BazaarLinkドキュメント

https://bazaarlink.ai/api/v1

  from openai import OpenAI

  client = OpenAI(
-     base_url="https://openrouter.ai/api/v1",
-     api_key="sk-or-...",
+     base_url="https://bazaarlink.ai/api/v1",
+     api_key="sk-bl-...",
  )

Authorization: Bearer sk-bl-YOUR_API_KEY

# Image — URL or base64 data URI
curl https://bazaarlink.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $BAZAARLINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"google/gemini-2.5-flash","messages":[{"role":"user","content":[
        {"type":"text","text":"What is in this?"},
        {"type":"image_url","image_url":{"url":"https://example.com/photo.jpg"}}
      ]}]}'

# File / PDF — base64 data URI only, no URL
curl https://bazaarlink.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $BAZAARLINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"google/gemini-2.5-flash","messages":[{"role":"user","content":[
        {"type":"file","file":{"filename":"doc.pdf","file_data":"data:application/pdf;base64,JVBER..."}},
        {"type":"text","text":"Summarize this."}
      ]}]}'

# Audio — raw base64, no URL. "format" is required
curl https://bazaarlink.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $BAZAARLINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"google/gemini-2.5-flash","messages":[{"role":"user","content":[
        {"type":"text","text":"Transcribe this."},
        {"type":"input_audio","input_audio":{"data":"UklGRi...","format":"wav"}}
      ]}]}'

# Video — URL (CDN) or base64 data URI
curl https://bazaarlink.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $BAZAARLINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"google/gemini-2.5-flash","messages":[{"role":"user","content":[
        {"type":"text","text":"Describe this video."},
        {"type":"video_url","video_url":{"url":"https://example.com/clip.mp4"}}
      ]}]}'

X-RateLimit-Limit: 200        # Max requests per minute for your tier
X-RateLimit-Remaining: 198    # Remaining requests in current window
X-RateLimit-Reset: 1740000060 # Unix timestamp when the window resets
X-Request-Id: chatcmpl-abc123 # Unique request ID for debugging

curl -N https://bazaarlink.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $BAZAARLINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"openai/gpt-5.4-image-2","messages":[{"role":"user","content":"a red cat on a sofa"}],"modalities":["image","text"],"stream":true}'

curl https://bazaarlink.ai/api/v1/videos \
  -H "Authorization: Bearer $BAZAARLINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"alibaba/wan2.7-t2v","prompt":"a bird flying over mountains","duration":3}'
# → 202 { "id": "vjob_xxx", "status": "pending" }

import base64

with open("document.pdf", "rb") as f:
    pdf_data = base64.b64encode(f.read()).decode()

response = client.chat.completions.create(
    model="anthropic/claude-sonnet-4.6",
    messages=[{
        "role": "user",
        "content": [
            {
                "type": "file",
                "file": {
                    "filename": "document.pdf",
                    "file_data": f"data:application/pdf;base64,{pdf_data}",
                },
            },
            {"type": "text", "text": "Summarize this document."},
        ],
    }],
)

response = client.chat.completions.create(
    model="google/gemini-2.5-flash",
    messages=[{
        "role": "user",
        "content": [
            {
                "type": "video_url",
                "video_url": {"url": "https://example.com/video.mp4"},
            },
            {"type": "text", "text": "What is happening in this video?"},
        ],
    }],
)

GET https://bazaarlink.ai/api/v1/keys
Authorization: Bearer sk-bl-YOUR_MGMT_KEY

# Response
{
  "keys": [
    {
      "id": "clxyz123...",
      "name": "Production Key",
      "keyType": "standard",
      "keyPrefix": "sk-bl-abc1",
      "keySuffix": "XyZ9",
      "enabled": true,
      "spendLimitUsd": 10.00,
      "spendLimitPeriod": "month",
      "expiresAt": null,
      "createdAt": "2026-01-01T00:00:00.000Z",
      "lastUsed": "2026-03-01T12:34:56.000Z",
      "requestCount": 1234,
      "totalTokens": 5678901
    }
  ]
}

POST https://bazaarlink.ai/api/v1/keys
Authorization: Bearer sk-bl-YOUR_MGMT_KEY
Content-Type: application/json

{
  "name": "Agent Key",
  "limit": 10.00,
  "limit_reset": "monthly",
  "expires_at": "2026-12-31T23:59:59Z"
}

# limit_reset: daily | weekly | monthly
# expires_at:  ISO 8601 datetime (optional)

# Response — save the key value, it won't be shown again
{
  "id": "clxyz789...",
  "name": "Agent Key",
  "key": "sk-bl-xyz789abcdef...",
  "keyType": "standard",
  "spendLimitUsd": 10.00,
  "spendLimitPeriod": "month",
  "expiresAt": "2026-12-31T23:59:59.000Z",
  "enabled": true,
  "createdAt": "2026-03-01T00:00:00.000Z"
}

PATCH https://bazaarlink.ai/api/v1/keys/:id
Authorization: Bearer sk-bl-YOUR_MGMT_KEY
Content-Type: application/json

{"enabled": false}              # disable key
{"spendLimitUsd": 5, "spendLimitPeriod": "week"}  # set spend limit
{"spendLimitUsd": null}         # remove spend limit
# Response: {"updated": true}

DELETE https://bazaarlink.ai/api/v1/keys/:id
Authorization: Bearer sk-bl-YOUR_MGMT_KEY

# Returns 204 No Content on success

GET https://bazaarlink.ai/api/v1/credits
Authorization: Bearer sk-bl-YOUR_MGMT_KEY

# Response
{
  "data": {
    "total_credits": 12.345,
    "total_usage": 3.210
  }
}

GET https://bazaarlink.ai/api/v1/usage?period=month
Authorization: Bearer sk-bl-YOUR_MGMT_KEY

# period: day | week | month | year

from openai import OpenAI

client = OpenAI(
    base_url="https://bazaarlink.ai/api/v1",
    api_key="sk-bl-YOUR_KEY",
    default_headers={
        "HTTP-Referer": "https://yourapp.com",  # Optional: your site URL
        "X-Title": "My Application",             # Optional: your app name
    },
)

response = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
)

{
  "error": {
    "message": "Insufficient credits. Please top up to continue.",
    "type": "invalid_request_error",
    "code": "insufficient_credits"
  }
}

// If the stream fails mid-flight, BazaarLink emits a final SSE event
// with a top-level "error" object, followed by data: [DONE]
data: {"error":{"message":"Upstream stream interrupted. The response is incomplete.","type":"upstream_error","code":502}}

data: [DONE]

// Chunks relayed verbatim from some upstreams may instead carry the error
// inline on the choice: choices[0].finish_reason === "error" with an
// "error" object ({ code, message }) on the choice — handle both shapes.
// Branch on error.code; error.type can vary by failure path.

# Model may return multiple tool_calls
if message.tool_calls:
    messages = [
        {"role": "user", "content": "Weather and time in Tokyo?"},
        message,
    ]

    for tool_call in message.tool_calls:
        # Execute each function
        if tool_call.function.name == "get_weather":
            result = {"temperature": 22, "condition": "Clear"}
        elif tool_call.function.name == "get_time":
            result = {"time": "2026-02-23T15:30:00+09:00"}

        messages.append({
            "role": "tool",
            "tool_call_id": tool_call.id,
            "content": json.dumps(result),
        })

    # Send all results back at once
    final = client.chat.completions.create(
        model="openai/gpt-4.1",
        messages=messages,
        tools=tools,
    )
    print(final.choices[0].message.content)

# Streaming: tool_calls arrive as partial deltas indexed by position —
# accumulate function.arguments per index until finish_reason == "tool_calls".
stream = client.chat.completions.create(
    model="openai/gpt-4.1",
    messages=[{"role": "user", "content": "What's the weather in Taipei?"}],
    tools=tools,
    tool_choice="auto",
    stream=True,
)

tool_calls = {}
for chunk in stream:
    delta = chunk.choices[0].delta
    if delta.tool_calls:
        for tc in delta.tool_calls:
            entry = tool_calls.setdefault(tc.index, {"id": "", "name": "", "arguments": ""})
            if tc.id:
                entry["id"] = tc.id
            if tc.function.name:
                entry["name"] = tc.function.name
            if tc.function.arguments:
                entry["arguments"] += tc.function.arguments
    if chunk.choices[0].finish_reason == "tool_calls":
        for call in tool_calls.values():
            print(call["name"], json.loads(call["arguments"]))

# Generic loop: keep calling the model while it keeps requesting tools,
# stop once it returns a plain answer. max_iterations guards against loops.
messages = [{"role": "user", "content": "What's the weather in Taipei, and what time is it there?"}]
max_iterations = 10

for _ in range(max_iterations):
    response = client.chat.completions.create(
        model="openai/gpt-4.1",
        messages=messages,
        tools=tools,
    )
    message = response.choices[0].message
    messages.append(message)

    if not message.tool_calls:
        break  # model gave a final answer

    for tool_call in message.tool_calls:
        args = json.loads(tool_call.function.arguments)
        result = TOOL_MAPPING[tool_call.function.name](**args)
        messages.append({
            "role": "tool",
            "tool_call_id": tool_call.id,
            "content": json.dumps(result),
        })
else:
    print("Warning: max_iterations reached without a final answer")

print(messages[-1].content)

// Enable middle-out on any model
{
  "model": "openai/gpt-4.1",
  "transforms": ["middle-out"],
  "messages": [
    { "role": "system", "content": "You are a helpful assistant." },
    ... // long conversation — middle will be trimmed to fit context
  ]
}

// Disable auto-trimming for small-context models
{ "transforms": [] }

# OpenAI-family models: nothing to add, long repeated prefixes cache automatically.
response = client.chat.completions.create(
    model="openai/gpt-4.1",
    messages=[
        {"role": "system", "content": "You are an expert..."},  # cached automatically if long/repeated
        {"role": "user", "content": "Question here"},
    ],
)

# Check cache savings in the response usage
usage = response.usage
print(f"Prompt tokens: {usage.prompt_tokens}")
print(f"Cached tokens: {usage.prompt_tokens_details.cached_tokens}")
print(f"Cache savings: {usage.prompt_tokens_details.cached_tokens / usage.prompt_tokens * 100:.1f}%")

# Claude models: you must mark the block to cache yourself.
response = client.chat.completions.create(
    model="anthropic/claude-sonnet-4.6",
    messages=[
        {
            "role": "system",
            "content": [
                {"type": "text", "text": "You are an expert...", "cache_control": {"type": "ephemeral"}}
            ],
        },  # BazaarLink does not add cache_control on your behalf
        {"role": "user", "content": "Question here"},
    ],
)

usage = response.usage
print(f"Cache read tokens: {getattr(usage, 'cache_read_input_tokens', 0)}")
print(f"Cache write tokens: {getattr(usage, 'cache_creation_input_tokens', 0)}")

response = client.chat.completions.create(
    model="deepseek/deepseek-r1",
    messages=[{"role": "user", "content": "Solve: if f(x) = x^2 + 3x, what is f(5)?"}],
)

# Read reasoning tokens from usage
usage = response.usage
print(f"Completion tokens: {usage.completion_tokens}")
if hasattr(usage, "completion_tokens_details"):
    details = usage.completion_tokens_details
    print(f"Reasoning tokens: {details.reasoning_tokens}")
    print(f"Output tokens: {details.accepted_prediction_tokens}")

const response = await client.chat.completions.create({
  model: "openai/o3-mini",
  messages: [{ role: "user", content: "Prove that sqrt(2) is irrational." }],
  // @ts-ignore - BazaarLink extension
  reasoning_effort: "high",  // low | medium | high
});

const usage = response.usage;
console.log("Reasoning tokens:", usage?.completion_tokens_details?.reasoning_tokens);

# Qwen3: explicitly enable thinking mode
response = client.chat.completions.create(
    model="qwen/qwen3-32b",
    messages=[{"role": "user", "content": "Prove the Pythagorean theorem"}],
    extra_body={"enable_thinking": True},  # opt-in to thinking
)

# usage.completion_tokens_details.reasoning_tokens shows thinking token count

// Claude extended thinking — specify thinking budget in tokens
const response = await client.chat.completions.create({
  model: "anthropic/claude-sonnet-4.5",
  messages: [{ role: "user", content: "Prove the Pythagorean theorem" }],
  // @ts-ignore - BazaarLink extension
  reasoning: { max_tokens: 5000 },
});

// OpenAI o3 — specify effort level
const response2 = await client.chat.completions.create({
  model: "openai/o3",
  messages: [{ role: "user", content: "Solve this math problem..." }],
  // @ts-ignore - BazaarLink extension
  reasoning: { effort: "high" },
});

// Hide thinking content from response (model still thinks)
const response3 = await client.chat.completions.create({
  model: "anthropic/claude-sonnet-4.5",
  messages: [{ role: "user", content: "What is 2+2?" }],
  // @ts-ignore - BazaarLink extension
  reasoning: { max_tokens: 2000, exclude: true },
});

import time

# Measure time to first token with streaming
start = time.time()
first_token_time = None

stream = client.chat.completions.create(
    model="google/gemini-2.5-flash",  # Fast model
    messages=[{"role": "user", "content": "Hello!"}],
    stream=True,
)

for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content and not first_token_time:
        first_token_time = time.time() - start

print(f"Time to first token: {first_token_time:.3f}s")

# Look up per-request latency and throughput after the fact, using the
# generation ID from the response (or the final streamed chunk).
curl "https://bazaarlink.ai/api/v1/generation?id=chatcmpl-abc123" \
  -H "Authorization: Bearer $BAZAARLINK_API_KEY"

# Response
{
  "data": {
    "id": "chatcmpl-abc123",
    "model": "google/gemini-2.5-flash",
    "duration_ms": 842,
    "throughput": 61.2,
    "usage": { "prompt_tokens": 12, "completion_tokens": 48, "total_tokens": 60 }
  }
}

# Use provider.sort for automatic latency optimization
response = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
    extra_body={
        "provider": {
            "sort": "latency",  # Always pick lowest-latency provider
        }
    },
)

# BazaarLink handles failover automatically — no code changes needed.
# Configure fallback models for maximum resilience:

response = client.chat.completions.create(
    model="openai/gpt-4o",       # Primary model
    messages=[{"role": "user", "content": "Hello!"}],
    extra_body={
        "models": [              # Fallback chain
            "openai/gpt-4o",
            "anthropic/claude-sonnet-4.6",
            "google/gemini-2.5-flash",
        ],
        "route": "fallback",     # Enable fallback routing
    },
)

# Check if failover was used (in usage logs)
# "is_failover": true indicates the primary provider was bypassed

CURSOR_MODEL_MAP=gpt-claude-sonnet:anthropic/claude-sonnet-4.6,gpt-opus:anthropic/claude-opus-4.7

{provider}/{model-name}

# Examples
openai/gpt-5.4-mini
anthropic/claude-sonnet-4.6
google/gemini-3-flash-preview
deepseek/deepseek-v3.2

curl https://bazaarlink.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $BAZAARLINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"auto","messages":[{"role":"user","content":"Review this TypeScript function"}]}'

:free
:extended
:thinking
:exacto

:floor   # lowest listed input price first
:nitro   # throughput-oriented shortcut
:online  # enable web-search routing

deepseek/deepseek-v4-flash

# Return 429 instead of switching to paid routing
-H "X-Free-Fallback: false"

HTTP/1.1 403 Forbidden
Content-Type: application/json

{
  "error": {
    "message": "Model is not allowed for this account",
    "code": "model_not_allowed"
  }
}

# Org-level list
GET    /api/orgs/:orgId/allowed-models
PATCH  /api/orgs/:orgId/allowed-models

# Team-level list
GET    /api/orgs/:orgId/teams/:teamId/allowed-models
PATCH  /api/orgs/:orgId/teams/:teamId/allowed-models

# Member-level list
GET    /api/orgs/:orgId/members/:memberId/allowed-models
PATCH  /api/orgs/:orgId/members/:memberId/allowed-models

# Example: restrict an org to OpenAI + a specific Anthropic model
curl -X PATCH https://bazaarlink.ai/api/orgs/$ORG_ID/allowed-models \
  -H "Authorization: Bearer sk-bl-..." \
  -H "Content-Type: application/json" \
  -d '{"allowedModels": ["openai/*", "anthropic/claude-sonnet-4.6"]}'

HTTP/1.1 429 Too Many Requests
Content-Type: application/json

{
  "error": {
    "message": "Spend circuit breaker tripped at member scope (minute window: $5.2341 ≥ $5.00). Try again later or contact your organization owner."
  }
}

# Org-level config
GET    /api/orgs/:orgId/circuit-breaker
PATCH  /api/orgs/:orgId/circuit-breaker

# Team-level config
GET    /api/orgs/:orgId/teams/:teamId/circuit-breaker
PATCH  /api/orgs/:orgId/teams/:teamId/circuit-breaker

# Member-level config
GET    /api/orgs/:orgId/members/:memberId/circuit-breaker
PATCH  /api/orgs/:orgId/members/:memberId/circuit-breaker

# Example: tighten the org-level cap to $2/min, $10/hr
curl -X PATCH https://bazaarlink.ai/api/orgs/$ORG_ID/circuit-breaker \
  -H "Authorization: Bearer sk-bl-..." \
  -H "Content-Type: application/json" \
  -d '{"cbMinuteUsd": 2, "cbHourlyUsd": 10, "cbEnabled": true}'

# GET response (org scope)
{
  "settings":         { "cbEnabled": true, "cbMinuteUsd": 2,  "cbHourlyUsd": 10  },
  "resolvedSettings": { "cbEnabled": true, "cbMinuteUsd": 2,  "cbHourlyUsd": 10  },
  "liveSpend":        { "minuteSpend": 0.4123, "hourSpend": 3.8721 }
}

# Key CRUD via Bearer auth requires a MANAGEMENT key (keyType: "management").
# Standard keys get 403 on /api/v1/keys — create a management key first,
# or rotate keys from the dashboard UI instead.

# Step 1: Create new key (management key auth)
POST https://bazaarlink.ai/api/v1/keys
Authorization: Bearer $BL_MANAGEMENT_KEY
{"name": "Production v2"}
# → saves new key: sk-bl-NEW_KEY_VALUE

# Step 2: Update your application
# export BAZAARLINK_API_KEY=sk-bl-NEW_KEY_VALUE

# Step 3: Verify new key works
curl https://bazaarlink.ai/api/v1/models \
  -H "Authorization: Bearer sk-bl-NEW_KEY_VALUE"

# Step 4: Revoke old key (management key auth again)
DELETE https://bazaarlink.ai/api/v1/keys/:old_key_id
Authorization: Bearer $BL_MANAGEMENT_KEY

# Query usage data (grouped / aggregated)
GET https://bazaarlink.ai/api/v1/usage
Authorization: Bearer sk-bl-YOUR_KEY

# With period filtering (day | week | month | year)
GET https://bazaarlink.ai/api/v1/usage?period=month

# Response
{
  "period": "month",
  "since": "2025-01-01T00:00:00.000Z",
  "credits": 10.5000,
  "totals": {
    "spend": 0.1812,
    "requests": 309,
    "tokens": 161200,
    "promptTokens": 95000,
    "completionTokens": 66200
  },
  "byModel": [{ "model": "openai/gpt-4o", "spend": 0.0028, "tokens": 1200, "requests": 5 }],
  "byKey":   [{ "keyName": "My Agent", "spend": 0.0028, "tokens": 1200, "requests": 5 }],
  "byApp":   [{ "appName": "MyApp", "spend": 0.0015, "tokens": 600, "requests": 3 }],
  "timeSeries": [{ "date": "2025-01-15", "model": "openai/gpt-4o", "cost": 0.0012, "tokens": 500, "requests": 2 }]
}

import httpx

# Aggregated stats (Bearer token — period: day | week | month | year)
response = httpx.get(
    "https://bazaarlink.ai/api/v1/usage",
    headers={"Authorization": "Bearer sk-bl-YOUR_KEY"},
    params={"period": "month"},
)

data = response.json()
totals = data["totals"]
print("This month: US$%.4f  (%d requests)" % (totals["spend"], totals["requests"]))

# Cost breakdown by model
for m in data["byModel"]:
    print("  %s: US$%.4f  (%d reqs, %d tokens)" % (m["model"], m["spend"], m["requests"], m["tokens"]))

{
  "orgType": "education",
  "eduConfig": {
    "allowedDomains": ["nthu.edu.tw", "student.nthu.edu.tw"],
    "sessionTtlSeconds": 86400,
    "verificationTtlSeconds": 900,
    "maxSessionsPerEmailPerKey": 5
  }
}

curl -X POST https://bazaarlink.ai/api/edu/request-code \
  -H "Content-Type: application/json" \
  -d '{
    "key": "sk-edu-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX",
    "email": "alice@nthu.edu.tw"
  }'

# Success (incl. unknown key/email — enumeration defence) → {"ok":true,"sent":true}
# Rate limit / resend cooldown → 429 {"error":"rate_limited"} or {"error":"cooldown"}
# Sends a 6-digit verification code to the email; default 15-minute lifetime

curl -X POST https://bazaarlink.ai/api/edu/verify \
  -H "Content-Type: application/json" \
  -d '{
    "key":   "sk-edu-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX",
    "email": "alice@nthu.edu.tw",
    "code":  "646291"
  }'

# Success → 200
{
  "token":     "edu-sess-827d11a1ec67d175cfd4f67f929261f4",
  "expiresAt": "2026-05-04T11:16:00.163Z",
  "organization": { "id": "...", "name": "NTHU AI Lab" }
}

# Wrong code → 400 {"error":"invalid"}
# 5 wrong attempts → 429 {"error":"too_many_attempts"} (code invalidated; re-request)

curl -X POST https://bazaarlink.ai/api/v1/chat/completions \
  -H "Authorization: Bearer edu-sess-827d11a1ec67d175cfd4f67f929261f4" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-haiku-4.5",
    "messages": [{"role": "user", "content": "Hello"}]
  }'