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Python SDK for the TensorFeed.ai API: AI news, status, model pricing, premium routing + history series + webhook watches, agent payments via USDC on Base (optional web3 auto-send)

Project description

tensorfeed

Python SDK for the TensorFeed.ai API.

Free endpoints (news, status, models, benchmarks, history, routing preview) need no auth. The premium tier (top-N routing, plus more endpoints landing later) is paid via USDC on Base. No accounts, no API keys, no traditional payment processors.

Install

pip install tensorfeed

Stdlib-only. No external dependencies.

Free Tier

from tensorfeed import TensorFeed

tf = TensorFeed()

# News
for article in tf.news(category="research", limit=10)["articles"]:
    print(article["title"])

# Live AI service status
for svc in tf.status()["services"]:
    print(f'{svc["name"]}: {svc["status"]}')

# Is a service down?
print(tf.is_down("claude"))

# Model pricing and benchmarks
print(tf.models())
print(tf.benchmarks())

# Daily history snapshots (the moat)
print(tf.history())  # list of available dates
print(tf.history_snapshot("2026-04-27", "pricing"))

# Free routing preview (top-1 model, 5 calls/day per IP)
preview = tf.routing_preview(task="code")
print(preview["recommendation"])

Premium Tier (paid, USDC on Base)

from tensorfeed import TensorFeed, PaymentRequired

tf = TensorFeed()

# Step 1: get a 30-minute quote
quote = tf.buy_credits(amount_usd=1.00)
print(f"Send {quote['amount_usd']} USDC on Base to {quote['wallet']}")
print(f"Memo: {quote['memo']} (expires in {quote['ttl_seconds']}s)")
print(f"Will get: {quote['credits']} credits")

# Step 2: send the USDC tx with your wallet
# (auto-send via web3 is on the roadmap; for v1.1 you sign and send manually)

# Step 3: confirm with the tx hash
result = tf.confirm(tx_hash="0xYOUR_TX_HASH", nonce=quote["memo"])
print(f"Got {result['credits']} credits, token: {result['token']}")
# The token is also stored on `tf` automatically; routing() will use it.

# Step 4: call premium endpoints
rec = tf.routing(task="code", budget=5.0, top_n=5)
for r in rec["recommendations"]:
    print(f'#{r["rank"]}: {r["model"]["name"]} (score: {r["composite_score"]:.2f})')

# Custom routing weights
rec = tf.routing(
    task="general",
    weights={"quality": 0.6, "cost": 0.3, "availability": 0.1, "latency": 0.0},
)

# Premium history series (1 credit each, range default = last 30 days, max 90)
prices = tf.pricing_series(model="Claude Opus 4.7")
print(f'Price changed {prices["summary"]["delta_pct_blended"]}% over the window')

scores = tf.benchmark_series(model="Claude Opus 4.7", benchmark="swe_bench")
print(f'SWE-bench moved {scores["summary"]["delta_pp"]} pp')

uptime = tf.status_uptime(provider="anthropic")
print(f'Anthropic uptime: {uptime["uptime_pct"]}% over {uptime["days_with_data"]} days')

diff = tf.history_compare(
    from_date="2026-04-01", to_date="2026-04-27", snapshot_type="pricing",
)
print(f'{len(diff["changed"])} price changes, {len(diff["added"])} new models')

# Premium webhook watches (1 credit per registration, free reads)
created = tf.create_watch(
    spec={
        "type": "price",
        "model": "Claude Opus 4.7",
        "field": "blended",
        "op": "lt",
        "threshold": 30,
    },
    callback_url="https://agent.example.com/hook",
    secret="any-shared-secret",  # used to sign deliveries
)
watch_id = created["watch"]["id"]
print(f"Watch {watch_id} active until {created['watch']['expires_at']}")

# When a delivery arrives, verify it:
#   sig = request.headers["X-TensorFeed-Signature"]  # "sha256=<hex>"
#   import hmac, hashlib
#   expected = "sha256=" + hmac.new(b"any-shared-secret", body, hashlib.sha256).hexdigest()
#   assert hmac.compare_digest(sig, expected)

print(tf.list_watches())          # see all your active watches
print(tf.get_watch(watch_id))     # check fire_count, last_fired_at
tf.delete_watch(watch_id)         # remove when done

# Check remaining credits
print(tf.balance())

Auto-Send (optional, web3 extra)

The base SDK keeps you dependency-free, but if you want to skip the manual tx step, install with the web3 extra:

pip install 'tensorfeed[web3]'

Then tf.purchase_credits() quotes, signs, broadcasts, and confirms in one call:

import os
from tensorfeed import TensorFeed

tf = TensorFeed()

result = tf.purchase_credits(
    amount_usd=1.00,
    private_key=os.environ["TENSORFEED_PRIVATE_KEY"],  # NEVER hardcode
    # rpc_url="https://base-mainnet.g.alchemy.com/v2/<key>",  # optional
)
print(result["token"])      # auto-stored on tf
print(result["tx_hash"])    # for your records
print(result["credits"])    # how many credits were minted

# Token already on tf, so:
rec = tf.routing(task="code")

Security: read the key from a secret manager or env var. Never commit it. The raw key is held in memory only for the duration of one signing call.

Reusing a Token Across Sessions

Save the token after confirm(). Reuse it next time:

# Save once
token = result["token"]

# Reuse in another process / job
tf = TensorFeed(token=token)
print(tf.balance())
rec = tf.routing(task="code")

Error Handling

from tensorfeed import TensorFeed, PaymentRequired, RateLimited, TensorFeedError

tf = TensorFeed(token="bad_token")
try:
    tf.routing(task="code")
except PaymentRequired as e:
    # 402: token invalid, expired, or out of credits
    # e.payload contains wallet, credits required, top_up_at, etc.
    print("Need to top up:", e.payload)
except RateLimited as e:
    # 429: free preview tier hit its 5/day per-IP limit
    print("Hit the rate limit:", e.payload)
except TensorFeedError as e:
    # Other API errors
    print("API error", e.status_code, e.payload)

API Reference

Free

Method Description
tf.news(category=, limit=) Latest AI news articles
tf.status() Real-time AI service status
tf.status_summary() Lightweight status summary
tf.models() Model pricing and specs
tf.benchmarks() Benchmark scores
tf.is_down(service_name) Check if a specific service is down
tf.agent_activity() Agent traffic metrics
tf.history() List of available daily snapshot dates
tf.history_snapshot(date, type) Read a specific snapshot
tf.routing_preview(task=) Top-1 routing recommendation (5/day/IP)
tf.health() API health check
tf.payment_info() Wallet, pricing, supported payment flows
tf.buy_credits(amount_usd=) Generate a 30-min payment quote
tf.confirm(tx_hash=, nonce=) Verify USDC tx, mint credit token

Token-required

Method Cost Description
tf.balance() Free Check remaining credits
tf.usage() Free Per-token call history (last 100 calls aggregated by endpoint)
tf.routing(task=, budget=, top_n=, weights=) 1 credit Top-N ranked routing with full detail
tf.pricing_series(model=, from_date=, to_date=) 1 credit Daily price points for one model with min/max/delta summary
tf.benchmark_series(model=, benchmark=, from_date=, to_date=) 1 credit Score evolution for a benchmark on one model, returns delta_pp
tf.status_uptime(provider=, from_date=, to_date=) 1 credit Uptime % per provider with incident days (degraded = half)
tf.history_compare(from_date=, to_date=, snapshot_type=) 1 credit Diff two snapshots: added, removed, changed entries with deltas
tf.create_watch(spec=, callback_url=, secret=, fire_cap=) 1 credit Register a webhook watch (price / status / digest)
tf.create_digest_watch(cadence=, callback_url=, secret=, fire_cap=) 1 credit Convenience: scheduled daily/weekly digest of pricing changes
tf.list_watches() Free List all active watches owned by the current token
tf.get_watch(watch_id) Free Read one watch including fire_count and last_fired_at
tf.delete_watch(watch_id) Free Remove an owned watch
tf.premium_agents_directory(category=, status=, sort=, limit=, ...) 1 credit Enriched directory: status, news, traffic, pricing, trending_score per agent
tf.news_search(q=, from_date=, to_date=, provider=, category=, limit=) 1 credit Full-text news search with date/provider filters, relevance scoring, recency boost
tf.cost_projection(models=, input_tokens_per_day=, output_tokens_per_day=, horizon=) 1 credit Project workload cost across 1-10 models, 4 horizons, cheapest-monthly ranking
tf.forecast(target=, model=, field=, benchmark=, lookback=, horizon=) 1 credit Linear-regression forecast for a price or benchmark series with 95% CI and confidence label
tf.provider_deepdive(provider) 1 credit One provider's full profile: status + all models + benchmarks joined + news + traffic
tf.compare_models(ids=) 1 credit Side-by-side compare of 2-5 models with normalized benchmarks + rankings
tf.whats_new(days=, news_limit=) 1 credit Agent morning brief: pricing changes + incidents + top news from last 1-7 days

Auto-send (requires tensorfeed[web3])

Method Description
tf.purchase_credits(amount_usd=, private_key=, rpc_url=) One-call quote + sign + broadcast + confirm. Returns token, credits, tx_hash, block_number.

Wallet & Trust

The TensorFeed payment wallet is 0x549c82e6bfc54bdae9a2073744cbc2af5d1fc6d1 on Base mainnet. USDC contract: 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913.

Cross-check this address before sending funds at:

If any source disagrees, do not send.

Premium Data Terms

Premium API responses are licensed for inference use only. Use of TensorFeed premium data for training, fine-tuning, evaluation, or distillation of ML models is prohibited (Section 17.1 of the Terms).

No refunds; credits do not expire

All credit purchases are final and non-refundable per Section 17.5 of the Terms. Credits never expire and are jointly redeemable on tensorfeed.ai and terminalfeed.io. The recommended pattern is to buy in small increments (for example, $1 USDC for 50 credits) until call volume is calibrated, then top up as needed.

Sanctions

Premium API access is unavailable to persons or entities subject to OFAC, EU, UK, or UN sanctions, and to residents of comprehensively sanctioned jurisdictions (Cuba, Iran, North Korea, Syria, Crimea, Donetsk, Luhansk). Inbound credit-purchase transactions are screened against the Chainalysis public sanctions API. See Section 17.9 of the Terms.

Links

License

MIT

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