AI_POC/TERES_fastapi_backend
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v0.21.1-fastapi

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dangzerong
2025-11-04 16:06:36 +08:00
parent 3e58c3d0e9
commit d57b5d76ae
218 changed files with 19617 additions and 72339 deletions
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186
rag/llm/cv_model.py
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@@ -13,12 +13,16 @@
# See the License for the specific language governing permissions and
# limitations under the License.
#
import base64
import json
import os
import tempfile
import logging
from abc import ABC
from copy import deepcopy
from io import BytesIO
from pathlib import Path
from urllib.parse import urljoin
import requests
from openai import OpenAI
@@ -38,6 +42,7 @@ class Base(ABC):
self.is_tools = False
self.tools = []
self.toolcall_sessions = {}
self.extra_body = None
def describe(self, image):
raise NotImplementedError("Please implement encode method!")
@@ -45,7 +50,7 @@ class Base(ABC):
def describe_with_prompt(self, image, prompt=None):
raise NotImplementedError("Please implement encode method!")
def _form_history(self, system, history, images=[]):
def _form_history(self, system, history, images=None):
hist = []
if system:
hist.append({"role": "system", "content": system})
@@ -73,24 +78,26 @@ class Base(ABC):
})
return pmpt
def chat(self, system, history, gen_conf, images=[], **kwargs):
def chat(self, system, history, gen_conf, images=None, **kwargs):
try:
response = self.client.chat.completions.create(
model=self.model_name,
messages=self._form_history(system, history, images)
messages=self._form_history(system, history, images),
extra_body=self.extra_body,
)
return response.choices[0].message.content.strip(), response.usage.total_tokens
except Exception as e:
return "**ERROR**: " + str(e), 0
def chat_streamly(self, system, history, gen_conf, images=[], **kwargs):
def chat_streamly(self, system, history, gen_conf, images=None, **kwargs):
ans = ""
tk_count = 0
try:
response = self.client.chat.completions.create(
model=self.model_name,
messages=self._form_history(system, history, images),
stream=True
stream=True,
extra_body=self.extra_body,
)
for resp in response:
if not resp.choices[0].delta.content:
@@ -167,6 +174,7 @@ class GptV4(Base):
def __init__(self, key, model_name="gpt-4-vision-preview", lang="Chinese", base_url="https://api.openai.com/v1", **kwargs):
if not base_url:
base_url = "https://api.openai.com/v1"
self.api_key = key
self.client = OpenAI(api_key=key, base_url=base_url)
self.model_name = model_name
self.lang = lang
@@ -177,6 +185,7 @@ class GptV4(Base):
res = self.client.chat.completions.create(
model=self.model_name,
messages=self.prompt(b64),
extra_body=self.extra_body,
)
return res.choices[0].message.content.strip(), total_token_count_from_response(res)
@@ -185,6 +194,7 @@ class GptV4(Base):
res = self.client.chat.completions.create(
model=self.model_name,
messages=self.vision_llm_prompt(b64, prompt),
extra_body=self.extra_body,
)
return res.choices[0].message.content.strip(),total_token_count_from_response(res)
@@ -218,6 +228,61 @@ class QWenCV(GptV4):
base_url = "https://dashscope.aliyuncs.com/compatible-mode/v1"
super().__init__(key, model_name, lang=lang, base_url=base_url, **kwargs)
def chat(self, system, history, gen_conf, images=None, video_bytes=None, filename=""):
if video_bytes:
try:
summary, summary_num_tokens = self._process_video(video_bytes, filename)
return summary, summary_num_tokens
except Exception as e:
return "**ERROR**: " + str(e), 0
return "**ERROR**: Method chat not supported yet.", 0
def _process_video(self, video_bytes, filename):
from dashscope import MultiModalConversation
video_suffix = Path(filename).suffix or ".mp4"
with tempfile.NamedTemporaryFile(delete=False, suffix=video_suffix) as tmp:
tmp.write(video_bytes)
tmp_path = tmp.name
video_path = f"file://{tmp_path}"
messages = [
{
"role": "user",
"content": [
{
"video": video_path,
"fps": 2,
},
{
"text": "Please summarize this video in proper sentences.",
},
],
}
]
def call_api():
response = MultiModalConversation.call(
api_key=self.api_key,
model=self.model_name,
messages=messages,
)
summary = response["output"]["choices"][0]["message"].content[0]["text"]
return summary, num_tokens_from_string(summary)
try:
return call_api()
except Exception as e1:
import dashscope
dashscope.base_http_api_url = "https://dashscope-intl.aliyuncs.com/api/v1"
try:
return call_api()
except Exception as e2:
raise RuntimeError(f"Both default and intl endpoint failed.\nFirst error: {e1}\nSecond error: {e2}")
class HunyuanCV(GptV4):
_FACTORY_NAME = "Tencent Hunyuan"
@@ -249,6 +314,17 @@ class StepFunCV(GptV4):
self.lang = lang
Base.__init__(self, **kwargs)
class VolcEngineCV(GptV4):
_FACTORY_NAME = "VolcEngine"
def __init__(self, key, model_name, lang="Chinese", base_url="https://ark.cn-beijing.volces.com/api/v3", **kwargs):
if not base_url:
base_url = "https://ark.cn-beijing.volces.com/api/v3"
ark_api_key = json.loads(key).get("ark_api_key", "")
self.client = OpenAI(api_key=ark_api_key, base_url=base_url)
self.model_name = json.loads(key).get("ep_id", "") + json.loads(key).get("endpoint_id", "")
self.lang = lang
Base.__init__(self, **kwargs)
class LmStudioCV(GptV4):
_FACTORY_NAME = "LM-Studio"
@@ -327,10 +403,27 @@ class OpenRouterCV(GptV4):
):
if not base_url:
base_url = "https://openrouter.ai/api/v1"
self.client = OpenAI(api_key=key, base_url=base_url)
api_key = json.loads(key).get("api_key", "")
self.client = OpenAI(api_key=api_key, base_url=base_url)
self.model_name = model_name
self.lang = lang
Base.__init__(self, **kwargs)
provider_order = json.loads(key).get("provider_order", "")
self.extra_body = {}
if provider_order:
def _to_order_list(x):
if x is None:
return []
if isinstance(x, str):
return [s.strip() for s in x.split(",") if s.strip()]
if isinstance(x, (list, tuple)):
return [str(s).strip() for s in x if str(s).strip()]
return []
provider_cfg = {}
provider_order = _to_order_list(provider_order)
provider_cfg["order"] = provider_order
provider_cfg["allow_fallbacks"] = False
self.extra_body["provider"] = provider_cfg
class LocalAICV(GptV4):
@@ -413,7 +506,7 @@ class OllamaCV(Base):
options["frequency_penalty"] = gen_conf["frequency_penalty"]
return options
def _form_history(self, system, history, images=[]):
def _form_history(self, system, history, images=None):
hist = deepcopy(history)
if system and hist[0]["role"] == "user":
hist.insert(0, {"role": "system", "content": system})
@@ -454,7 +547,7 @@ class OllamaCV(Base):
except Exception as e:
return "**ERROR**: " + str(e), 0
def chat(self, system, history, gen_conf, images=[]):
def chat(self, system, history, gen_conf, images=None):
try:
response = self.client.chat(
model=self.model_name,
@@ -468,7 +561,7 @@ class OllamaCV(Base):
except Exception as e:
return "**ERROR**: " + str(e), 0
def chat_streamly(self, system, history, gen_conf, images=[]):
def chat_streamly(self, system, history, gen_conf, images=None):
ans = ""
try:
response = self.client.chat(
@@ -496,13 +589,14 @@ class GeminiCV(Base):
client.configure(api_key=key)
_client = client.get_default_generative_client()
self.api_key=key
self.model_name = model_name
self.model = GenerativeModel(model_name=self.model_name)
self.model._client = _client
self.lang = lang
Base.__init__(self, **kwargs)
def _form_history(self, system, history, images=[]):
def _form_history(self, system, history, images=None):
hist = []
if system:
hist.append({"role": "user", "parts": [system, history[0]["content"]]})
@@ -538,7 +632,15 @@ class GeminiCV(Base):
res = self.model.generate_content(input)
return res.text, total_token_count_from_response(res)
def chat(self, system, history, gen_conf, images=[]):
def chat(self, system, history, gen_conf, images=None, video_bytes=None, filename=""):
if video_bytes:
try:
summary, summary_num_tokens = self._process_video(video_bytes, filename)
return summary, summary_num_tokens
except Exception as e:
return "**ERROR**: " + str(e), 0
generation_config = dict(temperature=gen_conf.get("temperature", 0.3), top_p=gen_conf.get("top_p", 0.7))
try:
response = self.model.generate_content(
@@ -549,7 +651,7 @@ class GeminiCV(Base):
except Exception as e:
return "**ERROR**: " + str(e), 0
def chat_streamly(self, system, history, gen_conf, images=[]):
def chat_streamly(self, system, history, gen_conf, images=None):
ans = ""
response = None
try:
@@ -570,6 +672,46 @@ class GeminiCV(Base):
yield total_token_count_from_response(response)
def _process_video(self, video_bytes, filename):
from google import genai
from google.genai import types
video_size_mb = len(video_bytes) / (1024 * 1024)
client = genai.Client(api_key=self.api_key)
tmp_path = None
try:
if video_size_mb <= 20:
response = client.models.generate_content(
model="models/gemini-2.5-flash",
contents=types.Content(parts=[
types.Part(inline_data=types.Blob(data=video_bytes, mime_type="video/mp4")),
types.Part(text="Please summarize the video in proper sentences.")
])
)
else:
logging.info(f"Video size {video_size_mb:.2f}MB exceeds 20MB. Using Files API...")
video_suffix = Path(filename).suffix or ".mp4"
with tempfile.NamedTemporaryFile(delete=False, suffix=video_suffix) as tmp:
tmp.write(video_bytes)
tmp_path = Path(tmp.name)
uploaded_file = client.files.upload(file=tmp_path)
response = client.models.generate_content(
model="gemini-2.5-flash",
contents=[uploaded_file, "Please summarize this video in proper sentences."]
)
summary = response.text or ""
logging.info(f"Video summarized: {summary[:32]}...")
return summary, num_tokens_from_string(summary)
except Exception as e:
logging.error(f"Video processing failed: {e}")
raise
finally:
if tmp_path and tmp_path.exists():
tmp_path.unlink()
class NvidiaCV(Base):
_FACTORY_NAME = "NVIDIA"
@@ -614,7 +756,7 @@ class NvidiaCV(Base):
response = response.json()
return (
response["choices"][0]["message"]["content"].strip(),
response["usage"]["total_tokens"],
total_token_count_from_response(response),
)
def _request(self, msg, gen_conf={}):
@@ -637,26 +779,26 @@ class NvidiaCV(Base):
response = self._request(vision_prompt)
return (
response["choices"][0]["message"]["content"].strip(),
response["usage"]["total_tokens"],
total_token_count_from_response(response)
)
def chat(self, system, history, gen_conf, images=[], **kwargs):
def chat(self, system, history, gen_conf, images=None, **kwargs):
try:
response = self._request(self._form_history(system, history, images), gen_conf)
return (
response["choices"][0]["message"]["content"].strip(),
response["usage"]["total_tokens"],
total_token_count_from_response(response)
)
except Exception as e:
return "**ERROR**: " + str(e), 0
def chat_streamly(self, system, history, gen_conf, images=[], **kwargs):
def chat_streamly(self, system, history, gen_conf, images=None, **kwargs):
total_tokens = 0
try:
response = self._request(self._form_history(system, history, images), gen_conf)
cnt = response["choices"][0]["message"]["content"]
if "usage" in response and "total_tokens" in response["usage"]:
total_tokens += response["usage"]["total_tokens"]
total_tokens += total_token_count_from_response(response)
for resp in cnt:
yield resp
except Exception as e:
@@ -716,7 +858,7 @@ class AnthropicCV(Base):
gen_conf["max_tokens"] = self.max_tokens
return gen_conf
def chat(self, system, history, gen_conf, images=[]):
def chat(self, system, history, gen_conf, images=None):
gen_conf = self._clean_conf(gen_conf)
ans = ""
try:
@@ -737,7 +879,7 @@ class AnthropicCV(Base):
except Exception as e:
return ans + "\n**ERROR**: " + str(e), 0
def chat_streamly(self, system, history, gen_conf, images=[]):
def chat_streamly(self, system, history, gen_conf, images=None):
gen_conf = self._clean_conf(gen_conf)
total_tokens = 0
try:
@@ -821,13 +963,13 @@ class GoogleCV(AnthropicCV, GeminiCV):
else:
return GeminiCV.describe_with_prompt(self, image, prompt)
def chat(self, system, history, gen_conf, images=[]):
def chat(self, system, history, gen_conf, images=None):
if "claude" in self.model_name:
return AnthropicCV.chat(self, system, history, gen_conf, images)
else:
return GeminiCV.chat(self, system, history, gen_conf, images)
def chat_streamly(self, system, history, gen_conf, images=[]):
def chat_streamly(self, system, history, gen_conf, images=None):
if "claude" in self.model_name:
for ans in AnthropicCV.chat_streamly(self, system, history, gen_conf, images):
yield ans