Implement stop_reason #57
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Note that for some reason Ollama does not always respond with `done_reason`. So that needs to be investigated further
| @@ -20,6 +20,13 @@ def logprobs | |||
| @extra[:logprobs] | |||
| end | |||
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| ## | |||
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Can we link to some relevant docs - similar to logprobs ? Although there's more providers to cover this time
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@0x1eef should we just link to stop_reason from OpenAI? or link all of them? There's probably no generic docs for it
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If we could link to the relevant docs for each I think that'd be helpful - failing that, let's just reference OpenAI
| LLM::Message.new( | ||
| _1.dig("content", "role"), | ||
| {text: _1.dig("content", "parts", 0, "text")} | ||
| {text: _1.dig("content", "parts", 0, "text")}, | ||
| {stop_reason:} |
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Can we write this as
{stop_reason: _1["stop_reason"]}| @@ -20,7 +20,8 @@ def parse_completion(raw) | |||
| { | |||
| model: raw["model"], | |||
| choices: raw["content"].map do | |||
| LLM::Message.new(raw["role"], _1["text"]) | |||
| stop_reason = raw["stop_reason"] | |||
| LLM::Message.new(raw["role"], _1["text"], {stop_reason:}) | |||
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Can we write this as:
{stop_reason: _1["stop_reason"]}| @@ -7,7 +7,7 @@ module ResponseParser | |||
| def parse_completion(raw) | |||
| { | |||
| model: raw["model"], | |||
| choices: [LLM::Message.new(*raw["message"].values_at("role", "content"))], | |||
| choices: [LLM::Message.new(*raw["message"].values_at("role", "content"), {stop_reason: raw["done_reason"]})], | |||
| @@ -19,7 +19,9 @@ def parse_completion(raw) | |||
| { | |||
| model: raw["model"], | |||
| choices: raw["choices"].map do | |||
| LLM::Message.new(*_1["message"].values_at("role", "content"), {logprobs: _1["logprobs"]}) | |||
| logprobs = _1["logprobs"] | |||
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Could this be:
logprobs, stop_reason = _1.values_at("logprobs", "finish_reason")| @@ -73,6 +73,10 @@ | |||
| total_tokens: 2598 | |||
| ) | |||
| end | |||
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| it "has stop reason" do | |||
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it "includes a stop reason" do
#..
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Closing because |
Changes
stop_reasontoLLM::Messagestop_reasonto Anthropic, Gemini, OpenAI and Ollama