai else f"" + ) + + +def _last_tool_text(state: dict) -> str | None: + """Pull the last ToolMessage content. + + On a deep agent this is the `task` tool's return value — i.e. the + subagent's final answer, which should carry the paid tool's output + verbatim. It is closer to the source of truth than the supervisor's + own reply, which may paraphrase. + """ + tool = next( + ( + m + for m in reversed(state.get("messages", []) or []) + if m.get("type") == "tool" + ), + None, + ) + return _flatten(tool.get("content", "")) if tool else None + + +def _strip_settlement_footer(text: str) -> str: + """Trim the settlement-receipt footer we render at the end of paid replies.""" + return re.sub(r"\n+---\n+_💳.*?_\s*$", "", text, flags=re.DOTALL) + + +async def _create_thread(client: httpx.AsyncClient) -> str: + response = await client.post("/threads", json={}) + response.raise_for_status() + return response.json()["thread_id"] + + +async def _run( + client: httpx.AsyncClient, + thread_id: str, + user_text: str, + payment_token: str | None, +) -> dict: + """Submit one run to the agent. + + Putting the token on `config.configurable.payment_token` is the whole + contract. LangGraph propagates `configurable` into the subagent, so + the paid tool sees it without the buyer knowing the agent's internal + topology. + """ + body: dict = { + "assistant_id": ASSISTANT_ID, + "input": {"messages": [{"type": "human", "content": user_text}]}, + } + if payment_token: + body["config"] = {"configurable": {"payment_token": payment_token}} + + response = await client.post(f"/threads/{thread_id}/runs/wait", json=body) + response.raise_for_status() + return response.json() + + +async def main() -> None: + print(f"Connecting to LangSmith Deployment at {DEPLOYMENT_URL}\n") + # `environment` is derived from the API-key prefix since payments-py 1.16. + payments = Payments.get_instance(PaymentOptions(nvm_api_key=NVM_API_KEY)) + + async with httpx.AsyncClient(base_url=DEPLOYMENT_URL, timeout=300.0) as client: + # --- Free path ------------------------------------------------------- + print("[1/4] Asking the agent what it can do (free, no token)...") + thread_id = await _create_thread(client) + free_state = await _run( + client, thread_id, "What can you do?", payment_token=None + ) + print(f" Agent reply:\n {_last_ai_text(free_state)}\n") + + # --- Acquire token --------------------------------------------------- + # Same scheme/network resolution the agent uses, so we mint the + # correct token kind for whichever plan you configured. + scheme = resolve_scheme(payments, NVM_PLAN_ID) + network = resolve_network(payments, NVM_PLAN_ID) or "erc4337" + print(f"[2/4] Plan resolves to scheme={scheme}, provider={network}") + pm = pick_payment_method(payments, network) + if pm is None: + return + print(f" Using payment method: {pm.brand} *{pm.last4}\n") + + # Two steps, on purpose. Passing spending limits / a payment method + # straight to `get_x402_access_token` (inline "create-on-the-fly" + # delegation) is deprecated and emits a FutureWarning: create the + # delegation first, then reference it by id. + print("[3/4] Creating a spending delegation...") + delegation = payments.delegation.create_delegation( + CreateDelegationPayload( + provider=network, + provider_payment_method_id=pm.id, + spending_limit_cents=10000, + duration_secs=3600, + currency="usd", + ) + ) + print(f" delegation = {delegation.delegation_id}") + + print(" Acquiring x402 access token from the plan...") + token_result = payments.x402.get_x402_access_token( + NVM_PLAN_ID, + token_options=X402TokenOptions( + scheme=scheme, + delegation_config=DelegationConfig( + delegation_id=delegation.delegation_id + ), + ), + ) + access_token = token_result["accessToken"] + print(f" token = {access_token[:24]}... (truncated)\n") + + # --- Paid path ------------------------------------------------------- + print(f"[4/4] Running research request with token: {RESEARCH_TOPIC!r}") + print(" (supervisor -> task() -> research-sub -> market_research)\n") + paid_state = await _run( + client, thread_id, RESEARCH_TOPIC, payment_token=access_token + ) + # Prefer the raw ToolMessage: two LLM layers sit between the paid + # tool and the final reply, and either may paraphrase. + tool_text = _last_tool_text(paid_state) + if tool_text: + print("Agent reply (raw subagent output):\n") + print(_strip_settlement_footer(tool_text)) + match = re.search(r"_💳[^_]*_", tool_text) + if match: + print(f"\n{match.group()}") + else: + print("Agent reply:\n") + print(_last_ai_text(paid_state)) + + +def cli() -> None: + """Sync entry point for the poetry script.""" + asyncio.run(main()) + + +if __name__ == "__main__": + cli() From 2126e109dce88eb26b0202d450937ef3f80555c0 Mon Sep 17 00:00:00 2001 From: Rodolphe Marques Date: Fri, 28 Aug 2026 20:35:26 +0200 Subject: [PATCH 2/4] docs: correct stale payment-transport and env claims in the LangChain demos MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Found while re-verifying both demos end-to-end. Comment-only drift; no behaviour changes. - token/route.ts pointed at `/api/x402/probe`, a route that no longer exists — the plan metadata comes from `/api/x402/init`. - Three places still described the proxy as forwarding a `payment-signature` header. It injects the token into the run body at `config.configurable.payment_token`; the agent gates inside its tool and runs no ASGI middleware. - langchain-research-agent-py/.env.example advertised NVM_CREDITS_PER_RESEARCH, which nothing reads. The per-call price comes from the plan's registry.credits.maxAmount at import time. --- langchain-chat-ui-nvm/.env.example | 7 ++++--- .../src/app/api/x402/token/route.ts | 15 ++++++++------- .../src/components/thread/payment-banner.tsx | 4 ++-- langchain-research-agent-py/.env.example | 4 +++- 4 files changed, 17 insertions(+), 13 deletions(-) diff --git a/langchain-chat-ui-nvm/.env.example b/langchain-chat-ui-nvm/.env.example index 4ad3dc80..5b915e4f 100644 --- a/langchain-chat-ui-nvm/.env.example +++ b/langchain-chat-ui-nvm/.env.example @@ -42,8 +42,9 @@ NVM_AGENT_ID= # The LangSmith Deployment / `langgraph dev` URL of the gated agent. The # Next.js catch-all proxy at /api/* forwards browser requests here while -# injecting payment-signature from a httpOnly cookie. Do NOT prefix this -# with NEXT_PUBLIC_ — server-side only. +# injecting the x402 access token from a httpOnly cookie into the run +# body at config.configurable.payment_token. Do NOT prefix this with +# NEXT_PUBLIC_ — server-side only. LANGGRAPH_API_URL=http://127.0.0.1:2024 # --------------------------------------------------------------------------- @@ -51,7 +52,7 @@ LANGGRAPH_API_URL=http://127.0.0.1:2024 # --------------------------------------------------------------------------- # Tell the LangGraph SDK to talk to our local proxy at /api, NOT directly -# to the agent. The proxy is what injects payment-signature. +# to the agent. The proxy is what injects config.configurable.payment_token. NEXT_PUBLIC_API_URL=http://localhost:3000/api # Graph / assistant id served by the agent. Defaults to "research" in diff --git a/langchain-chat-ui-nvm/src/app/api/x402/token/route.ts b/langchain-chat-ui-nvm/src/app/api/x402/token/route.ts index 9e4eb7a8..0868d4bc 100644 --- a/langchain-chat-ui-nvm/src/app/api/x402/token/route.ts +++ b/langchain-chat-ui-nvm/src/app/api/x402/token/route.ts @@ -6,15 +6,16 @@ * The delegation was just created by the user in the white-label popup; * its UUID arrived via `postMessage` on the chat surface. * - * `planId`, `scheme`, and `network` all come from the **agent's 402 - * envelope** (fetched server-side by `/api/x402/probe`), never from - * server-side env guesswork. The crypto vs card-delegation scheme - * mismatch is the kind of footgun the envelope is for — trust it. + * `planId`, `scheme`, and `network` come from `/api/x402/init`, which + * resolves them server-side from plan metadata via the SDK rather than + * from env guesswork. The agent gates inside its tool, so there is no + * 402 envelope to discover them from; the crypto vs card-delegation + * scheme mismatch is the footgun that resolution exists to avoid. * * The minted token is set on a **httpOnly** cookie. The browser never - * sees the raw token — the catch-all proxy reads the cookie and forwards - * it as a `payment-signature` header on outgoing LangGraph requests. - * NVM_API_KEY stays server-side. + * sees the raw token — the catch-all proxy reads the cookie and injects + * it into the run body at `config.configurable.payment_token`, which is + * what the agent's tool reads. NVM_API_KEY stays server-side. */ import { NextRequest, NextResponse } from "next/server"; diff --git a/langchain-chat-ui-nvm/src/components/thread/payment-banner.tsx b/langchain-chat-ui-nvm/src/components/thread/payment-banner.tsx index 88cbdd68..2e92dec6 100644 --- a/langchain-chat-ui-nvm/src/components/thread/payment-banner.tsx +++ b/langchain-chat-ui-nvm/src/components/thread/payment-banner.tsx @@ -7,8 +7,8 @@ * - **Unauthorized** — no token cookie yet. The "Authorize" button opens * the white-label popup; on success the banner flips to authorized. * - **Authorized** — token cookie present, the proxy will inject - * `payment-signature` on outgoing requests until the on-chain budget - * runs out. A "Reset" link clears the cookie so the user can swap + * `config.configurable.payment_token` into outgoing runs until the + * on-chain budget runs out. A "Reset" link clears the cookie so the user can swap * delegations without restarting the server. * * For the MVP we render this preemptively (so the user knows what to do diff --git a/langchain-research-agent-py/.env.example b/langchain-research-agent-py/.env.example index db866f6a..deede1ed 100644 --- a/langchain-research-agent-py/.env.example +++ b/langchain-research-agent-py/.env.example @@ -7,7 +7,9 @@ NVM_ENVIRONMENT=sandbox # https://nevermined.app; the same account plays both seller and buyer in # this demo. NVM_PLAN_ID=your-plan-id -NVM_CREDITS_PER_RESEARCH=1 +# Note: the per-call credit price is NOT set here — the agent reads it +# from the plan's own `registry.credits.maxAmount` at import time, so the +# charge always matches what the plan advertises. # Optional: the agent id this plan is associated with on Nevermined. When # set, surfaces on the x402 envelope's `extra.agentId` so buyers can # inspect what they're paying for. Leave blank to omit. From 3890b139c208dee95a073c5ca8e541aa81e65f79 Mon Sep 17 00:00:00 2001 From: Rodolphe Marques Date: Tue, 1 Sep 2026 13:58:57 +0200 Subject: [PATCH 3/4] fix(langchain-research-agent-py): move off two deprecated payments-py APIs MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Bumps payments-py 1.9.0 -> 1.16.1 and updates the two call shapes that now emit FutureWarnings: - `PaymentOptions(environment=...)` — the environment is derived from the API-key prefix (`sandbox:` / `live:`) since 1.16, so passing it is redundant. NVM_ENVIRONMENT drops out of .env.example with it. - Inline "create-on-the-fly" delegation: passing `spending_limit_cents` / `provider_payment_method_id` straight to `get_x402_access_token` is deprecated. The buyer now creates the delegation first and references it by id, matching the new deep-agent tutorial. Verified on 1.16.1 with FutureWarning promoted to an error: token mint, verify -> tool body -> settle, 5 credits redeemed, no warnings raised. The LLM-driven end-to-end could not be re-run — the OpenAI account is out of credits (429 insufficient_quota), which is unrelated to this change; the analyst was stubbed to exercise the payment path. Also documents the LangChain tutorial family in CLAUDE.md, including the deep agent's separate-virtualenv requirement, the `langgraph dev` silent port-fallback trap, and the tutorials still carrying these deprecated call shapes (http-simple-agent-py, weather-mcp-py, pricing-simulation-py, http-simple-agent-ts). --- CLAUDE.md | 35 ++++++++++++++++++++++ langchain-research-agent-py/.env.example | 3 +- langchain-research-agent-py/poetry.lock | 10 +++---- langchain-research-agent-py/pyproject.toml | 2 +- langchain-research-agent-py/src/agent.py | 8 ++--- langchain-research-agent-py/src/buyer.py | 35 +++++++++++++++------- 6 files changed, 72 insertions(+), 21 deletions(-) diff --git a/CLAUDE.md b/CLAUDE.md index 0d1df953..181d0927 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -95,6 +95,41 @@ app.use(paymentMiddleware(payments, { - **Test both agent and client** - Ensure the full payment flow works - **Check subdirectory CLAUDE.md files** - Some tutorials have specific instructions +## LangChain tutorial family + +Four tutorials share one payment contract — the buyer puts an x402 access token at +`config.configurable.payment_token` on the run, and the agent's tool reads it: + +| Tutorial | Harness | Gating | +|---|---|---| +| `langchain-paid-agent-py` | `create_react_agent` | in-tool, minimal | +| `langchain-research-agent-py` | `create_react_agent` | in-tool, freemium | +| `langchain-deep-agent-py` | `create_deep_agent` | in-tool, **inside a subagent** | +| `langchain-langsmith-deployment-py` | — | route-level ASGI middleware | + +`langchain-chat-ui-nvm` (Next.js) is the browser buyer for any of them; its proxy +injects the token into the run body, so pointing it at a different agent is a +`LANGGRAPH_API_URL` + `NEXT_PUBLIC_ASSISTANT_ID` change only. + +**Gotchas:** + +- **`langchain-deep-agent-py` needs its own virtualenv.** `deepagents` requires the + LangChain v1 stack (`langchain-core>=1.6.1`); `langchain-research-agent-py` + resolves `langchain-core 1.4` with `langchain-openai 0.3`. They cannot share one. +- **Only run one agent on port 2024 at a time.** `langgraph dev` does **not** fail + when the port is taken — it prints a warning and silently binds a random port, + after which the buyer 422s with "Invalid assistant". Check the startup banner's + `API:` line, not just "Application started up". +- **Two payments-py call shapes are deprecated since 1.16** and still present in the + non-LangChain tutorials (`http-simple-agent-py`, `mcp-examples/weather-mcp-py`, + `pricing-simulation-py`, `http-simple-agent-ts`): + - `PaymentOptions(environment=...)` — now derived from the API-key prefix. + - passing `spending_limit_cents` / `provider_payment_method_id` straight to + `get_x402_access_token` — create the delegation first, then pass + `DelegationConfig(delegation_id=...)`. +- The per-call credit price is **not** an env var in the research/deep tutorials — + it is read from the plan's `registry.credits.maxAmount` at import time. + ## Subdirectory CLAUDE.md Files The following tutorials have their own CLAUDE.md with specific instructions: diff --git a/langchain-research-agent-py/.env.example b/langchain-research-agent-py/.env.example index deede1ed..703c34cd 100644 --- a/langchain-research-agent-py/.env.example +++ b/langchain-research-agent-py/.env.example @@ -1,6 +1,7 @@ # --- Nevermined credentials (sandbox) --------------------------------------- +# Since payments-py 1.16 the environment is derived from the API-key prefix +# (`sandbox:` / `live:`), so there is no NVM_ENVIRONMENT here. NVM_API_KEY=your-nevermined-api-key -NVM_ENVIRONMENT=sandbox # --- Plan that gates the `market_research` tool ----------------------------- # Your Nevermined plan id. Create and subscribe to a plan at diff --git a/langchain-research-agent-py/poetry.lock b/langchain-research-agent-py/poetry.lock index a8db01fe..c5607546 100644 --- a/langchain-research-agent-py/poetry.lock +++ b/langchain-research-agent-py/poetry.lock @@ -2734,14 +2734,14 @@ re2 = ["google-re2 (>=1.1)"] [[package]] name = "payments-py" -version = "1.9.0" +version = "1.16.1" description = "" optional = false python-versions = "<4.0,>=3.10" groups = ["main"] files = [ - {file = "payments_py-1.9.0-py3-none-any.whl", hash = "sha256:3a2aaba9e33996ebed65ba2aa5545ef58f8b0854040fa7df4f3ef5f2b17b88d2"}, - {file = "payments_py-1.9.0.tar.gz", hash = "sha256:8932f5aed3bc18c0f97a5bef49ce9eaba22be489d9b86a23003684ebbc7cb740"}, + {file = "payments_py-1.16.1-py3-none-any.whl", hash = "sha256:a0ce39efaf480a0eaffee8f0f9d5d79570004596fdda587ed759ba8d3710a646"}, + {file = "payments_py-1.16.1.tar.gz", hash = "sha256:026df30f95b3bc4909d275486720a82bf8a4582d1d4d86d89525244e4e6d3f89"}, ] [package.dependencies] @@ -2766,7 +2766,7 @@ starlette = {version = ">=0.49.1,<0.50.0", optional = true, markers = "extra == websocket-client = ">=1.8.0,<2.0.0" [package.extras] -fastapi = ["fastapi (>=0.120.0,<0.121.0)", "starlette (>=0.49.1,<0.50.0)"] +fastapi = ["fastapi (>=0.120.0,<0.121.0)", "starlette (>=0.49.1,<0.50.0)", "uvicorn (>=0.31.1,<0.32.0)"] langchain = ["langchain-core (>=0.3.0)"] langsmith = ["fastapi (>=0.120.0,<0.121.0)", "langsmith (>=0.1.40,<1.0.0)", "starlette (>=0.49.1,<0.50.0)"] strands = ["strands-agents (>=1.0.0)"] @@ -4996,4 +4996,4 @@ cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and pyt [metadata] lock-version = "2.1" python-versions = ">=3.11,<4.0" -content-hash = "bf4721f0f7dfc9b93d7a17f114352e1bfd4c4fdc61711616b548b51e5bd27502" +content-hash = "7851ffe5df711c3cae8af127338e36159550b04d8d9a789c14845ff00c743aea" diff --git a/langchain-research-agent-py/pyproject.toml b/langchain-research-agent-py/pyproject.toml index e947a22e..a4295792 100644 --- a/langchain-research-agent-py/pyproject.toml +++ b/langchain-research-agent-py/pyproject.toml @@ -16,7 +16,7 @@ httpx = "^0.28" # `[langsmith]` extra brings in fastapi/starlette — required transitively by # `payments_py.x402.langchain.requires_payment` (which imports the langsmith # spans module; the SDK package __init__ eagerly loads the middleware). -payments-py = {version = "^1.9.0", extras = ["langsmith"]} +payments-py = {version = "^1.16.1", extras = ["langsmith"]} [tool.poetry.group.dev.dependencies] langgraph-cli = {extras = ["inmem"], version = "*"} diff --git a/langchain-research-agent-py/src/agent.py b/langchain-research-agent-py/src/agent.py index a72c8414..5cc47ffe 100644 --- a/langchain-research-agent-py/src/agent.py +++ b/langchain-research-agent-py/src/agent.py @@ -46,7 +46,6 @@ load_dotenv() NVM_API_KEY = os.environ["NVM_API_KEY"] -NVM_ENVIRONMENT = os.environ.get("NVM_ENVIRONMENT", "sandbox") NVM_PLAN_ID = os.environ["NVM_PLAN_ID"] NVM_AGENT_ID = os.environ.get("NVM_AGENT_ID") or None @@ -54,9 +53,10 @@ logger = logging.getLogger(__name__) -_payments = Payments.get_instance( - PaymentOptions(nvm_api_key=NVM_API_KEY, environment=NVM_ENVIRONMENT) -) +# `environment` is intentionally omitted: since payments-py 1.16 it is +# derived from the API-key prefix (`sandbox:` / `live:`) and passing it +# emits a FutureWarning. +_payments = Payments.get_instance(PaymentOptions(nvm_api_key=NVM_API_KEY)) def _resolve_plan_price() -> int: diff --git a/langchain-research-agent-py/src/buyer.py b/langchain-research-agent-py/src/buyer.py index 8769317c..d90c7e9f 100644 --- a/langchain-research-agent-py/src/buyer.py +++ b/langchain-research-agent-py/src/buyer.py @@ -25,13 +25,16 @@ from dotenv import load_dotenv from payments_py import PaymentOptions, Payments from payments_py.x402.resolve_scheme import resolve_network, resolve_scheme -from payments_py.x402.types import DelegationConfig, X402TokenOptions +from payments_py.x402.types import ( + CreateDelegationPayload, + DelegationConfig, + X402TokenOptions, +) load_dotenv() DEPLOYMENT_URL = os.environ.get("LANGSMITH_DEPLOYMENT_URL", "http://127.0.0.1:2024") NVM_API_KEY = os.environ["NVM_API_KEY"] -NVM_ENVIRONMENT = os.environ.get("NVM_ENVIRONMENT", "sandbox") NVM_PLAN_ID = os.environ["NVM_PLAN_ID"] ASSISTANT_ID = os.environ.get("ASSISTANT_ID", "research") RESEARCH_TOPIC = os.environ.get("INPUT", "Research the electric vehicle market") @@ -129,9 +132,8 @@ async def _run( async def main() -> None: print(f"Connecting to LangSmith Deployment at {DEPLOYMENT_URL}\n") - payments = Payments.get_instance( - PaymentOptions(nvm_api_key=NVM_API_KEY, environment=NVM_ENVIRONMENT) - ) + # `environment` is derived from the API-key prefix since payments-py 1.16. + payments = Payments.get_instance(PaymentOptions(nvm_api_key=NVM_API_KEY)) async with httpx.AsyncClient(base_url=DEPLOYMENT_URL, timeout=120.0) as client: # --- Free path ------------------------------------------------------- @@ -153,16 +155,29 @@ async def main() -> None: return print(f" Using payment method: {pm.brand} *{pm.last4}\n") - print("[3/4] Acquiring x402 access token from the plan...") + # Two steps, on purpose. Passing spending limits / a payment method + # straight to `get_x402_access_token` (inline "create-on-the-fly" + # delegation) is deprecated and emits a FutureWarning: create the + # delegation first, then reference it by id. + print("[3/4] Creating a spending delegation...") + delegation = payments.delegation.create_delegation( + CreateDelegationPayload( + provider=network, + provider_payment_method_id=pm.id, + spending_limit_cents=10000, + duration_secs=3600, + currency="usd", + ) + ) + print(f" delegation = {delegation.delegation_id}") + + print(" Acquiring x402 access token from the plan...") token_result = payments.x402.get_x402_access_token( NVM_PLAN_ID, token_options=X402TokenOptions( scheme=scheme, delegation_config=DelegationConfig( - provider_payment_method_id=pm.id, - spending_limit_cents=10000, - duration_secs=3600, - currency="usd", + delegation_id=delegation.delegation_id ), ), ) From a80db4e0014845b15b6bdf6e60509e87fbbdc635 Mon Sep 17 00:00:00 2001 From: Rodolphe Marques Date: Tue, 1 Sep 2026 14:22:10 +0200 Subject: [PATCH 4/4] fix(langchain-deep-agent-py): make the paid-call cap actually per-run MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Addresses aaitor's should-fix on #61. He was right, and it is worse than "may": there is no run id anywhere in a tool's config. Probing the real graph (langgraph 1.2 / deepagents 0.7) with a scripted model, a tool sees only `thread_id`, checkpoint bookkeeping, and what the caller passed — two runs on one thread produced the identical budget key. So the cap was per-CONVERSATION, permanently: after 3 paid calls the tool returned BUDGET_EXHAUSTED forever while its own message told the user to "ask a follow-up question to start a new run", which could not reset it. `_counts` also grew unbounded in a long-running server. Since the caller is the only party that knows where one run ends, the buyer now sends a fresh `nvm_run_id` in `configurable` alongside the token, and the budget keys on it. Without one the agent still caps, but reports the honest scope — a separate notice saying the limit applies to the conversation and naming the key that would make it per-run. The map is now an LRU bounded at 1024 keys, and a refund drops the key rather than leaving a 0. Verified against the real graph, no LLM and no charges: the cap resets across three runs on one thread with a nonce; falls back to thread scope without one and says so; stays bounded past the eviction threshold; refund grants exactly one more call; and unpaid PAYMENT_REQUIRED attempts never consume budget. I considered InjectedState instead — it does work in a deepagents subagent tool, but it exposes the SUBAGENT's own isolated conversation, which resets on every task() hop, so it cannot see sibling delegations within one turn. That is exactly the case this cap exists for. --- langchain-deep-agent-py/.env.example | 8 ++- langchain-deep-agent-py/README.md | 12 +++- langchain-deep-agent-py/src/agent.py | 102 +++++++++++++++++++++------ langchain-deep-agent-py/src/buyer.py | 14 +++- 4 files changed, 112 insertions(+), 24 deletions(-) diff --git a/langchain-deep-agent-py/.env.example b/langchain-deep-agent-py/.env.example index 0f0ffe36..ae34fd77 100644 --- a/langchain-deep-agent-py/.env.example +++ b/langchain-deep-agent-py/.env.example @@ -19,7 +19,13 @@ NVM_AGENT_ID= # A deep agent chooses for itself how many subagent hops a request needs, # and every hop that reaches `market_research` settles credits. This caps -# the paid calls per run so one message cannot bill without bound. +# the paid calls so one message cannot bill without bound. +# +# Scope depends on the caller: the cap is per-RUN when the caller sends a +# fresh `nvm_run_id` in config.configurable (src/buyer.py does), and +# per-CONVERSATION otherwise, because LangGraph exposes no run id to a +# tool and `thread_id` is all that is left. The agent says which one is +# in force when the budget runs out. NVM_MAX_PAID_CALLS_PER_RUN=3 # --- LLM -------------------------------------------------------------------- diff --git a/langchain-deep-agent-py/README.md b/langchain-deep-agent-py/README.md index f5396daf..820f8f01 100644 --- a/langchain-deep-agent-py/README.md +++ b/langchain-deep-agent-py/README.md @@ -40,7 +40,17 @@ These are properties of the harness, not bugs, and both are worth designing arou NVM_MAX_PAID_CALLS_PER_RUN=3 # in .env ``` -The cap is keyed by run, and an attempt that returns `PAYMENT_REQUIRED` is refunded — a user who authorizes mid-run still gets the calls they paid for. +**The caller has to say where a run begins.** LangGraph does *not* put a run id in `config.configurable` — verified against langgraph 1.2 / deepagents 0.7, where a tool sees only `thread_id`, checkpoint bookkeeping, and whatever the caller passed. `thread_id` is stable for a whole conversation, so keying a "per-run" cap on it silently makes it per-*conversation*: after N paid calls the tool refuses forever, however many new questions you ask. + +So `src/buyer.py` sends a fresh `nvm_run_id` alongside the token: + +```python +"config": {"configurable": {"payment_token": token, "nvm_run_id": str(uuid.uuid4())}} +``` + +Without it the agent still works and still caps — it just reports the honest scope (`"This conversation already performed N paid research call(s)"`) instead of claiming a new request will reset the count. An attempt that returns `PAYMENT_REQUIRED` is refunded, so a user who authorizes mid-run keeps the calls they paid for, and the counter map evicts least-recently-used keys so a long-running server does not grow without bound. + +The browser chat UI does not send `nvm_run_id` — its proxy injects only the token — so against the chat UI the cap is per conversation. That is the safe direction to fail: it under-spends, never over-spends. **2. Two LLM layers can paraphrase the tool's output.** The subagent relays to the supervisor, which relays to the user. Both are instructed to pass text through verbatim; neither is guaranteed to. The plain ReAct sibling has one such layer, so this is strictly worse here. Treat the tool's return value as the source of truth — `src/buyer.py` prints the raw `ToolMessage`, not the chat reply, for exactly this reason. diff --git a/langchain-deep-agent-py/src/agent.py b/langchain-deep-agent-py/src/agent.py index 37573060..f9d2c402 100644 --- a/langchain-deep-agent-py/src/agent.py +++ b/langchain-deep-agent-py/src/agent.py @@ -35,6 +35,7 @@ import logging import os import threading +from collections import OrderedDict from deepagents import create_deep_agent from dotenv import load_dotenv @@ -101,50 +102,104 @@ def _resolve_plan_price() -> int: "Please authorize and ask again." ) -_BUDGET_EXHAUSTED_NOTICE = ( +# The buyer's per-run nonce. LangGraph does **not** put a run id in +# `config["configurable"]` — verified against langgraph 1.2 / deepagents +# 0.7, where a tool sees only `thread_id`, checkpoint bookkeeping, and +# whatever the caller put there. So a genuinely per-run cap needs the +# caller to say which run this is; `src/buyer.py` sends a fresh value on +# every run, exactly as it sends `payment_token`. +RUN_ID_KEY = "nvm_run_id" + +# Bound on distinct budget keys held in memory. The agent is a +# long-running server, so without eviction the counter map grows for the +# life of the process — one entry per run (or per conversation), forever. +_MAX_TRACKED_KEYS = 1024 + +_BUDGET_EXHAUSTED_PER_RUN = ( "BUDGET_EXHAUSTED: This run already performed {limit} paid research " - "call(s), the per-run cap. Returning without charging again. Ask a " - "follow-up question to start a new run, or raise " - "NVM_MAX_PAID_CALLS_PER_RUN." + "call(s), the per-run cap. Returning without charging again. Send a new " + "request to get a fresh allowance, or raise NVM_MAX_PAID_CALLS_PER_RUN." +) + +# Different text on purpose: when the caller does not supply a run id the +# budget is per CONVERSATION, and telling the user to "ask a follow-up" +# would be a lie — a follow-up on the same thread reuses the same counter. +_BUDGET_EXHAUSTED_PER_THREAD = ( + "BUDGET_EXHAUSTED: This conversation already performed {limit} paid " + "research call(s). The caller did not supply a `{run_id_key}` in " + "`config.configurable`, so the cap applies to the whole conversation " + "rather than to one request. Start a new conversation, pass a per-run " + "`{run_id_key}`, or raise NVM_MAX_PAID_CALLS_PER_RUN." ) class _RunBudget: - """Counts paid calls per run so one turn cannot bill without bound. + """Caps paid calls so one request cannot bill without bound. Deep agents may fan out to several subagent calls for a single user - message. The counter is keyed by the LangGraph thread/run so - concurrent runs in the same process do not share a budget. + message, and each one that reaches the paid tool settles credits. + + **Scope depends on what the caller supplies.** Keyed on + ``configurable[RUN_ID_KEY]`` when present — that is a true per-run + cap. Absent it, the only stable identity a tool can see is + ``thread_id``, which persists across every run on that thread, so the + cap becomes per-conversation. That is a safe direction to fail (it + under-spends, never over-spends) but it is a different promise, so + ``scope_of`` reports which one is in force and the caller is told + plainly in the exhausted notice. + + Counting in this process rather than in graph state is deliberate: a + subagent's ``InjectedState`` is its own isolated conversation, reset + on every ``task()`` hop, so it cannot see sibling delegations within + the same turn — which is precisely what this cap is for. """ def __init__(self) -> None: self._lock = threading.Lock() - self._counts: dict[str, int] = {} + self._counts: OrderedDict[str, int] = OrderedDict() @staticmethod - def _key(config: RunnableConfig | None) -> str: + def key_and_scope(config: RunnableConfig | None) -> tuple[str, str]: + """Return the budget key and whether it scopes a run or a thread.""" configurable = (config or {}).get("configurable") or {} - return str( - configurable.get("run_id") - or configurable.get("thread_id") - or "default" - ) + run_id = configurable.get(RUN_ID_KEY) + if run_id: + return str(run_id), "run" + thread_id = configurable.get("thread_id") + if thread_id: + return str(thread_id), "thread" + return "default", "thread" + + def scope_of(self, config: RunnableConfig | None) -> str: + return self.key_and_scope(config)[1] def try_consume(self, config: RunnableConfig | None) -> bool: - """Reserve one paid call. False when the run is already at its cap.""" - key = self._key(config) + """Reserve one paid call. False when the budget is already spent.""" + key, _ = self.key_and_scope(config) with self._lock: used = self._counts.get(key, 0) if used >= MAX_PAID_CALLS_PER_RUN: + self._counts.move_to_end(key) return False self._counts[key] = used + 1 + self._counts.move_to_end(key) + while len(self._counts) > _MAX_TRACKED_KEYS: + # Evict least-recently-used. Dropping a key only refills + # that budget, so the worst case is a long-idle caller + # getting a fresh allowance — never an over-charge. + self._counts.popitem(last=False) return True def refund(self, config: RunnableConfig | None) -> None: """Give the reservation back when the call did not settle.""" - key = self._key(config) + key, _ = self.key_and_scope(config) with self._lock: - self._counts[key] = max(0, self._counts.get(key, 0) - 1) + remaining = self._counts.get(key, 0) - 1 + if remaining > 0: + self._counts[key] = remaining + else: + # Back to zero: drop the key instead of storing a 0. + self._counts.pop(key, None) _budget = _RunBudget() @@ -198,8 +253,15 @@ def market_research(topic: str, config: RunnableConfig) -> str: plan_id_short = f"{NVM_PLAN_ID[:24]}..." if len(NVM_PLAN_ID) > 24 else NVM_PLAN_ID if not _budget.try_consume(config): - logger.info("per-run paid-call cap reached (%s)", MAX_PAID_CALLS_PER_RUN) - return _BUDGET_EXHAUSTED_NOTICE.format(limit=MAX_PAID_CALLS_PER_RUN) + scope = _budget.scope_of(config) + logger.info( + "paid-call cap reached (%s, scope=%s)", MAX_PAID_CALLS_PER_RUN, scope + ) + if scope == "run": + return _BUDGET_EXHAUSTED_PER_RUN.format(limit=MAX_PAID_CALLS_PER_RUN) + return _BUDGET_EXHAUSTED_PER_THREAD.format( + limit=MAX_PAID_CALLS_PER_RUN, run_id_key=RUN_ID_KEY + ) try: analysis = _market_research_paid(topic, config=config) diff --git a/langchain-deep-agent-py/src/buyer.py b/langchain-deep-agent-py/src/buyer.py index 820df621..b4ff6fbd 100644 --- a/langchain-deep-agent-py/src/buyer.py +++ b/langchain-deep-agent-py/src/buyer.py @@ -22,6 +22,7 @@ import asyncio import os import re +import uuid import httpx from dotenv import load_dotenv @@ -126,13 +127,22 @@ async def _run( contract. LangGraph propagates `configurable` into the subagent, so the paid tool sees it without the buyer knowing the agent's internal topology. + + We also send a fresh `nvm_run_id`. LangGraph does not inject a run id + into `configurable` — a tool sees only `thread_id`, which is stable + for the whole conversation — so without this the agent's paid-call cap + would apply per conversation rather than per request. The caller is + the only party that knows where one run ends and the next begins. """ + configurable: dict = {"nvm_run_id": str(uuid.uuid4())} + if payment_token: + configurable["payment_token"] = payment_token + body: dict = { "assistant_id": ASSISTANT_ID, "input": {"messages": [{"type": "human", "content": user_text}]}, + "config": {"configurable": configurable}, } - if payment_token: - body["config"] = {"configurable": {"payment_token": payment_token}} response = await client.post(f"/threads/{thread_id}/runs/wait", json=body) response.raise_for_status()