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feat: add LM Arena provider, async‑ify Copilot & surface follow‑up suggestions
* **Provider/Blackbox.py**
* Raise `RateLimitError` when `"You have reached your request limit for the hour"` substring is detected
* **Provider/Copilot.py**
* Convert class to `AsyncGeneratorProvider`; rename `create_completion` → `create_async_generator`
* Swap `curl_cffi.requests.Session` for `AsyncSession`; reduce default timeout to **30 s**
* Fully async websocket flow (`await session.ws_connect`, `await wss.send/recv/close`)
* Emit new response types: `TitleGeneration`, `SourceLink`, aggregated `Sources`
* Track request completion with `done` flag; collect citations in `sources` dict
* **Provider/DuckDuckGo.py**
* Replace `duckduckgo_search.DDGS` with `duckai.DuckAI`
* Change base class to `AbstractProvider`; drop nodriver‑based auth
* **Provider/PollinationsAI.py**
* Re‑build text/audio model lists ensuring uniqueness; remove unused `extra_text_models`
* Fix image seed logic (`i==1` for first retry); propagate streaming `error` field via `ResponseError`
* **Provider/hf_space**
* **New file** `LMArenaProvider.py` implementing async queue/stream client
* Register `LMArenaProvider` in `hf_space/__init__.py`; delete `G4F` import
* **Provider/needs_auth/CopilotAccount.py**
* Inherit order changed to `Copilot, AsyncAuthedProvider`
* Refactor token & cookie propagation; add `cookies_to_dict` helper
* **Provider/needs_auth/OpenaiChat.py**
* Parse reasoning thoughts/summary; yield `Reasoning` responses
* Tighten access‑token validation and nodriver JS evaluations (`return_by_value`)
* Extend `Conversation` with `p` and `thoughts_summary`
* **providers/response.py**
* Add `SourceLink` response class returning single formatted citation link
* **providers/base_provider.py**
* Serialize `AuthResult` with custom `json.dump` to handle non‑serializable fields
* Gracefully skip empty cache files when loading auth data
* **image/copy_images.py**
* Ignore file extensions longer than 4 chars when inferring type
* **requests/__init__.py**
* Use `return_by_value=True` for `navigator.userAgent` extraction
* **models.py**
* Remove `G4F` from model provider lists; update `janus_pro_7b` best providers
* **GUI server/api.py**
* Stream `SuggestedFollowups` to client (`"suggestions"` event)
* **GUI static assets**
* **style.css**: bold chat title, add `.suggestions` styles, remove padding from `.chat-body`
* **chat.v1.js**
* Capture `suggestions` packets, render buttons, and send as quick replies
* Re‑order finish‑reason logic; adjust token count placement and system‑prompt toggling
* **chat-top-panel / footer** interactions updated accordingly
* **gui/client/static/js/chat.v1.js** & **css** further UI refinements (scroll handling, token counting, hide prompt toggle)
* Minor updates across multiple files to match new async interfaces and headers (`userAgent`, `raise_for_status`)
This commit is contained in:
hlohaus
parent
323765d810
commit
06546649db
19 changed files with 473 additions and 212 deletions
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@ -52,8 +52,8 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):
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audio_models = [default_audio_model]
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extra_image_models = ["flux-pro", "flux-dev", "flux-schnell", "midjourney", "dall-e-3", "turbo"]
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vision_models = [default_vision_model, "gpt-4o-mini", "openai", "openai-large", "searchgpt"]
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extra_text_models = vision_models
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_models_loaded = False
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# https://github.com/pollinations/pollinations/blob/master/text.pollinations.ai/generateTextPortkey.js#L15
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model_aliases = {
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### Text Models ###
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"gpt-4o-mini": "openai",
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@ -100,43 +100,32 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):
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cls.image_models = all_image_models
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# Update of text models
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text_response = requests.get("https://text.pollinations.ai/models")
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text_response.raise_for_status()
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models = text_response.json()
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# Purpose of text models
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cls.text_models = [
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model.get("name")
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for model in models
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if "input_modalities" in model and "text" in model["input_modalities"]
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]
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# Purpose of audio models
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cls.audio_models = {
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model.get("name"): model.get("voices")
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for model in models
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if model.get("audio")
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if "output_modalities" in model and "audio" in model["output_modalities"]
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}
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# Create a set of unique text models starting with default model
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unique_text_models = {cls.default_model}
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unique_text_models = cls.text_models.copy()
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# Add models from vision_models
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unique_text_models.update(cls.vision_models)
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unique_text_models.extend(cls.vision_models)
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# Add models from the API response
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for model in models:
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model_name = model.get("name")
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if model_name and "input_modalities" in model and "text" in model["input_modalities"]:
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unique_text_models.add(model_name)
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unique_text_models.append(model_name)
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# Convert to list and update text_models
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cls.text_models = list(unique_text_models)
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# Update extra_text_models with unique vision models
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cls.extra_text_models = [model for model in cls.vision_models if model != cls.default_model]
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cls.text_models = list(dict.fromkeys(unique_text_models))
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cls._models_loaded = True
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except Exception as e:
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@ -148,12 +137,10 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):
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debug.error(f"Failed to fetch models: {e}")
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# Return unique models across all categories
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all_models = set(cls.text_models)
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all_models.update(cls.image_models)
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all_models.update(cls.audio_models.keys())
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result = list(all_models)
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return result
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all_models = cls.text_models.copy()
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all_models.extend(cls.image_models)
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all_models.extend(cls.audio_models.keys())
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return list(dict.fromkeys(all_models))
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@classmethod
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async def create_async_generator(
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@ -265,15 +252,15 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):
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query = "&".join(f"{k}={quote_plus(str(v))}" for k, v in params.items() if v is not None)
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prompt = quote_plus(prompt)[:2048-256-len(query)]
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url = f"{cls.image_api_endpoint}prompt/{prompt}?{query}"
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def get_image_url(i: int = 0, seed: Optional[int] = None):
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if i == 0:
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def get_image_url(i: int, seed: Optional[int] = None):
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if i == 1:
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if not cache and seed is None:
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seed = random.randint(0, 2**32)
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else:
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seed = random.randint(0, 2**32)
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return f"{url}&seed={seed}" if seed else url
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async with ClientSession(headers=DEFAULT_HEADERS, connector=get_connector(proxy=proxy)) as session:
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async def get_image(i: int = 0, seed: Optional[int] = None):
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async def get_image(i: int, seed: Optional[int] = None):
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async with session.get(get_image_url(i, seed), allow_redirects=False) as response:
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try:
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await raise_for_status(response)
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@ -343,6 +330,8 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):
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if line[6:].startswith(b"[DONE]"):
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break
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result = json.loads(line[6:])
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if "error" in result:
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raise ResponseError(result["error"].get("message", result["error"]))
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if "usage" in result:
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yield Usage(**result["usage"])
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choices = result.get("choices", [{}])
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