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added support for MAX_INPUT_TOKENS #61

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added support for MAX_INPUT_TOKENS #61

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7 changes: 5 additions & 2 deletions api/rag.py
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Original file line number Diff line number Diff line change
Expand Up @@ -45,7 +45,7 @@ def append_dialog_turn(self, dialog_turn):
logger = logging.getLogger(__name__)

# Maximum token limit for embedding models
MAX_INPUT_TOKENS = 7500 # Safe threshold below 8192 token limit
MAX_INPUT_TOKENS = 3400 # Adjusted for embedding model with 4096 token limit
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medium

Consider adding a comment explaining why the token limit was adjusted to 3400. This will help future developers understand the reasoning behind this specific value.

Style Guide References

Suggested change
MAX_INPUT_TOKENS = 3400 # Adjusted for embedding model with 4096 token limit
MAX_INPUT_TOKENS = 3400 # Adjusted for embedding model with 4096 token limit. Testing indicates best performance at this level.


class Memory(adal.core.component.DataComponent):
"""Simple conversation management with a list of dialog turns."""
Expand Down Expand Up @@ -232,7 +232,10 @@ def __init__(self, use_s3: bool = False, local_ollama: bool = False): # noqa: F
# --- Initialize Embedder ---
self.embedder = adal.Embedder(
model_client=embedder_config["model_client"](),
model_kwargs=embedder_config["model_kwargs"],
model_kwargs={
**embedder_config["model_kwargs"],
"max_input_tokens": MAX_INPUT_TOKENS, # Use the configured token limit
},
Comment on lines +235 to +238
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medium

It's good that you're passing the MAX_INPUT_TOKENS to the embedder. Consider adding a brief comment explaining why this is important, such as preventing exceeding the model's token limit.

Style Guide References

Suggested change
model_kwargs={
**embedder_config["model_kwargs"],
"max_input_tokens": MAX_INPUT_TOKENS, # Use the configured token limit
},
model_kwargs={
**embedder_config["model_kwargs"],
"max_input_tokens": MAX_INPUT_TOKENS, # Prevents exceeding model's token limit
},

)

# Patch: ensure query embedding is always single string for Ollama
Expand Down