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* fix(vertex_ai): forward system and tools to partner model count_tokens Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(vertex_ai): avoid mutable token request construction Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(vertex_ai): return partner count_tokens provider errors as values so the proxy falls back locally * test(integration): cover Vertex AI partner count_tokens forwarding and local fallbacks Add wire-level cells for /v1/messages/count_tokens, /utils/token_counter, /v1/responses/input_tokens and the Gemini countTokens route on a Vertex AI Claude deployment: the system prompt and tools reach the partner count-tokens endpoint verbatim, null fields stay out of the body, malformed tools are rejected before any peer call, peer, token-endpoint and connection failures fall back to the local tokenizer unless disable_token_counter is set, generation on the same deployment keeps working, and concurrent bursts survive a peer outage, a slow peer and a worker SIGKILL. The sdk cells cover litellm.acount_tokens the same way. The _support/process.py and _support/client.py harness files are brought to main's content so the self-booting cells read INTEGRATION_PROXY_READY_SECONDS instead of a fixed 70 s boot budget. --------- Co-authored-by: jesus <jesus@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
31 lines
960 B
Python
31 lines
960 B
Python
from __future__ import annotations
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import json
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from typing import Final
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from cryptography.hazmat.primitives import serialization
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from cryptography.hazmat.primitives.asymmetric import rsa
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def service_account_json(project: str, token_url: str) -> str:
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private_key: Final = (
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rsa.generate_private_key(public_exponent=65537, key_size=2048)
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.private_bytes(
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serialization.Encoding.PEM,
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serialization.PrivateFormat.PKCS8,
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serialization.NoEncryption(),
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)
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.decode()
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)
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return json.dumps(
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{
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"type": "service_account",
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"project_id": project,
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"private_key_id": "scripted",
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"private_key": private_key,
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"client_email": f"scripted@{project}.iam.gserviceaccount.com",
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"client_id": "0",
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"auth_uri": f"{token_url}/_oauth/authorize",
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"token_uri": f"{token_url}/_oauth/token",
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}
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)
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