Metadata-Version: 2.4
Name: neuraltrust
Version: 1.5.0
Summary: Python SDK for AI agent telemetry and observability
Author-email: Neuraltrust <support@neuraltrust.ai>
License: MIT
Project-URL: Homepage, https://neuraltrust.ai
Project-URL: Documentation, https://github.com/neuraltrust/neuraltrust-instrumentation#readme
Project-URL: Repository, https://github.com/neuraltrust/neuraltrust-instrumentation
Project-URL: Issues, https://github.com/neuraltrust/neuraltrust-instrumentation/issues
Keywords: ai,agents,telemetry,observability,monitoring,openai,llm,tracing
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: System :: Monitoring
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: httpx>=0.26
Requires-Dist: openai-agents>=0.3.3
Requires-Dist: pydantic>=2.6
Requires-Dist: typing-extensions>=4.7
Provides-Extra: dev
Requires-Dist: pytest>=8.2; extra == "dev"
Requires-Dist: fastapi>=0.118; extra == "dev"
Requires-Dist: uvicorn[standard]>=0.37; extra == "dev"
Dynamic: license-file

# Neuraltrust SDK

Python SDK for instrumenting AI agent libraries to send telemetry to the Neuraltrust platform.

## Features

- 🔌 **OpenAI Agents SDK integration** via custom trace processor
- 📊 **Automatic span capture**: LLM calls, tool executions, agent runs, handoffs, guardrails
- 🚀 **Async batching transport** with exponential backoff and retry logic
- 🎯 **Sampling support** for high-volume production workloads
- 🔧 **Configurable via environment variables** or programmatic config
- 🧪 **Local test server** included for development

## Installation

Install the SDK using pip:

```bash
pip install neuraltrust
```

Or with uv:

```bash
uv add neuraltrust
```

## Quick Start (OpenAI Agents)

```python
from agents import Agent, Runner
from neuraltrust import register_openai_tracing

# Register the Neuraltrust trace processor
register_openai_tracing()

# Your agent code runs normally
agent = Agent(name="Assistant", instructions="You are helpful")
result = await Runner.run(agent, "Hello!")
```

## Configuration

### Environment Variables

```bash
# Required
export NEURALTRUST_API_KEY=your-api-key

# Optional
export NEURALTRUST_ENDPOINT=https://telemetry.neuraltrust.ai/v1/traces/batch
export NEURALTRUST_BATCH_SIZE=25
export NEURALTRUST_FLUSH_INTERVAL=2.0
export NEURALTRUST_TIMEOUT=5.0
export NEURALTRUST_MAX_RETRIES=3
export NEURALTRUST_SAMPLING_RATE=1.0

# Custom metadata (any NEURALTRUST_METADATA_* vars)
export NEURALTRUST_METADATA_ENVIRONMENT=production
export NEURALTRUST_METADATA_VERSION=1.2.3
```

### Programmatic Configuration

```python
from neuraltrust import TelemetryConfig, register_openai_tracing

config = TelemetryConfig(
    api_key="your-api-key",
    endpoint="https://telemetry.neuraltrust.ai/v1/traces/batch",
    batch_size=25,
    flush_interval_seconds=2.0,
    sampling_rate=0.1,  # Sample 10% of traces
    metadata={"environment": "staging", "version": "2.0.0"},
)

register_openai_tracing(config=config, replace_default=True)
```

### Replace Default Exporters

By default, the SDK adds Neuraltrust telemetry **in addition to** OpenAI's default trace exporter. To disable OpenAI's exporter and send traces only to Neuraltrust:

```python
register_openai_tracing(replace_default=True)
```

Or via environment variable:

```bash
export NEURALTRUST_REPLACE_DEFAULT=1
```

## Development & Testing

### Local Test Server

Start the included test API server:

```bash
uv run uvicorn examples.api.temp_server:app --host 127.0.0.1 --port 8000
```

Configure your SDK to point to it:

```bash
export NEURALTRUST_ENDPOINT=http://127.0.0.1:8000/v1/traces/batch
export NEURALTRUST_API_KEY=dummy
export NEURALTRUST_REPLACE_DEFAULT=1
```

Run the example:

```bash
uv run python examples/openai_agents/basic.py "your message here"
```

Inspect captured traces:

```bash
curl http://127.0.0.1:8000/v1/traces | jq
```

Reset stored traces:

```bash
curl -X DELETE http://127.0.0.1:8000/v1/traces
```

## Trace Data Structure

Each trace envelope contains:

- **Resource metadata**: SDK version, language, library name/version
- **Traces**: One or more logical workflows
  - `trace_id`: Unique identifier
  - `workflow_name`: Human-readable workflow name
  - `group_id`: Optional grouping (e.g., chat session ID)
  - `started_at` / `ended_at`: Unix timestamps
  - `attributes`: Key-value metadata
  - **Spans**: Individual operations within the trace
    - `id`: Unique span identifier
    - `parent_id`: Parent span (null for root)
    - `name`: Operation name (e.g., "Echo", "Response", "translate_to_french")
    - `kind`: Span type (`workflow`, `llm`, `tool`, `guardrail`, `handoff`)
    - `status`: Execution status (`ok`, `error`)
    - `started_at` / `ended_at`: Unix timestamps
    - `attributes`: Span-specific metadata (model, usage tokens, I/O, etc.)
    - `events`: Time-stamped events within the span

## Backend API Specification

See [`docs/backend/endpoints.md`](docs/backend/endpoints.md) for the complete backend API specification, including:

- `POST /v1/traces/batch`: Batch trace ingestion
- `GET /v1/traces/{trace_id}`: Retrieve trace by ID
- `POST /v1/traces/heartbeat`: Client health check
- Authentication, error codes, retry logic

## Span Attributes

### LLM Spans (`kind=llm`)

- `model`: Model identifier (e.g., `gpt-4o-mini-2024-07-18`)
- `response_model`, `response_output`: Response data
- `usage_input_tokens`, `usage_output_tokens`, `usage_total_tokens`: Token counts
- `temperature`: Sampling temperature

### Tool/Function Spans (`kind=tool`)

- `function_name`: Name of the tool/function
- `function_input`: Serialized input arguments
- `function_output`: Serialized output

### Workflow/Agent Spans (`kind=workflow`)

- `agent_tools`: Available tools
- `agent_handoffs`: Available handoff targets
- `agent_output_type`: Expected output type

### Guardrail Spans (`kind=guardrail`)

- `guardrail_triggered`: Whether the guardrail was triggered

### Handoff Spans (`kind=handoff`)

- `handoff_from`: Source agent
- `handoff_to`: Target agent

## Architecture

```
┌─────────────────────────────────────────────┐
│ OpenAI Agents SDK                           │
│   ├─ Agent runs                             │
│   ├─ LLM generations                        │
│   └─ Tool calls                             │
└──────────────┬──────────────────────────────┘
               │ TracingProcessor interface
               ▼
┌─────────────────────────────────────────────┐
│ NeuraltrustTraceProcessor                   │
│   ├─ Buffers spans per trace                │
│   ├─ Extracts span_data attributes          │
│   └─ Emits TraceEnvelope on trace end       │
└──────────────┬──────────────────────────────┘
               │
               ▼
┌─────────────────────────────────────────────┐
│ TelemetryClient                             │
│   ├─ Sampling                               │
│   └─ Async envelope queueing                │
└──────────────┬──────────────────────────────┘
               │
               ▼
┌─────────────────────────────────────────────┐
│ TelemetryTransport                          │
│   ├─ Background flush loop                  │
│   ├─ Batching (default: 25 items)           │
│   ├─ Exponential backoff retry              │
│   └─ HTTP POST with Bearer auth             │
└──────────────┬──────────────────────────────┘
               │
               ▼
┌─────────────────────────────────────────────┐
│ Neuraltrust Telemetry API                   │
│   POST /v1/traces/batch                     │
└─────────────────────────────────────────────┘
```

## Debugging

Enable debug logging to see trace/span lifecycle events:

```python
import logging
logging.basicConfig(level=logging.DEBUG)
```

Or via environment:

```bash
export LOG_LEVEL=DEBUG
```

Key log messages:

- `Trace started; trace_id=...`
- `Span ended; span_id=... stored_spans=N`
- `Trace envelope prepared; trace_id=... span_count=N`
- `Telemetry batch sent; items=N status=202`

## Future Roadmap

- [ ] LangChain integration
- [ ] LlamaIndex integration
- [ ] CrewAI integration
- [ ] OpenTelemetry exporter
- [ ] Prometheus metrics
- [ ] Local SQLite storage option

## License

MIT
