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https://github.com/Zippland/Snap-Solver.git
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gpt4o run successfully
This commit is contained in:
Zylan
221
models/gpt4o.py
221
models/gpt4o.py
@@ -1,6 +1,5 @@
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import json
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import requests
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from typing import Generator
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import os
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from typing import Generator, Dict, Optional
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from openai import OpenAI
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from .base import BaseModel
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@@ -22,52 +21,67 @@ class GPT4oModel(BaseModel):
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# Initial status
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yield {"status": "started", "content": ""}
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# Configure client with proxy if needed
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client_args = {
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"api_key": self.api_key,
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"base_url": "https://api.openai.com/v1" # Replace with actual GPT-4o API endpoint
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# Save original environment state
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original_env = {
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'http_proxy': os.environ.get('http_proxy'),
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'https_proxy': os.environ.get('https_proxy')
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}
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if proxies:
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session = requests.Session()
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session.proxies = proxies
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client_args["http_client"] = session
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client = OpenAI(**client_args)
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try:
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# Set proxy environment variables if provided
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if proxies:
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if 'http' in proxies:
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os.environ['http_proxy'] = proxies['http']
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if 'https' in proxies:
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os.environ['https_proxy'] = proxies['https']
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messages = [
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{
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"role": "system",
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"content": self.system_prompt
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},
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{
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"role": "user",
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"content": text
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# Create OpenAI client
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client = OpenAI(
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api_key=self.api_key,
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base_url="https://api.openai.com/v1" # Replace with actual GPT-4o API endpoint
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)
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messages = [
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{
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"role": "system",
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"content": self.system_prompt
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},
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{
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"role": "user",
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"content": text
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}
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]
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response = client.chat.completions.create(
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model=self.get_model_identifier(),
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messages=messages,
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temperature=self.temperature,
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stream=True,
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max_tokens=4000
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)
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for chunk in response:
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if hasattr(chunk.choices[0].delta, 'content'):
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content = chunk.choices[0].delta.content
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if content:
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yield {
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"status": "streaming",
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"content": content
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}
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# Send completion status
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yield {
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"status": "completed",
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"content": ""
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}
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]
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response = client.chat.completions.create(
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model=self.get_model_identifier(),
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messages=messages,
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temperature=self.temperature,
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stream=True,
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max_tokens=4000
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)
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for chunk in response:
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if hasattr(chunk.choices[0].delta, 'content'):
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content = chunk.choices[0].delta.content
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if content:
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yield {
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"status": "streaming",
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"content": content
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}
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# Send completion status
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yield {
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"status": "completed",
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"content": ""
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}
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finally:
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# Restore original environment state
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for key, value in original_env.items():
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if value is None:
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os.environ.pop(key, None)
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else:
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os.environ[key] = value
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except Exception as e:
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error_msg = str(e)
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@@ -87,64 +101,79 @@ class GPT4oModel(BaseModel):
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# Initial status
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yield {"status": "started", "content": ""}
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# Configure client with proxy if needed
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client_args = {
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"api_key": self.api_key,
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"base_url": "https://api.openai.com/v1" # Replace with actual GPT-4o API endpoint
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# Save original environment state
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original_env = {
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'http_proxy': os.environ.get('http_proxy'),
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'https_proxy': os.environ.get('https_proxy')
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}
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if proxies:
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session = requests.Session()
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session.proxies = proxies
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client_args["http_client"] = session
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client = OpenAI(**client_args)
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try:
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# Set proxy environment variables if provided
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if proxies:
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if 'http' in proxies:
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os.environ['http_proxy'] = proxies['http']
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if 'https' in proxies:
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os.environ['https_proxy'] = proxies['https']
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messages = [
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{
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"role": "system",
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"content": self.system_prompt
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},
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{
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"role": "user",
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"content": [
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/png;base64,{image_data}",
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"detail": "high"
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# Create OpenAI client
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client = OpenAI(
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api_key=self.api_key,
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base_url="https://api.openai.com/v1" # Replace with actual GPT-4o API endpoint
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)
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messages = [
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{
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"role": "system",
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"content": self.system_prompt
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},
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{
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"role": "user",
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"content": [
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/png;base64,{image_data}",
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"detail": "high"
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}
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},
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{
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"type": "text",
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"text": "Please analyze this question and provide a detailed solution. If you see multiple questions, focus on solving them one at a time."
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}
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},
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{
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"type": "text",
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"text": "Please analyze this question and provide a detailed solution. If you see multiple questions, focus on solving them one at a time."
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}
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]
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]
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}
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]
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response = client.chat.completions.create(
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model=self.get_model_identifier(),
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messages=messages,
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temperature=self.temperature,
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stream=True,
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max_tokens=4000
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)
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for chunk in response:
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if hasattr(chunk.choices[0].delta, 'content'):
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content = chunk.choices[0].delta.content
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if content:
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yield {
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"status": "streaming",
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"content": content
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}
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# Send completion status
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yield {
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"status": "completed",
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"content": ""
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}
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]
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response = client.chat.completions.create(
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model=self.get_model_identifier(),
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messages=messages,
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temperature=self.temperature,
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stream=True,
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max_tokens=4000
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)
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for chunk in response:
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if hasattr(chunk.choices[0].delta, 'content'):
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content = chunk.choices[0].delta.content
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if content:
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yield {
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"status": "streaming",
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"content": content
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}
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# Send completion status
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yield {
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"status": "completed",
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"content": ""
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}
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finally:
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# Restore original environment state
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for key, value in original_env.items():
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if value is None:
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os.environ.pop(key, None)
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else:
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os.environ[key] = value
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except Exception as e:
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error_msg = str(e)
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