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🐛 fix: fix the LLM logic

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This commit is contained in:
yyhhyyyyyy
2024-12-12 14:29:14 +08:00
parent 85d446e2d0
commit 2d8cd23fe7
3 changed files with 270 additions and 249 deletions
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457
app/services/llm.py
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@@ -3,6 +3,7 @@ import logging
import re
from typing import List
import g4f
from loguru import logger
from openai import AzureOpenAI, OpenAI
from openai.types.chat import ChatCompletion
@@ -13,243 +14,244 @@ _max_retries = 5
def _generate_response(prompt: str) -> str:
content = ""
llm_provider = config.app.get("llm_provider", "openai")
logger.info(f"llm provider: {llm_provider}")
if llm_provider == "g4f":
model_name = config.app.get("g4f_model_name", "")
if not model_name:
model_name = "gpt-3.5-turbo-16k-0613"
import g4f
content = g4f.ChatCompletion.create(
model=model_name,
messages=[{"role": "user", "content": prompt}],
)
else:
api_version = "" # for azure
if llm_provider == "moonshot":
api_key = config.app.get("moonshot_api_key")
model_name = config.app.get("moonshot_model_name")
base_url = "https://api.moonshot.cn/v1"
elif llm_provider == "ollama":
# api_key = config.app.get("openai_api_key")
api_key = "ollama" # any string works but you are required to have one
model_name = config.app.get("ollama_model_name")
base_url = config.app.get("ollama_base_url", "")
if not base_url:
base_url = "http://localhost:11434/v1"
elif llm_provider == "openai":
api_key = config.app.get("openai_api_key")
model_name = config.app.get("openai_model_name")
base_url = config.app.get("openai_base_url", "")
if not base_url:
base_url = "https://api.openai.com/v1"
elif llm_provider == "oneapi":
api_key = config.app.get("oneapi_api_key")
model_name = config.app.get("oneapi_model_name")
base_url = config.app.get("oneapi_base_url", "")
elif llm_provider == "azure":
api_key = config.app.get("azure_api_key")
model_name = config.app.get("azure_model_name")
base_url = config.app.get("azure_base_url", "")
api_version = config.app.get("azure_api_version", "2024-02-15-preview")
elif llm_provider == "gemini":
api_key = config.app.get("gemini_api_key")
model_name = config.app.get("gemini_model_name")
base_url = "***"
elif llm_provider == "qwen":
api_key = config.app.get("qwen_api_key")
model_name = config.app.get("qwen_model_name")
base_url = "***"
elif llm_provider == "cloudflare":
api_key = config.app.get("cloudflare_api_key")
model_name = config.app.get("cloudflare_model_name")
account_id = config.app.get("cloudflare_account_id")
base_url = "***"
elif llm_provider == "deepseek":
api_key = config.app.get("deepseek_api_key")
model_name = config.app.get("deepseek_model_name")
base_url = config.app.get("deepseek_base_url")
if not base_url:
base_url = "https://api.deepseek.com"
elif llm_provider == "ernie":
api_key = config.app.get("ernie_api_key")
secret_key = config.app.get("ernie_secret_key")
base_url = config.app.get("ernie_base_url")
model_name = "***"
if not secret_key:
raise ValueError(
f"{llm_provider}: secret_key is not set, please set it in the config.toml file."
)
try:
content = ""
llm_provider = config.app.get("llm_provider", "openai")
logger.info(f"llm provider: {llm_provider}")
if llm_provider == "g4f":
model_name = config.app.get("g4f_model_name", "")
if not model_name:
model_name = "gpt-3.5-turbo-16k-0613"
content = g4f.ChatCompletion.create(
model=model_name,
messages=[{"role": "user", "content": prompt}],
)
else:
raise ValueError(
"llm_provider is not set, please set it in the config.toml file."
)
api_version = "" # for azure
if llm_provider == "moonshot":
api_key = config.app.get("moonshot_api_key")
model_name = config.app.get("moonshot_model_name")
base_url = "https://api.moonshot.cn/v1"
elif llm_provider == "ollama":
# api_key = config.app.get("openai_api_key")
api_key = "ollama" # any string works but you are required to have one
model_name = config.app.get("ollama_model_name")
base_url = config.app.get("ollama_base_url", "")
if not base_url:
base_url = "http://localhost:11434/v1"
elif llm_provider == "openai":
api_key = config.app.get("openai_api_key")
model_name = config.app.get("openai_model_name")
base_url = config.app.get("openai_base_url", "")
if not base_url:
base_url = "https://api.openai.com/v1"
elif llm_provider == "oneapi":
api_key = config.app.get("oneapi_api_key")
model_name = config.app.get("oneapi_model_name")
base_url = config.app.get("oneapi_base_url", "")
elif llm_provider == "azure":
api_key = config.app.get("azure_api_key")
model_name = config.app.get("azure_model_name")
base_url = config.app.get("azure_base_url", "")
api_version = config.app.get("azure_api_version", "2024-02-15-preview")
elif llm_provider == "gemini":
api_key = config.app.get("gemini_api_key")
model_name = config.app.get("gemini_model_name")
base_url = "***"
elif llm_provider == "qwen":
api_key = config.app.get("qwen_api_key")
model_name = config.app.get("qwen_model_name")
base_url = "***"
elif llm_provider == "cloudflare":
api_key = config.app.get("cloudflare_api_key")
model_name = config.app.get("cloudflare_model_name")
account_id = config.app.get("cloudflare_account_id")
base_url = "***"
elif llm_provider == "deepseek":
api_key = config.app.get("deepseek_api_key")
model_name = config.app.get("deepseek_model_name")
base_url = config.app.get("deepseek_base_url")
if not base_url:
base_url = "https://api.deepseek.com"
elif llm_provider == "ernie":
api_key = config.app.get("ernie_api_key")
secret_key = config.app.get("ernie_secret_key")
base_url = config.app.get("ernie_base_url")
model_name = "***"
if not secret_key:
raise ValueError(
f"{llm_provider}: secret_key is not set, please set it in the config.toml file."
)
else:
raise ValueError(
"llm_provider is not set, please set it in the config.toml file."
)
if not api_key:
raise ValueError(
f"{llm_provider}: api_key is not set, please set it in the config.toml file."
)
if not model_name:
raise ValueError(
f"{llm_provider}: model_name is not set, please set it in the config.toml file."
)
if not base_url:
raise ValueError(
f"{llm_provider}: base_url is not set, please set it in the config.toml file."
)
if not api_key:
raise ValueError(
f"{llm_provider}: api_key is not set, please set it in the config.toml file."
)
if not model_name:
raise ValueError(
f"{llm_provider}: model_name is not set, please set it in the config.toml file."
)
if not base_url:
raise ValueError(
f"{llm_provider}: base_url is not set, please set it in the config.toml file."
)
if llm_provider == "qwen":
import dashscope
from dashscope.api_entities.dashscope_response import GenerationResponse
if llm_provider == "qwen":
import dashscope
from dashscope.api_entities.dashscope_response import GenerationResponse
dashscope.api_key = api_key
response = dashscope.Generation.call(
dashscope.api_key = api_key
response = dashscope.Generation.call(
model=model_name, messages=[{"role": "user", "content": prompt}]
)
if response:
if isinstance(response, GenerationResponse):
status_code = response.status_code
if status_code != 200:
raise Exception(
f'[{llm_provider}] returned an error response: "{response}"'
)
content = response["output"]["text"]
return content.replace("\n", "")
else:
raise Exception(
f'[{llm_provider}] returned an invalid response: "{response}"'
)
else:
raise Exception(f"[{llm_provider}] returned an empty response")
if llm_provider == "gemini":
import google.generativeai as genai
genai.configure(api_key=api_key, transport="rest")
generation_config = {
"temperature": 0.5,
"top_p": 1,
"top_k": 1,
"max_output_tokens": 2048,
}
safety_settings = [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_ONLY_HIGH",
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_ONLY_HIGH",
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_ONLY_HIGH",
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_ONLY_HIGH",
},
]
model = genai.GenerativeModel(
model_name=model_name,
generation_config=generation_config,
safety_settings=safety_settings,
)
try:
response = model.generate_content(prompt)
candidates = response.candidates
generated_text = candidates[0].content.parts[0].text
except (AttributeError, IndexError) as e:
print("Gemini Error:", e)
return generated_text
if llm_provider == "cloudflare":
import requests
response = requests.post(
f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model_name}",
headers={"Authorization": f"Bearer {api_key}"},
json={
"messages": [
{"role": "system", "content": "You are a friendly assistant"},
{"role": "user", "content": prompt},
]
},
)
result = response.json()
logger.info(result)
return result["result"]["response"]
if llm_provider == "ernie":
import requests
params = {
"grant_type": "client_credentials",
"client_id": api_key,
"client_secret": secret_key,
}
access_token = (
requests.post("https://aip.baidubce.com/oauth/2.0/token", params=params)
.json()
.get("access_token")
)
url = f"{base_url}?access_token={access_token}"
payload = json.dumps(
{
"messages": [{"role": "user", "content": prompt}],
"temperature": 0.5,
"top_p": 0.8,
"penalty_score": 1,
"disable_search": False,
"enable_citation": False,
"response_format": "text",
}
)
headers = {"Content-Type": "application/json"}
response = requests.request(
"POST", url, headers=headers, data=payload
).json()
return response.get("result")
if llm_provider == "azure":
client = AzureOpenAI(
api_key=api_key,
api_version=api_version,
azure_endpoint=base_url,
)
else:
client = OpenAI(
api_key=api_key,
base_url=base_url,
)
response = client.chat.completions.create(
model=model_name, messages=[{"role": "user", "content": prompt}]
)
if response:
if isinstance(response, GenerationResponse):
status_code = response.status_code
if status_code != 200:
raise Exception(
f'[{llm_provider}] returned an error response: "{response}"'
)
content = response["output"]["text"]
return content.replace("\n", "")
if isinstance(response, ChatCompletion):
content = response.choices[0].message.content
else:
raise Exception(
f'[{llm_provider}] returned an invalid response: "{response}"'
f'[{llm_provider}] returned an invalid response: "{response}", please check your network '
f"connection and try again."
)
else:
raise Exception(f"[{llm_provider}] returned an empty response")
if llm_provider == "gemini":
import google.generativeai as genai
genai.configure(api_key=api_key, transport="rest")
generation_config = {
"temperature": 0.5,
"top_p": 1,
"top_k": 1,
"max_output_tokens": 2048,
}
safety_settings = [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_ONLY_HIGH",
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_ONLY_HIGH",
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_ONLY_HIGH",
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_ONLY_HIGH",
},
]
model = genai.GenerativeModel(
model_name=model_name,
generation_config=generation_config,
safety_settings=safety_settings,
)
try:
response = model.generate_content(prompt)
candidates = response.candidates
generated_text = candidates[0].content.parts[0].text
except (AttributeError, IndexError) as e:
print("Gemini Error:", e)
return generated_text
if llm_provider == "cloudflare":
import requests
response = requests.post(
f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model_name}",
headers={"Authorization": f"Bearer {api_key}"},
json={
"messages": [
{"role": "system", "content": "You are a friendly assistant"},
{"role": "user", "content": prompt},
]
},
)
result = response.json()
logger.info(result)
return result["result"]["response"]
if llm_provider == "ernie":
import requests
params = {
"grant_type": "client_credentials",
"client_id": api_key,
"client_secret": secret_key,
}
access_token = (
requests.post("https://aip.baidubce.com/oauth/2.0/token", params=params)
.json()
.get("access_token")
)
url = f"{base_url}?access_token={access_token}"
payload = json.dumps(
{
"messages": [{"role": "user", "content": prompt}],
"temperature": 0.5,
"top_p": 0.8,
"penalty_score": 1,
"disable_search": False,
"enable_citation": False,
"response_format": "text",
}
)
headers = {"Content-Type": "application/json"}
response = requests.request(
"POST", url, headers=headers, data=payload
).json()
return response.get("result")
if llm_provider == "azure":
client = AzureOpenAI(
api_key=api_key,
api_version=api_version,
azure_endpoint=base_url,
)
else:
client = OpenAI(
api_key=api_key,
base_url=base_url,
)
response = client.chat.completions.create(
model=model_name, messages=[{"role": "user", "content": prompt}]
)
if response:
if isinstance(response, ChatCompletion):
content = response.choices[0].message.content
else:
raise Exception(
f'[{llm_provider}] returned an invalid response: "{response}", please check your network '
f"connection and try again."
f"[{llm_provider}] returned an empty response, please check your network connection and try again."
)
else:
raise Exception(
f"[{llm_provider}] returned an empty response, please check your network connection and try again."
)
return content.replace("\n", "")
return content.replace("\n", "")
except Exception as e:
return f"Error: {str(e)}"
def generate_script(
@@ -319,8 +321,10 @@ Generate a script for a video, depending on the subject of the video.
if i < _max_retries:
logger.warning(f"failed to generate video script, trying again... {i + 1}")
logger.success(f"completed: \n{final_script}")
if "Error: " in final_script:
logger.error(f"failed to generate video script: {final_script}")
else:
logger.success(f"completed: \n{final_script}")
return final_script.strip()
@@ -358,6 +362,9 @@ Please note that you must use English for generating video search terms; Chinese
for i in range(_max_retries):
try:
response = _generate_response(prompt)
if "Error: " in response:
logger.error(f"failed to generate video script: {response}")
return response
search_terms = json.loads(response)
if not isinstance(search_terms, list) or not all(
isinstance(term, str) for term in search_terms

2
app/services/task.py
View File

@@ -214,7 +214,7 @@ def start(task_id, params: VideoParams, stop_at: str = "video"):
# 1. Generate script
video_script = generate_script(task_id, params)
if not video_script:
if not video_script or "Error: " in video_script:
sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
return