fix doc

landing-ai · Mar 19, 2024 · 4f01bae · 4f01bae
1 parent 22d5b74
commit 4f01bae
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Showing 2 changed files with 10 additions and 5 deletions.
diff --git a/vision_agent/llm/llm.py b/vision_agent/llm/llm.py
@@ -64,7 +64,8 @@ def __call__(self, input: Union[str, List[Dict[str, str]]]) -> str:
  return self.chat(input)
 
  def generate_classifier(self, prompt: str) -> ImageTool:
- prompt = CHOOSE_PARAMS.format(api_doc=CLIP.description, question=prompt)
+ api_doc = CLIP.description + "\n" + str(CLIP.usage)
+ prompt = CHOOSE_PARAMS.format(api_doc=api_doc, question=prompt)
  response = self.client.chat.completions.create(
  model=self.model_name,
  response_format={"type": "json_object"},
@@ -97,7 +98,8 @@ def generate_detector(self, params: str) -> ImageTool:
  return GroundingDINO(**cast(Mapping, params))
 
  def generate_segmentor(self, params: str) -> ImageTool:
- params = CHOOSE_PARAMS.format(api_doc=GroundingSAM.description, question=params)
+ api_doc = GroundingSAM.description + "\n" + str(GroundingSAM.usage)
+ params = CHOOSE_PARAMS.format(api_doc=api_doc, question=params)
  response = self.client.chat.completions.create(
  model=self.model_name,
  response_format={"type": "json_object"},

diff --git a/vision_agent/lmm/lmm.py b/vision_agent/lmm/lmm.py
@@ -169,7 +169,8 @@ def generate(self, prompt: str, image: Optional[Union[str, Path]] = None) -> str
  return cast(str, response.choices[0].message.content)
 
  def generate_classifier(self, prompt: str) -> ImageTool:
- prompt = CHOOSE_PARAMS.format(api_doc=CLIP.doc, question=prompt)
+ api_doc = CLIP.description + "\n" + str(CLIP.usage)
+ prompt = CHOOSE_PARAMS.format(api_doc=api_doc, question=prompt)
  response = self.client.chat.completions.create(
  model=self.model_name,
  messages=[
@@ -191,7 +192,8 @@ def generate_classifier(self, prompt: str) -> ImageTool:
  return CLIP(**cast(Mapping, prompt))
 
  def generate_detector(self, params: str) -> ImageTool:
- params = CHOOSE_PARAMS.format(api_doc=GroundingDINO.doc, question=params)
+ api_doc = GroundingDINO.description + "\n" + str(GroundingDINO.usage)
+ params = CHOOSE_PARAMS.format(api_doc=api_doc, question=params)
  response = self.client.chat.completions.create(
  model=self.model_name,
  messages=[
@@ -213,7 +215,8 @@ def generate_detector(self, params: str) -> ImageTool:
  return GroundingDINO(**cast(Mapping, params))
 
  def generate_segmentor(self, prompt: str) -> ImageTool:
- prompt = CHOOSE_PARAMS.format(api_doc=GroundingSAM.doc, question=prompt)
+ api_doc = GroundingSAM.description + "\n" + str(GroundingSAM.usage)
+ prompt = CHOOSE_PARAMS.format(api_doc=api_doc, question=prompt)
  response = self.client.chat.completions.create(
  model=self.model_name,
  messages=[