fix: llama helper for text to summary, api helpers ip

.env.example

@@ -13,6 +13,7 @@ NEXT_PUBLIC_CLERK_AFTER_SIGN_UP_URL=/
 CEREBRAS_API_KEY=your_cerebras_api_key
 LLAMA_API_KEY=your_llama_api_key
 OPENAI_API_KEY=your_openai_api_key
+LLAMA_MODEL=llama3.1-8b
 
 # Redis
 REDIS_URL=redis://localhost:6379

backend/utils/cerebras_connect.py

@@ -0,0 +1,177 @@
+#!/usr/bin/env python3
+"""Module for connecting to Cerebras API and making model queries."""
+
+import os
+import sys
+from dotenv import load_dotenv
+from cerebras.cloud.sdk import (
+    Cerebras, AsyncCerebras, APIConnectionError, RateLimitError, APIStatusError
+)
+from cerebras.cloud.sdk.types.chat import ChatCompletion
+import cerebras.framework.torch as cbtorch
+# from cerebras.framework.torch import CerebrasPyTorch
+
+ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
+sys.path.append(ROOT)
+
+load_dotenv()
+CEREBRAS_API_KEY = os.getenv('CEREBRAS_API_KEY')
+if not CEREBRAS_API_KEY:
+    raise ValueError("CEREBRAS_API_KEY not found in environment variables")
+
+client = Cerebras(api_key=CEREBRAS_API_KEY)
+
+
+def query_cerebras(
+    content: str = "test",
+    model_name: str = "llama3.1-8b",
+    temperature: float = 0.7,
+    min_tokens: int = 800,
+    max_tokens: int = 1000,
+    top_p: float = 0.9
+) -> ChatCompletion:
+    """
+    Query Cerebras API with given content and parameters.
+
+    Args:
+        content: The prompt text to send to the model (default: "test")
+        model_name: Name of the model to use (default: llama3.1-8b)
+        temperature: Controls randomness in generation (0.0-1.0) (default: 0.7)
+        min_tokens: Minimum number of tokens to generate (default: 800)
+        max_tokens: Maximum number of tokens to generate (default: 1000)
+        top_p: Nucleus sampling parameter (0.0-1.0) (default: 0.9)
+
+    Returns:
+        ChatCompletion containing the model's response and metadata
+
+    Raises:
+        Exception: If there's an error querying the Cerebras API
+    """
+    try:
+        chat_completion = client.chat.completions.create(
+            messages=[{
+                "role": "user",
+                "content": content
+            }],
+            model=model_name,
+            temperature=temperature,
+            min_tokens=min_tokens,
+            max_tokens=max_tokens,
+            top_p=top_p
+        )
+        return chat_completion
+    except APIConnectionError as e:
+        print("The server could not be reached")
+        print(e.__cause__)  # an underlying Exception, likely raised within httpx.
+    except RateLimitError as e:
+        print("A 429 status code was received; we should back off a bit.")
+    except APIStatusError as e:
+        print("Another non-200-range status code was received")
+        print(e.status_code)
+        print(e.response)
+    except Exception as e:
+        raise Exception(f"Error querying Cerebras API: {str(e)}")
+
+
+def get_completion_text(response: ChatCompletion, debug: bool = False) -> str:
+    """
+    Extract the generated text from a Cerebras API response.
+
+    Args:
+        response: The ChatCompletion from query_cerebras
+        debug: If True, prints debug information about the response (default: False)
+
+    Returns:
+        The generated text string
+
+    Raises:
+        ValueError: If the response format is invalid or missing required fields
+    """
+    if debug:
+        choices = response.choices
+        choice0 = response.choices[0]
+        message = response.choices[0].message
+        content = response.choices[0].message.content
+
+        print("\nDebug Info:")
+        print(f'{choices=}\n')
+        print(f'{choice0=}\n')
+        print(f'{message=}\n')
+        print(f'{content=}\n')
+    try:
+        content = response.choices[0].message.content
+        return content
+    except (AttributeError, IndexError) as e:
+        raise ValueError(f"Invalid response format from Cerebras API: {str(e)}")
+
+def test_cerebras_api(
+    prompt: str = "Tell me about the WS3 chip",
+    model: str = "llama3.1-8b",
+    debug: bool = False
+) -> None:
+    """
+    Test the Cerebras API connection and response handling.
+
+    Args:
+        prompt: Test prompt to send to the model (default: "Tell me about the WS3 chip")
+        model: Model to test with (default: llama3.1-8b)
+        debug: If True, prints debug information (default: False)
+    """
+    try:
+        response = query_cerebras(
+            content=prompt,
+            model_name=model,
+            min_tokens=800,
+            max_tokens=1000
+        )
+        print("Raw response:")
+        print(response)
+
+        print("\nExtracted text:")
+        text = get_completion_text(response, debug=debug)
+        print(f"\nFinal output: {text}")
+
+    except Exception as e:
+        print(f"Error during test: {str(e)}")
+
+if __name__ == "__main__":
+    test_cerebras_api(debug=True)
+
+
+# TODO: cerebras_pytorch install. cuda compatible?
+
+
+"""
+ChatCompletionResponse(
+    id='chatcmpl-4bfbed53-110f-4988-a003-127e6a30756a',
+    choices=[
+        ChatCompletionResponseChoice(
+            finish_reason='length',
+            index=0,
+            message=ChatCompletionResponseChoiceMessage(
+                role='assistant',
+                content="I couldn't find any information on a widely known 'WS3 chip.' However, I can provide some possibilities based on available data:\n\n1. **WS3 chip in Apple devices**: Apple has been working on its own custom chipsets, such as the A14 Bionic, A15 Bionic, and A16 Bionic. However, I couldn't find any information on a 'WS3 chip' in Apple devices.\n\n2. **WS3 chip in other devices**: I found a few",
+                tool_calls=None
+            ),
+            logprobs=None
+        )
+    ],
+    created=1737583081,
+    model='llama3.1-8b',
+    object='chat.completion',
+    system_fingerprint='fp_6381a6c109',
+    time_info=ChatCompletionResponseTimeInfo(
+        completion_time=0.045409766,
+        prompt_time=0.002150612,
+        queue_time=8.8551e-05,
+        total_time=0.04952359199523926,
+        created=1737583081
+    ),
+    usage=ChatCompletionResponseUsage(
+        completion_tokens=100,
+        prompt_tokens=42,
+        total_tokens=142
+    ),
+    service_tier=None
+)
+"""