renamed to be: Open AI Co-Scientist

README.md

@@ -1,5 +1,5 @@
 ---
-title: Ai Co Scientist
+title: Open AI Co-Scientist
 emoji: 📊
 colorFrom: gray
 colorTo: gray
@@ -8,10 +8,10 @@ sdk_version: 5.38.2
 app_file: app.py
 pinned: false
 license: mit
-short_description: open-source implementation of Google's AI co-scientist syste
+short_description: Open-source AI-enabled Research Hypothesis Evolution System
 ---
 
-# AI Co-Scientist - Hypothesis Evolution System (Gradio Version)
+# Open AI Co-Scientist - Hypothesis Evolution System
 
 This project implements an AI-powered system for generating, reviewing, ranking, and evolving research hypotheses using a multi-agent architecture and Large Language Models (LLMs). The user interface is built with Gradio for rapid prototyping and interactive research.
 

README_HF.md

@@ -1,5 +1,5 @@
 ---
-title: AI Co-Scientist
+title: Open AI Co-Scientist
 emoji: 🔬
 colorFrom: blue
 colorTo: green
@@ -11,7 +11,7 @@ license: mit
 short_description: Generate, review, rank, and evolve research hypotheses using AI agents
 ---
 
-# 🔬 AI Co-Scientist - Hypothesis Evolution System
+# 🔬 Open AI Co-Scientist - Hypothesis Evolution System
 
 An AI-powered system for generating, reviewing, ranking, and evolving research hypotheses using multiple AI agents. This system helps researchers explore research spaces and identify promising hypotheses through iterative refinement.
 

app/agents.py

@@ -368,7 +368,7 @@ class MetaReviewAgent:
         return overview
 
 class SupervisorAgent:
-    """Orchestrates the AI Co-Scientist workflow."""
+    """Orchestrates the Open AI Co-Scientist workflow."""
     def __init__(self):
         self.generation_agent = GenerationAgent()
         self.reflection_agent = ReflectionAgent()

docs/SOTA-ChatGPT-5-Pro.md

@@ -231,4 +231,3 @@ A **research hypothesis** is a *testable, falsifiable claim* about a mechanism o
 [34]: https://www.nist.gov/news-events/news/2024/12/pre-deployment-evaluation-openais-o1-model?utm_source=chatgpt.com "Pre-Deployment Evaluation of OpenAI's o1 Model | NIST"
 [35]: https://www.microsoft.com/en-us/research/publication/causal-inference-using-llm-guided-discovery/?utm_source=chatgpt.com "Causal Inference Using LLM-Guided Discovery - microsoft.com"
 [36]: https://arxiv.org/abs/2402.11068?utm_source=chatgpt.com "[2402.11068] Large Language Models for Causal Discovery: Current ..."
-

docs/TODO.md

@@ -1,4 +1,4 @@
-# AI Co-Scientist - Prioritized Feature Roadmap
+# Open AI Co-Scientist - Prioritized Feature Roadmap
 
 This list outlines the top 10 priority features identified to make this system an indispensable tool for scientists and entrepreneurs.
 

docs/claude_planning.md

@@ -1,7 +1,7 @@
-# AI Co-Scientist Enhancement Plan - Top 10 Priority Improvements
+# Open AI Co-Scientist Enhancement Plan - Top 10 Priority Improvements
 
 ## Overview
-This document outlines the top 10 priority improvements for the AI Co-Scientist system based on comprehensive codebase analysis. The system is a multi-agent hypothesis generation and evolution platform that currently provides basic functionality but has significant potential for enhancement.
+This document outlines the top 10 priority improvements for the Open AI Co-Scientist system based on comprehensive codebase analysis. The system is a multi-agent hypothesis generation and evolution platform that currently provides basic functionality but has significant potential for enhancement.
 
 ## Current System Analysis
 The existing system includes:
@@ -190,4 +190,4 @@ The existing system includes:
 - **Performance**: Profiling and optimization throughout development
 - **Safety**: Conservative defaults and user education
 
-This planning document provides a roadmap for transforming the current basic implementation into a production-ready, research-grade AI co-scientist system.
+This planning document provides a roadmap for transforming the current basic implementation into a production-ready, research-grade Open AI Co-Scientist system.

docs/deployment.md

@@ -1,6 +1,6 @@
 # Deployment Guide: Cost Control for Hugging Face Spaces
 
-This guide covers strategies for deploying the AI Co-Scientist project to Hugging Face Spaces while controlling API costs from public usage.
+This guide covers strategies for deploying the Open AI Co-Scientist project to Hugging Face Spaces while controlling API costs from public usage.
 
 ## Problem Statement
 
@@ -259,7 +259,7 @@ CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]
 Create `README.md` in root with HF Spaces header:
 ```yaml
 ---
-title: AI Co-Scientist
+title: Open AI Co-Scientist
 emoji: 🔬
 colorFrom: blue
 colorTo: green
@@ -311,7 +311,7 @@ iface = gr.Interface(
 ```python
 import streamlit as st
 
-st.title("AI Co-Scientist")
+st.title("Open AI Co-Scientist")
 goal = st.text_area("Research Goal")
 model = st.selectbox("Model", ALLOWED_MODELS)
 
@@ -342,4 +342,4 @@ if st.button("Generate Hypotheses"):
 3. **User Feedback**: Monitor for requests for additional models
 4. **Performance Monitoring**: Track response times and error rates
 
-This deployment strategy balances functionality with cost control, ensuring your AI Co-Scientist remains accessible to the public while protecting your budget.
+This deployment strategy balances functionality with cost control, ensuring your Open AI Co-Scientist remains accessible to the public while protecting your budget.

docs/huggingface_deployment.md

@@ -1,6 +1,6 @@
 # Hugging Face Spaces Deployment Guide
 
-This guide explains how to deploy the AI Co-Scientist system as a Gradio app on Hugging Face Spaces.
+This guide explains how to deploy the Open AI Co-Scientist system as a Gradio app on Hugging Face Spaces.
 
 ## 📋 Prerequisites
 
@@ -14,7 +14,7 @@ This guide explains how to deploy the AI Co-Scientist system as a Gradio app on
 1. Go to [Hugging Face Spaces](https://huggingface.co/spaces)
 2. Click "Create new Space"
 3. Fill in the details:
-   - **Space name**: `ai-co-scientist` (or your preferred name)
+   - **Space name**: `open-ai-co-scientist` (or your preferred name)
    - **License**: MIT
    - **SDK**: Gradio
    - **Hardware**: CPU Basic (free tier is sufficient)
@@ -185,7 +185,7 @@ If you encounter issues:
 
 ## 🎉 Success!
 
-Once deployed, your AI Co-Scientist will be available at:
+Once deployed, your Open AI Co-Scientist will be available at:
 `https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME`
 
 Users can now generate and evolve research hypotheses using your deployed system!

docs/plan.md

@@ -1,8 +1,8 @@
-# Plan to Implement AI Co-Scientist Core Algorithms
+# Plan to Implement Open AI Co-Scientist Core Algorithms
 
 ## 1. Introduction
 
-**Goal:** Extend the existing Python codebase to implement the core algorithms and architecture of the AI co-scientist system as described in the paper "Towards an AI co-scientist" (Gottweis et al., 2025).
+**Goal:** Extend the existing Python codebase to implement the core algorithms and architecture of the AI Co-Scientist system as described in the paper "Towards an AI Co-Scientist" (Gottweis et al., 2025).
 
 **Current State:** The codebase provides a FastAPI web server with basic, sequential agent implementations (`Generation`, `Reflection`, `Ranking`, `Evolution`, `Proximity`, `MetaReview`) orchestrated by a `SupervisorAgent`. It includes data models (`Hypothesis`, `ResearchGoal`, `ContextMemory`) and API endpoints for setting goals and running cycles. LLM interaction is basic, relying on simple prompts for generation and review.