Unified Language Model API for Scientific Research
Access GPT-4, Claude 3, and other SOTA models via a single, reliable endpoint. Built for large-scale text analysis, computational social science, and reproducible NLP experiments.
import pandas as pd
from aqiapi import AQIAPIClient
# 1. Authenticate
client = AQIAPIClient(api_key='YOUR_API_KEY')
# 2. Load your data
df = pd.read_csv('user_reviews.csv')
# 3. Define analysis function
def get_sentiment(text):
response = client.analyze(
text=text,
task='sentiment',
model='claude-3-opus-20240229'
)
return response.result
# 4. Apply to DataFrame
df['sentiment'] = df['review_text'].apply(get_sentiment)
A Toolkit Designed for Data-driven Inquiry
We handle the engineering complexity, so you can focus on your research questions.
High-Throughput Processing
Optimized for large datasets with support for asynchronous batch requests to maximize efficiency.
Instant SOTA Model Access
A single API to access all major language models. No need to manage multiple keys or SDKs.
Reproducible Research
Pin specific model versions in your requests to ensure your experimental results are consistent and replicable.
Strict Data Privacy
We operate under a zero-retention policy for all API requests. Your proprietary research data remains yours, always.
Unlock New Research Possibilities
From social sciences to bioinformatics, power your analysis with Large Language Models.
Automated Literature Review
Rapidly summarize thousands of academic papers, extract key findings, and identify thematic connections across a body of literature.
Qualitative Data Coding
Accelerate the thematic analysis of interview transcripts, open-ended survey responses, and user feedback at scale.
Social Media Analysis
Analyze public discourse, track sentiment shifts over time, and identify emerging narratives from vast streams of social media data.
Technical FAQ
How do I handle large datasets efficiently?
Our API is designed for scale. We recommend using our asynchronous endpoints for batch processing. Our Python SDK includes helpers to easily map analysis functions across a Pandas DataFrame, optimizing for throughput.
How do you ensure reproducibility if models are constantly updated?
This is critical for research. You can specify a precise model version in your API call (e.g., `gpt-4-0613`). This ensures that you are always hitting the exact same model version, making your results verifiable and reproducible for publication.
Do you offer academic pricing or grants?
Yes. We are committed to supporting academic research. We offer significant discounts for university-affiliated researchers and provide free API credits for select non-commercial research projects. Please contact our Academic Program for more information.
Ready to Supercharge Your Analysis?
Get your API key and start integrating state-of-the-art NLP into your research workflow in minutes.
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