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Some applications use httpx or requests to talk to model providers directly — for example calling a custom endpoint, a self-hosted model, or a provider whose official Python SDK is not yet supported. The SDK’s HTTP fallback patches these libraries so those calls can be governed too.

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When to enable it

Enable the HTTP fallback when:
  • You call an LLM endpoint via httpx.post / requests.post rather than via the official openai, anthropic, or google-generativeai SDKs.
  • You want broad audit coverage across miscellaneous outbound model traffic.
If you only use the official provider SDKs, you don’t need this — those integrations already cover their full call surface.

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Configuration

The HTTP fallback is on by default. Disable it with: 
egisai.init(..., enable_http_fallback=False)

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Use

No code changes required — once egisai.init() runs with enable_http_fallback=True (the default), httpx.Client.send and requests.Session.send are wrapped. 
import egisai
import httpx

egisai.init(app="custom-llm-bot", env="production")

resp = httpx.post(
    "https://api.example-provider.com/v1/generate",
    headers={"Authorization": "Bearer …"},
    json={"prompt": "Hello", "model": "example-large"},
)
The wrapper:
  1. Inspects the URL to identify model-host traffic.
  2. Routes the call through the same evaluation pipeline used for the official SDKs.
  3. Audits the verdict.
When a call has already been gated by one of the official-SDK adapters in the same call chain, the HTTP wrapper detects this and skips re-evaluation to avoid double-counting.

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Notes and limitations

  • The fallback only inspects bodies it can decode as JSON. Calls using other content types are recorded but not policy-checked.
  • Streaming over HTTP (server-sent events / chunked transfer) is recorded as a single event when the connection closes.
  • For best fidelity with provider-specific call shapes, prefer the official SDK integration when one is available.

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What’s next

Configuration

Troubleshooting