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fixed api endpoint url and update .env.example
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sample_solutions/MultiAgentQnA/api/.env.example

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# - The API key is the litellm_master_key value from the generated vault.yml file
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#
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# **APISIX Gateway**: Provide your APISIX Gateway URL and authentication token
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# - For embedding: https://apisix-gateway.example.com/bge-base-en-v1.5
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# - For inference: https://apisix-gateway.example.com/Llama-3.1-8B-Instruct
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# - Note: APISIX requires the model name in the URL path
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# - For APISIX, include the model name in the INFERENCE_API_ENDPOINT path
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# - Example: https://apisix-gateway.example.com/Llama-3.1-8B-Instruct
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# - Set EMBEDDING_API_ENDPOINT separately for the embedding model
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# - Example: https://apisix-gateway.example.com/bge-base-en-v1.5
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# - To generate the APISIX authentication token, use the [generate-token.sh](https://github.com/opea-project/Enterprise-Inference/blob/main/core/scripts/generate-token.sh) script
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# - The token is generated using Keycloak client credentials
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# - Set EMBEDDING_API_ENDPOINT and INFERENCE_MODEL_ENDPOINT when using APISIX
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#
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# INFERENCE_API_TOKEN: Authentication token/API key for the inference service
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INFERENCE_API_ENDPOINT=https://api.example.com
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# APISIX Gateway Endpoints
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# Uncomment and set these when using APISIX Gateway:
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# EMBEDDING_API_ENDPOINT=https://api.example.com/bge-base-en-v1.5
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# INFERENCE_MODEL_ENDPOINT=https://api.example.com/Llama-3.1-8B-Instruct
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# IMPORTANT: Use exact APISIX route paths:
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# Example routes: /bge-base-en-v1.5-vllmcpu/* and /Llama-3.1-8B-Instruct-vllmcpu/*
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# INFERENCE_API_ENDPOINT=https://api.example.com/Llama-3.1-8B-Instruct-vllmcpu
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# EMBEDDING_API_ENDPOINT=https://api.example.com/bge-base-en-v1.5-vllmcpu
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# Local URL Endpoint (only needed for non-public domains)
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# If using a local domain like api.example.com mapped to localhost:

sample_solutions/MultiAgentQnA/api/config.py

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INFERENCE_API_TOKEN = os.getenv("INFERENCE_API_TOKEN")
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EMBEDDING_API_ENDPOINT = os.getenv("EMBEDDING_API_ENDPOINT")
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INFERENCE_MODEL_ENDPOINT = os.getenv("INFERENCE_MODEL_ENDPOINT")
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if not EMBEDDING_API_ENDPOINT:
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EMBEDDING_API_ENDPOINT = INFERENCE_API_ENDPOINT
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if not INFERENCE_MODEL_ENDPOINT:
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INFERENCE_MODEL_ENDPOINT = INFERENCE_API_ENDPOINT
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EMBEDDING_MODEL_NAME = os.getenv("EMBEDDING_MODEL_NAME", "bge-base-en-v1.5")
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INFERENCE_MODEL_NAME = os.getenv("INFERENCE_MODEL_NAME", "meta-llama/Llama-3.1-8B-Instruct")

sample_solutions/MultiAgentQnA/api/services/api_client.py

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def __init__(self):
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self.embedding_base_url = config.EMBEDDING_API_ENDPOINT
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self.inference_base_url = config.INFERENCE_MODEL_ENDPOINT
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self.inference_base_url = config.INFERENCE_API_ENDPOINT
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self.token = config.INFERENCE_API_TOKEN
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self.http_client = httpx.Client(verify=False)
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logger.info(f"✓ API Client initialized - Embedding: {self.embedding_base_url}, Inference: {self.inference_base_url}")

sample_solutions/PDFToPodcast/.env.example

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sample_solutions/PDFToPodcast/.gitignore

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sample_solutions/PDFToPodcast/Dockerfile

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