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https://github.com/sigoden/aichat
synced 2024-11-16 06:15:26 +00:00
refactor: rename model.mode to model.type (#625)
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sigoden
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@ -565,7 +565,7 @@
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async init() {
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try {
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const models = await fetchJSON(MODELS_API);
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this.models = models.filter(v => !v.mode || v.mode === "chat");
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this.models = models.filter(v => !v.type || v.type === "chat");
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} catch (err) {
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toast("No available model");
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console.error("Failed to load models", err);
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@ -741,7 +741,7 @@
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async init() {
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await Promise.all([
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fetchJSON(MODELS_API).then(models => {
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this.models = models.filter(v => !v.mode || v.mode === "chat");
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this.models = models.filter(v => !v.type || v.type === "chat");
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}).catch(err => {
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toast("No model available");
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console.error("Failed to load models", err);
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@ -83,17 +83,16 @@ clients:
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# name: xxxx # Only use it to distinguish clients with the same client type. Optional
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# models:
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# - name: xxxx
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# mode: chat # Chat model
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# max_input_tokens: 100000
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# supports_vision: true
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# supports_function_calling: true
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# - name: xxxx
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# mode: embedding # Embedding model
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# type: embedding # Embedding model
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# max_input_tokens: 2048
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# default_chunk_size: 2000
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# max_concurrent_chunks: 100
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# - name: xxxx
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# mode: rerank # Rerank model
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# type: rerank # Rerank model
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# max_input_tokens: 2048
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# patches:
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# <regex>: # The regex to match model names, e.g. '.*' 'gpt-4o' 'gpt-4o|gpt-4-.*'
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@ -172,7 +171,7 @@ clients:
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- name: llama3
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max_input_tokens: 8192
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- name: all-minilm:l6-v2
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mode: embedding
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type: embedding
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max_chunk_size: 1000
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# See https://learn.microsoft.com/en-us/azure/ai-services/openai/chatgpt-quickstart
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70
models.yaml
70
models.yaml
@ -30,17 +30,17 @@
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output_price: 1.5
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supports_function_calling: true
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- name: text-embedding-3-large
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mode: embedding
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type: embedding
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max_input_tokens: 8191
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default_chunk_size: 3000
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max_concurrent_chunks: 100
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- name: text-embedding-3-small
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mode: embedding
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type: embedding
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max_input_tokens: 8191
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default_chunk_size: 3000
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max_concurrent_chunks: 100
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- name: text-embedding-ada-002
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mode: embedding
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type: embedding
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max_input_tokens: 8191
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default_chunk_size: 3000
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max_concurrent_chunks: 100
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@ -74,7 +74,7 @@
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output_price: 1.5
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supports_function_calling: true
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- name: text-embedding-004
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mode: embedding
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type: embedding
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max_input_tokens: 2048
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default_chunk_size: 1500
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max_concurrent_chunks: 5
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@ -152,7 +152,7 @@
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input_price: 1
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output_price: 3
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- name: mistral-embed
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mode: embedding
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type: embedding
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max_input_tokens: 8092
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default_chunk_size: 2000
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@ -173,20 +173,20 @@
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output_price: 15
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supports_function_calling: true
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- name: embed-english-v3.0
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 96
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- name: embed-multilingual-v3.0
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 96
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- name: rerank-english-v3.0
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mode: rerank
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type: rerank
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max_input_tokens: 4096
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- name: rerank-multilingual-v3.0
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mode: rerank
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type: rerank
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max_input_tokens: 4096
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- platform: reka
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@ -304,12 +304,12 @@
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output_price: 0.375
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supports_function_calling: true
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- name: text-embedding-004
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mode: embedding
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type: embedding
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max_input_tokens: 3072
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default_chunk_size: 2000
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max_concurrent_chunks: 5
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- name: text-multilingual-embedding-002
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mode: embedding
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type: embedding
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max_input_tokens: 3072
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default_chunk_size: 2000
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max_concurrent_chunks: 5
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@ -457,12 +457,12 @@
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input_price: 0
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output_price: 0
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- name: '@cf/baai/bge-base-en-v1.5'
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: '@cf/baai/bge-large-en-v1.5'
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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@ -575,7 +575,7 @@
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output_price: 2.8
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supports_vision: true
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- name: text-embedding-v2
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mode: embedding
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type: embedding
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max_input_tokens: 2048
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default_chunk_size: 1500
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max_concurrent_chunks: 25
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@ -649,7 +649,7 @@
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output_price: 7
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supports_vision: true
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- name: embedding-2
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mode: embedding
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type: embedding
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max_input_tokens: 2048
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default_chunk_size: 1500
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@ -718,12 +718,12 @@
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input_price: 0.15
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output_price: 0.15
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- name: BAAI/bge-large-en-v1.5
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 30
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- name: thenlper/gte-large
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 30
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@ -770,52 +770,52 @@
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input_price: 0.14
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output_price: 0.14
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- name: BAAI/bge-large-en-v1.5
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: BAAI/bge-base-en-v1.5
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: BAAI/bge-m3
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mode: embedding
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type: embedding
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max_input_tokens: 8192
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default_chunk_size: 2000
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max_concurrent_chunks: 100
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- name: intfloat/e5-base-v2
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: intfloat/e5-large-v2
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: intfloat/multilingual-e5-large
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: sentence-transformers/all-MiniLM-L6-v2
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: sentence-transformers/paraphrase-MiniLM-L6-v2
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: thenlper/gte-base
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: thenlper/gte-large
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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@ -873,22 +873,22 @@
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output_price: 0.2
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supports_vision: true
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- name: nomic-ai/nomic-embed-text-v1.5
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mode: embedding
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type: embedding
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max_input_tokens: 8192
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default_chunk_size: 1500
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max_concurrent_chunks: 100
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- name: WhereIsAI/UAE-Large-V1
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: thenlper/gte-large
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: thenlper/gte-base
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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@ -1069,7 +1069,7 @@
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input_price: 0.86
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output_price: 0.86
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- name: thenlper/gte-large
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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@ -1110,17 +1110,17 @@
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output_price: 0.9
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max_concurrent_chunks: 100
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- name: WhereIsAI/UAE-Large-V1
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: BAAI/bge-large-en-v1.5
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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- name: BAAI/bge-base-en-v1.5
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mode: embedding
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type: embedding
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max_input_tokens: 512
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default_chunk_size: 1000
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max_concurrent_chunks: 100
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@ -145,15 +145,15 @@ macro_rules! register_client {
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}
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pub fn list_chat_models(config: &$crate::config::Config) -> Vec<&'static $crate::client::Model> {
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list_models(config).into_iter().filter(|v| v.mode() == "chat").collect()
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list_models(config).into_iter().filter(|v| v.model_type() == "chat").collect()
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}
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pub fn list_embedding_models(config: &$crate::config::Config) -> Vec<&'static $crate::client::Model> {
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list_models(config).into_iter().filter(|v| v.mode() == "embedding").collect()
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list_models(config).into_iter().filter(|v| v.model_type() == "embedding").collect()
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}
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pub fn list_rerank_models(config: &$crate::config::Config) -> Vec<&'static $crate::client::Model> {
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list_models(config).into_iter().filter(|v| v.mode() == "rerank").collect()
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list_models(config).into_iter().filter(|v| v.model_type() == "rerank").collect()
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}
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};
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}
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@ -111,8 +111,8 @@ impl Model {
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&self.data.name
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}
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pub fn mode(&self) -> &str {
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&self.data.mode
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pub fn model_type(&self) -> &str {
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&self.data.model_type
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}
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pub fn data(&self) -> &ModelData {
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@ -245,8 +245,8 @@ impl Model {
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#[derive(Debug, Clone, Default, Serialize, Deserialize)]
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pub struct ModelData {
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pub name: String,
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#[serde(default = "default_model_mode")]
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pub mode: String,
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#[serde(default = "default_model_type", rename = "type")]
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pub model_type: String,
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pub max_input_tokens: Option<usize>,
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pub input_price: Option<f64>,
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pub output_price: Option<f64>,
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@ -280,6 +280,6 @@ pub struct BuiltinModels {
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pub models: Vec<ModelData>,
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}
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fn default_model_mode() -> String {
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fn default_model_type() -> String {
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"chat".into()
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}
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