apunkt/trustgraph
1
0
Fork 0
mirror of https://github.com/trustgraph-ai/trustgraph.git synced 2026-07-23 20:21:03 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions 3

More LLMs

Browse source
This commit is contained in:
Cyber MacGeddon 2025-09-24 16:34:36 +01:00
parent a7466de418
commit 14c51f2766
4 changed files with 38 additions and 15 deletions
Download patch file Download diff file Expand all files Collapse all files

13
trustgraph-flow/trustgraph/model/text_completion/azure/llm.py
View file

@ -32,7 +32,7 @@ class Processor(LlmService):
token = params.get("token", default_token)
temperature = params.get("temperature", default_temperature)
max_output = params.get("max_output", default_max_output)
model = default_model
model = params.get("model", default_model)
if endpoint is None:
raise RuntimeError("Azure endpoint not specified")
@ -53,7 +53,7 @@ class Processor(LlmService):
self.token = token
self.temperature = temperature
self.max_output = max_output
self.model = model
self.default_model = model
def build_prompt(self, system, content):
@ -100,7 +100,12 @@ class Processor(LlmService):
return result
async def generate_content(self, system, prompt):
async def generate_content(self, system, prompt, model=None):
# Use provided model or fall back to default
model_name = model or self.default_model
logger.debug(f"Using model: {model_name}")
try:
@ -125,7 +130,7 @@ class Processor(LlmService):
text = resp,
in_token = inputtokens,
out_token = outputtokens,
model = self.model
model = model_name
)
return resp

13
trustgraph-flow/trustgraph/model/text_completion/llamafile/llm.py
View file

@ -39,7 +39,7 @@ class Processor(LlmService):
}
)
self.model = model
self.default_model = model
self.llamafile=llamafile
self.temperature = temperature
self.max_output = max_output
@ -50,14 +50,19 @@ class Processor(LlmService):
logger.info("Llamafile LLM service initialized")
async def generate_content(self, system, prompt):
async def generate_content(self, system, prompt, model=None):
# Use provided model or fall back to default
model_name = model or self.default_model
logger.debug(f"Using model: {model_name}")
prompt = system + "\n\n" + prompt
try:
resp = self.openai.chat.completions.create(
model=self.model,
model=model_name,
messages=[
{"role": "user", "content": prompt}
]
@ -82,7 +87,7 @@ class Processor(LlmService):
text = resp.choices[0].message.content,
in_token = inputtokens,
out_token = outputtokens,
model = "llama.cpp",
model = model_name,
)
return resp

13
trustgraph-flow/trustgraph/model/text_completion/lmstudio/llm.py
View file

@ -39,7 +39,7 @@ class Processor(LlmService):
}
)
self.model = model
self.default_model = model
self.url = url + "v1/"
self.temperature = temperature
self.max_output = max_output
@ -50,7 +50,12 @@ class Processor(LlmService):
logger.info("LMStudio LLM service initialized")
async def generate_content(self, system, prompt):
async def generate_content(self, system, prompt, model=None):
# Use provided model or fall back to default
model_name = model or self.default_model
logger.debug(f"Using model: {model_name}")
prompt = system + "\n\n" + prompt
@ -59,7 +64,7 @@ class Processor(LlmService):
logger.debug(f"Prompt: {prompt}")
resp = self.openai.chat.completions.create(
model=self.model,
model=model_name,
messages=[
{"role": "user", "content": prompt}
]
@ -86,7 +91,7 @@ class Processor(LlmService):
text = resp.choices[0].message.content,
in_token = inputtokens,
out_token = outputtokens,
model = self.model
model = model_name
)
return resp

14
trustgraph-flow/trustgraph/model/text_completion/tgi/llm.py
View file

@ -30,32 +30,40 @@ class Processor(LlmService):
base_url = params.get("url", default_base_url)
temperature = params.get("temperature", default_temperature)
max_output = params.get("max_output", default_max_output)
model = params.get("model", "tgi")
super(Processor, self).__init__(
**params | {
"temperature": temperature,
"max_output": max_output,
"url": base_url,
"model": model,
}
)
self.base_url = base_url
self.temperature = temperature
self.max_output = max_output
self.default_model = model
self.session = aiohttp.ClientSession()
logger.info(f"Using TGI service at {base_url}")
logger.info("TGI LLM service initialized")
async def generate_content(self, system, prompt):
async def generate_content(self, system, prompt, model=None):
# Use provided model or fall back to default
model_name = model or self.default_model
logger.debug(f"Using model: {model_name}")
headers = {
"Content-Type": "application/json",
}
request = {
"model": "tgi",
"model": model_name,
"messages": [
{
"role": "system",
@ -96,7 +104,7 @@ class Processor(LlmService):
text = ans,
in_token = inputtokens,
out_token = outputtokens,
model = "tgi",
model = model_name,
)
return resp