evoagent 0.2.2

An orchestration framework for evolving autonomous AI agents

⚔️🔗 EvoAgent

⚡ An orchestration framework for all your AI needs ⚡

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    =====================================================================
         🤖 Welcome to EVO AGENT! Your Evolution in AI Begins Here 🤖
    =====================================================================

Features

• 🤖 Multiple LLM Support (OpenAI, Anthropic, Groq)
• 📚 Vector Store Integration (FAISS, Qdrant, ChromaDB)
• 🔍 Advanced Document Processing
• 🎙️ Speech-to-Text Capabilities
• 🌐 Web Crawling
• 📊 Data Visualization
• 🎯 RAG Applications
• 🤝 PhiData Agent Integration
• 💬 Interactive Chatbots
• 🤖 Self-Evolving Autonomous Agents

Installation

pip install evoagent

Usage

EvoAgent Framework

from evoagent.agent import Agent

def example_function(input_text: str) -> str:
    return f"Processed: {input_text}"

agent = Agent()
agent.register_function(example_function)

query = "Analyze market trends in AI"
response = agent.process_query(query)
print(response)

RAG Implementation

from evoagent.vector_store import FAISSVectorStore
from evoagent.embeddings import HuggingFaceEmbeddings
from evoagent.llms import GroqLLM

vector_store = FAISSVectorStore()
embeddings = HuggingFaceEmbeddings()
llm = GroqLLM("llama3-8b-8192")

text = "AI is transforming industries with automation."
vector_store.add(text, embeddings.embed(text))

query = "How is AI impacting industries?"
response = llm.generate(query)
print(response)

Chatbot Integration

from evoagent.chatbot import Chatbot

chatbot = Chatbot(title="EvoAgent Chatbot")
chatbot.chat()

Contributing

git clone https://github.com/yourusername/evoagent.git
cd evoagent
pip install -e .

License

This project is licensed under the MIT License - see the LICENSE file for details.