# Chat Completions > Generate chat completions from a list of messages — the primary endpoint for text generation with all supported models. - Canonical: https://tchavi.com/en/docs/chat-completions --- Generate a chat completion from a list of messages. This is the primary endpoint for text generation with all supported models. The parameter tables below list the common fields shared across models. Each model may support additional model-specific parameters (e.g. vision input, tool calling, JSON mode). For the exhaustive list of parameters a given model accepts, open its details page at [Models](/en/models) and switch to the **API** tab — the parameter reference there is generated from the model's declared capabilities. ## Request body | Parameter | Type | Required | Description | | ------------------- | ------------------ | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `model` | string | Yes | Model ID (e.g. "gpt-4o-mini", "claude-sonnet-4-6") | | `messages` | array | Yes | Array of message objects. Each has a `role` (`system`, `user`, or `assistant`) and `content` that's either a plain string or an array of content blocks (`text`, `image_url`, `document_url`). `system` sets the AI's behavior; `user` is your message; `assistant` is a prior AI reply. | | `temperature` | number | No | Controls randomness. 0 = deterministic/focused, 1 = balanced (default), 2 = highly creative/random. | | `max_tokens` | integer | No | Maximum tokens to generate | | `stream` | boolean | No | Stream response as SSE. Default: false | | `top_p` | number | No | Nucleus sampling parameter (0–1) | | `stop` | string \| string[] | No | Up to 4 stop sequences. The model stops generating when it hits one. | | `frequency_penalty` | number | No | -2.0 to 2.0. Positive values penalize repeated tokens. Default: 0 | | `presence_penalty` | number | No | -2.0 to 2.0. Positive values push the model toward new topics. Default: 0 | | `seed` | integer | No | Reproducibility seed. Same seed + params returns similar output (best-effort). | | `response_format` | object | No | `{ type: "json_object" }` or `{ type: "json_schema", json_schema: ... }` for structured output. Model support varies — see the model's API tab. | | `tools` | array | No | Function definitions the model can call. Paired with `tool_choice`. Available on tool-capable models only. | **PDF input.** Attach a PDF on a `user` message by passing a content block with `{ type: "document_url", document_url: { url: ... } }`. Up to 5 PDFs per request. Only models with `supportsDocuments: true` accept this block — currently `claude-opus-4-7`, `claude-sonnet-4-6`, `claude-haiku-4-5-20251001`, `gpt-4.1`, and `gpt-4.1-mini`. ## Example request ```tchavi import Tchavi from '@tchavi/sdk'; const client = new Tchavi({ apiKey: 'YOUR_API_KEY' }); const response = await client.chat.completions.create({ model: 'gpt-4o-mini', messages: [ { role: 'system', content: 'You are a helpful assistant.' }, { role: 'user', content: 'What is the capital of Benin?' }, ], temperature: 0.7, }); console.log(response.choices[0].message.content); console.log('Credits used:', response.tchavi.credits_used); ``` ```openai from openai import OpenAI client = OpenAI( api_key="YOUR_API_KEY", base_url="https://tchavi.com/api/v1", ) response = client.chat.completions.create( model="gpt-4o-mini", messages=[ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "What is the capital of Benin?"}, ], temperature=0.7, ) print(response.choices[0].message.content) ``` ```javascript const response = await fetch('https://tchavi.com/api/v1/chat/completions', { method: 'POST', headers: { 'Content-Type': 'application/json', Authorization: 'Bearer YOUR_API_KEY', }, body: JSON.stringify({ model: 'gpt-4o-mini', messages: [ { role: 'system', content: 'You are a helpful assistant.' }, { role: 'user', content: 'What is the capital of Benin?' }, ], temperature: 0.7, }), }); const data = await response.json(); console.log(data.choices[0].message.content); // Check remaining credits console.log('Credits:', response.headers.get('X-Credits-Remaining')); ``` ```python import requests response = requests.post( "https://tchavi.com/api/v1/chat/completions", headers={ "Content-Type": "application/json", "Authorization": "Bearer YOUR_API_KEY", }, json={ "model": "gpt-4o-mini", "messages": [ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "What is the capital of Benin?"}, ], "temperature": 0.7, }, ) data = response.json() print(data["choices"][0]["message"]["content"]) # Check remaining credits print("Credits:", response.headers.get("X-Credits-Remaining")) ``` ```curl curl -X POST https://tchavi.com/api/v1/chat/completions \ -H "Content-Type: application/json" \ -H "Authorization: Bearer YOUR_API_KEY" \ -d '{ "model": "gpt-4o-mini", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the capital of Benin?" } ], "temperature": 0.7 }' ``` ## Example response ```json { "id": "chatcmpl-abc123", "object": "chat.completion", "created": 1711234567, "model": "gpt-4o-mini", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "The capital of Benin is Porto-Novo." }, "finish_reason": "stop" } ], "usage": { "prompt_tokens": 24, "completion_tokens": 12, "total_tokens": 36 }, "tchavi": { "credits_used": 2, "credits_remaining": 498, "model_tier": "budget" } } ``` ## Streaming Set `stream: true` to receive the response token-by-token as Server-Sent Events (SSE). This lets you display text as it arrives rather than waiting for the full response. ```tchavi import Tchavi from '@tchavi/sdk'; const client = new Tchavi({ apiKey: process.env.TCHAVI_API_KEY }); const stream = await client.chat.completions.create({ model: 'gpt-4o-mini', messages: [{ role: 'user', content: 'Tell me a short story.' }], stream: true, }); for await (const chunk of stream) { process.stdout.write(chunk.choices[0]?.delta?.content ?? ''); } ``` ```javascript const response = await fetch('https://tchavi.com/api/v1/chat/completions', { method: 'POST', headers: { 'Content-Type': 'application/json', Authorization: 'Bearer YOUR_API_KEY', }, body: JSON.stringify({ model: 'gpt-4o-mini', messages: [{ role: 'user', content: 'Tell me a short story.' }], stream: true, }), }); const reader = response.body.getReader(); const decoder = new TextDecoder(); while (true) { const { done, value } = await reader.read(); if (done) break; const lines = decoder.decode(value).split('\n'); for (const line of lines) { if (!line.startsWith('data: ') || line.includes('[DONE]')) continue; const delta = JSON.parse(line.slice(6)).choices[0]?.delta?.content ?? ''; process.stdout.write(delta); } } ``` ```python import requests, json response = requests.post( "https://tchavi.com/api/v1/chat/completions", headers={ "Content-Type": "application/json", "Authorization": "Bearer YOUR_API_KEY", }, json={ "model": "gpt-4o-mini", "messages": [{"role": "user", "content": "Tell me a short story."}], "stream": True, }, stream=True, ) for line in response.iter_lines(): if not line or line == b"data: [DONE]": continue data = json.loads(line.decode().removeprefix("data: ")) print(data["choices"][0]["delta"].get("content", ""), end="", flush=True) ```