Claude Code Guide
Set up Flaq AI Claude models and explore Claude Code skills
Try GPT 6 Sol API by OpenAI for file analysis, document summaries, and questions across files through Flaq AI's stable, affordable API with streaming responses.
const response = await fetch('https://api.flaq.ai/api/v1/chat/completions', {
method: 'POST',
headers: {
Authorization: 'Bearer YOUR_API_KEY',
Accept: 'text/event-stream',
'Content-Type': 'application/json'
},
body: JSON.stringify({
model: 'gpt-6-sol-file-analysis',
messages: [
{
role: 'user',
content: [
{ type: 'text', text: 'Summarize this file and extract the key risks.' },
{
type: 'file',
file: {
filename: 'demo.pdf',
file_data: 'https://example.com/demo.pdf'
}
}
]
}
],
stream: true,
max_tokens: 4096
})
});
if (!response.ok) {
const errorBody = await response.json().catch(() => null);
throw new Error(errorBody?.error?.message ?? errorBody?.message ?? `HTTP ${response.status}`);
}
const reader = response.body.getReader();
const decoder = new TextDecoder();
let buffer = '';
let assistantText = '';
while (true) {
const { done, value } = await reader.read();
if (done) break;
buffer += decoder.decode(value, { stream: true });
const frames = buffer.split(/\r?\n\r?\n/);
buffer = frames.pop() || '';
for (const frame of frames) {
const lines = frame.split(/\r?\n/).filter(Boolean);
let eventName = 'message';
const dataLines = [];
for (const line of lines) {
if (line.startsWith('event:')) {
eventName = line.slice(6).trim();
} else if (line.startsWith('data:')) {
dataLines.push(line.replace(/^data:\s*/, ''));
}
}
const raw = dataLines.join('\n').trim();
if (raw === '[DONE]') {
console.log('\nFinal text:', assistantText);
continue;
}
let payload;
try {
payload = JSON.parse(raw);
} catch {
continue;
}
if (eventName === 'error' || payload.error) {
const msg = payload.error?.message ?? payload.message ?? 'Chat request failed';
throw new Error(msg);
}
const delta = payload.choices?.[0]?.delta;
if (delta?.content) {
assistantText += delta.content;
console.log(assistantText);
}
}
}
import json
import requests
response = requests.post(
'https://api.flaq.ai/api/v1/chat/completions',
headers={
'Authorization': 'Bearer YOUR_API_KEY',
'Accept': 'text/event-stream',
'Content-Type': 'application/json',
},
json={
'model': 'gpt-6-sol-file-analysis',
'messages': [
{
'role': 'user',
'content': [
{'type': 'text', 'text': 'Summarize this file and extract the key risks.'},
{
'type': 'file',
'file': {
'filename': 'demo.pdf',
'file_data': 'https://example.com/demo.pdf'
}
},
],
}
],
'stream': True,
'max_tokens': 4096,
},
stream=True,
)
response.raise_for_status()
event_name = 'message'
assistant_text = ''
for raw_line in response.iter_lines(decode_unicode=True):
if not raw_line:
event_name = 'message'
continue
if raw_line.startswith('event:'):
event_name = raw_line.replace('event:', '', 1).strip()
continue
if raw_line.startswith('data:'):
raw_data = raw_line.replace('data:', '', 1).strip()
if raw_data == '[DONE]':
print('\nFinal text:', assistant_text)
continue
payload = json.loads(raw_data)
if event_name == 'error' or payload.get('error'):
error = payload.get('error') or payload
raise RuntimeError(error.get('message', 'Chat request failed'))
choices = payload.get('choices') or []
if choices:
delta = choices[0].get('delta') or {}
content = delta.get('content')
if content:
assistant_text += content
print(content, end='', flush=True)
curl -N -X POST "https://api.flaq.ai/api/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Accept: text/event-stream" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-6-sol-file-analysis",
"messages": [
{
"role": "user",
"content": [
{ "type": "text", "text": "Summarize this file and extract the key risks." },
{
"type": "file",
"file": {
"filename": "demo.pdf",
"file_data": "https://example.com/demo.pdf"
}
}
]
}
],
"stream": true,
"max_tokens": 4096
}'
| Parameters | Price | Original Price | Discount |
|---|
GPT 6 Sol File Analysis API applies OpenAI's GPT-6 Sol reasoning capabilities to dense documentation, multi-file synthesis, and evidence review on Flaq AI. This file analysis API integration helps software engineers, legal analysts, and enterprise teams extract details, compare claims with source files, and prepare summaries from supported files, images, and natural-language instructions for further review.
Note Please upload only documents, images, and prompt instructions that comply with OpenAI's safety and usage policies, Flaq AI terms, and applicable organizational data privacy standards. If an error occurs, verify that files are in supported formats, remove restricted content, and retry.
GPT 6 Sol File Analysis vs. GPT 6 Astra File Analysis
GPT 6 Astra is OpenAI's flagship model for its hardest reasoning work. GPT 6 Sol File Analysis balances model capability and cost for enterprise document review workflows.
GPT 6 Sol File Analysis vs. GPT 6 Luna File Analysis
GPT 6 Luna File Analysis is positioned for cost-sensitive, high-volume document tasks. GPT 6 Sol File Analysis suits workflows that call for detailed comparisons of legal or technical text.
GPT 6 Sol File Analysis vs. Claude Opus 5.5 File Analysis
Claude Opus 5.5 File Analysis supports document and image review in the Anthropic ecosystem. GPT 6 Sol File Analysis offers an OpenAI-based option for technical document questions, extraction, and chat-style integration on Flaq AI.
GPT 6 Sol File Analysis vs. Gemini File Understanding
Gemini file processing models fit workflows built around Google's multimodal tools. GPT 6 Sol File Analysis offers an OpenAI-based option for teams that want prompt-guided structured text and unified chat API access on Flaq AI.
Set up Flaq AI Claude models and explore Claude Code skills

Set up Flaq AI GPT models and explore Codex skills
Use Flaq AI LLM models in Hermes Agent
Use GLM 5.2, Kimi K3, and DeepSeek v4 in ZCode
Run DeepSeek Harness with Flaq AI DeepSeek models
Connect AI agents to Flaq image and video generation tools
Use GPT 6 Astra and Claude Fable 5.1 in WorkBuddy