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from models import RequestModel
async def get_image_message(base64_image, engine = None):
if "gpt" == engine:
return {
"type": "image_url",
"image_url": {
"url": base64_image,
}
}
if "claude" == engine:
return {
"type": "image",
"source": {
"type": "base64",
"media_type": "image/jpeg",
"data": base64_image.split(",")[1],
}
}
if "gemini" == engine:
return {
"inlineData": {
"mimeType": "image/jpeg",
"data": base64_image.split(",")[1],
}
}
raise ValueError("Unknown engine")
async def get_text_message(role, message, engine = None):
if "gpt" == engine or "claude" == engine:
return {"type": "text", "text": message}
if "gemini" == engine:
return {"text": message}
raise ValueError("Unknown engine")
async def get_gemini_payload(request, engine, provider):
headers = {
'Content-Type': 'application/json'
}
url = provider['base_url']
model = provider['model'][request.model]
if request.stream:
gemini_stream = "streamGenerateContent"
url = url.format(model=model, stream=gemini_stream, api_key=provider['api'])
messages = []
for msg in request.messages:
if isinstance(msg.content, list):
content = []
for item in msg.content:
if item.type == "text":
text_message = await get_text_message(msg.role, item.text, engine)
# print("text_message", text_message)
content.append(text_message)
elif item.type == "image_url":
image_message = await get_image_message(item.image_url.url, engine)
content.append(image_message)
else:
content = msg.content
if msg.role != "system":
messages.append({"role": msg.role, "parts": content})
payload = {
"contents": messages,
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
}
]
}
miss_fields = [
'model',
'messages',
'stream',
'tools',
'tool_choice',
'temperature',
'top_p',
'max_tokens',
'presence_penalty',
'frequency_penalty',
'n',
'user',
'include_usage',
'logprobs',
'top_logprobs'
]
for field, value in request.model_dump(exclude_unset=True).items():
if field not in miss_fields and value is not None:
payload[field] = value
return url, headers, payload
async def get_gpt_payload(request, engine, provider):
headers = {
'Authorization': f"Bearer {provider['api']}",
'Content-Type': 'application/json'
}
url = provider['base_url']
messages = []
for msg in request.messages:
if isinstance(msg.content, list):
content = []
for item in msg.content:
if item.type == "text":
text_message = await get_text_message(msg.role, item.text, engine)
content.append(text_message)
elif item.type == "image_url":
image_message = await get_image_message(item.image_url.url, engine)
content.append(image_message)
else:
content = msg.content
name = msg.name
if name:
messages.append({"role": msg.role, "name": name, "content": content})
else:
messages.append({"role": msg.role, "content": content})
model = provider['model'][request.model]
payload = {
"model": model,
"messages": messages,
}
miss_fields = [
'model',
'messages'
]
for field, value in request.model_dump(exclude_unset=True).items():
if field not in miss_fields and value is not None:
payload[field] = value
return url, headers, payload
async def gpt2claude_tools_json(json_dict):
import copy
json_dict = copy.deepcopy(json_dict)
keys_to_change = {
"parameters": "input_schema",
}
for old_key, new_key in keys_to_change.items():
if old_key in json_dict:
if new_key:
json_dict[new_key] = json_dict.pop(old_key)
else:
json_dict.pop(old_key)
# if "tools" in json_dict.keys():
# json_dict["tool_choice"] = {
# "type": "auto"
# }
return json_dict
async def get_claude_payload(request, engine, provider):
headers = {
"content-type": "application/json",
"x-api-key": f"{provider['api']}",
"anthropic-version": "2023-06-01",
"anthropic-beta": "tools-2024-05-16"
}
url = provider['base_url']
messages = []
for msg in request.messages:
if isinstance(msg.content, list):
content = []
for item in msg.content:
if item.type == "text":
text_message = await get_text_message(msg.role, item.text, engine)
content.append(text_message)
elif item.type == "image_url":
image_message = await get_image_message(item.image_url.url, engine)
content.append(image_message)
else:
content = msg.content
name = msg.name
if name:
# messages.append({"role": "assistant", "name": name, "content": content})
messages.append(
{
"role": "assistant",
"content": [
{
"type": "tool_use",
"id": "toolu_01RofFmKHUKsEaZvqESG5Hwz",
"name": name,
"input": {"text": messages[-1]["content"][0]["text"]},
}
]
}
)
messages.append(
{
"role": "user",
"content": [
{
"type": "tool_result",
"tool_use_id": "toolu_01RofFmKHUKsEaZvqESG5Hwz",
"content": content
}
]
}
)
elif msg.role != "system":
messages.append({"role": msg.role, "content": content})
elif msg.role == "system":
system_prompt = content
model = provider['model'][request.model]
payload = {
"model": model,
"messages": messages,
"system": system_prompt,
}
# json_post = {
# "model": model or self.engine,
# "messages": self.conversation[convo_id] if pass_history else [{
# "role": "user",
# "content": prompt
# }],
# "temperature": kwargs.get("temperature", self.temperature),
# "top_p": kwargs.get("top_p", self.top_p),
# "max_tokens": model_max_tokens,
# "stream": True,
# }
miss_fields = [
'model',
'messages',
'presence_penalty',
'frequency_penalty',
'n',
'user',
'include_usage',
]
for field, value in request.model_dump(exclude_unset=True).items():
if field not in miss_fields and value is not None:
payload[field] = value
if request.tools:
tools = []
for tool in request.tools:
print("tool", type(tool), tool)
json_tool = await gpt2claude_tools_json(tool.dict()["function"])
tools.append(json_tool)
payload["tools"] = tools
if "tool_choice" in payload:
payload["tool_choice"] = {
"type": "auto"
}
import json
print("payload", json.dumps(payload, indent=2, ensure_ascii=False))
return url, headers, payload
async def get_payload(request: RequestModel, engine, provider):
if engine == "gemini":
return await get_gemini_payload(request, engine, provider)
elif engine == "claude":
return await get_claude_payload(request, engine, provider)
elif engine == "gpt":
return await get_gpt_payload(request, engine, provider)
else:
raise ValueError("Unknown payload") |