docs: add agno framework integration documentation (#2047)

* docs: add agno framework integration documentation * Update qdrant-landing/content/documentation/frameworks/agno.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Apply suggestion from @Anush008 Co-authored-by: Anush <anushshetty90@gmail.com> * docs: remove inline-example & add agno to frameworks list --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Anush <anushshetty90@gmail.com>
2026-10-05 10:58:32 +02:00 · 2025-12-19 16:37:06 +05:30
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+---
+title: Agno
+---
+
+# Agno
+
+[Agno](https://github.com/agno-agi/agno) is an incredibly fast multi-agent framework, runtime and UI. It enables you to build multi-agent systems with memory, knowledge, human-in-the-loop capabilities, and Model Context Protocol (MCP) support.
+
+You can orchestrate agents as multi-agent teams (providing more autonomy) or step-based agentic workflows (offering more control). Agno works seamlessly with Qdrant as a vector database for knowledge bases, enabling efficient storage and retrieval of information for your AI agents.
+
+Agno supports both synchronous and asynchronous operations, making it flexible for various use cases and deployment scenarios.
+
+## Usage
+
+- Install the required dependencies
+
+```bash
+pip install agno qdrant-client
+```
+
+- Set up environment variables for Qdrant connection
+
+```bash
+export QDRANT_API_KEY="<your-qdrant-api-key>"
+export QDRANT_URL="<your-qdrant-url>"
+```
+
+- Create an agent with Qdrant knowledge base
+
+```python
+import os
+from agno.agent import Agent
+from agno.knowledge.knowledge import Knowledge
+from agno.vectordb.qdrant import Qdrant
+
+# Configure Qdrant vector database
+api_key = os.getenv("QDRANT_API_KEY")
+qdrant_url = os.getenv("QDRANT_URL")
+COLLECTION_NAME = "my-knowledge-base"
+
+vector_db = Qdrant(
+    collection=COLLECTION_NAME,
+    url=qdrant_url,
+    # or you can just url="http://localhost:6333"
+    api_key=api_key, # (optional)
+)
+
+# Create a knowledge base with Qdrant
+knowledge_base = Knowledge(
+    vector_db=vector_db,
+)
+
+# Add content to the knowledge base
+knowledge_base.add_content(
+    url="https://example.com/document.pdf"
+)
+
+# Create an agent with the knowledge base
+agent = Agent(
+    knowledge=knowledge_base,
+    debug_mode=True,
+)
+
+# Use the agent
+response = agent.print_response("What information do you have?")
+```
+
+## Further Reading
+
+- [Agno Documentation](https://docs.agno.com/introduction)
+- [Qdrant integration with Agno](https://docs.agno.com/integrations/vectordb/qdrant/overview)
+- [Qdrant Asynchronous](https://docs.agno.com/integrations/vectordb/qdrant/usage/async-qdrant-db)
+- [Agno GitHub Repository](https://github.com/agno-agi/agno)