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tessl/pypi-portkey-ai

Python client library for the Portkey API - Control Panel for AI Apps with unified API signature, automated fallbacks, retries, load balancing, semantic caching, virtual keys, and comprehensive observability features.

Pending
Overview
Eval results
Files

fine-tuning.mddocs/

Fine-Tuning

Model fine-tuning capabilities with job management, checkpoint handling, and training monitoring.

Capabilities

class FineTuning:
    jobs: Jobs
    checkpoints: Checkpoints

class Jobs:
    def create(self, **kwargs): ...
    def list(self, **kwargs): ...
    def retrieve(self, **kwargs): ...
    def cancel(self, **kwargs): ...

class Checkpoints:
    def list(self, **kwargs): ...
    def retrieve(self, **kwargs): ...

Usage Examples

# Create fine-tuning job
job = portkey.fine_tuning.jobs.create(
    training_file="file-123",
    model="gpt-3.5-turbo"
)

# Monitor job
job_status = portkey.fine_tuning.jobs.retrieve(job.id)

Install with Tessl CLI

npx tessl i tessl/pypi-portkey-ai

docs

administration.md

assistants-threads.md

batch-processing.md

beta-realtime.md

chat-completions.md

configuration-management.md

container-content.md

core-client.md

embeddings.md

evaluation-testing.md

feedback-collections.md

file-management.md

fine-tuning.md

framework-integrations.md

index.md

key-management.md

models.md

multimodal-apis.md

observability-analytics.md

prompt-management.md

provider-integration.md

text-completions.md

uploads.md

vector-stores.md

tile.json