ton
@@ -1,8 +1,8 @@
|
||||
# This file is machine-generated - editing it directly is not advised
|
||||
|
||||
julia_version = "1.11.2"
|
||||
julia_version = "1.11.4"
|
||||
manifest_format = "2.0"
|
||||
project_hash = "b483014657ef9f0fde60d7258585b291d6f0eeca"
|
||||
project_hash = "cb7f3c57318e927e8ac4dc2dea9acdcace566ed1"
|
||||
|
||||
[[deps.AliasTables]]
|
||||
deps = ["PtrArrays", "Random"]
|
||||
@@ -120,9 +120,9 @@ version = "1.11.0"
|
||||
|
||||
[[deps.Distributions]]
|
||||
deps = ["AliasTables", "FillArrays", "LinearAlgebra", "PDMats", "Printf", "QuadGK", "Random", "SpecialFunctions", "Statistics", "StatsAPI", "StatsBase", "StatsFuns"]
|
||||
git-tree-sha1 = "3101c32aab536e7a27b1763c0797dba151b899ad"
|
||||
git-tree-sha1 = "0b4190661e8a4e51a842070e7dd4fae440ddb7f4"
|
||||
uuid = "31c24e10-a181-5473-b8eb-7969acd0382f"
|
||||
version = "0.25.113"
|
||||
version = "0.25.118"
|
||||
|
||||
[deps.Distributions.extensions]
|
||||
DistributionsChainRulesCoreExt = "ChainRulesCore"
|
||||
@@ -158,9 +158,9 @@ version = "0.1.10"
|
||||
|
||||
[[deps.FileIO]]
|
||||
deps = ["Pkg", "Requires", "UUIDs"]
|
||||
git-tree-sha1 = "2dd20384bf8c6d411b5c7370865b1e9b26cb2ea3"
|
||||
git-tree-sha1 = "b66970a70db13f45b7e57fbda1736e1cf72174ea"
|
||||
uuid = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
|
||||
version = "1.16.6"
|
||||
version = "1.17.0"
|
||||
weakdeps = ["HTTP"]
|
||||
|
||||
[deps.FileIO.extensions]
|
||||
@@ -168,9 +168,9 @@ weakdeps = ["HTTP"]
|
||||
|
||||
[[deps.FilePathsBase]]
|
||||
deps = ["Compat", "Dates"]
|
||||
git-tree-sha1 = "7878ff7172a8e6beedd1dea14bd27c3c6340d361"
|
||||
git-tree-sha1 = "3bab2c5aa25e7840a4b065805c0cdfc01f3068d2"
|
||||
uuid = "48062228-2e41-5def-b9a4-89aafe57970f"
|
||||
version = "0.9.22"
|
||||
version = "0.9.24"
|
||||
weakdeps = ["Mmap", "Test"]
|
||||
|
||||
[deps.FilePathsBase.extensions]
|
||||
@@ -200,11 +200,9 @@ version = "1.11.0"
|
||||
|
||||
[[deps.GeneralUtils]]
|
||||
deps = ["CSV", "DataFrames", "DataStructures", "Dates", "Distributions", "JSON3", "MQTTClient", "PrettyPrinting", "Random", "SHA", "UUIDs"]
|
||||
git-tree-sha1 = "978d9a5c3fc30205dd72d4a2a2ed4fa85ebee5cf"
|
||||
repo-rev = "main"
|
||||
repo-url = "https://git.yiem.cc/ton/GeneralUtils"
|
||||
path = "/appfolder/app/dev/GeneralUtils"
|
||||
uuid = "c6c72f09-b708-4ac8-ac7c-2084d70108fe"
|
||||
version = "0.1.0"
|
||||
version = "0.2.3"
|
||||
|
||||
[[deps.HTTP]]
|
||||
deps = ["Base64", "CodecZlib", "ConcurrentUtilities", "Dates", "ExceptionUnwrapping", "Logging", "LoggingExtras", "MbedTLS", "NetworkOptions", "OpenSSL", "PrecompileTools", "Random", "SimpleBufferStream", "Sockets", "URIs", "UUIDs"]
|
||||
@@ -214,9 +212,9 @@ version = "1.10.13"
|
||||
|
||||
[[deps.HypergeometricFunctions]]
|
||||
deps = ["LinearAlgebra", "OpenLibm_jll", "SpecialFunctions"]
|
||||
git-tree-sha1 = "b1c2585431c382e3fe5805874bda6aea90a95de9"
|
||||
git-tree-sha1 = "68c173f4f449de5b438ee67ed0c9c748dc31a2ec"
|
||||
uuid = "34004b35-14d8-5ef3-9330-4cdb6864b03a"
|
||||
version = "0.3.25"
|
||||
version = "0.3.28"
|
||||
|
||||
[[deps.ICU_jll]]
|
||||
deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
|
||||
@@ -260,9 +258,9 @@ uuid = "41ab1584-1d38-5bbf-9106-f11c6c58b48f"
|
||||
version = "1.3.0"
|
||||
|
||||
[[deps.IrrationalConstants]]
|
||||
git-tree-sha1 = "630b497eafcc20001bba38a4651b327dcfc491d2"
|
||||
git-tree-sha1 = "e2222959fbc6c19554dc15174c81bf7bf3aa691c"
|
||||
uuid = "92d709cd-6900-40b7-9082-c6be49f344b6"
|
||||
version = "0.2.2"
|
||||
version = "0.2.4"
|
||||
|
||||
[[deps.IterTools]]
|
||||
git-tree-sha1 = "42d5f897009e7ff2cf88db414a389e5ed1bdd023"
|
||||
@@ -305,12 +303,10 @@ uuid = "b39eb1a6-c29a-53d7-8c32-632cd16f18da"
|
||||
version = "1.19.3+0"
|
||||
|
||||
[[deps.LLMMCTS]]
|
||||
deps = ["GeneralUtils", "JSON3"]
|
||||
git-tree-sha1 = "d8c653b8fafbd3757b7332985efaf1fdb8b6fe97"
|
||||
repo-rev = "main"
|
||||
repo-url = "https://git.yiem.cc/ton/LLMMCTS"
|
||||
deps = ["GeneralUtils", "JSON3", "PrettyPrinting"]
|
||||
path = "/appfolder/app/dev/LLMMCTS"
|
||||
uuid = "d76c5a4d-449e-4835-8cc4-dd86ec44f241"
|
||||
version = "0.1.2"
|
||||
version = "0.1.4"
|
||||
|
||||
[[deps.LaTeXStrings]]
|
||||
git-tree-sha1 = "dda21b8cbd6a6c40d9d02a73230f9d70fed6918c"
|
||||
@@ -370,9 +366,9 @@ version = "1.11.0"
|
||||
|
||||
[[deps.LogExpFunctions]]
|
||||
deps = ["DocStringExtensions", "IrrationalConstants", "LinearAlgebra"]
|
||||
git-tree-sha1 = "a2d09619db4e765091ee5c6ffe8872849de0feea"
|
||||
git-tree-sha1 = "13ca9e2586b89836fd20cccf56e57e2b9ae7f38f"
|
||||
uuid = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
|
||||
version = "0.3.28"
|
||||
version = "0.3.29"
|
||||
|
||||
[deps.LogExpFunctions.extensions]
|
||||
LogExpFunctionsChainRulesCoreExt = "ChainRulesCore"
|
||||
@@ -475,7 +471,7 @@ version = "0.3.27+1"
|
||||
[[deps.OpenLibm_jll]]
|
||||
deps = ["Artifacts", "Libdl"]
|
||||
uuid = "05823500-19ac-5b8b-9628-191a04bc5112"
|
||||
version = "0.8.1+2"
|
||||
version = "0.8.1+4"
|
||||
|
||||
[[deps.OpenSSL]]
|
||||
deps = ["BitFlags", "Dates", "MozillaCACerts_jll", "OpenSSL_jll", "Sockets"]
|
||||
@@ -493,7 +489,7 @@ version = "3.0.15+1"
|
||||
deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Pkg"]
|
||||
git-tree-sha1 = "13652491f6856acfd2db29360e1bbcd4565d04f1"
|
||||
uuid = "efe28fd5-8261-553b-a9e1-b2916fc3738e"
|
||||
version = "0.5.5+0"
|
||||
version = "0.5.5+2"
|
||||
|
||||
[[deps.OrderedCollections]]
|
||||
git-tree-sha1 = "12f1439c4f986bb868acda6ea33ebc78e19b95ad"
|
||||
@@ -502,9 +498,9 @@ version = "1.7.0"
|
||||
|
||||
[[deps.PDMats]]
|
||||
deps = ["LinearAlgebra", "SparseArrays", "SuiteSparse"]
|
||||
git-tree-sha1 = "949347156c25054de2db3b166c52ac4728cbad65"
|
||||
git-tree-sha1 = "48566789a6d5f6492688279e22445002d171cf76"
|
||||
uuid = "90014a1f-27ba-587c-ab20-58faa44d9150"
|
||||
version = "0.11.31"
|
||||
version = "0.11.33"
|
||||
|
||||
[[deps.Parsers]]
|
||||
deps = ["Dates", "PrecompileTools", "UUIDs"]
|
||||
@@ -556,15 +552,15 @@ uuid = "de0858da-6303-5e67-8744-51eddeeeb8d7"
|
||||
version = "1.11.0"
|
||||
|
||||
[[deps.PtrArrays]]
|
||||
git-tree-sha1 = "77a42d78b6a92df47ab37e177b2deac405e1c88f"
|
||||
git-tree-sha1 = "1d36ef11a9aaf1e8b74dacc6a731dd1de8fd493d"
|
||||
uuid = "43287f4e-b6f4-7ad1-bb20-aadabca52c3d"
|
||||
version = "1.2.1"
|
||||
version = "1.3.0"
|
||||
|
||||
[[deps.QuadGK]]
|
||||
deps = ["DataStructures", "LinearAlgebra"]
|
||||
git-tree-sha1 = "cda3b045cf9ef07a08ad46731f5a3165e56cf3da"
|
||||
git-tree-sha1 = "9da16da70037ba9d701192e27befedefb91ec284"
|
||||
uuid = "1fd47b50-473d-5c70-9696-f719f8f3bcdc"
|
||||
version = "2.11.1"
|
||||
version = "2.11.2"
|
||||
|
||||
[deps.QuadGK.extensions]
|
||||
QuadGKEnzymeExt = "Enzyme"
|
||||
@@ -623,11 +619,9 @@ version = "0.7.0"
|
||||
|
||||
[[deps.SQLLLM]]
|
||||
deps = ["CSV", "DataFrames", "DataStructures", "Dates", "FileIO", "GeneralUtils", "HTTP", "JSON3", "LLMMCTS", "LibPQ", "PrettyPrinting", "Random", "Revise", "StatsBase", "Tables", "URIs", "UUIDs"]
|
||||
git-tree-sha1 = "45e660e44de0950a5e5f92d467298d8b768b6023"
|
||||
repo-rev = "main"
|
||||
repo-url = "https://git.yiem.cc/ton/SQLLLM"
|
||||
path = "/appfolder/app/dev/SQLLLM"
|
||||
uuid = "2ebc79c7-cc10-4a3a-9665-d2e1d61e63d3"
|
||||
version = "0.2.0"
|
||||
version = "0.2.4"
|
||||
|
||||
[[deps.SQLStrings]]
|
||||
git-tree-sha1 = "55de0530689832b1d3d43491ee6b67bd54d3323c"
|
||||
@@ -672,9 +666,9 @@ version = "1.11.0"
|
||||
|
||||
[[deps.SpecialFunctions]]
|
||||
deps = ["IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"]
|
||||
git-tree-sha1 = "2f5d4697f21388cbe1ff299430dd169ef97d7e14"
|
||||
git-tree-sha1 = "64cca0c26b4f31ba18f13f6c12af7c85f478cfde"
|
||||
uuid = "276daf66-3868-5448-9aa4-cd146d93841b"
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||||
version = "2.4.0"
|
||||
version = "2.5.0"
|
||||
|
||||
[deps.SpecialFunctions.extensions]
|
||||
SpecialFunctionsChainRulesCoreExt = "ChainRulesCore"
|
||||
@@ -699,16 +693,16 @@ uuid = "82ae8749-77ed-4fe6-ae5f-f523153014b0"
|
||||
version = "1.7.0"
|
||||
|
||||
[[deps.StatsBase]]
|
||||
deps = ["DataAPI", "DataStructures", "LinearAlgebra", "LogExpFunctions", "Missings", "Printf", "Random", "SortingAlgorithms", "SparseArrays", "Statistics", "StatsAPI"]
|
||||
git-tree-sha1 = "5cf7606d6cef84b543b483848d4ae08ad9832b21"
|
||||
deps = ["AliasTables", "DataAPI", "DataStructures", "LinearAlgebra", "LogExpFunctions", "Missings", "Printf", "Random", "SortingAlgorithms", "SparseArrays", "Statistics", "StatsAPI"]
|
||||
git-tree-sha1 = "29321314c920c26684834965ec2ce0dacc9cf8e5"
|
||||
uuid = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
|
||||
version = "0.34.3"
|
||||
version = "0.34.4"
|
||||
|
||||
[[deps.StatsFuns]]
|
||||
deps = ["HypergeometricFunctions", "IrrationalConstants", "LogExpFunctions", "Reexport", "Rmath", "SpecialFunctions"]
|
||||
git-tree-sha1 = "b423576adc27097764a90e163157bcfc9acf0f46"
|
||||
git-tree-sha1 = "35b09e80be285516e52c9054792c884b9216ae3c"
|
||||
uuid = "4c63d2b9-4356-54db-8cca-17b64c39e42c"
|
||||
version = "1.3.2"
|
||||
version = "1.4.0"
|
||||
|
||||
[deps.StatsFuns.extensions]
|
||||
StatsFunsChainRulesCoreExt = "ChainRulesCore"
|
||||
|
||||
@@ -1,9 +1,10 @@
|
||||
name = "YiemAgent"
|
||||
uuid = "e012c34b-7f78-48e0-971c-7abb83b6f0a2"
|
||||
authors = ["narawat lamaiin <narawat@outlook.com>"]
|
||||
version = "0.1.4"
|
||||
version = "0.2.0"
|
||||
|
||||
[deps]
|
||||
CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
|
||||
DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
|
||||
DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
|
||||
Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
|
||||
@@ -21,7 +22,5 @@ URIs = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
|
||||
UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
|
||||
|
||||
[compat]
|
||||
CSV = "0.10.15"
|
||||
DataFrames = "1.7.0"
|
||||
GeneralUtils = "0.1, 0.2"
|
||||
LLMMCTS = "0.1.2"
|
||||
SQLLLM = "0.2.0"
|
||||
|
||||
72
fast_inference_guideline.txt
Normal file
72
fast_inference_guideline.txt
Normal file
@@ -0,0 +1,72 @@
|
||||
To make **LLM-driven inference** fast while maintaining its dynamic capabilities, there are a few practices or approaches to avoid, as they could lead to performance bottlenecks or inefficiencies. Here's what *not* to do:
|
||||
|
||||
---
|
||||
|
||||
### **1. Avoid Using Overly Large Models for Every Query**
|
||||
While larger LLMs like GPT-4 provide high accuracy and nuanced responses, they may slow down real-time processing due to their computational complexity. Instead:
|
||||
- Use distilled or smaller models (e.g., GPT-3.5 Turbo or fine-tuned versions) for faster inference without compromising much on quality.
|
||||
|
||||
---
|
||||
|
||||
### **2. Avoid Excessive Entity Preprocessing**
|
||||
Don’t rely on overly complicated preprocessing steps (like advanced NER models or regex-heavy pipelines) to extract entities from the query before invoking the LLM. This could add latency. Instead:
|
||||
- Design efficient prompts that allow the LLM to extract entities and generate responses simultaneously.
|
||||
|
||||
---
|
||||
|
||||
### **3. Avoid Asking the LLM Multiple Separate Questions**
|
||||
Running the LLM for multiple subtasks—for example, entity extraction first and response generation second—can significantly slow down the pipeline. Instead:
|
||||
- Create prompts that combine tasks into one pass, e.g., *"Identify the city name and generate a weather response for this query: 'What's the weather in London?'"*.
|
||||
|
||||
---
|
||||
|
||||
### **4. Don’t Overload the LLM with Context History**
|
||||
Excessively lengthy conversation history or irrelevant context in your prompts can slow down inference times. Instead:
|
||||
- Provide only the relevant context for each query, trimming unnecessary parts of the conversation.
|
||||
|
||||
---
|
||||
|
||||
### **5. Avoid Real-Time Dependence on External APIs**
|
||||
Using external APIs to fetch supplementary data (e.g., weather details or location info) during every query can introduce latency. Instead:
|
||||
- Pre-fetch API data asynchronously and use the LLM to integrate it dynamically into responses.
|
||||
|
||||
---
|
||||
|
||||
### **6. Avoid Running LLM on Underpowered Hardware**
|
||||
Running inference on CPUs or low-spec GPUs will result in slower response times. Instead:
|
||||
- Deploy the LLM on optimized infrastructure (e.g., high-performance GPUs like NVIDIA A100 or cloud platforms like Azure AI) to reduce latency.
|
||||
|
||||
---
|
||||
|
||||
### **7. Skip Lengthy Generative Prompts**
|
||||
Avoid prompts that encourage the LLM to produce overly detailed or verbose responses, as these take longer to process. Instead:
|
||||
- Use concise prompts that focus on generating actionable or succinct answers.
|
||||
|
||||
---
|
||||
|
||||
### **8. Don’t Ignore Optimization Techniques**
|
||||
Failing to optimize your LLM setup can drastically impact performance. For example:
|
||||
- Avoid skipping techniques like model quantization (reducing numerical precision to speed up inference) or distillation (training smaller models).
|
||||
|
||||
---
|
||||
|
||||
### **9. Don’t Neglect Response Caching**
|
||||
While you may not want a full caching system to avoid sunk costs, dismissing lightweight caching entirely can impact speed. Instead:
|
||||
- Use temporary session-based caching for very frequent queries, without committing to a full-fledged cache infrastructure.
|
||||
|
||||
---
|
||||
|
||||
### **10. Avoid One-Size-Fits-All Solutions**
|
||||
Applying the same LLM inference method to all queries—whether simple or complex—will waste processing resources. Instead:
|
||||
- Route basic queries to faster, specialized models and use the LLM for nuanced or multi-step queries only.
|
||||
|
||||
---
|
||||
|
||||
### Summary: Focus on Efficient Design
|
||||
By avoiding these pitfalls, you can ensure that LLM-driven inference remains fast and responsive:
|
||||
- Optimize prompts.
|
||||
- Use smaller models for simpler queries.
|
||||
- Run the LLM on high-performance hardware.
|
||||
- Trim unnecessary preprocessing or contextual steps.
|
||||
|
||||
Would you like me to help refine a prompt or suggest specific tools to complement your implementation? Let me know!
|
||||
1263
src/interface.jl
1263
src/interface.jl
File diff suppressed because it is too large
Load Diff
@@ -296,13 +296,14 @@ function checkinventory(a::T1, input::T2
|
||||
wineattributes_2 = extractWineAttributes_2(a, input)
|
||||
|
||||
_inventoryquery = "retailer name: $(a.retailername), $wineattributes_1, $wineattributes_2"
|
||||
inventoryquery = "Retrieves winery, wine_name, vintage, region, country, wine_type, grape, serving_temperature, sweetness, intensity, tannin, acidity, tasting_notes, price and currency of wines that match the following criteria - {$_inventoryquery}"
|
||||
inventoryquery = "Retrieves winery, wine_name, wine_id, vintage, region, country, wine_type, grape, serving_temperature, sweetness, intensity, tannin, acidity, tasting_notes, price and currency of wines that match the following criteria - {$_inventoryquery}"
|
||||
println("\ncheckinventory input: $inventoryquery ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
# add suppport for similarSQLVectorDB
|
||||
textresult, rawresponse = SQLLLM.query(inventoryquery, a.func[:executeSQL],
|
||||
a.func[:text2textInstructLLM],
|
||||
a.func[:text2textInstructLLM];
|
||||
insertSQLVectorDB=a.func[:insertSQLVectorDB],
|
||||
similarSQLVectorDB=a.func[:similarSQLVectorDB])
|
||||
similarSQLVectorDB=a.func[:similarSQLVectorDB],
|
||||
llmFormatName="qwen3")
|
||||
|
||||
println("\ncheckinventory result ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
println(textresult)
|
||||
@@ -330,7 +331,8 @@ julia>
|
||||
|
||||
# Signature
|
||||
"""
|
||||
function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<:AbstractString}
|
||||
function extractWineAttributes_1(a::T1, input::T2; maxattempt=10
|
||||
)::String where {T1<:agent, T2<:AbstractString}
|
||||
|
||||
systemmsg =
|
||||
"""
|
||||
@@ -384,19 +386,24 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
|
||||
header = ["Thought:", "Wine_name:", "Winery:", "Vintage:", "Region:", "Country:", "Wine_type:", "Grape_varietal:", "Tasting_notes:", "Wine_price:", "Occasion:", "Food_to_be_paired_with_wine:"]
|
||||
dictkey = ["thought", "wine_name", "winery", "vintage", "region", "country", "wine_type", "grape_varietal", "tasting_notes", "wine_price", "occasion", "food_to_be_paired_with_wine"]
|
||||
errornote = ""
|
||||
errornote = "N/A"
|
||||
|
||||
for attempt in 1:10
|
||||
#[WORKING] I should add generatequestion()
|
||||
llmkwargs=Dict(
|
||||
:num_ctx => 32768,
|
||||
:temperature => 0.5,
|
||||
)
|
||||
|
||||
for attempt in 1:maxattempt
|
||||
#[PENDING] I should add generatequestion()
|
||||
|
||||
if attempt > 1
|
||||
println("\nYiemAgent extractWineAttributes_1() attempt $attempt/10 ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
println("\nYiemAgent extractWineAttributes_1() attempt $attempt/$maxattempt ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
end
|
||||
|
||||
usermsg =
|
||||
"""
|
||||
User's query: $input
|
||||
$errornote
|
||||
P.S. $errornote
|
||||
"""
|
||||
|
||||
_prompt =
|
||||
@@ -406,29 +413,33 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
]
|
||||
|
||||
# put in model format
|
||||
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
|
||||
response = a.func[:text2textInstructLLM](prompt)
|
||||
prompt = GeneralUtils.formatLLMtext(_prompt, "granite3")
|
||||
response = a.func[:text2textInstructLLM](prompt;
|
||||
modelsize="medium", llmkwargs=llmkwargs, senderId=a.id)
|
||||
response = GeneralUtils.remove_french_accents(response)
|
||||
response = GeneralUtils.deFormatLLMtext(response, "granite3")
|
||||
|
||||
# check wheter all attributes are in the response
|
||||
checkFlag = false
|
||||
for word in header
|
||||
if !occursin(word, response)
|
||||
errornote = "$word attribute is missing in previous attempts"
|
||||
println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
errornote = "In your previous attempts, the $word attribute is missing. Please try again."
|
||||
println("\nYiemAgent extractWineAttributes_1() Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
checkFlag = true
|
||||
break
|
||||
end
|
||||
end
|
||||
checkFlag == true ? continue : nothing
|
||||
|
||||
# check whether response has all header
|
||||
# check whether response has all answer's key points
|
||||
detected_kw = GeneralUtils.detect_keyword(header, response)
|
||||
if 0 ∈ values(detected_kw)
|
||||
errornote = "\nYiemAgent extractWineAttributes_1() response does not have all header"
|
||||
errornote = "In your previous attempts, the response does not have all answer's key points"
|
||||
println("\nYiemAgent extractWineAttributes_1() Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
continue
|
||||
elseif sum(values(detected_kw)) > length(header)
|
||||
errornote = "\nYiemAgent extractWineAttributes_1() response has duplicated header"
|
||||
errornote = "In your previous attempts, the response has duplicated answer's key points"
|
||||
println("\nYiemAgent extractWineAttributes_1() Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
continue
|
||||
end
|
||||
responsedict = GeneralUtils.textToDict(response, header;
|
||||
@@ -452,8 +463,8 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
if responsedict[:wine_price] != "NA"
|
||||
# check whether wine_price is in ranged number
|
||||
if !occursin('-', responsedict[:wine_price])
|
||||
errornote = "wine_price must be a range number"
|
||||
println("ERROR YiemAgent extractWineAttributes_1() $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
errornote = "In your previous attempt, the 'wine_price' was not set to a ranged number. Please adjust it accordingly."
|
||||
println("\nERROR YiemAgent extractWineAttributes_1() $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
checkFlag = true
|
||||
break
|
||||
end
|
||||
@@ -467,8 +478,8 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
end
|
||||
# price range like 100-100 is not good
|
||||
if minprice == maxprice
|
||||
errornote = "wine_price with minimum equals to maximum is not valid"
|
||||
println("ERROR YiemAgent extractWineAttributes_1() $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
errornote = "In your previous attempt, you inputted 'wine_price' with a 'minimum' value equaling the 'maximum', which is not valid."
|
||||
println("\nERROR YiemAgent extractWineAttributes_1() $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
checkFlag = true
|
||||
break
|
||||
end
|
||||
@@ -568,14 +579,12 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
The preference form requires the following information:
|
||||
sweetness, acidity, tannin, intensity
|
||||
|
||||
<You must follow the following guidelines>
|
||||
You must follow the following guidelines:
|
||||
1) If specific information required in the preference form is not available in the query or there isn't any, mark with 'NA' to indicate this.
|
||||
Additionally, words like 'any' or 'unlimited' mean no information is available.
|
||||
2) Use the conversion table to convert the descriptive word level of sweetness, intensity, tannin, and acidity into a corresponding integer.
|
||||
3) Do not generate other comments.
|
||||
</You must follow the following guidelines>
|
||||
|
||||
<You should then respond to the user with>
|
||||
You should then respond to the user with:
|
||||
Sweetness_keyword: The exact keywords in the user's query describing the sweetness level of the wine.
|
||||
Sweetness: ( S ), where ( S ) represents integers indicating the range of sweetness levels. Example: 1-2
|
||||
Acidity_keyword: The exact keywords in the user's query describing the acidity level of the wine.
|
||||
@@ -584,9 +593,7 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
Tannin: ( T ), where ( T ) represents integers indicating the range of tannin level. Example: 1-3
|
||||
Intensity_keyword: The exact keywords in the user's query describing the intensity level of the wine.
|
||||
Intensity: ( I ), where ( I ) represents integers indicating the range of intensity level. Example: 2-4
|
||||
</You should then respond to the user with>
|
||||
|
||||
<You should only respond in format as described below>
|
||||
You should only respond in format as described below:
|
||||
Sweetness_keyword: ...
|
||||
Sweetness: ...
|
||||
Acidity_keyword: ...
|
||||
@@ -595,9 +602,8 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
Tannin: ...
|
||||
Intensity_keyword: ...
|
||||
Intensity: ...
|
||||
</You should only respond in format as described below>
|
||||
|
||||
<Here are some examples>
|
||||
Here are some examples:
|
||||
User's query: I want a wine with a medium-bodied, low acidity, medium tannin.
|
||||
Sweetness_keyword: NA
|
||||
Sweetness: NA
|
||||
@@ -617,7 +623,6 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
Tannin: NA
|
||||
Intensity_keyword: NA
|
||||
Intensity: NA
|
||||
</Here are some examples>
|
||||
|
||||
Let's begin!
|
||||
"""
|
||||
@@ -630,7 +635,7 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
"""
|
||||
$conversiontable
|
||||
User's query: $input
|
||||
$errornote
|
||||
P.S. $errornote
|
||||
"""
|
||||
|
||||
_prompt =
|
||||
@@ -640,17 +645,20 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
]
|
||||
|
||||
# put in model format
|
||||
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
|
||||
prompt = GeneralUtils.formatLLMtext(_prompt, "granite3")
|
||||
|
||||
response = a.func[:text2textInstructLLM](prompt)
|
||||
response = GeneralUtils.deFormatLLMtext(response, "granite3")
|
||||
|
||||
# check whether response has all header
|
||||
# check whether response has all answer's key points
|
||||
detected_kw = GeneralUtils.detect_keyword(header, response)
|
||||
if 0 ∈ values(detected_kw)
|
||||
errornote = "\nYiemAgent extractWineAttributes_2() response does not have all header"
|
||||
errornote = "In your previous attempt does not have all answer's key points"
|
||||
println("\nERROR YiemAgent extractWineAttributes_2() Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
continue
|
||||
elseif sum(values(detected_kw)) > length(header)
|
||||
errornote = "\nYiemAgent extractWineAttributes_2() response has duplicated header"
|
||||
errornote = "In your previous attempt has duplicated answer's key points"
|
||||
println("\nERROR YiemAgent extractWineAttributes_2() Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
continue
|
||||
end
|
||||
|
||||
@@ -662,8 +670,8 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
keyword = Symbol(i * "_keyword") # e.g. sweetness_keyword
|
||||
value = responsedict[keyword]
|
||||
if value != "NA" && !occursin(value, input)
|
||||
errornote = "WARNING. Keyword $keyword: $value does not appear in the input. You must use information from the input only"
|
||||
println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
errornote = "In your previous attempt, keyword $keyword: $value does not appear in the input. You must use information from the input only"
|
||||
println("\nERROR YiemAgent extractWineAttributes_2() Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
continue
|
||||
end
|
||||
|
||||
@@ -679,7 +687,7 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
|
||||
if !occursin("keyword", string(k))
|
||||
if v !== "NA" && (!occursin('-', v) || length(v) > 5)
|
||||
errornote = "WARNING: The non-range value {$k: $v} is not allowed. It should be specified in a range format, i.e. min-max."
|
||||
println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
println("\nERROR YiemAgent extractWineAttributes_2() Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
continue
|
||||
end
|
||||
end
|
||||
@@ -755,7 +763,7 @@ function paraphrase(text2textInstructLLM::Function, text::String)
|
||||
for attempt in 1:10
|
||||
usermsg = """
|
||||
Text: $text
|
||||
$errornote
|
||||
P.S. $errornote
|
||||
"""
|
||||
|
||||
_prompt =
|
||||
@@ -765,10 +773,11 @@ function paraphrase(text2textInstructLLM::Function, text::String)
|
||||
]
|
||||
|
||||
# put in model format
|
||||
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
|
||||
prompt = GeneralUtils.formatLLMtext(_prompt, "granite3")
|
||||
|
||||
try
|
||||
response = text2textInstructLLM(prompt)
|
||||
response = GeneralUtils.deFormatLLMtext(response, "granite3")
|
||||
# sometime the model response like this "here's how I would respond: ..."
|
||||
if occursin("respond:", response)
|
||||
errornote = "You don't need to intro your response"
|
||||
@@ -780,13 +789,13 @@ function paraphrase(text2textInstructLLM::Function, text::String)
|
||||
response = replace(response, '`' => "")
|
||||
response = GeneralUtils.remove_french_accents(response)
|
||||
|
||||
# check whether response has all header
|
||||
# check whether response has all answer's key points
|
||||
detected_kw = GeneralUtils.detect_keyword(header, response)
|
||||
if 0 ∈ values(detected_kw)
|
||||
errornote = "\nYiemAgent paraphrase() response does not have all header"
|
||||
errornote = "\nYiemAgent paraphrase() response does not have all answer's key points"
|
||||
continue
|
||||
elseif sum(values(detected_kw)) > length(header)
|
||||
errornote = "\nnYiemAgent paraphrase() response has duplicated header"
|
||||
errornote = "\nnYiemAgent paraphrase() response has duplicated answer's key points"
|
||||
continue
|
||||
end
|
||||
|
||||
@@ -984,7 +993,7 @@ end
|
||||
# ]
|
||||
|
||||
# # put in model format
|
||||
# prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
|
||||
# prompt = GeneralUtils.formatLLMtext(_prompt, "granite3")
|
||||
# prompt *=
|
||||
# """
|
||||
# <|start_header_id|>assistant<|end_header_id|>
|
||||
|
||||
99
src/type.jl
99
src/type.jl
@@ -9,11 +9,48 @@ using GeneralUtils
|
||||
|
||||
abstract type agent end
|
||||
|
||||
|
||||
mutable struct companion <: agent
|
||||
name::String # agent name
|
||||
id::String # agent id
|
||||
systemmsg::Union{String, Nothing}
|
||||
systemmsg::String # system message
|
||||
tools::Dict # tools
|
||||
maxHistoryMsg::Integer # e.g. 21th and earlier messages will get summarized
|
||||
chathistory::Vector{Dict{Symbol, Any}}
|
||||
memory::Dict{Symbol, Any}
|
||||
func::NamedTuple # NamedTuple of functions
|
||||
llmFormatName::String
|
||||
end
|
||||
|
||||
function companion(
|
||||
func::NamedTuple # NamedTuple of functions
|
||||
;
|
||||
systemmsg::Union{String, Nothing}= nothing,
|
||||
name::String= "Assistant",
|
||||
id::String= GeneralUtils.uuid4snakecase(),
|
||||
maxHistoryMsg::Integer= 20,
|
||||
chathistory::Vector{Dict{Symbol, String}} = Vector{Dict{Symbol, String}}(),
|
||||
llmFormatName::String= "granite3"
|
||||
)
|
||||
|
||||
if systemmsg === nothing
|
||||
systemmsg =
|
||||
"""
|
||||
Your name: $name
|
||||
Your sex: Female
|
||||
Your role: You are a helpful assistant.
|
||||
You should follow the following guidelines:
|
||||
- Focus on the latest conversation.
|
||||
- Your like to be short and concise.
|
||||
|
||||
Let's begin!
|
||||
"""
|
||||
end
|
||||
|
||||
tools = Dict( # update input format
|
||||
"CHATBOX"=> Dict(
|
||||
:description => "- CHATBOX which you can use to talk with the user. The input is your intentions for the dialogue. Be specific.",
|
||||
),
|
||||
)
|
||||
|
||||
""" Memory
|
||||
Ref: Chat prompt format https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/discussions/3
|
||||
@@ -22,38 +59,23 @@ mutable struct companion <: agent
|
||||
Dict(:name=>"user", :text=> "Wassup!", :timestamp=> Dates.now()),
|
||||
Dict(:name=>"assistant", :text=> "Hi I'm your assistant.", :timestamp=> Dates.now()),
|
||||
]
|
||||
|
||||
"""
|
||||
chathistory::Vector{Dict{Symbol, Any}}
|
||||
memory::Dict{Symbol, Any}
|
||||
|
||||
# communication function
|
||||
text2textInstructLLM::Function
|
||||
end
|
||||
|
||||
function companion(
|
||||
text2textInstructLLM::Function
|
||||
;
|
||||
id::String= string(uuid4()),
|
||||
systemmsg::Union{String, Nothing}= nothing,
|
||||
maxHistoryMsg::Integer= 20,
|
||||
chathistory::Vector{Dict{Symbol, String}} = Vector{Dict{Symbol, String}}(),
|
||||
)
|
||||
|
||||
memory = Dict{Symbol, Any}(
|
||||
:chatbox=> "",
|
||||
:shortmem=> OrderedDict{Symbol, Any}(),
|
||||
:events=> Vector{Dict{Symbol, Any}}(),
|
||||
:state=> Dict{Symbol, Any}(),
|
||||
:state=> Dict{Symbol, Any}(), # state of the agent
|
||||
:recap=> OrderedDict{Symbol, Any}(), # recap summary of the conversation
|
||||
)
|
||||
|
||||
newAgent = companion(
|
||||
name,
|
||||
id,
|
||||
systemmsg,
|
||||
tools,
|
||||
maxHistoryMsg,
|
||||
chathistory,
|
||||
memory,
|
||||
text2textInstructLLM
|
||||
func,
|
||||
llmFormatName
|
||||
)
|
||||
|
||||
return newAgent
|
||||
@@ -61,6 +83,7 @@ end
|
||||
|
||||
|
||||
|
||||
|
||||
""" A sommelier agent.
|
||||
|
||||
# Arguments
|
||||
@@ -134,19 +157,10 @@ mutable struct sommelier <: agent
|
||||
retailername::String
|
||||
tools::Dict
|
||||
maxHistoryMsg::Integer # e.g. 21th and earlier messages will get summarized
|
||||
|
||||
""" Memory
|
||||
Ref: Chat prompt format https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/discussions/3
|
||||
NO "system" message in chathistory because I want to add it at the inference time
|
||||
chathistory= [
|
||||
Dict(:name=>"user", :text=> "Wassup!", :timestamp=> Dates.now()),
|
||||
Dict(:name=>"assistant", :text=> "Hi I'm your assistant.", :timestamp=> Dates.now()),
|
||||
]
|
||||
|
||||
"""
|
||||
chathistory::Vector{Dict{Symbol, Any}}
|
||||
memory::Dict{Symbol, Any}
|
||||
func # NamedTuple of functions
|
||||
llmFormatName::String
|
||||
end
|
||||
|
||||
function sommelier(
|
||||
@@ -157,6 +171,7 @@ function sommelier(
|
||||
retailername::String= "retailer_name",
|
||||
maxHistoryMsg::Integer= 20,
|
||||
chathistory::Vector{Dict{Symbol, String}} = Vector{Dict{Symbol, String}}(),
|
||||
llmFormatName::String= "granite3"
|
||||
)
|
||||
|
||||
tools = Dict( # update input format
|
||||
@@ -170,16 +185,17 @@ function sommelier(
|
||||
:input => """<input>Input is a JSON-formatted string that contains a detailed and precise search query.</input><input example>{\"wine type\": \"rose\", \"price\": \"max 35\", \"sweetness level\": \"sweet\", \"intensity level\": \"light bodied\", \"Tannin level\": \"low\", \"Acidity level\": \"low\"}</input example>""",
|
||||
:output => """<output>Output are wines that match the search query in JSON format.""",
|
||||
),
|
||||
# "finalanswer"=> Dict(
|
||||
# :description => "<tool description>Useful for when you are ready to recommend wines to the user.</tool description>",
|
||||
# :input => """<input format>{\"finalanswer\": \"some text\"}.</input format><input example>{\"finalanswer\": \"I recommend Zena Crown Vista\"}</input example>""",
|
||||
# :output => "" ,
|
||||
# :func => nothing,
|
||||
# ),
|
||||
)
|
||||
|
||||
""" Memory
|
||||
Ref: Chat prompt format https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/discussions/3
|
||||
NO "system" message in chathistory because I want to add it at the inference time
|
||||
chathistory= [
|
||||
Dict(:name=>"user", :text=> "Wassup!", :timestamp=> Dates.now()),
|
||||
Dict(:name=>"assistant", :text=> "Hi I'm your assistant.", :timestamp=> Dates.now()),
|
||||
]
|
||||
"""
|
||||
memory = Dict{Symbol, Any}(
|
||||
:chatbox=> "",
|
||||
:shortmem=> OrderedDict{Symbol, Any}(
|
||||
:available_wine=> [],
|
||||
:found_wine=> [], # used by decisionMaker(). This is to prevent decisionMaker() keep presenting the same wines
|
||||
@@ -198,7 +214,8 @@ function sommelier(
|
||||
maxHistoryMsg,
|
||||
chathistory,
|
||||
memory,
|
||||
func
|
||||
func,
|
||||
llmFormatName
|
||||
)
|
||||
|
||||
return newAgent
|
||||
|
||||
239
src/util.jl
239
src/util.jl
@@ -154,11 +154,11 @@ function chatHistoryToText(vecd::Vector; withkey=true, range=nothing)::String
|
||||
# Loop through each dictionary in the input vector
|
||||
for d in elements
|
||||
# Extract the 'name' and 'text' keys from the dictionary
|
||||
name = d[:name]
|
||||
name = titlecase(d[:name])
|
||||
_text = d[:text]
|
||||
|
||||
# Append the formatted string to the text variable
|
||||
text *= "$name:> $_text \n"
|
||||
text *= "$name> $_text \n"
|
||||
end
|
||||
else
|
||||
# Loop through each dictionary in the input vector
|
||||
@@ -239,7 +239,8 @@ function eventdict(;
|
||||
outcome::Union{String, Nothing}=nothing,
|
||||
note::Union{String, Nothing}=nothing,
|
||||
)
|
||||
return Dict{Symbol, Any}(
|
||||
|
||||
d = Dict{Symbol, Any}(
|
||||
:event_description=> event_description,
|
||||
:timestamp=> timestamp,
|
||||
:subject=> subject,
|
||||
@@ -252,6 +253,8 @@ function eventdict(;
|
||||
:outcome=> outcome,
|
||||
:note=> note,
|
||||
)
|
||||
|
||||
return d
|
||||
end
|
||||
|
||||
|
||||
@@ -310,221 +313,34 @@ function createTimeline(events::T1; eventindex::Union{UnitRange, Nothing}=nothin
|
||||
end
|
||||
|
||||
|
||||
# function createTimeline(events::T1; eventindex::Union{UnitRange, Nothing}=nothing
|
||||
# ) where {T1<:AbstractVector}
|
||||
# # Initialize empty timeline string
|
||||
# timeline = ""
|
||||
|
||||
# """ Convert a single chat dictionary into LLM model instruct format.
|
||||
|
||||
# # Llama 3 instruct format example
|
||||
# <|system|>
|
||||
# You are a helpful AI assistant.<|end|>
|
||||
# <|user|>
|
||||
# I am going to Paris, what should I see?<|end|>
|
||||
# <|assistant|>
|
||||
# Paris, the capital of France, is known for its stunning architecture, art museums."<|end|>
|
||||
# <|user|>
|
||||
# What is so great about #1?<|end|>
|
||||
# <|assistant|>
|
||||
|
||||
|
||||
# # Arguments
|
||||
# - `name::T`
|
||||
# message owner name e.f. "system", "user" or "assistant"
|
||||
# - `text::T`
|
||||
|
||||
# # Return
|
||||
# - `formattedtext::String`
|
||||
# text formatted to model format
|
||||
|
||||
# # Example
|
||||
# ```jldoctest
|
||||
# julia> using Revise
|
||||
# julia> using YiemAgent
|
||||
# julia> d = Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",)
|
||||
# julia> formattedtext = YiemAgent.formatLLMtext_phi3instruct(d[:name], d[:text])
|
||||
|
||||
# ```
|
||||
|
||||
# Signature
|
||||
# """
|
||||
# function formatLLMtext_phi3instruct(name::T, text::T) where {T<:AbstractString}
|
||||
# formattedtext =
|
||||
# """
|
||||
# <|$name|>
|
||||
# $text<|end|>\n
|
||||
# """
|
||||
|
||||
# return formattedtext
|
||||
# end
|
||||
|
||||
|
||||
# """ Convert a single chat dictionary into LLM model instruct format.
|
||||
|
||||
# # Llama 3 instruct format example
|
||||
# <|begin_of_text|>
|
||||
# <|start_header_id|>system<|end_header_id|>
|
||||
# You are a helpful assistant.
|
||||
# <|eot_id|>
|
||||
# <|start_header_id|>user<|end_header_id|>
|
||||
# Get me an icecream.
|
||||
# <|eot_id|>
|
||||
# <|start_header_id|>assistant<|end_header_id|>
|
||||
# Go buy it yourself at 7-11.
|
||||
# <|eot_id|>
|
||||
|
||||
# # Arguments
|
||||
# - `name::T`
|
||||
# message owner name e.f. "system", "user" or "assistant"
|
||||
# - `text::T`
|
||||
|
||||
# # Return
|
||||
# - `formattedtext::String`
|
||||
# text formatted to model format
|
||||
|
||||
# # Example
|
||||
# ```jldoctest
|
||||
# julia> using Revise
|
||||
# julia> using YiemAgent
|
||||
# julia> d = Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",)
|
||||
# julia> formattedtext = YiemAgent.formatLLMtext_llama3instruct(d[:name], d[:text])
|
||||
# "<|begin_of_text|>\n <|start_header_id|>system<|end_header_id|>\n You are a helpful, respectful and honest assistant.\n <|eot_id|>\n"
|
||||
# ```
|
||||
|
||||
# Signature
|
||||
# """
|
||||
# function formatLLMtext_llama3instruct(name::T, text::T) where {T<:AbstractString}
|
||||
# formattedtext =
|
||||
# if name == "system"
|
||||
# """
|
||||
# <|begin_of_text|>
|
||||
# <|start_header_id|>$name<|end_header_id|>
|
||||
# $text
|
||||
# <|eot_id|>
|
||||
# """
|
||||
# # Determine which indices to use - either provided range or full length
|
||||
# ind =
|
||||
# if eventindex !== nothing
|
||||
# [eventindex...]
|
||||
# else
|
||||
# """
|
||||
# <|start_header_id|>$name<|end_header_id|>
|
||||
# $text
|
||||
# <|eot_id|>
|
||||
# """
|
||||
# 1:length(events)
|
||||
# end
|
||||
|
||||
# return formattedtext
|
||||
# end
|
||||
# # Iterate through events and format each one
|
||||
# for (i, event) in zip(ind, events)
|
||||
# # If no outcome exists, format without outcome
|
||||
# subject = titlecase(event[:subject])
|
||||
# if event[:outcome] === nothing
|
||||
|
||||
|
||||
|
||||
# """ Convert a chat messages in vector of dictionary into LLM model instruct format.
|
||||
|
||||
# # Arguments
|
||||
# - `messages::Vector{Dict{Symbol, T}}`
|
||||
# message owner name e.f. "system", "user" or "assistant"
|
||||
# - `formatname::T`
|
||||
# format name to be used
|
||||
|
||||
# # Return
|
||||
# - `formattedtext::String`
|
||||
# text formatted to model format
|
||||
|
||||
# # Example
|
||||
# ```jldoctest
|
||||
# julia> using Revise
|
||||
# julia> using YiemAgent
|
||||
# julia> chatmessage = [
|
||||
# Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",),
|
||||
# Dict(:name=> "user",:text=> "list me all planets in our solar system.",),
|
||||
# Dict(:name=> "assistant",:text=> "I'm sorry. I don't know. You tell me.",),
|
||||
# ]
|
||||
# julia> formattedtext = YiemAgent.formatLLMtext(chatmessage, "llama3instruct")
|
||||
# "<|begin_of_text|>\n <|start_header_id|>system<|end_header_id|>\n You are a helpful, respectful and honest assistant.\n <|eot_id|>\n <|start_header_id|>user<|end_header_id|>\n list me all planets in our solar system.\n <|eot_id|>\n <|start_header_id|>assistant<|end_header_id|>\n I'm sorry. I don't know. You tell me.\n <|eot_id|>\n"
|
||||
# ```
|
||||
|
||||
# # Signature
|
||||
# """
|
||||
# function formatLLMtext(messages::Vector{Dict{Symbol, T}},
|
||||
# formatname::String="llama3instruct") where {T<:Any}
|
||||
# f = if formatname == "llama3instruct"
|
||||
# formatLLMtext_llama3instruct
|
||||
# elseif formatname == "mistral"
|
||||
# # not define yet
|
||||
# elseif formatname == "phi3instruct"
|
||||
# formatLLMtext_phi3instruct
|
||||
# timeline *= "Event_$i) Who: $subject Action_name: $(event[:actionname]) Action_input: $(event[:actioninput])\n"
|
||||
# # If outcome exists, include it in formatting
|
||||
# else
|
||||
# error("$formatname template not define yet")
|
||||
# end
|
||||
|
||||
# str = ""
|
||||
# for t in messages
|
||||
# str *= f(t[:name], t[:text])
|
||||
# end
|
||||
|
||||
# # add <|assistant|> so that the model don't generate it and I don't need to clean it up later
|
||||
# if formatname == "phi3instruct"
|
||||
# str *= "<|assistant|>\n"
|
||||
# end
|
||||
|
||||
# return str
|
||||
# end
|
||||
|
||||
|
||||
# """
|
||||
|
||||
# Arguments\n
|
||||
# -----
|
||||
|
||||
# Return\n
|
||||
# -----
|
||||
|
||||
# Example\n
|
||||
# -----
|
||||
# ```jldoctest
|
||||
# julia>
|
||||
# ```
|
||||
|
||||
# TODO\n
|
||||
# -----
|
||||
# [] update docstring
|
||||
# [PENDING] implement the function
|
||||
|
||||
# Signature\n
|
||||
# -----
|
||||
# """
|
||||
# function iterativeprompting(a::T, prompt::String, verification::Function) where {T<:agent}
|
||||
# msgMeta = GeneralUtils.generate_msgMeta(
|
||||
# a.config[:externalService][:text2textinstruct],
|
||||
# senderName= "iterativeprompting",
|
||||
# senderId= a.id,
|
||||
# receiverName= "text2textinstruct",
|
||||
# )
|
||||
|
||||
# outgoingMsg = Dict(
|
||||
# :msgMeta=> msgMeta,
|
||||
# :payload=> Dict(
|
||||
# :text=> prompt,
|
||||
# )
|
||||
# )
|
||||
|
||||
# success = nothing
|
||||
# result = nothing
|
||||
# critique = ""
|
||||
|
||||
# # iteration loop
|
||||
# while true
|
||||
# # send prompt to LLM
|
||||
# response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
|
||||
# error("--> iterativeprompting")
|
||||
# # check for correctness and get feedback
|
||||
# success, _critique = verification(response)
|
||||
|
||||
# if success
|
||||
# result = response
|
||||
# break
|
||||
# else
|
||||
# # add critique to prompt
|
||||
# critique *= _critique * "\n"
|
||||
# replace!(prompt, "Critique: ..." => "Critique: $critique")
|
||||
# timeline *= "Event_$i) Who: $subject Action_name: $(event[:actionname]) Action_input: $(event[:actioninput]) Action output: $(event[:outcome])\n"
|
||||
# end
|
||||
# end
|
||||
|
||||
# return (success=success, result=result)
|
||||
# # Return formatted timeline string
|
||||
# return timeline
|
||||
# end
|
||||
|
||||
|
||||
@@ -555,11 +371,6 @@ end
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -36,7 +36,12 @@ function executeSQLVectorDB(sql)
|
||||
return result
|
||||
end
|
||||
|
||||
function text2textInstructLLM(prompt::String; maxattempt::Integer=2, modelsize::String="medium")
|
||||
function text2textInstructLLM(prompt::String; maxattempt::Integer=3, modelsize::String="medium",
|
||||
llmkwargs=Dict(
|
||||
:num_ctx => 32768,
|
||||
:temperature => 0.1,
|
||||
)
|
||||
)
|
||||
msgMeta = GeneralUtils.generate_msgMeta(
|
||||
config[:externalservice][:loadbalancer][:mqtttopic];
|
||||
msgPurpose="inference",
|
||||
@@ -51,10 +56,7 @@ function text2textInstructLLM(prompt::String; maxattempt::Integer=2, modelsize::
|
||||
:msgMeta => msgMeta,
|
||||
:payload => Dict(
|
||||
:text => prompt,
|
||||
:kwargs => Dict(
|
||||
:num_ctx => 16384,
|
||||
:temperature => 0.2,
|
||||
)
|
||||
:kwargs => llmkwargs
|
||||
)
|
||||
)
|
||||
|
||||
@@ -195,7 +197,7 @@ function insertSommelierDecision(recentevents::T1, decision::T2; maxdistance::In
|
||||
row, col = size(df)
|
||||
distance = row == 0 ? Inf : df[1, :distance]
|
||||
if row == 0 || distance > maxdistance # no close enough SQL stored in the database
|
||||
recentevents_embedding = a.func[:getEmbedding](recentevents)[1]
|
||||
recentevents_embedding = getEmbedding(recentevents)[1]
|
||||
recentevents = replace(recentevents, "'" => "")
|
||||
decision_json = JSON3.write(decision)
|
||||
decision_base64 = base64encode(decision_json)
|
||||
|
||||
Reference in New Issue
Block a user