Cognitive Reference Guard
Internal reasoning guardrails verify DOIs against active academic database registers. If a reference cannot be validated, the model automatically flags, replaces, or structures it cleanly.
Banish hallucinated citations and fake DOIs. Lensetek Research AI is a specialized Large Language Model (LLM) matching the standard `/v1/chat/completions` API schema that acts as an intelligent cognitive guardrail.
Standard LLMs often generate plausible-sounding but entirely fabricated citations and DOI links. Lensetek actively reasons and audits references in real-time.
Generates papers that do not exist, invalid DOIs, or attributes findings to the wrong authors.
Cross-checks all generated citation metadata in real-time, rewriting or discarding invalid entries.
Internal reasoning guardrails verify DOIs against active academic database registers. If a reference cannot be validated, the model automatically flags, replaces, or structures it cleanly.
No code changes required. The model endpoint matches the standard `/v1/chat/completions` API schema. Simply target the base URL and keep using standard OpenAI client libraries.
Feeds tabular data such as CSV summaries into the model with automatic structure optimization, preventing parsing errors and token waste on large spreadsheet inputs.
Since Lensetek's Cognitive Research Model matches OpenAI's standard payload schema, switching your codebase is as simple as re-targeting the `baseUrl` and `model` parameters.
X-RapidAPI-Key in client-side code (frontend browsers, mobile applications). Always route requests through a secure backend proxy or serverless function.
curl --request POST \
--url https://lensetek-research-ai.p.rapidapi.com/v1/chat/completions \
--header 'Content-Type: application/json' \
--header 'X-RapidAPI-Host: lensetek-research-ai.p.rapidapi.com' \
--header 'X-RapidAPI-Key: YOUR_RAPIDAPI_KEY' \
--data '{
"model": "lensetek/research-v4-flash",
"messages": [
{
"role": "user",
"content": "Perform a reference check on CRISPR gene editing advancements."
}
]
}'
import openai
# Replace base URL and use your RapidAPI Key as API Key
client = openai.OpenAI(
base_url="https://lensetek-research-ai.p.rapidapi.com/v1",
api_key="YOUR_RAPIDAPI_KEY"
)
# Custom header for RapidAPI routing required by some SDK wrappers
response = client.chat.completions.create(
model="lensetek/research-v4-flash",
messages=[
{"role": "user", "content": "Draft paper with verified DOIs."}
],
extra_headers={
"X-RapidAPI-Host": "lensetek-research-ai.p.rapidapi.com"
}
)
print(response.choices[0].message.content)
const axios = require('axios');
axios.post(
'https://lensetek-research-ai.p.rapidapi.com/v1/chat/completions',
{
model: 'lensetek/research-v4-flash',
messages: [
{ role: 'user', content: 'Generate outline with active DOI check.' }
]
},
{
headers: {
'Content-Type': 'application/json',
'X-RapidAPI-Host': 'lensetek-research-ai.p.rapidapi.com',
'X-RapidAPI-Key': 'YOUR_RAPIDAPI_KEY'
}
}
).then(res => console.log(res.data))
.catch(err => console.error(err));
package main
import (
"bytes"
"fmt"
"net/http"
)
func main() {
url := "https://lensetek-research-ai.p.rapidapi.com/v1/chat/completions"
payload := []byte(`{
"model": "lensetek/research-v4-flash",
"messages": [{"role": "user", "content": "Cite 2 verified journals."}]
}`)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(payload))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("X-RapidAPI-Host", "lensetek-research-ai.p.rapidapi.com")
req.Header.Set("X-RapidAPI-Key", "YOUR_RAPIDAPI_KEY")
resp, _ := http.DefaultClient.Do(req)
defer resp.Body.Close()
fmt.Println("Status Code:", resp.StatusCode)
}
Subscribe directly on RapidAPI. All plans share an operational bandwidth quota of 10,240 MB per month.
Perfect for local development, API prototyping, and evaluating the citation filter capabilities.
No base fee. Pay dynamically per inference request. Ideal for integrating the model into custom pipelines.
For volume researchers and platforms. Includes 1,000 free requests per month, then discounted pay-per-use rates apply.
Switch your model parameter, feed technical logs, and build academic applications with high confidence in reference integrity.
Get Started on RapidAPI