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Merge pull request #287 from derkoe/feat/add-azure-openai-manifold-pi…
…peline Add Azure OpenAI manifold pipeline example
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examples/pipelines/providers/azure_openai_manifold_pipeline.py
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from typing import List, Union, Generator, Iterator | ||
from pydantic import BaseModel | ||
import requests | ||
import os | ||
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class Pipeline: | ||
class Valves(BaseModel): | ||
# You can add your custom valves here. | ||
AZURE_OPENAI_API_KEY: str | ||
AZURE_OPENAI_ENDPOINT: str | ||
AZURE_OPENAI_API_VERSION: str | ||
AZURE_OPENAI_MODELS: str | ||
AZURE_OPENAI_MODEL_NAMES: str | ||
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def __init__(self): | ||
self.type = "manifold" | ||
self.name = "Azure OpenAI: " | ||
self.valves = self.Valves( | ||
**{ | ||
"AZURE_OPENAI_API_KEY": os.getenv("AZURE_OPENAI_API_KEY", "your-azure-openai-api-key-here"), | ||
"AZURE_OPENAI_ENDPOINT": os.getenv("AZURE_OPENAI_ENDPOINT", "your-azure-openai-endpoint-here"), | ||
"AZURE_OPENAI_API_VERSION": os.getenv("AZURE_OPENAI_API_VERSION", "2024-02-01"), | ||
"AZURE_OPENAI_MODELS": os.getenv("AZURE_OPENAI_MODELS", "gpt-35-turbo;gpt-4o"), | ||
"AZURE_OPENAI_MODEL_NAMES": os.getenv("AZURE_OPENAI_MODEL_NAMES", "GPT-35 Turbo;GPT-4o"), | ||
} | ||
) | ||
self.set_pipelines() | ||
pass | ||
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def set_pipelines(self): | ||
models = self.valves.AZURE_OPENAI_MODELS.split(";") | ||
model_names = self.valves.AZURE_OPENAI_MODEL_NAMES.split(";") | ||
self.pipelines = [ | ||
{"id": model, "name": name} for model, name in zip(models, model_names) | ||
] | ||
print(f"azure_openai_manifold_pipeline - models: {self.pipelines}") | ||
pass | ||
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async def on_valves_updated(self): | ||
self.set_pipelines() | ||
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async def on_startup(self): | ||
# This function is called when the server is started. | ||
print(f"on_startup:{__name__}") | ||
pass | ||
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async def on_shutdown(self): | ||
# This function is called when the server is stopped. | ||
print(f"on_shutdown:{__name__}") | ||
pass | ||
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def pipe( | ||
self, user_message: str, model_id: str, messages: List[dict], body: dict | ||
) -> Union[str, Generator, Iterator]: | ||
# This is where you can add your custom pipelines like RAG. | ||
print(f"pipe:{__name__}") | ||
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print(messages) | ||
print(user_message) | ||
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headers = { | ||
"api-key": self.valves.AZURE_OPENAI_API_KEY, | ||
"Content-Type": "application/json", | ||
} | ||
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url = f"{self.valves.AZURE_OPENAI_ENDPOINT}/openai/deployments/{model_id}/chat/completions?api-version={self.valves.AZURE_OPENAI_API_VERSION}" | ||
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allowed_params = {'messages', 'temperature', 'role', 'content', 'contentPart', 'contentPartImage', | ||
'enhancements', 'dataSources', 'n', 'stream', 'stop', 'max_tokens', 'presence_penalty', | ||
'frequency_penalty', 'logit_bias', 'user', 'function_call', 'funcions', 'tools', | ||
'tool_choice', 'top_p', 'log_probs', 'top_logprobs', 'response_format', 'seed'} | ||
# remap user field | ||
if "user" in body and not isinstance(body["user"], str): | ||
body["user"] = body["user"]["id"] if "id" in body["user"] else str(body["user"]) | ||
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()))}") | ||
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try: | ||
r = requests.post( | ||
url=url, | ||
json=filtered_body, | ||
headers=headers, | ||
stream=True, | ||
) | ||
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r.raise_for_status() | ||
if body["stream"]: | ||
return r.iter_lines() | ||
else: | ||
return r.json() | ||
except Exception as e: | ||
if r: | ||
text = r.text | ||
return f"Error: {e} ({text})" | ||
else: | ||
return f"Error: {e}" |