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Merge pull request #1564 from chandan84/fix/support_litellm_extra_headers
Fix/support litellm extra headers
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@ -30,6 +30,14 @@ model="" # the OpenAI model you've deployed on Azure (e.g. gpt-4o)
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fallback_models=["..."]
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```
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Passing custom headers to the underlying LLM Model API can be done by setting extra_headers parameter to litellm.
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```
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[litellm]
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extra_headers='{"projectId": "<authorized projectId >", ...}') #The value of this setting should be a JSON string representing the desired headers, a ValueError is thrown otherwise.
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```
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This enables users to pass authorization tokens or API keys, when routing requests through an API management gateway.
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### Ollama
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You can run models locally through either [VLLM](https://docs.litellm.ai/docs/providers/vllm) or [Ollama](https://docs.litellm.ai/docs/providers/ollama)
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@ -11,6 +11,7 @@ from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
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from pr_agent.algo.utils import ReasoningEffort, get_version
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from pr_agent.config_loader import get_settings
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from pr_agent.log import get_logger
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import json
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OPENAI_RETRIES = 5
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@ -254,6 +255,16 @@ class LiteLLMAIHandler(BaseAiHandler):
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if self.repetition_penalty:
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kwargs["repetition_penalty"] = self.repetition_penalty
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#Added support for extra_headers while using litellm to call underlying model, via a api management gateway, would allow for passing custom headers for security and authorization
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if get_settings().get("LITELLM.EXTRA_HEADERS", None):
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try:
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litellm_extra_headers = json.loads(get_settings().litellm.extra_headers)
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if not isinstance(litellm_extra_headers, dict):
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raise ValueError("LITELLM.EXTRA_HEADERS must be a JSON object")
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except json.JSONDecodeError as e:
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raise ValueError(f"LITELLM.EXTRA_HEADERS contains invalid JSON: {str(e)}")
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kwargs["extra_headers"] = litellm_extra_headers
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get_logger().debug("Prompts", artifact={"system": system, "user": user})
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if get_settings().config.verbosity_level >= 2:
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