""" title: GitHub Models Manifold (models.github.ai) author: unleashit author_url: https://gist.github.com/unleashit/e76ed4cd9667d03145b6aa826d0b3d4a version: 0.1 """ from typing import List, Union, Generator, Iterator from pydantic import BaseModel import requests class Pipe: class Valves(BaseModel): GITHUB_PAT: str = "" GITHUB_MODELS_BASE_URL: str = "https://models.github.ai" def __init__(self): self.id = "github_models" self.type = "manifold" self.name = "GitHub: " self.valves = self.Valves() self.pipelines = self.get_github_models() def get_github_models(self): if self.valves.GITHUB_PAT: try: headers = { "Authorization": f"Bearer {self.valves.GITHUB_PAT}", "Content-Type": "application/json", "Accept": "application/vnd.github+json", } r = requests.get( f"{self.valves.GITHUB_MODELS_BASE_URL}/catalog/models", headers=headers, ) models = r.json() return [ { "id": model["id"], "name": model["name"], "description": (model["summary"] if "summary" in model else ""), } for model in models if "text" in model["supported_input_modalities"] ] except Exception as e: print(f"Error: {e}") return [ { "id": "error", "name": "Could not fetch models from GitHub Models, please update the PAT in the valves.", }, ] else: return [] def pipes(self) -> List[dict]: return self.get_github_models() def pipe(self, body: dict) -> Union[str, Generator, Iterator]: # This is where you can add your custom pipelines like RAG. print(f"pipe:{__name__}") headers = { "Authorization": f"Bearer {self.valves.GITHUB_PAT}", "Content-Type": "application/json", } allowed_params = { "messages", "temperature", "top_p", "stream", "stop", "model", "max_tokens", "stream_options", } # Remap the model name to the model id body["model"] = ".".join(body["model"].split(".")[1:]) filtered_body = {k: v for k, v in body.items() if k in allowed_params} # log fields that were filtered out as a single line if len(body) != len(filtered_body): print( f"Dropped params: {', '.join(set(body.keys()) - set(filtered_body.keys()))}" ) try: r = requests.post( url=f"{self.valves.GITHUB_MODELS_BASE_URL}/inference/chat/completions", json=filtered_body, headers=headers, stream=True, ) r.raise_for_status() if body["stream"]: return r.iter_lines() else: return r.json() except Exception as e: return f"Error: {e} {r.text}"