eq-chatbot-core 1.7.1

Core library for LLM chatbot integration with multi-provider support (OpenAI, Anthropic, LangDock, OpenRouter, Mammouth, Azure, Vertex AI, Local)

eq-chatbot-core

Core library for LLM chatbot integration with multi-provider support.

Language / Sprache: DE | EN

---

English

Overview

eq-chatbot-core is a Python library for integrating Large Language Models (LLMs) into your applications. It provides a unified interface across cloud and local providers, security primitives, an MCP client, a RAG pipeline, and an optional HTTP/SSE sidecar — usable from any language.

Originally extracted from an Odoo 18 chatbot integration; works standalone without any Odoo dependency.

Key Features

• Multi-Provider Support — OpenAI, Anthropic, Azure AI, Google Vertex AI, LangDock, OpenRouter, Mammouth AI, Local (LM Studio/Ollama)
• Unified API — same interface regardless of provider
• Temperature Safety — automatic model-specific temperature clamping
• Security — Fernet encryption, prompt-injection detection, file-upload validation, token-bucket rate limiting
• RAG Pipeline — chunking, embeddings, Qdrant-backed retrieval, context-window management
• MCP Client — HTTP/SSE and stdio transports, hardened against DNS rebinding and SSRF
• CLI Tool — provider testing, model discovery, programmatic JSON I/O chat
• HTTP/SSE Server Mode (v1.7.0) — run as a local sidecar (eq-chatbot serve) for cross-language integrations (Avalonia/.NET, Electron, native mobile)

Installation

# Basic installation
uv pip install eq-chatbot-core
# (or: pip install eq-chatbot-core)

# With optional extras
uv pip install eq-chatbot-core[pdf]       # PDF→image conversion (vision)
uv pip install eq-chatbot-core[security]  # MIME-type file validation
uv pip install eq-chatbot-core[azure]     # Azure AI Foundry
uv pip install eq-chatbot-core[vertex]    # Google Vertex AI
uv pip install eq-chatbot-core[server]    # HTTP/SSE sidecar (FastAPI + uvicorn)
uv pip install eq-chatbot-core[local]     # Local sentence-transformers embeddings

# All optional dependencies
uv pip install eq-chatbot-core[pdf,security,azure,vertex,server,local,dev]

Quick Start

from eq_chatbot_core.providers import get_provider

provider = get_provider("openai", api_key="sk-...")

response = provider.chat_completion(
    messages=[{"role": "user", "content": "Hello!"}],
    model="gpt-4o",
)
print(response.content)

For more — streaming, other providers, ADC for Vertex, error handling — see docs/providers.md.

Documentation

Topic	Docs
Multi-provider integration	docs/providers.md
CLI commands	docs/cli.md
HTTP/SSE server mode	docs/server-mode.md
Security (encryption, injection, files, rate limit)	docs/security.md
MCP client (HTTP/SSE + stdio)	docs/mcp.md
RAG pipeline (chunking, embedding, retrieval)	docs/rag.md
Testing (markers, integration setup, cost-aware patterns)	docs/testing.md

---

Deutsch

Überblick

eq-chatbot-core ist eine Python-Bibliothek zur Integration von Large Language Models (LLMs) in Anwendungen. Bietet eine einheitliche Schnittstelle über Cloud- und lokale Provider, Security-Primitives, einen MCP-Client, eine RAG-Pipeline und einen optionalen HTTP/SSE-Sidecar — aus jeder Sprache nutzbar.

Ursprünglich aus einer Odoo-18-Chatbot-Integration extrahiert; funktioniert standalone ohne Odoo-Abhängigkeit.

Hauptfunktionen

• Multi-Provider-Unterstützung — OpenAI, Anthropic, Azure AI, Google Vertex AI, LangDock, OpenRouter, Mammouth AI, Local (LM Studio/Ollama)
• Einheitliche API — gleiche Schnittstelle unabhängig vom Provider
• Temperature-Sicherheit — automatisches modellspezifisches Temperature-Clamping
• Sicherheit — Fernet-Verschlüsselung, Prompt-Injection-Erkennung, File-Upload-Validierung, Token-Bucket-Rate-Limiting
• RAG-Pipeline — Chunking, Embeddings, Qdrant-basiertes Retrieval, Context-Window-Management
• MCP-Client — HTTP/SSE und stdio Transports, gehärtet gegen DNS-Rebinding und SSRF
• CLI-Tool — Provider-Tests, Modell-Discovery, programmatische JSON-I/O-Chat-Calls
• HTTP/SSE-Server-Mode (v1.7.0) — lokaler Sidecar (eq-chatbot serve) für Cross-Language-Integrationen (Avalonia/.NET, Electron, native Mobile)

Installation

# Basis-Installation
uv pip install eq-chatbot-core
# (oder: pip install eq-chatbot-core)

# Mit optionalen Extras
uv pip install eq-chatbot-core[pdf]       # PDF→Bild-Konvertierung (Vision)
uv pip install eq-chatbot-core[security]  # MIME-Type-File-Validation
uv pip install eq-chatbot-core[azure]     # Azure AI Foundry
uv pip install eq-chatbot-core[vertex]    # Google Vertex AI
uv pip install eq-chatbot-core[server]    # HTTP/SSE-Sidecar (FastAPI + uvicorn)
uv pip install eq-chatbot-core[local]     # Lokale sentence-transformers-Embeddings

# Alle optionalen Abhängigkeiten
uv pip install eq-chatbot-core[pdf,security,azure,vertex,server,local,dev]

Quick Start

from eq_chatbot_core.providers import get_provider

provider = get_provider("openai", api_key="sk-...")

response = provider.chat_completion(
    messages=[{"role": "user", "content": "Hallo!"}],
    model="gpt-4o",
)
print(response.content)

Für mehr — Streaming, andere Provider, ADC für Vertex, Error-Handling — siehe docs/providers.md.

Dokumentation

Thema	Docs
Multi-Provider-Integration	docs/providers.md
CLI-Befehle	docs/cli.md
HTTP/SSE-Server-Mode	docs/server-mode.md
Security (Verschlüsselung, Injection, Files, Rate-Limit)	docs/security.md
MCP-Client (HTTP/SSE + stdio)	docs/mcp.md
RAG-Pipeline (Chunking, Embedding, Retrieval)	docs/rag.md
Testing (Marker, Integration-Setup, Cost-Aware-Patterns)	docs/testing.md

---

Technical Information

Field	Value
Package Name	eq-chatbot-core
Version	1.7.0
Author	Equitania Software GmbH
Contact	[e-mail]
License	MIT
Python	>=3.10
Homepage	https://www.ownerp.com
Repository	https://github.com/equitania/eq-chatbot-core

Contributing

Contributions are welcome. Please open an issue or submit a pull request.

License

MIT — see LICENSE.