返回提交历史
Modified
README.md
+1
-0
Modified
docs/async_client.md
+11
-2
Modified
docs/client.md
+8
-1
Modified
g4f/Provider/Airforce.py
+167
-159
Modified
g4f/Provider/AmigoChat.py
+11
-6
Modified
g4f/Provider/Blackbox.py
+18
-11
Added
g4f/Provider/Blackbox2.py
+69
-0
Modified
g4f/Provider/DeepInfraChat.py
+13
-35
Modified
g4f/Provider/ReplicateHome.py
+0
-2
Modified
g4f/Provider/__init__.py
+1
-1
Renamed
g4f/Provider/needs_auth/HuggingChat.py
+11
-8
Modified
g4f/Provider/needs_auth/HuggingFace.py
+2
-2
Modified
g4f/Provider/needs_auth/HuggingFace2.py
+2
-2
Modified
g4f/Provider/needs_auth/__init__.py
+2
-1
Modified
g4f/client/__init__.py
+20
-14
Modified
g4f/models.py
+36
-14
XFEstudio/gpt4free
update providers and documentation with image handling improvements (#2451)
* refactor(g4f/Provider/Airforce.py): Enhance Airforce provider with dynamic model fetching * refactor(g4f/Provider/Blackbox.py): Enhance Blackbox AI provider configuration and streamline code * feat(g4f/Provider/RobocodersAPI.py): Add RobocodersAPI new async chat provider * refactor(g4f/client/__init__.py): Improve provider handling in async_generate method * refactor(g4f/models.py): Update provider configurations for multiple models * refactor(g4f/Provider/Blackbox.py): Streamline model configuration and improve response handling * feat(g4f/Provider/DDG.py): Enhance model support and improve conversation handling * refactor(g4f/Provider/Copilot.py): Enhance Copilot provider with model support * refactor(g4f/Provider/AmigoChat.py): update models and improve code structure * chore(g4f/Provider/not_working/AIUncensored.): move AIUncensored to not_working directory * chore(g4f/Provider/not_working/Allyfy.py): remove Allyfy provider * Update (g4f/Provider/not_working/AIUncensored.py g4f/Provider/not_working/__init__.py) * refactor(g4f/Provider/ChatGptEs.py): Implement format_prompt for message handling * refactor(g4f/Provider/Blackbox.py): Update message formatting and improve code structure * refactor(g4f/Provider/LLMPlayground.py): Enhance text generation and error handling * refactor(g4f/Provider/needs_auth/PollinationsAI.py): move PollinationsAI to needs_auth directory * refactor(g4f/Provider/Liaobots.py): Update Liaobots provider models and aliases * feat(g4f/Provider/DeepInfraChat.py): Add new DeepInfra models and aliases * Update (g4f/Provider/__init__.py) * Update (g4f/models.py) * g4f/models.py * Update g4f/models.py * Update g4f/Provider/LLMPlayground.py * Update (g4f/models.py g4f/Provider/Airforce.py g4f/Provider/__init__.py g4f/Provider/LLMPlayground.py) * Update g4f/Provider/__init__.py * refactor(g4f/Provider/Airforce.py): Enhance text generation with retry and timeout * Update g4f/Provider/AmigoChat.py g4f/Provider/__init__.py * refactor(g4f/Provider/Blackbox.py): update model prefixes and image handling Fixes #2445 - Update model prefixes for gpt-4o, gemini-pro, and claude-sonnet-3.5 - Add 'gpt-3.5-turbo' alias for 'blackboxai' model - Modify image handling in create_async_generator method - Add 'imageGenerationMode' and 'webSearchModePrompt' flags to API request - Remove redundant 'imageBase64' field from image data structure * New provider (g4f/Provider/Blackbox2.py) Support for model llama-3.1-70b text generation * docs(docs/async_client.md): update AsyncClient API guide with minor improvements - Improve formatting and readability of code examples - Add line breaks for better visual separation of sections - Fix minor typos and inconsistencies in text - Enhance clarity of explanations in various sections - Remove unnecessary whitespace * feat(docs/client.md): add response_format parameter - Add 'response_format' parameter to image generation examples - Specify 'url' format for standard image generation - Include 'b64_json' format for base64 encoded image response - Update documentation to reflect new parameter usage - Improve code examples for clarity and consistency * docs(README.md): update usage examples and add image generation - Update text generation example to use new Client API - Add image generation example with Client API - Update configuration section with new cookie setting instructions - Add response_format parameter to image generation example - Remove outdated information and reorganize sections - Update contributors list * refactor(g4f/client/__init__.py): optimize image processing and response handling - Modify _process_image_response to handle 'url' format without local saving - Update ImagesResponse construction to include 'created' timestamp - Simplify image processing logic for different response formats - Improve error handling and logging for image generation - Enhance type hints and docstrings for better code clarity * feat(g4f/models.py): update model providers and add new models - Add Blackbox2 to Provider imports - Update gpt-3.5-turbo best provider to Blackbox - Add Blackbox2 to llama-3.1-70b best providers - Rename dalle_3 to dall_e_3 and update its best providers - Add new models: solar_mini, openhermes_2_5, lfm_40b, zephyr_7b, neural_7b, mythomax_13b - Update ModelUtils.convert with new models and changes - Remove duplicate 'dalle-3' entry in ModelUtils.convert * refactor(Airforce): improve API handling and add authentication - Implement API key authentication with check_api_key method - Refactor image generation to use new imagine2 endpoint - Improve text generation with better error handling and streaming - Update model aliases and add new image models - Enhance content filtering for various model outputs - Replace StreamSession with aiohttp's ClientSession for async operations - Simplify model fetching logic and remove redundant code - Add is_image_model method for better model type checking - Update class attributes for better organization and clarity * feat(g4f/Provider/HuggingChat.py): update HuggingChat model list and aliases Request by @TheFirstNoob - Add 'Qwen/Qwen2.5-72B-Instruct' as the first model in the list - Update model aliases to include 'qwen-2.5-72b' - Reorder existing models in the list for consistency - Remove duplicate entry for 'Qwen/Qwen2.5-72B-Instruct' in models list * refactor(g4f/Provider/ReplicateHome.py): remove unused text models Request by @TheFirstNoob - Removed the 'meta/meta-llama-3-70b-instruct' and 'mistralai/mixtral-8x7b-instruct-v0.1' text models from the list - Updated the list to only include the remaining text and image models - This change simplifies the model configuration and reduces the number of available models, focusing on the core text and image models provided by Replicate * refactor(g4f/Provider/HuggingChat.py): Move HuggingChat to needs_auth directory Request by @TheFirstNoob * Update (g4f/Provider/needs_auth/HuggingChat.py) * Update g4f/models.py * Update g4f/Provider/Airforce.py * Update g4f/models.py g4f/Provider/needs_auth/HuggingChat.py * Added 'Airforce' provider to the 'o1-mini' model (g4f/models.py) * Update (g4f/Provider/Airforce.py g4f/Provider/AmigoChat.py) * Update g4f/models.py g4f/Provider/DeepInfraChat.py g4f/Provider/Airforce.py * Update g4f/Provider/DeepInfraChat.py * Update (g4f/Provider/DeepInfraChat.py) * Update g4f/Provider/Blackbox.py * Update (docs/client.md docs/async_client.md g4f/client/__init__.py) * Update (docs/async_client.md docs/client.md) * Update (g4f/client/__init__.py) --------- Co-authored-by: kqlio67 <kqlio67@users.noreply.github.com> Co-authored-by: kqlio67 <> Co-authored-by: H Lohaus <hlohaus@users.noreply.github.com>
b198d900
代码差异
16 个文件
+372
-258
@@ -196,6 +196,7 @@ client = Client()
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response = client.images.generate(
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model="flux",
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prompt="a white siamese cat",
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response_format="url"
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# Add any other necessary parameters
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201
)
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@@ -164,6 +164,11 @@ asyncio.run(main())
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```
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### Image Generation
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**The `response_format` parameter is optional and can have the following values:**
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- **If not specified (default):** The image will be saved locally, and a local path will be returned (e.g., "/images/1733331238_cf9d6aa9-f606-4fea-ba4b-f06576cba309.jpg").
169
- **"url":** Returns a URL to the generated image.
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- **"b64_json":** Returns the image as a base64-encoded JSON string.
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167
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**Generate images using a specified prompt:**
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```python
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import asyncio
@@ -174,7 +179,9 @@ async def main():
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response = await client.images.generate(
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prompt="a white siamese cat",
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model="flux"
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model="flux",
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response_format="url"
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# Add any other necessary parameters
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)
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image_url = response.data[0].url
@@ -195,6 +202,7 @@ async def main():
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prompt="a white siamese cat",
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model="flux",
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response_format="b64_json"
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# Add any other necessary parameters
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)
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base64_text = response.data[0].b64_json
@@ -224,7 +232,8 @@ async def main():
224
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task2 = client.images.generate(
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model="flux",
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prompt="a white siamese cat"
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prompt="a white siamese cat",
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response_format="url"
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)
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try:
@@ -130,6 +130,11 @@ for chunk in stream:
130
130
```
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132
### Image Generation
133
**The `response_format` parameter is optional and can have the following values:**
134
- **If not specified (default):** The image will be saved locally, and a local path will be returned (e.g., "/images/1733331238_cf9d6aa9-f606-4fea-ba4b-f06576cba309.jpg").
135
- **"url":** Returns a URL to the generated image.
136
- **"b64_json":** Returns the image as a base64-encoded JSON string.
137
133
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**Generate images using a specified prompt:**
134
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```python
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from g4f.client import Client
@@ -138,7 +143,8 @@ client = Client()
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response = client.images.generate(
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model="flux",
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prompt="a white siamese cat"
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prompt="a white siamese cat",
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response_format="url"
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# Add any other necessary parameters
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)
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@@ -157,6 +163,7 @@ response = client.images.generate(
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model="flux",
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prompt="a white siamese cat",
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response_format="b64_json"
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# Add any other necessary parameters
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)
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base64_text = response.data[0].b64_json
@@ -1,18 +1,17 @@
1
1
from __future__ import annotations
2
3
import random
4
2
import json
3
import random
5
4
import re
6
7
5
import requests
8
6
from requests.packages.urllib3.exceptions import InsecureRequestWarning
9
requests.packages.urllib3.disable_warnings(InsecureRequestWarning)
10
7
from urllib.parse import quote
8
from aiohttp import ClientSession
11
9
12
10
from ..typing import AsyncResult, Messages
13
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
14
11
from ..image import ImageResponse
15
from ..requests import StreamSession, raise_for_status
12
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
13
14
requests.packages.urllib3.disable_warnings(InsecureRequestWarning)
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15
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def split_message(message: str, max_length: int = 1000) -> list[str]:
18
17
"""Splits the message into parts up to (max_length)."""
@@ -30,197 +29,203 @@ def split_message(message: str, max_length: int = 1000) -> list[str]:
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class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://llmplayground.net"
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31
api_endpoint_completions = "https://api.airforce/chat/completions"
33
api_endpoint_imagine = "https://api.airforce/imagine2"
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api_endpoint_imagine2 = "https://api.airforce/imagine2"
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working = True
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needs_auth = True
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supports_stream = True
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supports_system_message = True
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supports_message_history = True
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@classmethod
39
def fetch_completions_models(cls):
40
response = requests.get('https://api.airforce/models', verify=False)
41
response.raise_for_status()
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data = response.json()
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return [model['id'] for model in data['data']]
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@classmethod
46
def fetch_imagine_models(cls):
47
response = requests.get('https://api.airforce/imagine/models', verify=False)
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response.raise_for_status()
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return response.json()
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51
40
default_model = "gpt-4o-mini"
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41
default_image_model = "flux"
53
additional_models_imagine = ["stable-diffusion-xl-base", "stable-diffusion-xl-lightning", "flux-1.1-pro"]
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42
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@classmethod
56
def get_models(cls):
57
if not cls.models:
58
cls.image_models = [*cls.fetch_imagine_models(), *cls.additional_models_imagine]
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cls.models = [
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*cls.fetch_completions_models(),
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*cls.image_models
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]
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return cls.models
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model_aliases = {
66
### completions ###
67
# openchat
43
additional_models_imagine = ["flux-1.1-pro", "dall-e-3"]
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model_aliases = {
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# Alias mappings for models
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"openchat-3.5": "openchat-3.5-0106",
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# deepseek-ai
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"deepseek-coder": "deepseek-coder-6.7b-instruct",
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# NousResearch
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49
"hermes-2-dpo": "Nous-Hermes-2-Mixtral-8x7B-DPO",
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50
"hermes-2-pro": "hermes-2-pro-mistral-7b",
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# teknium
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"openhermes-2.5": "openhermes-2.5-mistral-7b",
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# liquid
81
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"lfm-40b": "lfm-40b-moe",
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# DiscoResearch
84
"german-7b": "discolm-german-7b-v1",
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# meta-llama
53
"discolm-german-7b": "discolm-german-7b-v1",
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54
"llama-2-7b": "llama-2-7b-chat-int8",
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"llama-2-7b": "llama-2-7b-chat-fp16",
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"llama-3.1-70b": "llama-3.1-70b-chat",
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"llama-3.1-8b": "llama-3.1-8b-chat",
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55
"llama-3.1-70b": "llama-3.1-70b-turbo",
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"llama-3.1-8b": "llama-3.1-8b-turbo",
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# inferless
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"neural-7b": "neural-chat-7b-v3-1",
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# HuggingFaceH4
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57
"zephyr-7b": "zephyr-7b-beta",
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### imagine ###
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"sdxl": "stable-diffusion-xl-base",
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"sdxl": "stable-diffusion-xl-lightning",
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"flux-pro": "flux-1.1-pro",
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60
}
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61
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62
@classmethod
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def create_async_generator(
63
def fetch_completions_models(cls):
64
response = requests.get('https://api.airforce/models', verify=False)
65
response.raise_for_status()
66
data = response.json()
67
return [model['id'] for model in data['data']]
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69
@classmethod
70
def fetch_imagine_models(cls):
71
response = requests.get(
72
'https://api.airforce/imagine/models',
73
'https://api.airforce/v1/imagine2/models',
74
verify=False
75
)
76
response.raise_for_status()
77
return response.json()
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image_models = fetch_imagine_models.__get__(None, object)() + additional_models_imagine
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@classmethod
82
def is_image_model(cls, model: str) -> bool:
83
return model in cls.image_models
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models = list(dict.fromkeys([default_model] +
86
fetch_completions_models.__get__(None, object)() +
87
image_models))
88
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@classmethod
90
async def check_api_key(cls, api_key: str) -> bool:
91
"""
92
Always returns True to allow all models.
93
"""
94
if not api_key or api_key == "null":
95
return True # No restrictions if no key.
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headers = {
98
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36",
99
"Accept": "*/*",
100
}
101
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try:
103
async with ClientSession(headers=headers) as session:
104
async with session.get(f"https://api.airforce/check?key={api_key}") as response:
105
if response.status == 200:
106
data = await response.json()
107
return data.get('info') in ['Sponsor key', 'Premium key']
108
return False
109
except Exception as e:
110
print(f"Error checking API key: {str(e)}")
111
return False
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@classmethod
114
async def generate_image(
109
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cls,
110
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model: str,
111
messages: Messages,
112
proxy: str = None,
113
prompt: str = None,
114
seed: int = None,
115
size: str = "1:1", # "1:1", "16:9", "9:16", "21:9", "9:21", "1:2", "2:1"
116
stream: bool = False,
117
**kwargs
117
prompt: str,
118
api_key: str,
119
size: str,
120
seed: int,
121
proxy: str = None
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122
) -> AsyncResult:
119
model = cls.get_model(model)
123
headers = {
124
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:133.0) Gecko/20100101 Firefox/133.0",
125
"Accept": "image/avif,image/webp,image/png,image/svg+xml,image/*;q=0.8,*/*;q=0.5",
126
"Accept-Encoding": "gzip, deflate, br, zstd",
127
"Content-Type": "application/json",
128
"Authorization": f"Bearer {api_key}",
129
}
130
params = {"model": model, "prompt": prompt, "size": size, "seed": seed}
120
131
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if model in cls.image_models:
122
if prompt is None:
123
prompt = messages[-1]['content']
124
return cls._generate_image(model, prompt, proxy, seed, size)
125
else:
126
return cls._generate_text(model, messages, proxy, stream, **kwargs)
132
async with ClientSession(headers=headers) as session:
133
async with session.get(cls.api_endpoint_imagine2, params=params, proxy=proxy) as response:
134
if response.status == 200:
135
image_url = str(response.url)
136
yield ImageResponse(images=image_url, alt=f"Generated image: {prompt}")
137
else:
138
error_text = await response.text()
139
raise RuntimeError(f"Image generation failed: {response.status} - {error_text}")
127
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@classmethod
129
async def _generate_image(
142
async def generate_text(
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cls,
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model: str,
132
prompt: str,
133
proxy: str = None,
134
seed: int = None,
135
size: str = "1:1",
136
**kwargs
145
messages: Messages,
146
max_tokens: int,
147
temperature: float,
148
top_p: float,
149
stream: bool,
150
api_key: str,
151
proxy: str = None
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) -> AsyncResult:
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headers = {
139
"accept": "*/*",
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"accept-language": "en-US,en;q=0.9",
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"cache-control": "no-cache",
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"user-agent": "Mozilla/5.0"
154
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:133.0) Gecko/20100101 Firefox/133.0",
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"Accept": "application/json, text/event-stream",
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"Accept-Encoding": "gzip, deflate, br, zstd",
157
"Content-Type": "application/json",
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"Authorization": f"Bearer {api_key}",
159
}
160
full_message = "\n".join([msg['content'] for msg in messages])
161
message_chunks = split_message(full_message, max_length=1000)
162
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data = {
164
"messages": [{"role": "user", "content": chunk} for chunk in message_chunks],
165
"model": model,
166
"max_tokens": max_tokens,
167
"temperature": temperature,
168
"top_p": top_p,
169
"stream": stream,
143
170
}
144
if seed is None:
145
seed = random.randint(0, 100000)
146
147
async with StreamSession(headers=headers, proxy=proxy) as session:
148
params = {
149
"model": model,
150
"prompt": prompt,
151
"size": size,
152
"seed": seed
153
}
154
async with session.get(f"{cls.api_endpoint_imagine}", params=params) as response:
155
await raise_for_status(response)
156
content_type = response.headers.get('Content-Type', '').lower()
157
158
if 'application/json' in content_type:
159
raise RuntimeError(await response.json().get("error", {}).get("message"))
160
elif content_type.startswith("image/"):
161
image_url = f"{cls.api_endpoint_imagine}?model={model}&prompt={quote(prompt)}&size={size}&seed={seed}"
162
yield ImageResponse(images=image_url, alt=prompt)
171
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async with ClientSession(headers=headers) as session:
173
async with session.post(cls.api_endpoint_completions, json=data, proxy=proxy) as response:
174
response.raise_for_status()
175
176
if stream:
177
async for line in response.content:
178
line = line.decode('utf-8').strip()
179
if line.startswith('data: '):
180
try:
181
json_str = line[6:] # Remove 'data: ' prefix
182
chunk = json.loads(json_str)
183
if 'choices' in chunk and chunk['choices']:
184
delta = chunk['choices'][0].get('delta', {})
185
if 'content' in delta:
186
filtered_content = cls._filter_response(delta['content'])
187
yield filtered_content
188
except json.JSONDecodeError:
189
continue
190
else:
191
# Non-streaming response
192
result = await response.json()
193
if 'choices' in result and result['choices']:
194
message = result['choices'][0].get('message', {})
195
content = message.get('content', '')
196
filtered_content = cls._filter_response(content)
197
yield filtered_content
163
198
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@classmethod
165
async def _generate_text(
200
async def create_async_generator(
166
201
cls,
167
202
model: str,
168
203
messages: Messages,
204
prompt: str = None,
169
205
proxy: str = None,
170
stream: bool = False,
171
206
max_tokens: int = 4096,
172
207
temperature: float = 1,
173
208
top_p: float = 1,
209
stream: bool = True,
210
api_key: str = None,
211
size: str = "1:1",
212
seed: int = None,
174
213
**kwargs
175
214
) -> AsyncResult:
176
headers = {
177
"accept": "*/*",
178
"accept-language": "en-US,en;q=0.9",
179
"authorization": "Bearer missing api key",
180
"content-type": "application/json",
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"user-agent": "Mozilla/5.0"
182
}
215
if not await cls.check_api_key(api_key):
216
pass
183
217
184
full_message = "\n".join(
185
[f"{msg['role'].capitalize()}: {msg['content']}" for msg in messages]
186
)
187
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message_chunks = split_message(full_message, max_length=1000)
189
190
async with StreamSession(headers=headers, proxy=proxy) as session:
191
full_response = ""
192
for chunk in message_chunks:
193
data = {
194
"messages": [{"role": "user", "content": chunk}],
195
"model": model,
196
"max_tokens": max_tokens,
197
"temperature": temperature,
198
"top_p": top_p,
199
"stream": stream
200
}
201
202
async with session.post(cls.api_endpoint_completions, json=data) as response:
203
await raise_for_status(response)
204
content_type = response.headers.get('Content-Type', '').lower()
205
206
if 'application/json' in content_type:
207
json_data = await response.json()
208
if json_data.get("model") == "error":
209
raise RuntimeError(json_data['choices'][0]['message'].get('content', ''))
210
if stream:
211
async for line in response.iter_lines():
212
if line:
213
line = line.decode('utf-8').strip()
214
if line.startswith("data: ") and line != "data: [DONE]":
215
json_data = json.loads(line[6:])
216
content = json_data['choices'][0]['delta'].get('content', '')
217
if content:
218
yield cls._filter_content(content)
219
else:
220
content = json_data['choices'][0]['message']['content']
221
full_response += cls._filter_content(content)
222
223
yield full_response
218
if cls.is_image_model(model):
219
if prompt is None:
220
prompt = messages[-1]['content']
221
if seed is None:
222
seed = random.randint(0, 10000)
223
224
async for result in cls.generate_image(model, prompt, api_key, size, seed, proxy):
225
yield result
226
else:
227
async for result in cls.generate_text(model, messages, max_tokens, temperature, top_p, stream, api_key, proxy):
228
yield result
224
229
225
230
@classmethod
226
231
def _filter_content(cls, part_response: str) -> str:
@@ -229,16 +234,19 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
229
234
'',
230
235
part_response
231
236
)
232
237
233
238
part_response = re.sub(
234
239
r"Rate limit \(\d+\/minute\) exceeded\. Join our discord for more: .+https:\/\/discord\.com\/invite\/\S+",
235
240
'',
236
241
part_response
237
242
)
238
239
part_response = re.sub(
240
r"\[ERROR\] '\w{8}-\w{4}-\w{4}-\w{4}-\w{12}'", # any-uncensored
241
'',
242
part_response
243
)
243
244
244
return part_response
245
246
@classmethod
247
def _filter_response(cls, response: str) -> str:
248
filtered_response = re.sub(r"\[ERROR\] '\w{8}-\w{4}-\w{4}-\w{4}-\w{12}'", '', response) # any-uncensored
249
filtered_response = re.sub(r'<\|im_end\|>', '', response) # hermes-2-pro-mistral-7b
250
filtered_response = re.sub(r'</s>', '', response) # neural-chat-7b-v3-1
251
filtered_response = cls._filter_content(filtered_response)
252
return filtered_response
@@ -129,8 +129,6 @@ class AmigoChat(AsyncGeneratorProvider, ProviderModelMixin):
129
129
### image ###
130
130
"flux-realism": "flux-realism",
131
131
"flux-dev": "flux/dev",
132
133
"dalle-3": "dall-e-3",
134
132
}
135
133
136
134
@classmethod
@@ -141,7 +139,12 @@ class AmigoChat(AsyncGeneratorProvider, ProviderModelMixin):
141
139
return MODELS['image'][model]['persona_id']
142
140
else:
143
141
raise ValueError(f"Unknown model: {model}")
144
142
143
@staticmethod
144
def generate_chat_id() -> str:
145
"""Generate a chat ID in format: 8-4-4-4-12 hexadecimal digits"""
146
return str(uuid.uuid4())
147
145
148
@classmethod
146
149
async def create_async_generator(
147
150
cls,
@@ -182,22 +185,24 @@ class AmigoChat(AsyncGeneratorProvider, ProviderModelMixin):
182
185
"x-device-language": "en-US",
183
186
"x-device-platform": "web",
184
187
"x-device-uuid": device_uuid,
185
"x-device-version": "1.0.42"
188
"x-device-version": "1.0.45"
186
189
}
187
190
188
191
async with StreamSession(headers=headers, proxy=proxy) as session:
189
192
if model not in cls.image_models:
190
193
data = {
194
"chatId": cls.generate_chat_id(),
195
"frequency_penalty": frequency_penalty,
196
"max_tokens": max_tokens,
191
197
"messages": messages,
192
198
"model": model,
193
199
"personaId": cls.get_personaId(model),
194
"frequency_penalty": frequency_penalty,
195
"max_tokens": max_tokens,
196
200
"presence_penalty": presence_penalty,
197
201
"stream": stream,
198
202
"temperature": temperature,
199
203
"top_p": top_p
200
204
}
205
print(data)
201
206
async with session.post(cls.chat_api_endpoint, json=data, timeout=timeout) as response:
202
207
await raise_for_status(response)
203
208
async for line in response.iter_lines():
@@ -25,14 +25,14 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
25
25
26
26
default_model = 'blackboxai'
27
27
default_vision_model = default_model
28
default_image_model = 'Image Generation'
29
image_models = ['Image Generation', 'repomap']
28
default_image_model = 'flux'
29
image_models = ['flux', 'repomap']
30
30
vision_models = [default_model, 'gpt-4o', 'gemini-pro', 'gemini-1.5-flash', 'llama-3.1-8b', 'llama-3.1-70b', 'llama-3.1-405b']
31
31
32
32
userSelectedModel = ['gpt-4o', 'gemini-pro', 'claude-sonnet-3.5', 'blackboxai-pro']
33
33
34
34
agentMode = {
35
'Image Generation': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"},
35
'flux': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"}
36
36
}
37
37
38
38
trendingAgentMode = {
@@ -79,9 +79,9 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
79
79
}
80
80
81
81
additional_prefixes = {
82
'gpt-4o': '@gpt-4o',
83
'gemini-pro': '@gemini-pro',
84
'claude-sonnet-3.5': '@claude-sonnet'
82
'gpt-4o': '@GPT-4o',
83
'gemini-pro': '@Gemini-PRO',
84
'claude-sonnet-3.5': '@Claude-Sonnet-3.5'
85
85
}
86
86
87
87
model_prefixes = {
@@ -95,9 +95,9 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
95
95
models = list(dict.fromkeys([default_model, *userSelectedModel, *list(agentMode.keys()), *list(trendingAgentMode.keys())]))
96
96
97
97
model_aliases = {
98
"gpt-3.5-turbo": "blackboxai",
98
99
"gemini-flash": "gemini-1.5-flash",
99
"claude-3.5-sonnet": "claude-sonnet-3.5",
100
"flux": "Image Generation",
100
"claude-3.5-sonnet": "claude-sonnet-3.5"
101
101
}
102
102
103
103
@classmethod
@@ -173,9 +173,14 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
173
173
174
174
if image is not None:
175
175
messages[-1]['data'] = {
176
'fileText': '',
177
'imageBase64': to_data_uri(image),
178
'title': image_name
176
"imagesData": [
177
{
178
"filePath": f"MultipleFiles/{image_name}",
179
"contents": to_data_uri(image)
180
}
181
],
182
"fileText": "",
183
"title": ""
179
184
}
180
185
181
186
headers = {
@@ -219,6 +224,8 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
219
224
"userSelectedModel": model if model in cls.userSelectedModel else None,
220
225
"webSearchMode": web_search,
221
226
"validated": validated_value,
227
"imageGenerationMode": False,
228
"webSearchModePrompt": False
222
229
}
223
230
224
231
async with ClientSession(headers=headers) as session:
@@ -0,0 +1,69 @@
1
from __future__ import annotations
2
3
import random
4
import asyncio
5
from aiohttp import ClientSession
6
7
from ..typing import AsyncResult, Messages
8
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
9
10
class Blackbox2(AsyncGeneratorProvider, ProviderModelMixin):
11
url = "https://www.blackbox.ai"
12
api_endpoint = "https://www.blackbox.ai/api/improve-prompt"
13
working = True
14
supports_system_message = True
15
supports_message_history = True
16
17
default_model = 'llama-3.1-70b'
18
models = [default_model]
19
20
@classmethod
21
async def create_async_generator(
22
cls,
23
model: str,
24
messages: Messages,
25
proxy: str = None,
26
max_retries: int = 3,
27
delay: int = 1,
28
**kwargs
29
) -> AsyncResult:
30
headers = {
31
'accept': '*/*',
32
'accept-language': 'en-US,en;q=0.9',
33
'content-type': 'text/plain;charset=UTF-8',
34
'dnt': '1',
35
'origin': 'https://www.blackbox.ai',
36
'priority': 'u=1, i',
37
'referer': 'https://www.blackbox.ai',
38
'sec-ch-ua': '"Chromium";v="131", "Not_A Brand";v="24"',
39
'sec-ch-ua-mobile': '?0',
40
'sec-ch-ua-platform': '"Linux"',
41
'sec-fetch-dest': 'empty',
42
'sec-fetch-mode': 'cors',
43
'sec-fetch-site': 'same-origin',
44
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36'
45
}
46
47
data = {
48
"messages": messages,
49
"max_tokens": None
50
}
51
52
async with ClientSession(headers=headers) as session:
53
for attempt in range(max_retries):
54
try:
55
async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
56
response.raise_for_status()
57
response_data = await response.json()
58
if 'prompt' in response_data:
59
yield response_data['prompt']
60
return
61
else:
62
raise KeyError("'prompt' key not found in the response")
63
except Exception as e:
64
if attempt == max_retries - 1:
65
yield f"Error after {max_retries} attempts: {str(e)}"
66
else:
67
wait_time = delay * (2 ** attempt) + random.uniform(0, 1)
68
print(f"Attempt {attempt + 1} failed. Retrying in {wait_time:.2f} seconds...")
69
await asyncio.sleep(wait_time)
@@ -1,11 +1,11 @@
1
1
from __future__ import annotations
2
2
3
from aiohttp import ClientSession
3
from aiohttp import ClientSession, ClientResponseError
4
4
import json
5
6
5
from ..typing import AsyncResult, Messages, ImageType
7
6
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
8
7
8
9
9
class DeepInfraChat(AsyncGeneratorProvider, ProviderModelMixin):
10
10
url = "https://deepinfra.com/chat"
11
11
api_endpoint = "https://api.deepinfra.com/v1/openai/chat/completions"
@@ -13,11 +13,12 @@ class DeepInfraChat(AsyncGeneratorProvider, ProviderModelMixin):
13
13
supports_stream = True
14
14
supports_system_message = True
15
15
supports_message_history = True
16
16
17
17
default_model = 'meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo'
18
18
models = [
19
19
'meta-llama/Meta-Llama-3.1-8B-Instruct',
20
20
default_model,
21
'Qwen/QwQ-32B-Preview',
21
22
'microsoft/WizardLM-2-8x22B',
22
23
'Qwen/Qwen2.5-72B-Instruct',
23
24
'Qwen/Qwen2.5-Coder-32B-Instruct',
@@ -26,60 +27,37 @@ class DeepInfraChat(AsyncGeneratorProvider, ProviderModelMixin):
26
27
model_aliases = {
27
28
"llama-3.1-8b": "meta-llama/Meta-Llama-3.1-8B-Instruct",
28
29
"llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo",
30
"qwq-32b": "Qwen/QwQ-32B-Preview",
29
31
"wizardlm-2-8x22b": "microsoft/WizardLM-2-8x22B",
30
32
"qwen-2-72b": "Qwen/Qwen2.5-72B-Instruct",
31
33
"qwen-2.5-coder-32b": "Qwen2.5-Coder-32B-Instruct",
32
34
"nemotron-70b": "nvidia/Llama-3.1-Nemotron-70B-Instruct",
33
35
}
34
36
35
36
@classmethod
37
def get_model(cls, model: str) -> str:
38
if model in cls.models:
39
return model
40
elif model in cls.model_aliases:
41
return cls.model_aliases[model]
42
else:
43
return cls.default_model
44
45
37
@classmethod
46
38
async def create_async_generator(
47
39
cls,
48
40
model: str,
49
41
messages: Messages,
50
42
proxy: str = None,
51
image: ImageType = None,
52
image_name: str = None,
53
43
**kwargs
54
44
) -> AsyncResult:
55
model = cls.get_model(model)
56
57
45
headers = {
58
'Accept-Language': 'en-US,en;q=0.9',
59
'Cache-Control': 'no-cache',
60
'Connection': 'keep-alive',
61
46
'Content-Type': 'application/json',
62
47
'Origin': 'https://deepinfra.com',
63
'Pragma': 'no-cache',
64
48
'Referer': 'https://deepinfra.com/',
65
'Sec-Fetch-Dest': 'empty',
66
'Sec-Fetch-Mode': 'cors',
67
'Sec-Fetch-Site': 'same-site',
68
'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36',
69
'X-Deepinfra-Source': 'web-embed',
49
'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36',
50
'X-Deepinfra-Source': 'web-page',
70
51
'accept': 'text/event-stream',
71
'sec-ch-ua': '"Not;A=Brand";v="24", "Chromium";v="128"',
72
'sec-ch-ua-mobile': '?0',
73
'sec-ch-ua-platform': '"Linux"',
74
52
}
75
53
76
async with ClientSession(headers=headers) as session:
77
data = {
78
'model': model,
79
'messages': messages,
80
'stream': True
81
}
54
data = {
55
'model': model,
56
'messages': messages,
57
'stream': True
58
}
82
59
60
async with ClientSession(headers=headers) as session:
83
61
async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
84
62
response.raise_for_status()
85
63
async for line in response.content:
@@ -28,8 +28,6 @@ class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin):
28
28
]
29
29
30
30
text_models = [
31
'meta/meta-llama-3-70b-instruct',
32
'mistralai/mixtral-8x7b-instruct-v0.1',
33
31
'google-deepmind/gemma-2b-it',
34
32
'yorickvp/llava-13b',
35
33
]
@@ -14,6 +14,7 @@ from .local import *
14
14
from .Airforce import Airforce
15
15
from .AmigoChat import AmigoChat
16
16
from .Blackbox import Blackbox
17
from .Blackbox2 import Blackbox2
17
18
from .ChatGpt import ChatGpt
18
19
from .ChatGptEs import ChatGptEs
19
20
from .Cloudflare import Cloudflare
@@ -24,7 +25,6 @@ from .DeepInfraChat import DeepInfraChat
24
25
from .Free2GPT import Free2GPT
25
26
from .FreeGpt import FreeGpt
26
27
from .GizAI import GizAI
27
from .HuggingChat import HuggingChat
28
28
from .Liaobots import Liaobots
29
29
from .MagickPen import MagickPen
30
30
from .PerplexityLabs import PerplexityLabs
@@ -8,22 +8,24 @@ try:
8
8
has_curl_cffi = True
9
9
except ImportError:
10
10
has_curl_cffi = False
11
from ..typing import CreateResult, Messages
12
from ..errors import MissingRequirementsError
13
from ..requests.raise_for_status import raise_for_status
14
from .base_provider import ProviderModelMixin, AbstractProvider
15
from .helper import format_prompt
11
from ...typing import CreateResult, Messages
12
from ...errors import MissingRequirementsError
13
from ...requests.raise_for_status import raise_for_status
14
from ..base_provider import ProviderModelMixin, AbstractProvider
15
from ..helper import format_prompt
16
16
17
17
class HuggingChat(AbstractProvider, ProviderModelMixin):
18
18
url = "https://huggingface.co/chat"
19
19
working = True
20
20
supports_stream = True
21
needs_auth = True
21
22
default_model = "meta-llama/Meta-Llama-3.1-70B-Instruct"
22
23
23
24
models = [
25
'Qwen/Qwen2.5-72B-Instruct',
24
26
'meta-llama/Meta-Llama-3.1-70B-Instruct',
25
27
'CohereForAI/c4ai-command-r-plus-08-2024',
26
'Qwen/Qwen2.5-72B-Instruct',
28
'Qwen/QwQ-32B-Preview',
27
29
'nvidia/Llama-3.1-Nemotron-70B-Instruct-HF',
28
30
'Qwen/Qwen2.5-Coder-32B-Instruct',
29
31
'meta-llama/Llama-3.2-11B-Vision-Instruct',
@@ -33,9 +35,10 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
33
35
]
34
36
35
37
model_aliases = {
38
"qwen-2.5-72b": "Qwen/Qwen2.5-72B-Instruct",
36
39
"llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct",
37
40
"command-r-plus": "CohereForAI/c4ai-command-r-plus-08-2024",
38
"qwen-2-72b": "Qwen/Qwen2.5-72B-Instruct",
41
"qwq-32b": "Qwen/QwQ-32B-Preview",
39
42
"nemotron-70b": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
40
43
"qwen-2.5-coder-32b": "Qwen/Qwen2.5-Coder-32B-Instruct",
41
44
"llama-3.2-11b": "meta-llama/Llama-3.2-11B-Vision-Instruct",
@@ -173,4 +176,4 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
173
176
full_response = full_response.replace('<|im_end|', '').replace('\u0000', '').strip()
174
177
175
178
if not stream:
176
yield full_response
179
yield full_response
@@ -7,7 +7,7 @@ from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
7
7
from ...errors import ModelNotFoundError
8
8
from ...requests import StreamSession, raise_for_status
9
9
10
from ..HuggingChat import HuggingChat
10
from .HuggingChat import HuggingChat
11
11
12
12
class HuggingFace(AsyncGeneratorProvider, ProviderModelMixin):
13
13
url = "https://huggingface.co/chat"
@@ -88,4 +88,4 @@ def format_prompt(messages: Messages) -> str:
88
88
for idx, message in enumerate(messages)
89
89
if message["role"] == "assistant"
90
90
])
91
return f"{history}<s>[INST] {question} [/INST]"
91
return f"{history}<s>[INST] {question} [/INST]"