{"uid":"cap_HcpCpcS0v4JR0itQgVnAW","slug":"citiview-qwen-2-5-coder-32b-chat-completions-bd82fe60","name":"Citiview Qwen 2.5 Coder 32B Chat Completions","description":"Citiview Agent Market: 211 pay-per-call tools for AI agents. Cited answers, deep research, agent memory, file hosting, webhooks, schedules, sanctions and link safety checks, OpenAI-compatible LLMs on 11 models, web search, scraping, PDF, OCR, speech, Solana and EVM token risk, DeFi, prediction odds, SEC data. Pay per call in USDC with x402. No key, no signup.","url":"https://agents.citiviewgroup.com/v1/coder/chat/completions?utm_source=zero.xyz","method":"GET","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method"],"properties":{"type":{"type":"string","const":"http"},"method":{"enum":["GET"],"type":"string"},"queryParams":{"type":"object","required":["prompt"],"properties":{"prompt":{"type":"string","description":"User message"},"system":{"type":"string","description":"Optional system message"},"max_tokens":{"type":"integer"},"temperature":{"type":"number"}}}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object"}}}}},"responseSchema":{"type":"json","example":{"id":"chatcmpl-...","model":"qwen2.5-coder-32b","usage":{"total_tokens":18,"prompt_tokens":14,"completion_tokens":4},"object":"chat.completion","choices":[{"index":0,"message":{"role":"assistant","content":"Bonjour !"},"finish_reason":"stop"}]}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.005112","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.005112/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.005112","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.005112","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_ijKu6MjB1NyFJ9lReOpFD","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.005112","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"OpenAI-compatible chat completions powered by Qwen 2.5 Coder 32B for code generation, review, and bug fixing, billed per request via x402 micropayments","exampleAgentPrompt":"Can you write me a Python function that reads a CSV file, filters rows where the 'status' column equals 'active', and returns the result as a list of dicts? Use a temperature of 0.2 and limit the output to 512 tokens.","exampleUseCases":[{"title":"Automated code review in CI pipeline","prompt":"Review this TypeScript function I just wrote and tell me if there are any bugs, performance issues, or bad practices: function mergeArrays(a, b) { return [...new Set([...a, ...b])] } — keep the response concise and use temperature 0.1."},{"title":"Bug fix from error message","prompt":"I'm getting a Python KeyError: 'user_id' in this code snippet — can you find and fix the bug? Here's the code: `data = request.json; name = data['name']; uid = data['user_id']`. The input JSON sometimes omits user_id."},{"title":"Boilerplate code generation","prompt":"Generate a complete Express.js REST API with GET and POST routes for a /users endpoint, including basic input validation and JSON response formatting. Keep it under 300 lines and use temperature 0.3."}],"resultDescription":"Returns an OpenAI-compatible chat completion response containing the model-generated code, review, or explanation as the assistant message content, with standard fields like choices, usage token counts, and finish_reason. Streaming is supported for real-time token delivery.","failureModes":["Payment not included or insufficient — request rejected with 402 Payment Required","Prompt exceeds context window — model may truncate or return an error","max_tokens set too low for complex code output — response cut off mid-generation","Invalid or malformed query parameters — 400 Bad Request","Model hallucinations — generated code may contain subtle logical errors requiring review","Temperature out of valid range — may cause 400 error"],"whenToPreferThis":"Choose this endpoint when you need a large, specialized code-focused model (32B parameters, Qwen Coder) with OpenAI-compatible API shape and no API key management — just pay per request via x402. Prefer over general LLM endpoints when tasks are code-heavy (generation, debugging, review) and you want a model fine-tuned specifically for programming tasks rather than a general chat model.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-14T06:47:11.099Z","isFirstParty":false,"canonicalSlug":"citiview-qwen-2-5-coder-32b-chat-completions-bd82fe60"}