euron-qa

name	euron-qa
description	Answer Euron Gen AI Bootcamp doubts instantly. Covers Euri API setup across all frameworks (Python, LangChain, OpenAI SDK, TypeScript, n8n, curl), MCP server setup, common errors, model recommendations, and token limits. Use when someone in the bootcamp asks a question.

Euron Bootcamp Q&A - Instant Answer Reference

Goal

Instantly answer any Euron Gen AI Certification Bootcamp doubt by looking up the right code snippet, config, or troubleshooting step from this reference.

Quick Context

• Bootcamp: Euron Gen AI Certification Bootcamp 2.0 (by Sudhanshu sir)
• Portal: https://euron.one/euri
• API Base URL: https://api.euron.one/api/v1/euri
• Auth: Authorization: Bearer <EURI_API_KEY>
• Daily limit: 200,000 tokens (input + output), resets midnight UTC
• Key principle: Euri is OpenAI-compatible. Anywhere you use ChatOpenAI(...) or OpenAI(...), just add base_url pointing to Euri.

---

COMMON QUESTIONS & ANSWERS

Q1: "How do I use Euri with LangChain?"

Answer (copy-paste ready):

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="gpt-4.1-nano",  # or gemini-2.5-flash, any Euri model
    api_key="your-euri-api-key",
    base_url="https://api.euron.one/api/v1/euri"
)

response = llm.invoke("Hello!")
print(response.content)

That's it. Everywhere Sudhanshu sir uses ChatOpenAI(...), just add the base_url parameter pointing to Euri. Everything else (agents, chains, tools) stays exactly the same.

---

Q2: "How do I use Euri with OpenAI Python SDK?"

from openai import OpenAI

client = OpenAI(
    api_key="your-euri-api-key",
    base_url="https://api.euron.one/api/v1/euri"
)

response = client.chat.completions.create(
    model="gemini-2.5-flash",
    messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)

---

Q3: "How do I use the Euri Python SDK (euriai)?"

pip install euriai

from euriai import EuriaiClient

client = EuriaiClient(
    api_key="your-euri-api-key",
    model="gemini-2.5-flash"
)

response = client.generate_completion(
    prompt="What is AI?",
    temperature=0.7,
    max_tokens=500
)
print(response["choices"][0]["message"]["content"])

---

Q4: "How do I use Euri with LangChain's euriai integration?"

pip install euriai[langchain]

from euriai.langchain import EuriaiChatModel

chat = EuriaiChatModel(api_key="your-key", model="gemini-2.5-flash")
result = chat.invoke("Explain Docker")
print(result.content)

---

Q5: "How do I use Euri with raw HTTP / requests?"

import requests

response = requests.post(
    "https://api.euron.one/api/v1/euri/chat/completions",
    headers={
        "Authorization": "Bearer your-euri-api-key",
        "Content-Type": "application/json",
    },
    json={
        "model": "gemini-2.5-flash",
        "messages": [{"role": "user", "content": "Hello!"}],
        "temperature": 0.7,
        "max_tokens": 500,
    },
)

data = response.json()
print(data["choices"][0]["message"]["content"])

---

Q6: "How do I use Euri with curl?"

curl -X POST https://api.euron.one/api/v1/euri/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "messages": [{"role": "user", "content": "Hello!"}],
    "model": "gemini-2.5-flash"
  }'

---

Q7: "How do I use Euri with TypeScript / Node.js?"

const response = await fetch("https://api.euron.one/api/v1/euri/chat/completions", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.EURI_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "gemini-2.5-flash",
    messages: [{ role: "user", content: "Hello!" }],
  }),
});

const data = await response.json();
console.log(data.choices[0].message.content);

---

Q8: "How do I use Euri in n8n?"

Option A — OpenAI Credential (easiest):

1. Create "OpenAI" credential in n8n
2. Set API Key: your Euri API key
3. Set Base URL: https://api.euron.one/api/v1/euri
4. Use any OpenAI node — it routes through Euri automatically

Option B — HTTP Request Node:

• Method: POST
• URL: https://api.euron.one/api/v1/euri/chat/completions
• Headers: Authorization: Bearer {{ $env.EURI_API_KEY }}
• Body JSON:

{
  "model": "gemini-2.5-flash",
  "messages": [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "{{ $json.userMessage }}"}
  ],
  "temperature": 0.7,
  "max_tokens": 1000
}

• Extract response: {{ $json.choices[0].message.content }}

---

Q9: "How do I generate embeddings with Euri?"

from openai import OpenAI

client = OpenAI(
    api_key="your-euri-api-key",
    base_url="https://api.euron.one/api/v1/euri"
)

response = client.embeddings.create(
    model="gemini-embedding-001",  # or text-embedding-3-small
    input="Your text here"
)
print(response.data[0].embedding[:5])  # First 5 dimensions

Available embedding models:

Model	ID	Dimensions
Gemini Embedding 001	gemini-embedding-001	1536
Text Embedding 3 Small	text-embedding-3-small	1536
M2 BERT 80M 32K	togethercomputer/m2-bert-80M-32k-retrieval	1536

---

Q10: "How do I generate images with Euri?"

from openai import OpenAI

client = OpenAI(
    api_key="your-euri-api-key",
    base_url="https://api.euron.one/api/v1/euri"
)

response = client.images.generate(
    model="gemini-3-pro-image-preview",
    prompt="A futuristic city at sunset, cyberpunk style",
    n=1
)
print(response.data[0].url)

---

Q11: "Which model should I use?"

Use Case	Model ID	Why
General purpose	gemini-2.5-flash	Best balance of speed + quality
Complex reasoning	gemini-2.5-pro	2M context, best reasoning
Fast & cheap	gpt-4.1-nano	Cheapest, ultra-fast
Also fast & cheap	gpt-5-nano-2025-08-07	Newer nano model
Code generation	gpt-4.1-mini or gemini-2.5-flash	Good at code
Web search	groq/compound	Built-in web search
Embeddings (RAG)	gemini-embedding-001	Best quality embeddings
Image generation	gemini-3-pro-image-preview	Only image model on Euri

Full model list (24 models):

Text Models (20):

• qwen/qwen3-32b (Alibaba, 128K)
• gemini-2.0-flash (Google, 1M)
• gemini-2.5-pro (Google, 2M)
• gemini-2.5-flash (Google, 1M)
• gemini-2.5-pro-preview-06-05 (Google, 2M)
• gemini-2.5-flash-preview-05-20 (Google, 1M)
• gemini-2.5-flash-lite-preview-06-17 (Google, 128K)
• groq/compound (Groq, 131K)
• groq/compound-mini (Groq, 131K)
• llama-4-scout-17b-16e-instruct (Meta, 128K)
• llama-4-maverick-17b-128e-instruct (Meta, 128K)
• llama-3.3-70b-versatile (Meta, 128K)
• llama-3.1-8b-instant (Meta, 128K)
• llama-guard-4-12b (Meta, 128K)
• gpt-5-nano-2025-08-07 (OpenAI, 128K)
• gpt-5-mini-2025-08-07 (OpenAI, 128K)
• gpt-4.1-nano (OpenAI, 128K)
• gpt-4.1-mini (OpenAI, 128K)
• openai/gpt-oss-20b (OpenAI, 128K)
• openai/gpt-oss-120b (OpenAI, 128K)

---

Q12: "I'm getting an error / API not working"

Common fixes:

1. 401 Unauthorized — API key is wrong or missing

   • Get your key from https://euron.one/euri
   • Header must be: Authorization: Bearer YOUR_KEY (not Api-Key or X-API-Key)

2. Model not found — Wrong model ID

   • Use exact IDs from the model list above (case-sensitive)
   • Common mistake: gpt-4.1 instead of gpt-4.1-nano

3. Rate limit / 429 — Hit 200K daily token limit

   • Wait until midnight UTC for reset
   • Use shorter prompts and lower max_tokens
   • Switch to cheaper models (gpt-4.1-nano)

4. Response content is array instead of string

   • Euri sometimes returns content as [{type:"text", text:"..."}] instead of a plain string
   • Handle both: content if isinstance(content, str) else content[0]["text"]

5. LangChain version issues

   • Use langchain_openai (not langchain.chat_models)
   • pip install langchain-openai (separate package)

6. "Connection refused" or timeout

   • Check internet connection
   • Verify base URL: https://api.euron.one/api/v1/euri (no trailing slash)

---

Q13: "How do I build agents/chains with Euri + LangChain?"

Same as normal LangChain — just use the Euri LLM:

from langchain_openai import ChatOpenAI
from langchain.agents import create_react_agent, AgentExecutor
from langchain.tools import Tool

# Euri-powered LLM
llm = ChatOpenAI(
    model="gemini-2.5-flash",
    api_key="your-euri-api-key",
    base_url="https://api.euron.one/api/v1/euri"
)

# Use llm in any chain, agent, or tool — works identically to OpenAI

Key insight: Euri is a drop-in replacement. ANY LangChain tutorial or Sudhanshu sir's code works — just add the base_url parameter.

---

Q14: "How do I set up the MCP servers from class?"

Full guide: See Angelina AI System/Euron/MAIL-MCP-SETUP.md

Quick setup pattern for any MCP server:

cd "Gen AI 2.O/MCP/<server-folder>"
python3 -m venv venv
source venv/bin/activate       # macOS/Linux
# venv\Scripts\activate        # Windows
pip install -r requirements.txt
python authenticate.py          # For Google services only

8 MCP servers available:

1. Gmail (4 tools) — send, read, search, mark seen
2. Google Calendar (5 tools) — list, create, search, delete events
3. Google Sheets (5 tools) — read, write, append, create, list
4. Supabase (6 tools) — query, insert, update, delete, SQL
5. MongoDB (7 tools) — query, insert, update, delete, aggregate
6. AWS S3 (6 tools) — list, upload, download, delete, presigned URLs
7. Azure Blob (7 tools) — list, upload, download, delete, SAS URLs
8. Social Media (10 tools) — YouTube + Instagram + Facebook

Claude Desktop config location:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

Cursor config location:

• ~/.cursor/mcp.json (macOS/Linux)
• %USERPROFILE%\.cursor\mcp.json (Windows)

Common MCP errors:

• "MCP Server disconnected" → Make sure script has mcp.run(transport="stdio"), don't use -m mcp run
• "Auth token missing" → Run python authenticate.py again
• "Failed to refresh token" → Delete token.json, re-authenticate
• "Google hasn't verified this app" → Click Advanced → Go to App (safe, it's your own app)

---

Q15: "How do I use Euri with CrewAI / AutoGen / other frameworks?"

Same pattern — Euri is OpenAI-compatible:

CrewAI:

from crewai import LLM

llm = LLM(
    model="openai/gemini-2.5-flash",
    api_key="your-euri-key",
    base_url="https://api.euron.one/api/v1/euri"
)

AutoGen:

config_list = [{
    "model": "gemini-2.5-flash",
    "api_key": "your-euri-key",
    "base_url": "https://api.euron.one/api/v1/euri"
}]

LiteLLM:

import litellm
response = litellm.completion(
    model="openai/gemini-2.5-flash",
    api_key="your-euri-key",
    api_base="https://api.euron.one/api/v1/euri",
    messages=[{"role": "user", "content": "Hello!"}]
)

Rule of thumb: Any framework that supports custom base_url or OpenAI-compatible endpoints works with Euri. Just swap the base URL.

---

Q16: "How many tokens do I get? What's the limit?"

• 200,000 tokens per day (input + output combined)
• Resets at midnight UTC
• That's roughly 150,000 words or 300+ pages of text per day
• For practicals, this is more than enough — you won't hit limits during class
• Tip: Use gpt-4.1-nano or gemini-2.5-flash-lite for testing to conserve tokens

---

Q17: "Where do I get my API key?"

1. Go to https://euron.one/euri
2. Sign in with your Euron account
3. Copy your API key from the dashboard
4. Use it as api_key in code or Authorization: Bearer <key> in HTTP headers

---

Q18: "Can I use Euri for free?"

Yes! Euri gives 200,000 free tokens per day. No credit card needed. Access to all 24 models including GPT-4.1, Gemini 2.5, Llama 4, and more.

---

RESPONSE TEMPLATE

When answering bootcamp doubts, use this format:

Hey [Name]! [Short explanation of the fix]

[Code snippet — copy-paste ready]

[One-line explanation of what changed]

Good free models to use:
- gpt-4.1-nano — fast & cheap
- gemini-2.5-flash — best general purpose
- gemini-2.5-pro — smartest

You get 200K free tokens/day so you won't hit limits during practicals.

---

FILES REFERENCE

For deeper answers, check these files:

• Full API docs: Angelina AI System/Euron/README.md
• TypeScript client: Angelina AI System/Euron/euri-client.ts
• Model definitions: Angelina AI System/Euron/euri-models.ts
• Python examples: Angelina AI System/Euron/examples/python-sdk.py
• TypeScript examples: Angelina AI System/Euron/examples/basic-chat.ts
• n8n integration: Angelina AI System/Euron/examples/n8n-http-request.md
• MCP setup guide: Angelina AI System/Euron/MAIL-MCP-SETUP.md
• Model Arena: Angelina AI System/Euron/model-arena/arena.html
• API Tester: Angelina AI System/Euron/euri-tester/index.html

---

Schema

Inputs

Name	Type	Required	Description
question	string	Yes	Bootcamp student question about Euri API, MCP, models, or errors

Outputs

Name	Type	Description
answer	string	Copy-paste ready answer with code snippets

Cost

Free (reference lookup only)