{"uid":"cap_0cypjqgmXXko5XX5bmgcO","slug":"llama-3-1-8b-instruct-chat-completion-ari001-f72f2bf8","name":"Llama-3.1-8B-Instruct Chat Completion (ari001)","description":"","url":"https://ari001.tailb4ac3a.ts.net/v1/ventures/llm_chat_api/llama3_1_8b?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method","bodyType","body"],"properties":{"body":{"type":"object","required":["messages"],"properties":{"messages":{"type":"array","items":{"type":"object","required":["role","content"],"properties":{"role":{"enum":["system","user","assistant"]},"content":{"type":"string"}}},"maxItems":32,"minItems":1},"max_tokens":{"type":"integer","maximum":1024,"minimum":1}}},"type":{"type":"string","const":"http"},"method":{"enum":["POST","PUT","PATCH"],"type":"string"},"bodyType":{"enum":["json","form-data","text"],"type":"string"}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object","required":["ok","service"],"properties":{"ok":{"type":"boolean"},"error":{"type":"string","description":"present when ok is false"},"model":{"type":"string"},"usage":{"type":"object","properties":{"prompt_tokens":{"type":["integer","null"]},"completion_tokens":{"type":["integer","null"]}}},"method":{"type":"string"},"message":{"type":"object","properties":{"role":{"const":"assistant"},"content":{"type":"string"}}},"service":{"type":"string"}}}}}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.003","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"registry","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":"$0.003/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_NH9F2Qa2pYXyeCYARhL8k","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.003","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Runs OpenAI-style chat completions using the Llama-3.1-8B-Instruct model, returning the assistant message, model name, and token usage.","exampleAgentPrompt":"Ask Llama-3.1-8B-Instruct to summarize the following text in three bullet points, using up to 300 tokens: 'Artificial intelligence is transforming industries by automating complex tasks, improving decision-making, and enabling new forms of human-computer interaction.'","exampleUseCases":[{"title":"Automated customer support draft replies","prompt":"I have a customer message that says 'My order hasn't arrived after 2 weeks, what do I do?' — use Llama-3.1-8B-Instruct to draft a polite, helpful support reply in under 200 tokens."},{"title":"Code explanation for developer tools","prompt":"Send this Python snippet to Llama 3.1 8B and ask it to explain what it does in plain English, keeping the response under 512 tokens: 'def fib(n): return n if n <= 1 else fib(n-1) + fib(n-2)'"},{"title":"Agentic reasoning step for a pipeline","prompt":"I need Llama-3.1-8B to act as a reasoning assistant: given the system message 'You are a helpful planner' and the user message 'List 5 steps to launch a newsletter', return the plan with max 1024 tokens."}],"resultDescription":"Returns a JSON object with: a boolean 'ok' field, the assistant's reply as a message object with role='assistant' and a content string, the model name string, token usage (prompt_tokens and completion_tokens), and a service identifier string. 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Best when total conversation context fits within 16,000 characters and response length is under 1024 tokens.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T18:40:38.447Z","isFirstParty":false,"canonicalSlug":"llama-3-1-8b-instruct-chat-completion-ari001-f72f2bf8"}