mirror of
https://github.com/FoundationAgents/MetaGPT.git
synced 2026-06-08 15:05:17 +02:00
feat: merge feature/skills
This commit is contained in:
莘权 马
commit
fb137b018c
22 changed files with 1018 additions and 54 deletions
2
.gitignore
vendored
2
.gitignore
vendored
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@ -167,3 +167,5 @@ output.wav
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# output folder
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output
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tmp.png
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|
|
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18
.well-known/ai-plugin.json
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18
.well-known/ai-plugin.json
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|
@ -0,0 +1,18 @@
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{
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||||
"schema_version": "v1",
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"name_for_model": "text processing tools",
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"name_for_human": "MetaGPT Text Plugin",
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"description_for_model": "Plugins for text processing, including text-to-speech, text-to-image, text-to-embedding, text summarization, text-to-code, vector similarity calculation, web content crawling, and more.",
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"description_for_human": "Plugins for text processing, including text-to-speech, text-to-image, text-to-embedding, text summarization, text-to-code, vector similarity calculation, web content crawling, and more.",
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||||
"auth": {
|
||||
"type": "none"
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||||
},
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||||
"api": {
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||||
"type": "openapi",
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||||
"url": "https://github.com/iorisa/MetaGPT/blob/feature/oas3/.well-known/metagpt_oas3_api.yaml",
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"has_user_authentication": false
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||||
},
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||||
"logo_url": "https://github.com/iorisa/MetaGPT/blob/feature/oas3/docs/resources/MetaGPT-logo.png",
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||||
"contact_email": "mashenquan@fuzhi.cn",
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||||
"legal_info_url": "https://github.com/iorisa/MetaGPT/blob/feature/oas3/docs/README_CN.md"
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}
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||||
236
.well-known/metagpt_oas3_api.yaml
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236
.well-known/metagpt_oas3_api.yaml
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@ -0,0 +1,236 @@
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openapi: "3.0.0"
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||||
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||||
info:
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||||
title: "MetaGPT Export OpenAPIs"
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||||
version: "1.0"
|
||||
servers:
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||||
- url: "/oas3"
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||||
variables:
|
||||
port:
|
||||
default: '8080'
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||||
description: HTTP service port
|
||||
|
||||
paths:
|
||||
/tts/azsure:
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||||
post:
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||||
summary: "Convert Text to Base64-encoded .wav File Stream"
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description: "For more details, check out: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
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||||
operationId: azure_tts.oas3_azsure_tts
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||||
requestBody:
|
||||
required: true
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
required:
|
||||
- text
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||||
properties:
|
||||
text:
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||||
type: string
|
||||
description: Text to convert
|
||||
lang:
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||||
type: string
|
||||
description: The language code or locale, e.g., en-US (English - United States)
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default: "zh-CN"
|
||||
voice:
|
||||
type: string
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||||
description: "Voice style, see: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts), [Voice Gallery](https://speech.microsoft.com/portal/voicegallery)"
|
||||
default: "zh-CN-XiaomoNeural"
|
||||
style:
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||||
type: string
|
||||
description: "Speaking style to express different emotions. For more details, checkout: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
|
||||
default: "affectionate"
|
||||
role:
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||||
type: string
|
||||
description: "Role to specify age and gender. For more details, checkout: [Azure Text-to_Speech](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts)"
|
||||
default: "Girl"
|
||||
subscription_key:
|
||||
type: string
|
||||
description: "Key used to access Azure AI service API, see: [Azure Portal](https://portal.azure.com/) > `Resource Management` > `Keys and Endpoint`"
|
||||
default: ""
|
||||
region:
|
||||
type: string
|
||||
description: "Location (or region) of your resource, see: [Azure Portal](https://portal.azure.com/) > `Resource Management` > `Keys and Endpoint`"
|
||||
default: ""
|
||||
responses:
|
||||
'200':
|
||||
description: "Base64-encoded .wav file data if successful, otherwise an empty string."
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
wav_data:
|
||||
type: string
|
||||
format: base64
|
||||
'400':
|
||||
description: "Bad Request"
|
||||
'500':
|
||||
description: "Internal Server Error"
|
||||
|
||||
/txt2img/openai:
|
||||
post:
|
||||
summary: "Convert Text to Base64-encoded Image Data Stream"
|
||||
operationId: openai_text_to_image.oas3_openai_text_to_image
|
||||
requestBody:
|
||||
required: true
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
text:
|
||||
type: string
|
||||
description: "The text used for image conversion."
|
||||
size_type:
|
||||
type: string
|
||||
enum: ["256x256", "512x512", "1024x1024"]
|
||||
default: "1024x1024"
|
||||
description: "Size of the generated image."
|
||||
openai_api_key:
|
||||
type: string
|
||||
default: ""
|
||||
description: "OpenAI API key, For more details, checkout: `https://platform.openai.com/account/api-keys`"
|
||||
responses:
|
||||
'200':
|
||||
description: "Base64-encoded image data."
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
image_data:
|
||||
type: string
|
||||
format: base64
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||||
'400':
|
||||
description: "Bad Request"
|
||||
'500':
|
||||
description: "Internal Server Error"
|
||||
/txt2embedding/openai:
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||||
post:
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||||
summary: Text to embedding
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||||
operationId: openai_text_to_embedding.oas3_openai_text_to_embedding
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||||
description: Retrieve an embedding for the provided text using the OpenAI API.
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||||
requestBody:
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||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
input:
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||||
type: string
|
||||
description: The text used for embedding.
|
||||
model:
|
||||
type: string
|
||||
description: "ID of the model to use. For more details, checkout: [models](https://api.openai.com/v1/models)"
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||||
enum:
|
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- text-embedding-ada-002
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responses:
|
||||
"200":
|
||||
description: Successful response
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
$ref: "#/components/schemas/ResultEmbedding"
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||||
"4XX":
|
||||
description: Client error
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||||
content:
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||||
application/json:
|
||||
schema:
|
||||
$ref: "#/components/schemas/Error"
|
||||
"5XX":
|
||||
description: Server error
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
$ref: "#/components/schemas/Error"
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||||
|
||||
/txt2image/metagpt:
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||||
post:
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||||
summary: "Text to Image"
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||||
description: "Generate an image from the provided text using the MetaGPT Text-to-Image API."
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||||
operationId: metagpt_text_to_image.oas3_metagpt_text_to_image
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||||
requestBody:
|
||||
required: true
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
required:
|
||||
- text
|
||||
properties:
|
||||
text:
|
||||
type: string
|
||||
description: "The text used for image conversion."
|
||||
size_type:
|
||||
type: string
|
||||
enum: ["512x512", "512x768"]
|
||||
default: "512x512"
|
||||
description: "Size of the generated image."
|
||||
model_url:
|
||||
type: string
|
||||
description: "Model reset API URL for text-to-image."
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||||
default: ""
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||||
responses:
|
||||
'200':
|
||||
description: "Base64-encoded image data."
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
image_data:
|
||||
type: string
|
||||
format: base64
|
||||
'400':
|
||||
description: "Bad Request"
|
||||
'500':
|
||||
description: "Internal Server Error"
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||||
|
||||
components:
|
||||
schemas:
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||||
Embedding:
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||||
type: object
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||||
description: Represents an embedding vector returned by the embedding endpoint.
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||||
properties:
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||||
object:
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||||
type: string
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||||
example: embedding
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||||
embedding:
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type: array
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||||
items:
|
||||
type: number
|
||||
example: [0.0023064255, -0.009327292, ...]
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||||
index:
|
||||
type: integer
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||||
example: 0
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||||
Usage:
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||||
type: object
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||||
properties:
|
||||
prompt_tokens:
|
||||
type: integer
|
||||
example: 8
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||||
total_tokens:
|
||||
type: integer
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||||
example: 8
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||||
ResultEmbedding:
|
||||
type: object
|
||||
properties:
|
||||
object:
|
||||
type: string
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||||
example: result_embedding
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||||
data:
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||||
type: array
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||||
items:
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||||
$ref: "#/components/schemas/Embedding"
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||||
model:
|
||||
type: string
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||||
example: text-embedding-ada-002
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||||
usage:
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||||
$ref: "#/components/schemas/Usage"
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||||
Error:
|
||||
type: object
|
||||
properties:
|
||||
error:
|
||||
type: string
|
||||
example: An error occurred
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||||
35
.well-known/openapi.yaml
Normal file
35
.well-known/openapi.yaml
Normal file
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@ -0,0 +1,35 @@
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|||
openapi: "3.0.0"
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||||
|
||||
info:
|
||||
title: Hello World
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||||
version: "1.0"
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||||
servers:
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||||
- url: /openapi
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||||
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||||
paths:
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||||
/greeting/{name}:
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||||
post:
|
||||
summary: Generate greeting
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||||
description: Generates a greeting message.
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||||
operationId: hello.post_greeting
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||||
responses:
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||||
200:
|
||||
description: greeting response
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||||
content:
|
||||
text/plain:
|
||||
schema:
|
||||
type: string
|
||||
example: "hello dave!"
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||||
parameters:
|
||||
- name: name
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||||
in: path
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||||
description: Name of the person to greet.
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||||
required: true
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||||
schema:
|
||||
type: string
|
||||
example: "dave"
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||||
requestBody:
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
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||||
|
|
@ -70,3 +70,6 @@ SD_T2I_API: "/sdapi/v1/txt2img"
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### for Research
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||||
MODEL_FOR_RESEARCHER_SUMMARY: gpt-3.5-turbo
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||||
MODEL_FOR_RESEARCHER_REPORT: gpt-3.5-turbo-16k
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||||
|
||||
### Meta Models
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#METAGPT_TEXT_TO_IMAGE_MODEL: MODEL_URL
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|
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@ -1,53 +0,0 @@
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|||
#!/usr/bin/env python
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||||
# -*- coding: utf-8 -*-
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||||
"""
|
||||
@Time : 2023/6/9 22:22
|
||||
@Author : Leo Xiao
|
||||
@File : azure_tts.py
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||||
"""
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from azure.cognitiveservices.speech import AudioConfig, SpeechConfig, SpeechSynthesizer
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|
||||
from metagpt.actions.action import Action
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from metagpt.config import Config
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||||
|
||||
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class AzureTTS(Action):
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def __init__(self, name, context=None, llm=None):
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super().__init__(name, context, llm)
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self.config = Config()
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||||
|
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# 参数参考：https://learn.microsoft.com/zh-cn/azure/cognitive-services/speech-service/language-support?tabs=tts#voice-styles-and-roles
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def synthesize_speech(self, lang, voice, role, text, output_file):
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subscription_key = self.config.get('AZURE_TTS_SUBSCRIPTION_KEY')
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||||
region = self.config.get('AZURE_TTS_REGION')
|
||||
speech_config = SpeechConfig(
|
||||
subscription=subscription_key, region=region)
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||||
|
||||
speech_config.speech_synthesis_voice_name = voice
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||||
audio_config = AudioConfig(filename=output_file)
|
||||
synthesizer = SpeechSynthesizer(
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speech_config=speech_config,
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audio_config=audio_config)
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||||
|
||||
# if voice=="zh-CN-YunxiNeural":
|
||||
ssml_string = f"""
|
||||
<speak version='1.0' xmlns='http://www.w3.org/2001/10/synthesis' xml:lang='{lang}' xmlns:mstts='http://www.w3.org/2001/mstts'>
|
||||
<voice name='{voice}'>
|
||||
<mstts:express-as style='affectionate' role='{role}'>
|
||||
{text}
|
||||
</mstts:express-as>
|
||||
</voice>
|
||||
</speak>
|
||||
"""
|
||||
|
||||
synthesizer.speak_ssml_async(ssml_string).get()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
azure_tts = AzureTTS("azure_tts")
|
||||
azure_tts.synthesize_speech(
|
||||
"zh-CN",
|
||||
"zh-CN-YunxiNeural",
|
||||
"Boy",
|
||||
"你好，我是卡卡",
|
||||
"output.wav")
|
||||
26
metagpt/learn/text_to_embedding.py
Normal file
26
metagpt/learn/text_to_embedding.py
Normal file
|
|
@ -0,0 +1,26 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/8/18
|
||||
@Author : mashenquan
|
||||
@File : text_to_embedding.py
|
||||
@Desc : Text-to-Embedding skill, which provides text-to-embedding functionality.
|
||||
"""
|
||||
import os
|
||||
|
||||
from metagpt.tools.openai_text_to_embedding import oas3_openai_text_to_embedding
|
||||
from metagpt.utils.common import initialize_environment
|
||||
|
||||
|
||||
def text_to_embedding(text, model="text-embedding-ada-002", openai_api_key=""):
|
||||
"""Text to embedding
|
||||
|
||||
:param text: The text used for embedding.
|
||||
:param model: One of ['text-embedding-ada-002'], ID of the model to use. For more details, checkout: `https://api.openai.com/v1/models`.
|
||||
:param openai_api_key: OpenAI API key, For more details, checkout: `https://platform.openai.com/account/api-keys`
|
||||
:return: A json object of :class:`ResultEmbedding` class if successful, otherwise `{}`.
|
||||
"""
|
||||
initialize_environment()
|
||||
if os.environ.get("OPENAI_API_KEY") or openai_api_key:
|
||||
return oas3_openai_text_to_embedding(text, model=model, openai_api_key=openai_api_key)
|
||||
raise EnvironmentError
|
||||
30
metagpt/learn/text_to_image.py
Normal file
30
metagpt/learn/text_to_image.py
Normal file
|
|
@ -0,0 +1,30 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/8/18
|
||||
@Author : mashenquan
|
||||
@File : text_to_image.py
|
||||
@Desc : Text-to-Image skill, which provides text-to-image functionality.
|
||||
"""
|
||||
import os
|
||||
|
||||
from metagpt.tools.metagpt_text_to_image import oas3_metagpt_text_to_image
|
||||
from metagpt.tools.openai_text_to_image import oas3_openai_text_to_image
|
||||
from metagpt.utils.common import initialize_environment
|
||||
|
||||
|
||||
def text_to_image(text, size_type: str = "512x512", openai_api_key="", model_url=""):
|
||||
"""Text to image
|
||||
|
||||
:param text: The text used for image conversion.
|
||||
:param openai_api_key: OpenAI API key, For more details, checkout: `https://platform.openai.com/account/api-keys`
|
||||
:param size_type: If using OPENAI, the available size options are ['256x256', '512x512', '1024x1024'], while for MetaGPT, the options are ['512x512', '512x768'].
|
||||
:param model_url: MetaGPT model url
|
||||
:return: The image data is returned in Base64 encoding.
|
||||
"""
|
||||
initialize_environment()
|
||||
if os.environ.get("METAGPT_TEXT_TO_IMAGE_MODEL") or model_url:
|
||||
return oas3_metagpt_text_to_image(text, size_type, model_url)
|
||||
if os.environ.get("OPENAI_API_KEY") or openai_api_key:
|
||||
return oas3_openai_text_to_image(text, size_type, openai_api_key)
|
||||
raise EnvironmentError
|
||||
35
metagpt/learn/text_to_speech.py
Normal file
35
metagpt/learn/text_to_speech.py
Normal file
|
|
@ -0,0 +1,35 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/8/17
|
||||
@Author : mashenquan
|
||||
@File : text_to_speech.py
|
||||
@Desc : Text-to-Speech skill, which provides text-to-speech functionality
|
||||
"""
|
||||
import os
|
||||
|
||||
from metagpt.tools.azure_tts import oas3_azsure_tts
|
||||
from metagpt.utils.common import initialize_environment
|
||||
|
||||
|
||||
def text_to_speech(text, lang="zh-CN", voice="zh-CN-XiaomoNeural", style="affectionate", role="Girl",
|
||||
subscription_key="", region=""):
|
||||
"""Text to speech
|
||||
For more details, check out:`https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts`
|
||||
|
||||
:param lang: The value can contain a language code such as en (English), or a locale such as en-US (English - United States). For more details, checkout: `https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts`
|
||||
:param voice: For more details, checkout: `https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts`, `https://speech.microsoft.com/portal/voicegallery`
|
||||
:param style: Speaking style to express different emotions like cheerfulness, empathy, and calm. For more details, checkout: `https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts`
|
||||
:param role: With roles, the same voice can act as a different age and gender. For more details, checkout: `https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts`
|
||||
:param text: The text used for voice conversion.
|
||||
:param subscription_key: key is used to access your Azure AI service API, see: `https://portal.azure.com/` > `Resource Management` > `Keys and Endpoint`
|
||||
:param region: This is the location (or region) of your resource. You may need to use this field when making calls to this API.
|
||||
:return: Returns the Base64-encoded .wav file data if successful, otherwise an empty string.
|
||||
|
||||
"""
|
||||
initialize_environment()
|
||||
if (os.environ.get("AZURE_TTS_SUBSCRIPTION_KEY") and os.environ.get("AZURE_TTS_REGION")) or \
|
||||
(subscription_key and region):
|
||||
return oas3_azsure_tts(text, lang, voice, style, role, subscription_key, region)
|
||||
|
||||
raise EnvironmentError
|
||||
114
metagpt/tools/azure_tts.py
Normal file
114
metagpt/tools/azure_tts.py
Normal file
|
|
@ -0,0 +1,114 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/8/17
|
||||
@Author : mashenquan
|
||||
@File : azure_tts.py
|
||||
@Desc : azure TTS OAS3 api, which provides text-to-speech functionality
|
||||
"""
|
||||
from pathlib import Path
|
||||
from uuid import uuid4
|
||||
import base64
|
||||
import sys
|
||||
|
||||
sys.path.append(str(Path(__file__).resolve().parent.parent.parent)) # fix-bug: No module named 'metagpt'
|
||||
from metagpt.utils.common import initialize_environment
|
||||
from metagpt.logs import logger
|
||||
|
||||
from azure.cognitiveservices.speech import AudioConfig, SpeechConfig, SpeechSynthesizer
|
||||
import os
|
||||
|
||||
|
||||
class AzureTTS:
|
||||
"""Azure Text-to-Speech"""
|
||||
|
||||
def __init__(self, subscription_key, region):
|
||||
"""
|
||||
:param subscription_key: key is used to access your Azure AI service API, see: `https://portal.azure.com/` > `Resource Management` > `Keys and Endpoint`
|
||||
:param region: This is the location (or region) of your resource. You may need to use this field when making calls to this API.
|
||||
"""
|
||||
self.subscription_key = subscription_key if subscription_key else os.environ.get('AZURE_TTS_SUBSCRIPTION_KEY')
|
||||
self.region = region if region else os.environ.get('AZURE_TTS_REGION')
|
||||
|
||||
# 参数参考：https://learn.microsoft.com/zh-cn/azure/cognitive-services/speech-service/language-support?tabs=tts#voice-styles-and-roles
|
||||
def synthesize_speech(self, lang, voice, text, output_file):
|
||||
speech_config = SpeechConfig(
|
||||
subscription=self.subscription_key, region=self.region)
|
||||
speech_config.speech_synthesis_voice_name = voice
|
||||
audio_config = AudioConfig(filename=output_file)
|
||||
synthesizer = SpeechSynthesizer(
|
||||
speech_config=speech_config,
|
||||
audio_config=audio_config)
|
||||
|
||||
# More detail: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-synthesis-markup-voice
|
||||
ssml_string = "<speak version='1.0' xmlns='http://www.w3.org/2001/10/synthesis' " \
|
||||
f"xml:lang='{lang}' xmlns:mstts='http://www.w3.org/2001/mstts'>" \
|
||||
f"<voice name='{voice}'>{text}</voice></speak>"
|
||||
|
||||
return synthesizer.speak_ssml_async(ssml_string).get()
|
||||
|
||||
@staticmethod
|
||||
def role_style_text(role, style, text):
|
||||
return f'<mstts:express-as role="{role}" style="{style}">{text}</mstts:express-as>'
|
||||
|
||||
@staticmethod
|
||||
def role_text(role, text):
|
||||
return f'<mstts:express-as role="{role}">{text}</mstts:express-as>'
|
||||
|
||||
@staticmethod
|
||||
def style_text(style, text):
|
||||
return f'<mstts:express-as style="{style}">{text}</mstts:express-as>'
|
||||
|
||||
|
||||
# Export
|
||||
def oas3_azsure_tts(text, lang="", voice="", style="", role="", subscription_key="", region=""):
|
||||
"""Text to speech
|
||||
For more details, check out:`https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts`
|
||||
|
||||
:param lang: The value can contain a language code such as en (English), or a locale such as en-US (English - United States). For more details, checkout: `https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts`
|
||||
:param voice: For more details, checkout: `https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts`, `https://speech.microsoft.com/portal/voicegallery`
|
||||
:param style: Speaking style to express different emotions like cheerfulness, empathy, and calm. For more details, checkout: `https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts`
|
||||
:param role: With roles, the same voice can act as a different age and gender. For more details, checkout: `https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts`
|
||||
:param text: The text used for voice conversion.
|
||||
:param subscription_key: key is used to access your Azure AI service API, see: `https://portal.azure.com/` > `Resource Management` > `Keys and Endpoint`
|
||||
:param region: This is the location (or region) of your resource. You may need to use this field when making calls to this API.
|
||||
:return: Returns the Base64-encoded .wav file data if successful, otherwise an empty string.
|
||||
|
||||
"""
|
||||
if not text:
|
||||
return ""
|
||||
|
||||
if not lang:
|
||||
lang = "zh-CN"
|
||||
if not voice:
|
||||
voice = "zh-CN-XiaomoNeural"
|
||||
if not role:
|
||||
role = "Girl"
|
||||
if not style:
|
||||
style = "affectionate"
|
||||
if not subscription_key:
|
||||
subscription_key = os.environ.get("AZURE_TTS_SUBSCRIPTION_KEY")
|
||||
if not region:
|
||||
region = os.environ.get("AZURE_TTS_REGION")
|
||||
|
||||
xml_value = AzureTTS.role_style_text(role=role, style=style, text=text)
|
||||
tts = AzureTTS(subscription_key=subscription_key, region=region)
|
||||
filename = Path(__file__).resolve().parent / (str(uuid4()).replace("-", "") + ".wav")
|
||||
try:
|
||||
tts.synthesize_speech(lang=lang, voice=voice, text=xml_value, output_file=str(filename))
|
||||
with open(str(filename), mode="rb") as reader:
|
||||
data = reader.read()
|
||||
base64_string = base64.b64encode(data).decode('utf-8')
|
||||
filename.unlink()
|
||||
except Exception as e:
|
||||
logger.error(f"text:{text}, error:{e}")
|
||||
return ""
|
||||
|
||||
return base64_string
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
initialize_environment()
|
||||
|
||||
v = oas3_azsure_tts("测试，test")
|
||||
print(v)
|
||||
27
metagpt/tools/hello.py
Normal file
27
metagpt/tools/hello.py
Normal file
|
|
@ -0,0 +1,27 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/5/2 16:03
|
||||
@Author : mashenquan
|
||||
@File : hello.py
|
||||
@Desc : Implement the OpenAPI Specification 3.0 demo and use the following command to test the HTTP service:
|
||||
|
||||
curl -X 'POST' \
|
||||
'http://localhost:8080/openapi/greeting/dave' \
|
||||
-H 'accept: text/plain' \
|
||||
-H 'Content-Type: application/json' \
|
||||
-d '{}'
|
||||
"""
|
||||
|
||||
import connexion
|
||||
|
||||
|
||||
# openapi implement
|
||||
def post_greeting(name: str) -> str:
|
||||
return f"Hello {name}\n"
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
app = connexion.AioHttpApp(__name__, specification_dir='../../.well-known/')
|
||||
app.add_api("openapi.yaml", arguments={"title": "Hello World Example"})
|
||||
app.run(port=8080)
|
||||
46
metagpt/tools/metagpt_oas3_api_svc.py
Normal file
46
metagpt/tools/metagpt_oas3_api_svc.py
Normal file
|
|
@ -0,0 +1,46 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/8/17
|
||||
@Author : mashenquan
|
||||
@File : metagpt_oas3_api_svc.py
|
||||
@Desc : MetaGPT OpenAPI Specification 3.0 REST API service
|
||||
"""
|
||||
import asyncio
|
||||
from pathlib import Path
|
||||
import sys
|
||||
|
||||
import connexion
|
||||
|
||||
sys.path.append(str(Path(__file__).resolve().parent.parent.parent)) # fix-bug: No module named 'metagpt'
|
||||
from metagpt.utils.common import initialize_environment
|
||||
|
||||
|
||||
def oas_http_svc():
|
||||
"""Start the OAS 3.0 OpenAPI HTTP service"""
|
||||
initialize_environment()
|
||||
|
||||
app = connexion.FlaskApp(__name__, specification_dir='../../.well-known/')
|
||||
app.add_api("metagpt_oas3_api.yaml")
|
||||
app.add_api("openapi.yaml")
|
||||
app.run(port=8080)
|
||||
|
||||
|
||||
async def async_main():
|
||||
"""Start the OAS 3.0 OpenAPI HTTP service in the background."""
|
||||
loop = asyncio.get_event_loop()
|
||||
loop.run_in_executor(None, oas_http_svc)
|
||||
|
||||
# TODO: replace following codes:
|
||||
while True:
|
||||
await asyncio.sleep(1)
|
||||
print("sleep")
|
||||
|
||||
|
||||
def main():
|
||||
oas_http_svc()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# asyncio.run(async_main())
|
||||
main()
|
||||
112
metagpt/tools/metagpt_text_to_image.py
Normal file
112
metagpt/tools/metagpt_text_to_image.py
Normal file
|
|
@ -0,0 +1,112 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/8/18
|
||||
@Author : mashenquan
|
||||
@File : metagpt_text_to_image.py
|
||||
@Desc : MetaGPT Text-to-Image OAS3 api, which provides text-to-image functionality.
|
||||
"""
|
||||
import base64
|
||||
import os
|
||||
import sys
|
||||
from pathlib import Path
|
||||
from typing import List, Dict
|
||||
|
||||
import requests
|
||||
from pydantic import BaseModel
|
||||
|
||||
sys.path.append(str(Path(__file__).resolve().parent.parent.parent)) # fix-bug: No module named 'metagpt'
|
||||
from metagpt.utils.common import initialize_environment
|
||||
from metagpt.logs import logger
|
||||
|
||||
|
||||
class MetaGPTText2Image:
|
||||
def __init__(self, model_url):
|
||||
"""
|
||||
:param model_url: Model reset api url
|
||||
"""
|
||||
self.model_url = model_url if model_url else os.environ.get('METAGPT_TEXT_TO_IMAGE_MODEL')
|
||||
|
||||
def text_2_image(self, text, size_type="512x512"):
|
||||
"""Text to image
|
||||
|
||||
:param text: The text used for image conversion.
|
||||
:param size_type: One of ['512x512', '512x768']
|
||||
:return: The image data is returned in Base64 encoding.
|
||||
"""
|
||||
|
||||
headers = {
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
dims = size_type.split("x")
|
||||
data = {
|
||||
"prompt": text,
|
||||
"negative_prompt": "(easynegative:0.8),black, dark,Low resolution",
|
||||
"override_settings": {"sd_model_checkpoint": "galaxytimemachinesGTM_photoV20"},
|
||||
"seed": -1,
|
||||
"batch_size": 1,
|
||||
"n_iter": 1,
|
||||
"steps": 20,
|
||||
"cfg_scale": 11,
|
||||
"width": int(dims[0]),
|
||||
"height": int(dims[1]), # 768,
|
||||
"restore_faces": False,
|
||||
"tiling": False,
|
||||
"do_not_save_samples": False,
|
||||
"do_not_save_grid": False,
|
||||
"enable_hr": False,
|
||||
"hr_scale": 2,
|
||||
"hr_upscaler": "Latent",
|
||||
"hr_second_pass_steps": 0,
|
||||
"hr_resize_x": 0,
|
||||
"hr_resize_y": 0,
|
||||
"hr_upscale_to_x": 0,
|
||||
"hr_upscale_to_y": 0,
|
||||
"truncate_x": 0,
|
||||
"truncate_y": 0,
|
||||
"applied_old_hires_behavior_to": None,
|
||||
"eta": None,
|
||||
"sampler_index": "DPM++ SDE Karras",
|
||||
"alwayson_scripts": {},
|
||||
}
|
||||
|
||||
class ImageResult(BaseModel):
|
||||
images: List
|
||||
parameters: Dict
|
||||
|
||||
try:
|
||||
response = requests.post(self.model_url, headers=headers, json=data)
|
||||
response.raise_for_status() # Raise an exception for 4xx or 5xx responses
|
||||
result = ImageResult(**response.json())
|
||||
if len(result.images) == 0:
|
||||
return ""
|
||||
return result.images[0]
|
||||
except requests.exceptions.RequestException as e:
|
||||
logger.error(f"An error occurred:{e}")
|
||||
return ""
|
||||
|
||||
|
||||
# Export
|
||||
def oas3_metagpt_text_to_image(text, size_type: str = "512x512", model_url=""):
|
||||
"""Text to image
|
||||
|
||||
:param text: The text used for image conversion.
|
||||
:param model_url: Model reset api
|
||||
:param size_type: One of ['512x512', '512x768']
|
||||
:return: The image data is returned in Base64 encoding.
|
||||
"""
|
||||
if not text:
|
||||
return ""
|
||||
if not model_url:
|
||||
model_url = os.environ.get('METAGPT_TEXT_TO_IMAGE_MODEL')
|
||||
return MetaGPTText2Image(model_url).text_2_image(text, size_type=size_type)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
initialize_environment()
|
||||
|
||||
v = oas3_metagpt_text_2_image("Panda emoji")
|
||||
data = base64.b64decode(v)
|
||||
with open("tmp.png", mode="wb") as writer:
|
||||
writer.write(data)
|
||||
print(v)
|
||||
92
metagpt/tools/openai_text_to_embedding.py
Normal file
92
metagpt/tools/openai_text_to_embedding.py
Normal file
|
|
@ -0,0 +1,92 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/8/18
|
||||
@Author : mashenquan
|
||||
@File : openai_text_to_embedding.py
|
||||
@Desc : OpenAI Text-to-Embedding OAS3 api, which provides text-to-embedding functionality.
|
||||
For more details, checkout: `https://platform.openai.com/docs/api-reference/embeddings/object`
|
||||
"""
|
||||
import os
|
||||
from pathlib import Path
|
||||
from typing import List
|
||||
|
||||
import requests
|
||||
from pydantic import BaseModel
|
||||
import sys
|
||||
|
||||
sys.path.append(str(Path(__file__).resolve().parent.parent.parent)) # fix-bug: No module named 'metagpt'
|
||||
from metagpt.utils.common import initialize_environment
|
||||
from metagpt.logs import logger
|
||||
|
||||
|
||||
class Embedding(BaseModel):
|
||||
"""Represents an embedding vector returned by embedding endpoint."""
|
||||
object: str # The object type, which is always "embedding".
|
||||
embedding: List[
|
||||
float] # The embedding vector, which is a list of floats. The length of vector depends on the model as listed in the embedding guide.
|
||||
index: int # The index of the embedding in the list of embeddings.
|
||||
|
||||
|
||||
class Usage(BaseModel):
|
||||
prompt_tokens: int
|
||||
total_tokens: int
|
||||
|
||||
|
||||
class ResultEmbedding(BaseModel):
|
||||
object: str
|
||||
data: List[Embedding]
|
||||
model: str
|
||||
usage: Usage
|
||||
|
||||
|
||||
class OpenAIText2Embedding:
|
||||
def __init__(self, openai_api_key):
|
||||
"""
|
||||
:param openai_api_key: OpenAI API key, For more details, checkout: `https://platform.openai.com/account/api-keys`
|
||||
"""
|
||||
self.openai_api_key = openai_api_key if openai_api_key else os.environ.get('OPENAI_API_KEY')
|
||||
|
||||
def text_2_embedding(self, text, model="text-embedding-ada-002"):
|
||||
"""Text to embedding
|
||||
|
||||
:param text: The text used for embedding.
|
||||
:param model: One of ['text-embedding-ada-002'], ID of the model to use. For more details, checkout: `https://api.openai.com/v1/models`.
|
||||
:return: A json object of :class:`ResultEmbedding` class if successful, otherwise `{}`.
|
||||
"""
|
||||
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer {self.openai_api_key}"
|
||||
}
|
||||
data = {"input": text, "model": model}
|
||||
try:
|
||||
response = requests.post("https://api.openai.com/v1/embeddings", headers=headers, json=data)
|
||||
response.raise_for_status() # Raise an exception for 4xx or 5xx responses
|
||||
return response.json()
|
||||
except requests.exceptions.RequestException as e:
|
||||
logger.error(f"An error occurred:{e}")
|
||||
return {}
|
||||
|
||||
|
||||
# Export
|
||||
def oas3_openai_text_to_embedding(text, model="text-embedding-ada-002", openai_api_key=""):
|
||||
"""Text to embedding
|
||||
|
||||
:param text: The text used for embedding.
|
||||
:param model: One of ['text-embedding-ada-002'], ID of the model to use. For more details, checkout: `https://api.openai.com/v1/models`.
|
||||
:param openai_api_key: OpenAI API key, For more details, checkout: `https://platform.openai.com/account/api-keys`
|
||||
:return: A json object of :class:`ResultEmbedding` class if successful, otherwise `{}`.
|
||||
"""
|
||||
if not text:
|
||||
return ""
|
||||
if not openai_api_key:
|
||||
openai_api_key = os.environ.get("OPENAI_API_KEY")
|
||||
return OpenAIText2Embedding(openai_api_key).text_2_embedding(text, model=model)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
initialize_environment()
|
||||
|
||||
v = oas3_openai_text_to_embedding("Panda emoji")
|
||||
print(v)
|
||||
100
metagpt/tools/openai_text_to_image.py
Normal file
100
metagpt/tools/openai_text_to_image.py
Normal file
|
|
@ -0,0 +1,100 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/8/17
|
||||
@Author : mashenquan
|
||||
@File : openai_text_to_image.py
|
||||
@Desc : OpenAI Text-to-Image OAS3 api, which provides text-to-image functionality.
|
||||
"""
|
||||
import base64
|
||||
import os
|
||||
import sys
|
||||
from pathlib import Path
|
||||
from typing import List
|
||||
|
||||
import requests
|
||||
from pydantic import BaseModel
|
||||
|
||||
sys.path.append(str(Path(__file__).resolve().parent.parent.parent)) # fix-bug: No module named 'metagpt'
|
||||
from metagpt.utils.common import initialize_environment
|
||||
from metagpt.logs import logger
|
||||
|
||||
|
||||
class OpenAIText2Image:
|
||||
def __init__(self, openai_api_key):
|
||||
"""
|
||||
:param openai_api_key: OpenAI API key, For more details, checkout: `https://platform.openai.com/account/api-keys`
|
||||
"""
|
||||
self.openai_api_key = openai_api_key if openai_api_key else os.environ.get('OPENAI_API_KEY')
|
||||
|
||||
def text_2_image(self, text, size_type="1024x1024"):
|
||||
"""Text to image
|
||||
|
||||
:param text: The text used for image conversion.
|
||||
:param size_type: One of ['256x256', '512x512', '1024x1024']
|
||||
:return: The image data is returned in Base64 encoding.
|
||||
"""
|
||||
|
||||
class ImageUrl(BaseModel):
|
||||
url: str
|
||||
|
||||
class ImageResult(BaseModel):
|
||||
data: List[ImageUrl]
|
||||
created: int
|
||||
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer {self.openai_api_key}"
|
||||
}
|
||||
data = {"prompt": text, "n": 1, "size": size_type}
|
||||
try:
|
||||
response = requests.post("https://api.openai.com/v1/images/generations", headers=headers, json=data)
|
||||
response.raise_for_status() # Raise an exception for 4xx or 5xx responses
|
||||
result = ImageResult(**response.json())
|
||||
except requests.exceptions.RequestException as e:
|
||||
logger.error(f"An error occurred:{e}")
|
||||
return ""
|
||||
if len(result.data) > 0:
|
||||
return OpenAIText2Image.get_image_data(result.data[0].url)
|
||||
return ""
|
||||
|
||||
@staticmethod
|
||||
def get_image_data(url):
|
||||
"""Fetch image data from a URL and encode it as Base64
|
||||
|
||||
:param url: Image url
|
||||
:return: Base64-encoded image data.
|
||||
"""
|
||||
try:
|
||||
response = requests.get(url)
|
||||
response.raise_for_status() # Raise an exception for 4xx or 5xx responses
|
||||
image_data = response.content
|
||||
base64_image = base64.b64encode(image_data).decode("utf-8")
|
||||
return base64_image
|
||||
|
||||
except requests.exceptions.RequestException as e:
|
||||
logger.error(f"An error occurred:{e}")
|
||||
return ""
|
||||
|
||||
|
||||
# Export
|
||||
def oas3_openai_text_to_image(text, size_type: str = "1024x1024", openai_api_key=""):
|
||||
"""Text to image
|
||||
|
||||
:param text: The text used for image conversion.
|
||||
:param openai_api_key: OpenAI API key, For more details, checkout: `https://platform.openai.com/account/api-keys`
|
||||
:param size_type: One of ['256x256', '512x512', '1024x1024']
|
||||
:return: The image data is returned in Base64 encoding.
|
||||
"""
|
||||
if not text:
|
||||
return ""
|
||||
if not openai_api_key:
|
||||
openai_api_key = os.environ.get("OPENAI_API_KEY")
|
||||
return OpenAIText2Image(openai_api_key).text_2_image(text, size_type=size_type)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
initialize_environment()
|
||||
|
||||
v = oas3_openai_text_to_image("Panda emoji")
|
||||
print(v)
|
||||
|
|
@ -4,14 +4,18 @@
|
|||
@Time : 2023/4/29 16:07
|
||||
@Author : alexanderwu
|
||||
@File : common.py
|
||||
@Modified By: mashenquan, 2023-8-17, add `initalize_enviroment()` to load `config/config.yaml` to `os.environ`
|
||||
"""
|
||||
import ast
|
||||
import contextlib
|
||||
import inspect
|
||||
import os
|
||||
import re
|
||||
from pathlib import Path
|
||||
from typing import List, Tuple
|
||||
|
||||
import yaml
|
||||
|
||||
from metagpt.logs import logger
|
||||
|
||||
|
||||
|
|
@ -254,3 +258,12 @@ def parse_recipient(text):
|
|||
pattern = r"## Send To:\s*([A-Za-z]+)\s*?" # hard code for now
|
||||
recipient = re.search(pattern, text)
|
||||
return recipient.group(1) if recipient else ""
|
||||
|
||||
|
||||
def initialize_environment():
|
||||
"""Load `config/config.yaml` to `os.environ`"""
|
||||
yaml_file_path = Path(__file__).resolve().parent.parent.parent / "config/config.yaml"
|
||||
with open(str(yaml_file_path), "r") as yaml_file:
|
||||
data = yaml.safe_load(yaml_file)
|
||||
for k, v in data.items():
|
||||
os.environ[k] = str(v)
|
||||
|
|
|
|||
|
|
@ -38,4 +38,6 @@ typing_extensions==4.5.0
|
|||
aiofiles
|
||||
libcst==1.0.1
|
||||
qdrant-client==1.4.0
|
||||
connexion[swagger-ui]
|
||||
aiohttp_jinja2
|
||||
|
||||
|
|
|
|||
0
tests/metagpt/learn/__init__.py
Normal file
0
tests/metagpt/learn/__init__.py
Normal file
40
tests/metagpt/learn/test_text_to_embedding.py
Normal file
40
tests/metagpt/learn/test_text_to_embedding.py
Normal file
|
|
@ -0,0 +1,40 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/8/18
|
||||
@Author : mashenquan
|
||||
@File : test_text_to_embedding.py
|
||||
@Desc : Unit tests.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import base64
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from metagpt.learn.text_to_embedding import text_to_embedding
|
||||
|
||||
|
||||
async def mock_text_to_embedding():
|
||||
class Input(BaseModel):
|
||||
input: str
|
||||
|
||||
inputs = [
|
||||
{"input": "Panda emoji"}
|
||||
]
|
||||
|
||||
for i in inputs:
|
||||
seed = Input(**i)
|
||||
data = text_to_embedding(seed.input)
|
||||
v = ResultEmbedding(**data)
|
||||
assert len(v.data) > 0
|
||||
|
||||
|
||||
def test_suite():
|
||||
loop = asyncio.get_event_loop()
|
||||
task = loop.create_task(mock_text_to_embedding())
|
||||
loop.run_until_complete(task)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
test_suite()
|
||||
41
tests/metagpt/learn/test_text_to_image.py
Normal file
41
tests/metagpt/learn/test_text_to_image.py
Normal file
|
|
@ -0,0 +1,41 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/8/18
|
||||
@Author : mashenquan
|
||||
@File : test_text_to_image.py
|
||||
@Desc : Unit tests.
|
||||
"""
|
||||
import asyncio
|
||||
import base64
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from metagpt.learn.text_to_image import text_to_image
|
||||
|
||||
|
||||
async def mock_text_to_image():
|
||||
class Input(BaseModel):
|
||||
input: str
|
||||
size_type: str
|
||||
|
||||
inputs = [
|
||||
{"input": "Panda emoji", "size_type": "512x512"}
|
||||
]
|
||||
|
||||
for i in inputs:
|
||||
seed = Input(**i)
|
||||
base64_data = text_to_image(seed.input)
|
||||
assert base64_data != ""
|
||||
print(f"{seed.input} -> {base64_data}")
|
||||
assert base64.b64decode(base64_data, validate=True)
|
||||
|
||||
|
||||
def test_suite():
|
||||
loop = asyncio.get_event_loop()
|
||||
task = loop.create_task(mock_text_to_image())
|
||||
loop.run_until_complete(task)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
test_suite()
|
||||
40
tests/metagpt/learn/test_text_to_speech.py
Normal file
40
tests/metagpt/learn/test_text_to_speech.py
Normal file
|
|
@ -0,0 +1,40 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/8/18
|
||||
@Author : mashenquan
|
||||
@File : test_text_to_speech.py
|
||||
@Desc : Unit tests.
|
||||
"""
|
||||
import asyncio
|
||||
import base64
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from metagpt.learn.text_to_speech import text_to_speech
|
||||
|
||||
|
||||
async def mock_text_to_speech():
|
||||
class Input(BaseModel):
|
||||
input: str
|
||||
|
||||
inputs = [
|
||||
{"input": "Panda emoji"}
|
||||
]
|
||||
|
||||
for i in inputs:
|
||||
seed = Input(**i)
|
||||
base64_data = text_to_speech(seed.input)
|
||||
assert base64_data != ""
|
||||
print(f"{seed.input} -> {base64_data}")
|
||||
assert base64.b64decode(base64_data, validate=True)
|
||||
|
||||
|
||||
def test_suite():
|
||||
loop = asyncio.get_event_loop()
|
||||
task = loop.create_task(mock_text_to_speech())
|
||||
loop.run_until_complete(task)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
test_suite()
|
||||
|
|
@ -4,8 +4,13 @@
|
|||
@Time : 2023/7/1 22:50
|
||||
@Author : alexanderwu
|
||||
@File : test_azure_tts.py
|
||||
@Modified By: mashenquan, 2023-8-17, move to `tools` folder.
|
||||
"""
|
||||
from metagpt.actions.azure_tts import AzureTTS
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
sys.path.append(str(Path(__file__).resolve().parent.parent.parent.parent)) # fix-bug: No module named 'metagpt'
|
||||
from metagpt.tools.azure_tts import AzureTTS
|
||||
|
||||
|
||||
def test_azure_tts():
|
||||
Loading…
Add table
Add a link
Reference in a new issue