Set up your environment variables to connect to Future AGI. Get your API keys here
import os
os.environ["FI_API_KEY"] = "YOUR_API_KEY"
os.environ["FI_SECRET_KEY"] = "YOUR_SECRET_KEY"
import os
os.environ["FI_API_KEY"] = "YOUR_API_KEY"
os.environ["FI_SECRET_KEY"] = "YOUR_SECRET_KEY"
process.env.FI_API_KEY = FI_API_KEY;
process.env.FI_SECRET_KEY = FI_SECRET_KEY;
2. Register Your Observe Project
Register your project with the necessary configuration.
from fi_instrumentation import register, Transport
from fi_instrumentation.fi_types import ProjectType
# Setup OTel via our register function
trace_provider = register(
project_type=ProjectType.OBSERVE,
project_name="FUTURE_AGI", # Your project name
session_name="chat-bot" # Session name
transport=Transport.GRPC, # Transport mechanism for your traces
)
from fi_instrumentation import register, Transport
from fi_instrumentation.fi_types import ProjectType
# Setup OTel via our register function
trace_provider = register(
project_type=ProjectType.OBSERVE,
project_name="FUTURE_AGI", # Your project name
session_name="chat-bot" # Session name
transport=Transport.GRPC, # Transport mechanism for your traces
)
import { register, ProjectType } from "@traceai/fi-core";
const traceProvider = register({
project_type: ProjectType.OBSERVE,
project_name: "FUTURE_AGI",
session_name: "chat-bot"
});
Configuration Parameters:
- project_type: Set as
ProjectType.OBSERVE for observe
- project_name: A descriptive name for your project
- session_name: A descriptive name for your session . Learn more about sessions
- transport (optional): Set the transport for your traces. The available options are
GRPC and HTTP.
Instrument your project:
There are 2 ways to implement tracing in your project
- Auto Instrumentor : Instrument your project with FutureAGI’s Auto Instrumentor. Recommended for most use cases.
- Manual Tracing : Manually track your project with Open Telemetry. Useful for more customized tracing. Learn more →
Example: Instrumenting with Auto Instrumentor ( OpenAI )
First, install the traceAI openai package:
pip install traceAI-openai
pip install traceAI-openai
npm install @traceai/openai
Instrument your project with FutureAGI’s OpenAI Instrumentor.
from traceai_openai import OpenAIInstrumentor
OpenAIInstrumentor().instrument(tracer_provider=trace_provider)
from traceai_openai import OpenAIInstrumentor
OpenAIInstrumentor().instrument(tracer_provider=trace_provider)
import { OpenAIInstrumentation } from "@traceai/openai";
const openaiInstrumentation = new OpenAIInstrumentation({});
Initialize the OpenAI client and make OpenAI requests as you normally would. Our Instrumentor will automatically trace these requests for you, which can be viewed in your Observe dashboard.
from openai import OpenAI
os.environ["OPENAI_API_KEY"] = "your-openai-api-key"
client = OpenAI()
completion = client.chat.completions.create(
model="gpt-4o",
messages=[
{
"role": "user",
"content": "Write a one-sentence bedtime story about a unicorn."
}
]
)
print(completion.choices[0].message.content)
from openai import OpenAI
os.environ["OPENAI_API_KEY"] = "your-openai-api-key"
client = OpenAI()
completion = client.chat.completions.create(
model="gpt-4o",
messages=[
{
"role": "user",
"content": "Write a one-sentence bedtime story about a unicorn."
}
]
)
print(completion.choices[0].message.content)
import { OpenAI } from "openai";
const client = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
});
const completion = await client.chat.completions.create({
model: "gpt-4o",
messages: [{ role: "user", content: "Write a one-sentence bedtime story about a unicorn." }],
});
console.log(completion.choices[0].message.content);
To know more about the supported frameworks and how to instrument them, check out our Auto Instrumentation page.
