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Merge pull request #197 from Hawksight-AI/semantic-extract
Robust LLM Extraction and Groq 401 Fix
This commit is contained in:
Mohd Kaif
@@ -243,68 +243,136 @@ class BaseProvider:
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mode = instructor.Mode.TOOLS # Default mode
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if provider_name == "OpenAIProvider" and self.client:
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client = instructor.from_openai(self.client)
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elif provider_name == "AnthropicProvider" and self.client:
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client = instructor.from_anthropic(self.client)
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elif provider_name == "GeminiProvider" and self.client:
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client = instructor.from_gemini(
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self.client,
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mode=instructor.Mode.GEMINI_JSON
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)
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elif provider_name == "GroqProvider" and self.client:
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# Try using from_groq if available (newer instructor versions)
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if hasattr(instructor, "from_groq"):
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client = instructor.from_groq(self.client, mode=instructor.Mode.JSON)
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if hasattr(instructor, "from_provider"):
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try:
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client = instructor.from_provider(
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provider=f"openai/{kwargs.get('model', self.model)}",
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api_key=self.api_key
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)
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except Exception:
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client = instructor.from_openai(self.client)
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else:
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# Fallback: Create OpenAI client pointing to Groq
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# This avoids the "Client should be an instance of openai.OpenAI" warning
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client = instructor.from_openai(self.client)
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elif provider_name == "AnthropicProvider" and self.client:
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if hasattr(instructor, "from_provider"):
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try:
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client = instructor.from_provider(
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provider=f"anthropic/{kwargs.get('model', self.model)}",
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api_key=self.api_key
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)
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except Exception:
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client = instructor.from_anthropic(self.client)
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else:
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client = instructor.from_anthropic(self.client)
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elif provider_name == "GeminiProvider" and self.client:
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if hasattr(instructor, "from_provider"):
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try:
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client = instructor.from_provider(
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provider=f"gemini/{kwargs.get('model', self.model)}",
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api_key=self.api_key
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)
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except Exception:
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client = instructor.from_gemini(
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self.client,
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mode=instructor.Mode.GEMINI_JSON
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)
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else:
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client = instructor.from_gemini(
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self.client,
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mode=instructor.Mode.GEMINI_JSON
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)
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elif provider_name == "GroqProvider" and self.client:
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# Try using from_provider which is recommended for Groq in latest instructor
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if hasattr(instructor, "from_provider"):
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try:
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client = instructor.from_provider(
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provider=f"groq/{kwargs.get('model', self.model)}",
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api_key=self.api_key
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)
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except Exception:
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client = None
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if not client:
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# Try using from_groq if available (newer instructor versions)
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if hasattr(instructor, "from_groq"):
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client = instructor.from_groq(self.client, mode=instructor.Mode.JSON)
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else:
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# Fallback: Create OpenAI client pointing to Groq
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# This avoids the "Client should be an instance of openai.OpenAI" warning
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try:
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from openai import OpenAI
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# Fix: Use self.api_key instead of self.client.api_key
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groq_client = OpenAI(
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base_url="https://api.groq.com/openai/v1",
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api_key=self.api_key,
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)
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client = instructor.from_openai(groq_client, mode=instructor.Mode.JSON)
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except Exception:
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# Last resort: try passing the groq client directly
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client = instructor.from_openai(self.client, mode=instructor.Mode.JSON)
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elif provider_name == "OllamaProvider":
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# Try from_provider for Ollama if available
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if hasattr(instructor, "from_provider"):
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try:
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client = instructor.from_provider(
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provider=f"ollama/{kwargs.get('model', self.model)}",
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)
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except Exception:
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client = None
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if not client:
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# Create OpenAI-compatible client for Ollama
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try:
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from openai import OpenAI
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groq_client = OpenAI(
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base_url="https://api.groq.com/openai/v1",
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api_key=self.client.api_key,
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# Ollama typically runs on localhost:11434/v1
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base_url = getattr(self, "base_url", "http://localhost:11434")
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if not base_url.endswith("/v1"):
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base_url = f"{base_url.rstrip('/')}/v1"
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ollama_client = OpenAI(
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base_url=base_url,
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api_key="ollama", # required but unused
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)
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client = instructor.from_openai(groq_client, mode=instructor.Mode.JSON)
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except Exception:
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# Last resort: try passing the groq client directly
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client = instructor.from_openai(self.client, mode=instructor.Mode.JSON)
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elif provider_name == "OllamaProvider":
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# Create OpenAI-compatible client for Ollama
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try:
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from openai import OpenAI
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# Ollama typically runs on localhost:11434/v1
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base_url = getattr(self, "base_url", "http://localhost:11434")
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if not base_url.endswith("/v1"):
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base_url = f"{base_url.rstrip('/')}/v1"
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ollama_client = OpenAI(
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base_url=base_url,
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api_key="ollama", # required but unused
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)
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client = instructor.from_openai(ollama_client, mode=instructor.Mode.JSON)
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except ImportError:
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pass
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client = instructor.from_openai(ollama_client, mode=instructor.Mode.JSON)
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except ImportError:
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pass
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elif provider_name == "DeepSeekProvider" and self.client:
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# DeepSeek is OpenAI compatible
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# We need to wrap the underlying client if it exposes the OpenAI interface
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# or create a new OpenAI client if self.client is a deepseek.Client (which might be just a wrapper)
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# Assuming deepseek.Client is compatible or we can use OpenAI client
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try:
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# DeepSeek usually works with standard OpenAI client
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# If self.client is deepseek.Client, check if we can wrap it
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# Otherwise create a new OpenAI client
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from openai import OpenAI
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if isinstance(self.client, OpenAI):
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client = instructor.from_openai(self.client, mode=instructor.Mode.JSON)
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else:
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# Try creating fresh client
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ds_client = OpenAI(
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api_key=self.api_key,
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base_url="https://api.deepseek.com"
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)
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client = instructor.from_openai(ds_client, mode=instructor.Mode.JSON)
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except Exception:
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pass
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# Try from_provider for DeepSeek
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if hasattr(instructor, "from_provider"):
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try:
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client = instructor.from_provider(
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provider=f"deepseek/{kwargs.get('model', self.model)}",
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api_key=self.api_key
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)
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except Exception:
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client = None
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if not client:
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# DeepSeek is OpenAI compatible
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try:
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from openai import OpenAI
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if isinstance(self.client, OpenAI):
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client = instructor.from_openai(self.client, mode=instructor.Mode.JSON)
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else:
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# Try creating fresh client
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ds_client = OpenAI(
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api_key=self.api_key,
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base_url="https://api.deepseek.com"
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)
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client = instructor.from_openai(ds_client, mode=instructor.Mode.JSON)
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except Exception:
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pass
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# Global LiteLLM support - if litellm is passed in kwargs or config
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if not client and (kwargs.get("litellm") or self.config.get("litellm")):
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if hasattr(instructor, "from_provider"):
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try:
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# Format for litellm in instructor is litellm/model_name
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provider_model = kwargs.get("model", self.model)
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litellm_provider = f"litellm/{provider_model}"
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client = instructor.from_provider(litellm_provider, api_key=self.api_key)
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except Exception:
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pass
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if client:
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# Map generate arguments to client arguments
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