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feat(g4f/Provider/HuggingChat.py: Enhance HuggingChat provider functionality

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kqlio67 2024-11-12 09:04:33 +02:00
parent 21a26f6882
commit fde29c53e8
2 changed files with 49 additions and 7 deletions
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38
g4f/Provider/HuggingChat.py
View file

@ -19,6 +19,7 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
'CohereForAI/c4ai-command-r-plus-08-2024',
'Qwen/Qwen2.5-72B-Instruct',
'nvidia/Llama-3.1-Nemotron-70B-Instruct-HF',
'Qwen/Qwen2.5-Coder-32B-Instruct',
'meta-llama/Llama-3.2-11B-Vision-Instruct',
'NousResearch/Hermes-3-Llama-3.1-8B',
'mistralai/Mistral-Nemo-Instruct-2407',
@ -30,6 +31,7 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
"command-r-plus": "CohereForAI/c4ai-command-r-plus-08-2024",
"qwen-2-72b": "Qwen/Qwen2.5-72B-Instruct",
"nemotron-70b": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
"qwen-2.5-coder-32b": "Qwen/Qwen2.5-Coder-32B-Instruct",
"llama-3.2-11b": "meta-llama/Llama-3.2-11B-Vision-Instruct",
"hermes-3": "NousResearch/Hermes-3-Llama-3.1-8B",
"mistral-nemo": "mistralai/Mistral-Nemo-Instruct-2407",
@ -83,13 +85,34 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
raise RuntimeError(f"Request failed with status code: {response.status_code}, response: {response.text}")
conversationId = response.json().get('conversationId')
response = session.get(f'https://huggingface.co/chat/conversation/{conversationId}/__data.json?x-sveltekit-invalidated=01')
data: list = response.json()["nodes"][1]["data"]
# Get the data response and parse it properly
response = session.get(f'https://huggingface.co/chat/conversation/{conversationId}/__data.json?x-sveltekit-invalidated=11')
# Split the response content by newlines and parse each line as JSON
try:
json_data = None
for line in response.text.split('\n'):
if line.strip():
try:
parsed = json.loads(line)
if isinstance(parsed, dict) and "nodes" in parsed:
json_data = parsed
break
except json.JSONDecodeError:
continue
if not json_data:
raise RuntimeError("Failed to parse response data")
data: list = json_data["nodes"][1]["data"]
keys: list[int] = data[data[0]["messages"]]
message_keys: dict = data[keys[0]]
messageId: str = data[message_keys["id"]]
except (KeyError, IndexError, TypeError) as e:
raise RuntimeError(f"Failed to extract message ID: {str(e)}")
settings = {
"inputs": format_prompt(messages),
"id": messageId,
@ -120,7 +143,8 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
'data': (None, json.dumps(settings, separators=(',', ':'))),
}
response = requests.post(f'https://huggingface.co/chat/conversation/{conversationId}',
response = requests.post(
f'https://huggingface.co/chat/conversation/{conversationId}',
cookies=session.cookies,
headers=headers,
files=files,
@ -142,10 +166,18 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
elif line["type"] == "stream":
token = line["token"].replace('\u0000', '')
full_response += token
if stream:
yield token
elif line["type"] == "finalAnswer":
break
full_response = full_response.replace('<|im_end|', '').replace('\u0000', '').strip()
if not stream:
yield full_response
@classmethod
def supports_model(cls, model: str) -> bool:
"""Check if the model is supported by the provider."""
return model in cls.models or model in cls.model_aliases

10
g4f/models.py
View file

@ -361,6 +361,13 @@ qwen_2_72b = Model(
best_provider = IterListProvider([DeepInfraChat, HuggingChat, HuggingFace])
)
# qwen 2.5
qwen_2_5_coder_32b = Model(
name = 'qwen-2.5-coder-32b',
base_provider = 'Qwen',
best_provider = IterListProvider([HuggingChat, HuggingFace])
)
### Upstage ###
solar_mini = Model(
name = 'solar-mini',
@ -704,6 +711,9 @@ class ModelUtils:
# qwen 2
'qwen-2-72b': qwen_2_72b,
# qwen 2.5
'qwen-2.5-coder-32b': qwen_2_5_coder_32b,
### Upstage ###
'solar-mini': solar_mini,